diff --git a/course.yml b/course.yml
index 0b9a039..e3dea16 100644
--- a/course.yml
+++ b/course.yml
@@ -45,6 +45,7 @@ plan:
   slug: eda4
   date: 2023-10-09
   materials:
+  - lesson: pydata/pandas_joins
   - lesson: pydata/pandas_correlations
 
 - title: "Svátky klidu a konce kurzu"
diff --git a/lessons/pydata/pandas_correlations/index.ipynb b/lessons/pydata/pandas_correlations/index.ipynb
index aabdc5e..7151d89 100644
--- a/lessons/pydata/pandas_correlations/index.ipynb
+++ b/lessons/pydata/pandas_correlations/index.ipynb
@@ -4,6100 +4,36 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Pandas - spojování tabulek a vztahy mezi více proměnnými\n",
-    "\n",
-    "Tato lekce se nese ve znamení mnohosti a propojování - naučíš se:\n",
-    "\n",
-    "- pracovat s více tabulkami najednou\n",
-    "- nacházet spojitosti mezi dvěma (a více) proměnnými\n",
-    "\n",
-    "Při tom společně projdeme (ne poprvé a ne naposledy) čištění reálných datových sad."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Importy jako obvykle\n",
-    "import pandas as pd\n",
-    "import matplotlib.pyplot as plt\n",
-    "import seaborn as sns\n",
-    "\n",
-    "%matplotlib inline"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "toc-hr-collapsed": false
-   },
-   "source": [
-    "## Spojování tabulek\n",
-    "\n",
-    "V lekci, kde jsme zpracovávali data o počasí, jsme ti ukázali, že je pomocí funkce `concat` možné slepit dohromady několik objektů `DataFrame` či `Series`, pokud mají \"kompatibilní\" index. Nyní se na problematiku podíváme trochu blíže a ukážeme si, jak spojovat tabulky na základě různých sloupců, a co dělat, když řádky z jedné tabulky nepasují přesně na tabulku druhou.\n",
-    "\n",
-    "Obecně pro spojování `pandas` nabízí čtyři funkce / metody, z nichž každá má svoje typické využití (možnostmi se ovšem překrývají):\n",
-    "\n",
-    "- [`concat`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.concat.html) je univerzální funkce pro slepování dvou či více tabulek / sloupců - pod sebe, vedle sebe, s přihlédnutím k indexům i bez něj. \n",
-    "- [`append`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.append.html) (metoda) je jednodušší alternativou `concat`, pokud jen chceš do nějaké tabulky přidat pár řádků.\n",
-    "- [`merge`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.merge.html) je univerzální funkce pro spojování tabulek na základě vazby mezi indexy nebo sloupci.\n",
-    "- [`join`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.join.html) (metoda) zjednodušuje práci, když chceš spojit dvě tabulky na základě indexu.\n",
-    "\n",
-    "Detailní rozbor toho, co která umí, najdeš v [dokumentaci](https://pandas.pydata.org/pandas-docs/stable/user_guide/merging.html). My si je také postupně ukážeme."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Jednoduché skládání"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "#### Pod sebou\n",
-    "\n",
-    "To je asi ten nejjednodušší případ - máme dva objekty `Series` nebo dva kusy tabulky se stejnými sloupci a chceme je spojit pod sebou. Na to se používá funkce [`concat`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.concat.html):"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "a = pd.Series([\"jedna\", \"dvě\", \"tři\"])\n",
-    "b = pd.Series([\"čtyři\", \"pět\", \"šest\"])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0    jedna\n",
-       "1      dvě\n",
-       "2      tři\n",
-       "0    čtyři\n",
-       "1      pět\n",
-       "2     šest\n",
-       "dtype: object"
-      ]
-     },
-     "execution_count": 3,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "pd.concat([a, b])"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "💡 Vidíš, že se index opakuje? Vytvořili jsme dvě `Series`, u kterých jsme index neřešili. Jenže `pandas` na rozdíl od nás ano, a tak poslušně oba indexy spojil, i za cenu duplicitních hodnot. Za cenu použití dodatečného argumentu `ignore_index=True` se tomu lze vyhnout, což si ukážeme na příklady spojování dvou tabulek o stejných sloupcích:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0     jedna\n",
-       "1       dvě\n",
-       "2       tři\n",
-       "3     jedna\n",
-       "4       dvě\n",
-       "5       tři\n",
-       "6     jedna\n",
-       "7       dvě\n",
-       "8       tři\n",
-       "9     jedna\n",
-       "10      dvě\n",
-       "11      tři\n",
-       "12    jedna\n",
-       "13      dvě\n",
-       "14      tři\n",
-       "dtype: object"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "pd.concat([a, a, a, a, a], ignore_index=True)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "#### Vedle sebe\n",
-    "\n",
-    "Toto asi použijete zřídka, ale když chceme \"lepit\" doprava (třeba deset `Series`), stačí přidat nám dobře známý argument `axis`:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>0</th>\n",
-       "      <th>1</th>\n",
-       "      <th>2</th>\n",
-       "      <th>3</th>\n",
-       "      <th>4</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>jedna</td>\n",
-       "      <td>jedna</td>\n",
-       "      <td>jedna</td>\n",
-       "      <td>jedna</td>\n",
-       "      <td>jedna</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>dvě</td>\n",
-       "      <td>dvě</td>\n",
-       "      <td>dvě</td>\n",
-       "      <td>dvě</td>\n",
-       "      <td>dvě</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>tři</td>\n",
-       "      <td>tři</td>\n",
-       "      <td>tři</td>\n",
-       "      <td>tři</td>\n",
-       "      <td>tři</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "       0      1      2      3      4\n",
-       "0  jedna  jedna  jedna  jedna  jedna\n",
-       "1    dvě    dvě    dvě    dvě    dvě\n",
-       "2    tři    tři    tři    tři    tři"
-      ]
-     },
-     "execution_count": 5,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "pd.concat([a, a, a, a, a], axis=\"columns\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "**Příklad:** Jak co nejrychleji \"nakreslit prázdnou šachovnici\" (obě slova jsou v uvozovkách)?"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>A</th>\n",
-       "      <th>B</th>\n",
-       "      <th>C</th>\n",
-       "      <th>D</th>\n",
-       "      <th>E</th>\n",
-       "      <th>F</th>\n",
-       "      <th>G</th>\n",
-       "      <th>H</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>8</th>\n",
-       "      <td>⬜</td>\n",
-       "      <td>⬛</td>\n",
-       "      <td>⬜</td>\n",
-       "      <td>⬛</td>\n",
-       "      <td>⬜</td>\n",
-       "      <td>⬛</td>\n",
-       "      <td>⬜</td>\n",
-       "      <td>⬛</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>7</th>\n",
-       "      <td>⬛</td>\n",
-       "      <td>⬜</td>\n",
-       "      <td>⬛</td>\n",
-       "      <td>⬜</td>\n",
-       "      <td>⬛</td>\n",
-       "      <td>⬜</td>\n",
-       "      <td>⬛</td>\n",
-       "      <td>⬜</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6</th>\n",
-       "      <td>⬜</td>\n",
-       "      <td>⬛</td>\n",
-       "      <td>⬜</td>\n",
-       "      <td>⬛</td>\n",
-       "      <td>⬜</td>\n",
-       "      <td>⬛</td>\n",
-       "      <td>⬜</td>\n",
-       "      <td>⬛</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>5</th>\n",
-       "      <td>⬛</td>\n",
-       "      <td>⬜</td>\n",
-       "      <td>⬛</td>\n",
-       "      <td>⬜</td>\n",
-       "      <td>⬛</td>\n",
-       "      <td>⬜</td>\n",
-       "      <td>⬛</td>\n",
-       "      <td>⬜</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>⬜</td>\n",
-       "      <td>⬛</td>\n",
-       "      <td>⬜</td>\n",
-       "      <td>⬛</td>\n",
-       "      <td>⬜</td>\n",
-       "      <td>⬛</td>\n",
-       "      <td>⬜</td>\n",
-       "      <td>⬛</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>⬛</td>\n",
-       "      <td>⬜</td>\n",
-       "      <td>⬛</td>\n",
-       "      <td>⬜</td>\n",
-       "      <td>⬛</td>\n",
-       "      <td>⬜</td>\n",
-       "      <td>⬛</td>\n",
-       "      <td>⬜</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>⬜</td>\n",
-       "      <td>⬛</td>\n",
-       "      <td>⬜</td>\n",
-       "      <td>⬛</td>\n",
-       "      <td>⬜</td>\n",
-       "      <td>⬛</td>\n",
-       "      <td>⬜</td>\n",
-       "      <td>⬛</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>⬛</td>\n",
-       "      <td>⬜</td>\n",
-       "      <td>⬛</td>\n",
-       "      <td>⬜</td>\n",
-       "      <td>⬛</td>\n",
-       "      <td>⬜</td>\n",
-       "      <td>⬛</td>\n",
-       "      <td>⬜</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "   A  B  C  D  E  F  G  H\n",
-       "8  ⬜  ⬛  ⬜  ⬛  ⬜  ⬛  ⬜  ⬛\n",
-       "7  ⬛  ⬜  ⬛  ⬜  ⬛  ⬜  ⬛  ⬜\n",
-       "6  ⬜  ⬛  ⬜  ⬛  ⬜  ⬛  ⬜  ⬛\n",
-       "5  ⬛  ⬜  ⬛  ⬜  ⬛  ⬜  ⬛  ⬜\n",
-       "4  ⬜  ⬛  ⬜  ⬛  ⬜  ⬛  ⬜  ⬛\n",
-       "3  ⬛  ⬜  ⬛  ⬜  ⬛  ⬜  ⬛  ⬜\n",
-       "2  ⬜  ⬛  ⬜  ⬛  ⬜  ⬛  ⬜  ⬛\n",
-       "1  ⬛  ⬜  ⬛  ⬜  ⬛  ⬜  ⬛  ⬜"
-      ]
-     },
-     "execution_count": 6,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "sachy = pd.concat(\n",
-    "    [\n",
-    "        pd.concat(   \n",
-    "            [pd.DataFrame([[\"⬜\", \"⬛\"], [\"⬛\", \"⬜\"]])] * 4,\n",
-    "            axis=1)\n",
-    "    ] * 4\n",
-    ")\n",
-    "sachy.index = list(range(8, 0, -1))\n",
-    "sachy.columns = list(\"ABCDEFGH\")\n",
-    "sachy"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Spojování různorodých tabulek"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "🎦 Pro spojování heterogenních dat (v datové hantýrce \"joinování\") sáhneme po trochu komplexnějších filmových datech..."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Máme staženo několik souborů, načteme si je (zatím hrubě, \"raw\") - s přihlédnutím k tomu, že první dva nejsou v pravém slova smyslu \"comma-separated\", ale používají k oddělení hodnot tabulátor (tady pomůže argument `sep`). Také zohledníme, že v nich řetězec `\"\\N\"` představuje chybějící hodnoty (pomůže argument `na_values`):"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "imdb_titles_raw = pd.read_csv(\"title.basics.tsv.gz\", sep=\"\\t\", na_values=\"\\\\N\")\n",
-    "imdb_ratings_raw = pd.read_csv(\"title.ratings.tsv.gz\", sep=\"\\t\", na_values=\"\\\\N\")\n",
-    "boxoffice_raw = pd.read_csv(\"boxoffice_march_2019.csv.gz\")\n",
-    "rotten_tomatoes_raw = pd.read_csv(\"rotten_tomatoes_top_movies_2019-01-15.csv\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Co který soubor obsahuje? \n",
-    "\n",
-    "- První dva soubory obsahují volně dostupná (byť \"jen\" pro nekomerční použití) data o filmech z IMDb (Internet Movie Database). My jsme si zvolili obecné informace a uživatelská (číselná) hodnocení. Detailní popis souborů, stejně jako odkazy na další soubory, najdeš na https://www.imdb.com/interfaces/. Z důvodů paměťové náročnosti jsme datovou sadu ořezali o epizody seriálů, protože nás nebudou zajímat a s trochu štěstí přežijeme i na počítačích s menší operační pamětí.\n",
-    "\n",
-    "- Soubor `boxoffice_march_2019.csv.gz` obsahuje informace o výdělcích jednotlivých filmů. Pochází z ukázkového datasetu pro soutěž \"TMDB Box Office Prediction\" na serveru Kaggle: https://www.kaggle.com/c/tmdb-box-office-prediction/data\n",
-    "\n",
-    "- Soubor `rotten_tomatoes_top_movies_2019-01-15.csv` obsahuje procentuální hodnocení filmů ze serveru Rotten Tomatoes, které se počítá jako podíl pozitivních hodnoceních od filmových kritiku (je to tedy jiný princip než na IMDb). Staženo z: https://data.world/prasert/rotten-tomatoes-top-movies-by-genre\n",
-    "\n",
-    "Pojďme se podívat na nedostatky těchto souborů a postupně je skládat dohromady. Zajímalo by nás (a snad i tebe!), jak souvisí hodnocení s komerční úspěšností filmu, jak se liší hodnocení rotten tomatoes od těch na IMDb."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>tconst</th>\n",
-       "      <th>titleType</th>\n",
-       "      <th>primaryTitle</th>\n",
-       "      <th>originalTitle</th>\n",
-       "      <th>isAdult</th>\n",
-       "      <th>startYear</th>\n",
-       "      <th>endYear</th>\n",
-       "      <th>runtimeMinutes</th>\n",
-       "      <th>genres</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>tt0000001</td>\n",
-       "      <td>short</td>\n",
-       "      <td>Carmencita</td>\n",
-       "      <td>Carmencita</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1894.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>Documentary,Short</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>tt0000002</td>\n",
-       "      <td>short</td>\n",
-       "      <td>Le clown et ses chiens</td>\n",
-       "      <td>Le clown et ses chiens</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1892.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>Animation,Short</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>tt0000003</td>\n",
-       "      <td>short</td>\n",
-       "      <td>Pauvre Pierrot</td>\n",
-       "      <td>Pauvre Pierrot</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1892.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>Animation,Comedy,Romance</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>tt0000004</td>\n",
-       "      <td>short</td>\n",
-       "      <td>Un bon bock</td>\n",
-       "      <td>Un bon bock</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1892.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Animation,Short</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>tt0000005</td>\n",
-       "      <td>short</td>\n",
-       "      <td>Blacksmith Scene</td>\n",
-       "      <td>Blacksmith Scene</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1893.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>Comedy,Short</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1783511</th>\n",
-       "      <td>tt9916734</td>\n",
-       "      <td>video</td>\n",
-       "      <td>Manca: Peleo</td>\n",
-       "      <td>Manca: Peleo</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2018.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Music,Short</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1783512</th>\n",
-       "      <td>tt9916754</td>\n",
-       "      <td>movie</td>\n",
-       "      <td>Chico Albuquerque - Revelações</td>\n",
-       "      <td>Chico Albuquerque - Revelações</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2013.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Documentary</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1783513</th>\n",
-       "      <td>tt9916756</td>\n",
-       "      <td>short</td>\n",
-       "      <td>Pretty Pretty Black Girl</td>\n",
-       "      <td>Pretty Pretty Black Girl</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2019.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Short</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1783514</th>\n",
-       "      <td>tt9916764</td>\n",
-       "      <td>short</td>\n",
-       "      <td>38</td>\n",
-       "      <td>38</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2018.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>Short</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1783515</th>\n",
-       "      <td>tt9916856</td>\n",
-       "      <td>short</td>\n",
-       "      <td>The Wind</td>\n",
-       "      <td>The Wind</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2015.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>27.0</td>\n",
-       "      <td>Short</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>1783516 rows × 9 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "            tconst titleType                    primaryTitle  \\\n",
-       "0        tt0000001     short                      Carmencita   \n",
-       "1        tt0000002     short          Le clown et ses chiens   \n",
-       "2        tt0000003     short                  Pauvre Pierrot   \n",
-       "3        tt0000004     short                     Un bon bock   \n",
-       "4        tt0000005     short                Blacksmith Scene   \n",
-       "...            ...       ...                             ...   \n",
-       "1783511  tt9916734     video                    Manca: Peleo   \n",
-       "1783512  tt9916754     movie  Chico Albuquerque - Revelações   \n",
-       "1783513  tt9916756     short        Pretty Pretty Black Girl   \n",
-       "1783514  tt9916764     short                              38   \n",
-       "1783515  tt9916856     short                        The Wind   \n",
-       "\n",
-       "                          originalTitle  isAdult  startYear  endYear  \\\n",
-       "0                            Carmencita        0     1894.0      NaN   \n",
-       "1                Le clown et ses chiens        0     1892.0      NaN   \n",
-       "2                        Pauvre Pierrot        0     1892.0      NaN   \n",
-       "3                           Un bon bock        0     1892.0      NaN   \n",
-       "4                      Blacksmith Scene        0     1893.0      NaN   \n",
-       "...                                 ...      ...        ...      ...   \n",
-       "1783511                    Manca: Peleo        0     2018.0      NaN   \n",
-       "1783512  Chico Albuquerque - Revelações        0     2013.0      NaN   \n",
-       "1783513        Pretty Pretty Black Girl        0     2019.0      NaN   \n",
-       "1783514                              38        0     2018.0      NaN   \n",
-       "1783515                        The Wind        0     2015.0      NaN   \n",
-       "\n",
-       "         runtimeMinutes                    genres  \n",
-       "0                   1.0         Documentary,Short  \n",
-       "1                   5.0           Animation,Short  \n",
-       "2                   4.0  Animation,Comedy,Romance  \n",
-       "3                   NaN           Animation,Short  \n",
-       "4                   1.0              Comedy,Short  \n",
-       "...                 ...                       ...  \n",
-       "1783511             NaN               Music,Short  \n",
-       "1783512             NaN               Documentary  \n",
-       "1783513             NaN                     Short  \n",
-       "1783514             NaN                     Short  \n",
-       "1783515            27.0                     Short  \n",
-       "\n",
-       "[1783516 rows x 9 columns]"
-      ]
-     },
-     "execution_count": 8,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "imdb_titles_raw"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "648.8971881866455"
-      ]
-     },
-     "execution_count": 9,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# Kolik tabulka zabírá megabajtů paměti? (1 MB = 2**20 bajtů)\n",
-    "imdb_titles_raw.memory_usage(deep=True).sum() / 2**20 "
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Jistě budeme chtít převést sloupce na správné typy. Jaké jsou v základu?"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 10,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "tconst             object\n",
-       "titleType          object\n",
-       "primaryTitle       object\n",
-       "originalTitle      object\n",
-       "isAdult             int64\n",
-       "startYear         float64\n",
-       "endYear           float64\n",
-       "runtimeMinutes    float64\n",
-       "genres             object\n",
-       "dtype: object"
-      ]
-     },
-     "execution_count": 10,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "imdb_titles_raw.dtypes"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Na co budeme převádět?\n",
-    "\n",
-    "- `tconst` je řetězec, který posléze použijeme jako index, protože představuje unikátní identifikátor v databázi IMDb.\n",
-    "- `titleType`:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 11,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "titleType\n",
-       "short           676930\n",
-       "movie           514654\n",
-       "video           227582\n",
-       "tvSeries        162781\n",
-       "tvMovie         126507\n",
-       "tvMiniSeries     25574\n",
-       "videoGame        23310\n",
-       "tvSpecial        17007\n",
-       "tvShort           9171\n",
-       "Name: count, dtype: int64"
-      ]
-     },
-     "execution_count": 11,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "imdb_titles_raw[\"titleType\"].value_counts()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Jen devět různých hodnot ve skoro 2 milionech řádků? To je ideální kandidát na převedení na typ `\"category\"`.\n",
-    "\n",
-    "- `primaryTitle` a `originalTitle` vypadají jako obyčejné řetězce (pokud možno anglický a pokud možno původní název)\n",
-    "- `isAdult` určuje, zda se jedná o dílo pro dospělé. Tento sloupec bychom nejspíše měli převést na `bool`."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 12,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "isAdult\n",
-       "0    1692292\n",
-       "1      91224\n",
-       "Name: count, dtype: int64"
-      ]
-     },
-     "execution_count": 12,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "imdb_titles_raw[\"isAdult\"].value_counts()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "- `startYear` a `endYear` obsahují roky, t.j. celá čísla, ovšem kvůli chybějícím hodnotám je pro ně zvolen typ `float64`. V `pandas` raději zvolíme tzv. \"nullable integer\", který se zapisuje s velkým \"I\". Když nevíš, jaký podtyp konkrétně, sáhni po `Int64`.\n",
-    "- totéž platí pro `runtimeMinutes`."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 13,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "startYear           2115.0\n",
-       "endYear             2027.0\n",
-       "runtimeMinutes    125156.0\n",
-       "dtype: float64"
-      ]
-     },
-     "execution_count": 13,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "imdb_titles_raw[[\"startYear\", \"endYear\", \"runtimeMinutes\"]].max()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Mimochodem všimli jste si, že máme díla z budoucnosti (rok 2115)?"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 14,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "startYear\n",
-       "2020.0    340\n",
-       "2021.0     36\n",
-       "2022.0     14\n",
-       "2023.0      1\n",
-       "2024.0      2\n",
-       "2025.0      1\n",
-       "2115.0      1\n",
-       "Name: count, dtype: int64"
-      ]
-     },
-     "execution_count": 14,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "imdb_titles_raw[\"startYear\"].plot.hist()\n",
-    "imdb_titles_raw.query(\"startYear > 2019\")[\"startYear\"].value_counts().sort_index()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Takhle nějak by přetypování mohlo vypadat:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 15,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "tconst              object\n",
-       "titleType         category\n",
-       "primaryTitle        object\n",
-       "originalTitle       object\n",
-       "isAdult               bool\n",
-       "startYear            Int64\n",
-       "endYear              Int64\n",
-       "runtimeMinutes       Int64\n",
-       "genres              object\n",
-       "dtype: object"
-      ]
-     },
-     "execution_count": 15,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "(\n",
-    "    imdb_titles_raw\n",
-    "    .assign(\n",
-    "        titleType=imdb_titles_raw[\"titleType\"].astype(\"category\"),\n",
-    "        startYear=imdb_titles_raw[\"startYear\"].astype(\"Int64\"),\n",
-    "        endYear=imdb_titles_raw[\"endYear\"].astype(\"Int64\"),\n",
-    "        isAdult=imdb_titles_raw[\"isAdult\"].astype(bool),\n",
-    "        runtimeMinutes=imdb_titles_raw[\"runtimeMinutes\"].astype(\"Int64\")\n",
-    "    )\n",
-    ").dtypes"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Takhle už by to mohlo být. Jen si ještě:\n",
-    "\n",
-    "- pro přehlednost přejmenujeme některé sloupce (pomocí metody [`rename`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.rename.html))\n",
-    "- použijeme `tconst` jako index\n",
-    "\n",
-    "A tabulka `imdb_titles` bude připravená k použití!"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 16,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>title_type</th>\n",
-       "      <th>title</th>\n",
-       "      <th>original_title</th>\n",
-       "      <th>is_adult</th>\n",
-       "      <th>start_year</th>\n",
-       "      <th>end_year</th>\n",
-       "      <th>length</th>\n",
-       "      <th>genres</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tconst</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>tt0000001</th>\n",
-       "      <td>short</td>\n",
-       "      <td>Carmencita</td>\n",
-       "      <td>Carmencita</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1894</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>1</td>\n",
-       "      <td>Documentary,Short</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt0000002</th>\n",
-       "      <td>short</td>\n",
-       "      <td>Le clown et ses chiens</td>\n",
-       "      <td>Le clown et ses chiens</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1892</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>5</td>\n",
-       "      <td>Animation,Short</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt0000003</th>\n",
-       "      <td>short</td>\n",
-       "      <td>Pauvre Pierrot</td>\n",
-       "      <td>Pauvre Pierrot</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1892</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>4</td>\n",
-       "      <td>Animation,Comedy,Romance</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt0000004</th>\n",
-       "      <td>short</td>\n",
-       "      <td>Un bon bock</td>\n",
-       "      <td>Un bon bock</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1892</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>Animation,Short</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt0000005</th>\n",
-       "      <td>short</td>\n",
-       "      <td>Blacksmith Scene</td>\n",
-       "      <td>Blacksmith Scene</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1893</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>1</td>\n",
-       "      <td>Comedy,Short</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt9916734</th>\n",
-       "      <td>video</td>\n",
-       "      <td>Manca: Peleo</td>\n",
-       "      <td>Manca: Peleo</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2018</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>Music,Short</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt9916754</th>\n",
-       "      <td>movie</td>\n",
-       "      <td>Chico Albuquerque - Revelações</td>\n",
-       "      <td>Chico Albuquerque - Revelações</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2013</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>Documentary</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt9916756</th>\n",
-       "      <td>short</td>\n",
-       "      <td>Pretty Pretty Black Girl</td>\n",
-       "      <td>Pretty Pretty Black Girl</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2019</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>Short</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt9916764</th>\n",
-       "      <td>short</td>\n",
-       "      <td>38</td>\n",
-       "      <td>38</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2018</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>Short</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt9916856</th>\n",
-       "      <td>short</td>\n",
-       "      <td>The Wind</td>\n",
-       "      <td>The Wind</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2015</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>27</td>\n",
-       "      <td>Short</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>1783516 rows × 8 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "          title_type                           title  \\\n",
-       "tconst                                                 \n",
-       "tt0000001      short                      Carmencita   \n",
-       "tt0000002      short          Le clown et ses chiens   \n",
-       "tt0000003      short                  Pauvre Pierrot   \n",
-       "tt0000004      short                     Un bon bock   \n",
-       "tt0000005      short                Blacksmith Scene   \n",
-       "...              ...                             ...   \n",
-       "tt9916734      video                    Manca: Peleo   \n",
-       "tt9916754      movie  Chico Albuquerque - Revelações   \n",
-       "tt9916756      short        Pretty Pretty Black Girl   \n",
-       "tt9916764      short                              38   \n",
-       "tt9916856      short                        The Wind   \n",
-       "\n",
-       "                           original_title  is_adult  start_year  end_year  \\\n",
-       "tconst                                                                      \n",
-       "tt0000001                      Carmencita     False        1894      <NA>   \n",
-       "tt0000002          Le clown et ses chiens     False        1892      <NA>   \n",
-       "tt0000003                  Pauvre Pierrot     False        1892      <NA>   \n",
-       "tt0000004                     Un bon bock     False        1892      <NA>   \n",
-       "tt0000005                Blacksmith Scene     False        1893      <NA>   \n",
-       "...                                   ...       ...         ...       ...   \n",
-       "tt9916734                    Manca: Peleo     False        2018      <NA>   \n",
-       "tt9916754  Chico Albuquerque - Revelações     False        2013      <NA>   \n",
-       "tt9916756        Pretty Pretty Black Girl     False        2019      <NA>   \n",
-       "tt9916764                              38     False        2018      <NA>   \n",
-       "tt9916856                        The Wind     False        2015      <NA>   \n",
-       "\n",
-       "           length                    genres  \n",
-       "tconst                                       \n",
-       "tt0000001       1         Documentary,Short  \n",
-       "tt0000002       5           Animation,Short  \n",
-       "tt0000003       4  Animation,Comedy,Romance  \n",
-       "tt0000004    <NA>           Animation,Short  \n",
-       "tt0000005       1              Comedy,Short  \n",
-       "...           ...                       ...  \n",
-       "tt9916734    <NA>               Music,Short  \n",
-       "tt9916754    <NA>               Documentary  \n",
-       "tt9916756    <NA>                     Short  \n",
-       "tt9916764    <NA>                     Short  \n",
-       "tt9916856      27                     Short  \n",
-       "\n",
-       "[1783516 rows x 8 columns]"
-      ]
-     },
-     "execution_count": 16,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "imdb_titles = (\n",
-    "    imdb_titles_raw\n",
-    "    .assign(\n",
-    "        titleType=imdb_titles_raw[\"titleType\"].astype(\"category\"),\n",
-    "        startYear=imdb_titles_raw[\"startYear\"].astype(\"Int64\"),\n",
-    "        endYear=imdb_titles_raw[\"endYear\"].astype(\"Int64\"),\n",
-    "        isAdult=imdb_titles_raw[\"isAdult\"].astype(bool),\n",
-    "        runtimeMinutes=imdb_titles_raw[\"runtimeMinutes\"].astype(\"Int64\")\n",
-    "    )\n",
-    "    .rename({\n",
-    "        \"primaryTitle\": \"title\",\n",
-    "        \"originalTitle\": \"original_title\",\n",
-    "        \"titleType\": \"title_type\",\n",
-    "        \"runtimeMinutes\": \"length\",\n",
-    "        \"startYear\": \"start_year\",\n",
-    "        \"endYear\": \"end_year\",\n",
-    "        \"isAdult\": \"is_adult\",\n",
-    "    }, axis=\"columns\")\n",
-    "    .set_index(\"tconst\")\n",
-    ")\n",
-    "imdb_titles"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 17,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "537.2908029556274"
-      ]
-     },
-     "execution_count": 17,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# Kolik tabulka zabírá megabajtů paměti?\n",
-    "imdb_titles.memory_usage(deep=True).sum() / 2**20   # O chlup méně, zase tolik jsme si ale nepomohli."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Připravíme si ještě speciální tabulku jenom pro filmy, protože další datové sady se zabývají jenom jimi.\n",
-    "\n",
-    "U této tabulky navíc vyhodíme zbytečné sloupce `title_type`, `end_year` a přejmenujeme `start_year` prostě na `year`:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 18,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>title</th>\n",
-       "      <th>original_title</th>\n",
-       "      <th>is_adult</th>\n",
-       "      <th>year</th>\n",
-       "      <th>length</th>\n",
-       "      <th>genres</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tconst</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>tt0000009</th>\n",
-       "      <td>Miss Jerry</td>\n",
-       "      <td>Miss Jerry</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1894</td>\n",
-       "      <td>45</td>\n",
-       "      <td>Romance</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt0000147</th>\n",
-       "      <td>The Corbett-Fitzsimmons Fight</td>\n",
-       "      <td>The Corbett-Fitzsimmons Fight</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1897</td>\n",
-       "      <td>20</td>\n",
-       "      <td>Documentary,News,Sport</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt0000335</th>\n",
-       "      <td>Soldiers of the Cross</td>\n",
-       "      <td>Soldiers of the Cross</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1900</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>Biography,Drama</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt0000502</th>\n",
-       "      <td>Bohemios</td>\n",
-       "      <td>Bohemios</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1905</td>\n",
-       "      <td>100</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt0000574</th>\n",
-       "      <td>The Story of the Kelly Gang</td>\n",
-       "      <td>The Story of the Kelly Gang</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1906</td>\n",
-       "      <td>70</td>\n",
-       "      <td>Biography,Crime,Drama</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt9916622</th>\n",
-       "      <td>Rodolpho Teóphilo - O Legado de um Pioneiro</td>\n",
-       "      <td>Rodolpho Teóphilo - O Legado de um Pioneiro</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2015</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>Documentary</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt9916680</th>\n",
-       "      <td>De la ilusión al desconcierto: cine colombiano...</td>\n",
-       "      <td>De la ilusión al desconcierto: cine colombiano...</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2007</td>\n",
-       "      <td>100</td>\n",
-       "      <td>Documentary</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt9916706</th>\n",
-       "      <td>Dankyavar Danka</td>\n",
-       "      <td>Dankyavar Danka</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2013</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>Comedy</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt9916730</th>\n",
-       "      <td>6 Gunn</td>\n",
-       "      <td>6 Gunn</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2017</td>\n",
-       "      <td>116</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt9916754</th>\n",
-       "      <td>Chico Albuquerque - Revelações</td>\n",
-       "      <td>Chico Albuquerque - Revelações</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2013</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>Documentary</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>514654 rows × 6 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                                                       title  \\\n",
-       "tconst                                                         \n",
-       "tt0000009                                         Miss Jerry   \n",
-       "tt0000147                      The Corbett-Fitzsimmons Fight   \n",
-       "tt0000335                              Soldiers of the Cross   \n",
-       "tt0000502                                           Bohemios   \n",
-       "tt0000574                        The Story of the Kelly Gang   \n",
-       "...                                                      ...   \n",
-       "tt9916622        Rodolpho Teóphilo - O Legado de um Pioneiro   \n",
-       "tt9916680  De la ilusión al desconcierto: cine colombiano...   \n",
-       "tt9916706                                    Dankyavar Danka   \n",
-       "tt9916730                                             6 Gunn   \n",
-       "tt9916754                     Chico Albuquerque - Revelações   \n",
-       "\n",
-       "                                              original_title  is_adult  year  \\\n",
-       "tconst                                                                         \n",
-       "tt0000009                                         Miss Jerry     False  1894   \n",
-       "tt0000147                      The Corbett-Fitzsimmons Fight     False  1897   \n",
-       "tt0000335                              Soldiers of the Cross     False  1900   \n",
-       "tt0000502                                           Bohemios     False  1905   \n",
-       "tt0000574                        The Story of the Kelly Gang     False  1906   \n",
-       "...                                                      ...       ...   ...   \n",
-       "tt9916622        Rodolpho Teóphilo - O Legado de um Pioneiro     False  2015   \n",
-       "tt9916680  De la ilusión al desconcierto: cine colombiano...     False  2007   \n",
-       "tt9916706                                    Dankyavar Danka     False  2013   \n",
-       "tt9916730                                             6 Gunn     False  2017   \n",
-       "tt9916754                     Chico Albuquerque - Revelações     False  2013   \n",
-       "\n",
-       "           length                  genres  \n",
-       "tconst                                     \n",
-       "tt0000009      45                 Romance  \n",
-       "tt0000147      20  Documentary,News,Sport  \n",
-       "tt0000335    <NA>         Biography,Drama  \n",
-       "tt0000502     100                     NaN  \n",
-       "tt0000574      70   Biography,Crime,Drama  \n",
-       "...           ...                     ...  \n",
-       "tt9916622    <NA>             Documentary  \n",
-       "tt9916680     100             Documentary  \n",
-       "tt9916706    <NA>                  Comedy  \n",
-       "tt9916730     116                     NaN  \n",
-       "tt9916754    <NA>             Documentary  \n",
-       "\n",
-       "[514654 rows x 6 columns]"
-      ]
-     },
-     "execution_count": 18,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "movies = (\n",
-    "    imdb_titles\n",
-    "    .query(\"title_type == 'movie'\")\n",
-    "    .drop([\"title_type\", \"end_year\"], axis=\"columns\")\n",
-    "    .rename({\"start_year\": \"year\"}, axis=\"columns\")\n",
-    ")\n",
-    "movies"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 19,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "(514654, 6)\n",
-      "title             object\n",
-      "original_title    object\n",
-      "is_adult            bool\n",
-      "year               Int64\n",
-      "length             Int64\n",
-      "genres            object\n",
-      "dtype: object\n"
-     ]
-    }
-   ],
-   "source": [
-    "print(movies.shape)\n",
-    "print(movies.dtypes)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Nyní se podíváme na zoubek hodnocením z IMDb, na tabulky `imdb_ratings_raw`:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 20,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>tconst</th>\n",
-       "      <th>averageRating</th>\n",
-       "      <th>numVotes</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>tt0000001</td>\n",
-       "      <td>5.8</td>\n",
-       "      <td>1486</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>tt0000002</td>\n",
-       "      <td>6.4</td>\n",
-       "      <td>179</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>tt0000003</td>\n",
-       "      <td>6.6</td>\n",
-       "      <td>1117</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>tt0000004</td>\n",
-       "      <td>6.4</td>\n",
-       "      <td>109</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>tt0000005</td>\n",
-       "      <td>6.2</td>\n",
-       "      <td>1820</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>923691</th>\n",
-       "      <td>tt9916380</td>\n",
-       "      <td>9.7</td>\n",
-       "      <td>58</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>923692</th>\n",
-       "      <td>tt9916420</td>\n",
-       "      <td>7.0</td>\n",
-       "      <td>5</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>923693</th>\n",
-       "      <td>tt9916460</td>\n",
-       "      <td>9.2</td>\n",
-       "      <td>12</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>923694</th>\n",
-       "      <td>tt9916720</td>\n",
-       "      <td>5.2</td>\n",
-       "      <td>11</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>923695</th>\n",
-       "      <td>tt9916766</td>\n",
-       "      <td>7.2</td>\n",
-       "      <td>5</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>923696 rows × 3 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "           tconst  averageRating  numVotes\n",
-       "0       tt0000001            5.8      1486\n",
-       "1       tt0000002            6.4       179\n",
-       "2       tt0000003            6.6      1117\n",
-       "3       tt0000004            6.4       109\n",
-       "4       tt0000005            6.2      1820\n",
-       "...           ...            ...       ...\n",
-       "923691  tt9916380            9.7        58\n",
-       "923692  tt9916420            7.0         5\n",
-       "923693  tt9916460            9.2        12\n",
-       "923694  tt9916720            5.2        11\n",
-       "923695  tt9916766            7.2         5\n",
-       "\n",
-       "[923696 rows x 3 columns]"
-      ]
-     },
-     "execution_count": 20,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "imdb_ratings_raw"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 21,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "tconst            object\n",
-       "averageRating    float64\n",
-       "numVotes           int64\n",
-       "dtype: object"
-      ]
-     },
-     "execution_count": 21,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "imdb_ratings_raw.dtypes"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "To by vlastně skoro mohlo být!\n",
-    "\n",
-    "Tak jen nastavíme index (opět `tconst`) a přejmenujeme sloupce:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 22,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
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-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>imdb_rating</th>\n",
-       "      <th>imdb_votes</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tconst</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>tt0000001</th>\n",
-       "      <td>5.8</td>\n",
-       "      <td>1486</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt0000002</th>\n",
-       "      <td>6.4</td>\n",
-       "      <td>179</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt0000003</th>\n",
-       "      <td>6.6</td>\n",
-       "      <td>1117</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt0000004</th>\n",
-       "      <td>6.4</td>\n",
-       "      <td>109</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt0000005</th>\n",
-       "      <td>6.2</td>\n",
-       "      <td>1820</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt9916380</th>\n",
-       "      <td>9.7</td>\n",
-       "      <td>58</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt9916420</th>\n",
-       "      <td>7.0</td>\n",
-       "      <td>5</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt9916460</th>\n",
-       "      <td>9.2</td>\n",
-       "      <td>12</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt9916720</th>\n",
-       "      <td>5.2</td>\n",
-       "      <td>11</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt9916766</th>\n",
-       "      <td>7.2</td>\n",
-       "      <td>5</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>923696 rows × 2 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "           imdb_rating  imdb_votes\n",
-       "tconst                            \n",
-       "tt0000001          5.8        1486\n",
-       "tt0000002          6.4         179\n",
-       "tt0000003          6.6        1117\n",
-       "tt0000004          6.4         109\n",
-       "tt0000005          6.2        1820\n",
-       "...                ...         ...\n",
-       "tt9916380          9.7          58\n",
-       "tt9916420          7.0           5\n",
-       "tt9916460          9.2          12\n",
-       "tt9916720          5.2          11\n",
-       "tt9916766          7.2           5\n",
-       "\n",
-       "[923696 rows x 2 columns]"
-      ]
-     },
-     "execution_count": 22,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "ratings = (imdb_ratings_raw\n",
-    "    .rename({\n",
-    "        \"averageRating\": \"imdb_rating\",\n",
-    "        \"numVotes\": \"imdb_votes\"\n",
-    "    }, axis=\"columns\")\n",
-    "    .set_index(\"tconst\")\n",
-    ")\n",
-    "ratings"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "#### První join\n",
-    "\n",
-    "Máme připravené dvě krásné tabulky, které sdílejí stejný index, a můžeme vesele spojovat. Protože pomocí `join`, `merge` a `concat` lze volbou vhodných parametrů dosáhnout identického výsledku (což je jedním z nešvarů knihovny `pandas`), ukážeme si všechny tři alternativy podle subjektivního pořadí vhodnosti."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 23,
-   "metadata": {
-    "scrolled": true
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
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-       "\n",
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-       "        vertical-align: top;\n",
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-       "\n",
-       "    .dataframe thead th {\n",
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-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>title</th>\n",
-       "      <th>original_title</th>\n",
-       "      <th>is_adult</th>\n",
-       "      <th>year</th>\n",
-       "      <th>length</th>\n",
-       "      <th>genres</th>\n",
-       "      <th>imdb_rating</th>\n",
-       "      <th>imdb_votes</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tconst</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>tt0000009</th>\n",
-       "      <td>Miss Jerry</td>\n",
-       "      <td>Miss Jerry</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1894</td>\n",
-       "      <td>45</td>\n",
-       "      <td>Romance</td>\n",
-       "      <td>5.5</td>\n",
-       "      <td>77.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt0000147</th>\n",
-       "      <td>The Corbett-Fitzsimmons Fight</td>\n",
-       "      <td>The Corbett-Fitzsimmons Fight</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1897</td>\n",
-       "      <td>20</td>\n",
-       "      <td>Documentary,News,Sport</td>\n",
-       "      <td>5.2</td>\n",
-       "      <td>289.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt0000335</th>\n",
-       "      <td>Soldiers of the Cross</td>\n",
-       "      <td>Soldiers of the Cross</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1900</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>Biography,Drama</td>\n",
-       "      <td>6.3</td>\n",
-       "      <td>39.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt0000502</th>\n",
-       "      <td>Bohemios</td>\n",
-       "      <td>Bohemios</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1905</td>\n",
-       "      <td>100</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt0000574</th>\n",
-       "      <td>The Story of the Kelly Gang</td>\n",
-       "      <td>The Story of the Kelly Gang</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1906</td>\n",
-       "      <td>70</td>\n",
-       "      <td>Biography,Crime,Drama</td>\n",
-       "      <td>6.2</td>\n",
-       "      <td>505.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt9916622</th>\n",
-       "      <td>Rodolpho Teóphilo - O Legado de um Pioneiro</td>\n",
-       "      <td>Rodolpho Teóphilo - O Legado de um Pioneiro</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2015</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>Documentary</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt9916680</th>\n",
-       "      <td>De la ilusión al desconcierto: cine colombiano...</td>\n",
-       "      <td>De la ilusión al desconcierto: cine colombiano...</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2007</td>\n",
-       "      <td>100</td>\n",
-       "      <td>Documentary</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt9916706</th>\n",
-       "      <td>Dankyavar Danka</td>\n",
-       "      <td>Dankyavar Danka</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2013</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>Comedy</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt9916730</th>\n",
-       "      <td>6 Gunn</td>\n",
-       "      <td>6 Gunn</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2017</td>\n",
-       "      <td>116</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt9916754</th>\n",
-       "      <td>Chico Albuquerque - Revelações</td>\n",
-       "      <td>Chico Albuquerque - Revelações</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2013</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>Documentary</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>514654 rows × 8 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                                                       title  \\\n",
-       "tconst                                                         \n",
-       "tt0000009                                         Miss Jerry   \n",
-       "tt0000147                      The Corbett-Fitzsimmons Fight   \n",
-       "tt0000335                              Soldiers of the Cross   \n",
-       "tt0000502                                           Bohemios   \n",
-       "tt0000574                        The Story of the Kelly Gang   \n",
-       "...                                                      ...   \n",
-       "tt9916622        Rodolpho Teóphilo - O Legado de um Pioneiro   \n",
-       "tt9916680  De la ilusión al desconcierto: cine colombiano...   \n",
-       "tt9916706                                    Dankyavar Danka   \n",
-       "tt9916730                                             6 Gunn   \n",
-       "tt9916754                     Chico Albuquerque - Revelações   \n",
-       "\n",
-       "                                              original_title  is_adult  year  \\\n",
-       "tconst                                                                         \n",
-       "tt0000009                                         Miss Jerry     False  1894   \n",
-       "tt0000147                      The Corbett-Fitzsimmons Fight     False  1897   \n",
-       "tt0000335                              Soldiers of the Cross     False  1900   \n",
-       "tt0000502                                           Bohemios     False  1905   \n",
-       "tt0000574                        The Story of the Kelly Gang     False  1906   \n",
-       "...                                                      ...       ...   ...   \n",
-       "tt9916622        Rodolpho Teóphilo - O Legado de um Pioneiro     False  2015   \n",
-       "tt9916680  De la ilusión al desconcierto: cine colombiano...     False  2007   \n",
-       "tt9916706                                    Dankyavar Danka     False  2013   \n",
-       "tt9916730                                             6 Gunn     False  2017   \n",
-       "tt9916754                     Chico Albuquerque - Revelações     False  2013   \n",
-       "\n",
-       "           length                  genres  imdb_rating  imdb_votes  \n",
-       "tconst                                                              \n",
-       "tt0000009      45                 Romance          5.5        77.0  \n",
-       "tt0000147      20  Documentary,News,Sport          5.2       289.0  \n",
-       "tt0000335    <NA>         Biography,Drama          6.3        39.0  \n",
-       "tt0000502     100                     NaN          NaN         NaN  \n",
-       "tt0000574      70   Biography,Crime,Drama          6.2       505.0  \n",
-       "...           ...                     ...          ...         ...  \n",
-       "tt9916622    <NA>             Documentary          NaN         NaN  \n",
-       "tt9916680     100             Documentary          NaN         NaN  \n",
-       "tt9916706    <NA>                  Comedy          NaN         NaN  \n",
-       "tt9916730     116                     NaN          NaN         NaN  \n",
-       "tt9916754    <NA>             Documentary          NaN         NaN  \n",
-       "\n",
-       "[514654 rows x 8 columns]"
-      ]
-     },
-     "execution_count": 23,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "movies.join(ratings)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "K tabulce se nenápadně přidaly dva sloupce z tabulky `ratings`, a to takovým způsobem, že se porovnaly hodnoty indexu (tedy `tconst`) a spárovaly se ty části řádku, kde se tento index shoduje.\n",
-    "\n",
-    "💡 Uvědom si (ačkoliv z volání funkcí v `pandas` to není úplně zřejmé), že se tady děje něco fundamentálně odlišného od \"nalepení doprava\" - tabulky tu nejsou chápány jako čtverečky, které jde skládat jako lego, nýbrž jako zdroj údajů o jednotlivých objektech, které je potřeba spojit sémanticky.\n",
-    "\n",
-    "Jak ale vidíš, tabulka obsahuje spoustu řádků, kde ve sloupcích s hodnocením chybí hodnoty (respektive nachází se `NaN`). To vychází ze způsobu, jakým metoda `join` ve výchozím nastavení \"joinuje\" - použije všechny řádky z levé tabulky bez ohledu na to, jestli jim odpovídá nějaký protějšek v tabulce pravé. Naštěstí lze pomocí argumentu `how` specifikovat i jiné způsoby spojování:\n",
-    "\n",
-    "- `left` (výchozí pro metodu `join`) - vezmou se všechny prvky z levé tabulky a jim odpovídající prvky z pravé tabulky (kde nejsou, doplní se `NaN`)\n",
-    "- `right` - vezmou se všechny prvky z pravé tabulky a jim odpovídající prvky z levé tabulky (kde nejsou, doplní se `NaN`)\n",
-    "- `inner` (výchozí pro funkci `merge`) - vezmou se jen ty prvky, které jsou v levé i pravé tabulce.\n",
-    "- `outer` (výchozí pro funkci `concat`) - vezmou se všechny prvky, z levé i pravé tabulky, kde něco chybí, doplní se `NaN`.\n",
-    "\n",
-    "V podobě Vennově diagramu, kde kruhy představují množiny řádků v obou zdrojových tabulkách a modrou barvou jsou zvýrazněny řádky v tabulce cílové:\n",
-    "\n",
-    "![Typy joinů](static/joins.svg)\n",
-    "\n",
-    "*Obrázek adaptován z https://upload.wikimedia.org/wikipedia/commons/9/9d/SQL_Joins.svg (autor: Arbeck)*\n",
-    "\n",
-    "💡 Až budeme probírat databáze, tyto čtyři typu joinů se nám znovu vynoří.\n",
-    "\n",
-    "Následující výpis ukáže, kolik řádků bychom dostali při použití různých hodnot `how`:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 24,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "movies.join(ratings, how=\"left\"): 514654 řádků.\n",
-      "movies.join(ratings, how=\"right\"): 923696 řádků.\n",
-      "movies.join(ratings, how=\"inner\"): 232496 řádků.\n",
-      "movies.join(ratings, how=\"outer\"): 1205854 řádků.\n"
-     ]
-    }
-   ],
-   "source": [
-    "for how in [\"left\", \"right\", \"inner\", \"outer\"]:\n",
-    "    print(f\"movies.join(ratings, how=\\\"{how}\\\"):\", movies.join(ratings, how=how).shape[0], \"řádků.\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "A teď tedy ty tři alternativy:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 25,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
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-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>title</th>\n",
-       "      <th>original_title</th>\n",
-       "      <th>is_adult</th>\n",
-       "      <th>year</th>\n",
-       "      <th>length</th>\n",
-       "      <th>genres</th>\n",
-       "      <th>imdb_rating</th>\n",
-       "      <th>imdb_votes</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tconst</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>tt0000009</th>\n",
-       "      <td>Miss Jerry</td>\n",
-       "      <td>Miss Jerry</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1894</td>\n",
-       "      <td>45</td>\n",
-       "      <td>Romance</td>\n",
-       "      <td>5.5</td>\n",
-       "      <td>77</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt0000147</th>\n",
-       "      <td>The Corbett-Fitzsimmons Fight</td>\n",
-       "      <td>The Corbett-Fitzsimmons Fight</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1897</td>\n",
-       "      <td>20</td>\n",
-       "      <td>Documentary,News,Sport</td>\n",
-       "      <td>5.2</td>\n",
-       "      <td>289</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt0000335</th>\n",
-       "      <td>Soldiers of the Cross</td>\n",
-       "      <td>Soldiers of the Cross</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1900</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>Biography,Drama</td>\n",
-       "      <td>6.3</td>\n",
-       "      <td>39</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt0000574</th>\n",
-       "      <td>The Story of the Kelly Gang</td>\n",
-       "      <td>The Story of the Kelly Gang</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1906</td>\n",
-       "      <td>70</td>\n",
-       "      <td>Biography,Crime,Drama</td>\n",
-       "      <td>6.2</td>\n",
-       "      <td>505</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt0000615</th>\n",
-       "      <td>Robbery Under Arms</td>\n",
-       "      <td>Robbery Under Arms</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1907</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>Drama</td>\n",
-       "      <td>4.8</td>\n",
-       "      <td>14</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt9910930</th>\n",
-       "      <td>Jeg ser deg</td>\n",
-       "      <td>Jeg ser deg</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2019</td>\n",
-       "      <td>75</td>\n",
-       "      <td>Crime,Documentary</td>\n",
-       "      <td>4.6</td>\n",
-       "      <td>5</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt9911774</th>\n",
-       "      <td>Padmavyuhathile Abhimanyu</td>\n",
-       "      <td>Padmavyuhathile Abhimanyu</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2019</td>\n",
-       "      <td>130</td>\n",
-       "      <td>Drama</td>\n",
-       "      <td>8.5</td>\n",
-       "      <td>363</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt9913056</th>\n",
-       "      <td>Swarm Season</td>\n",
-       "      <td>Swarm Season</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2019</td>\n",
-       "      <td>86</td>\n",
-       "      <td>Documentary</td>\n",
-       "      <td>6.2</td>\n",
-       "      <td>5</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt9913084</th>\n",
-       "      <td>Diabolik sono io</td>\n",
-       "      <td>Diabolik sono io</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2019</td>\n",
-       "      <td>75</td>\n",
-       "      <td>Documentary</td>\n",
-       "      <td>6.2</td>\n",
-       "      <td>6</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt9914286</th>\n",
-       "      <td>Sokagin Çocuklari</td>\n",
-       "      <td>Sokagin Çocuklari</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2019</td>\n",
-       "      <td>98</td>\n",
-       "      <td>Drama,Family</td>\n",
-       "      <td>9.8</td>\n",
-       "      <td>72</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>232496 rows × 8 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                                   title                 original_title  \\\n",
-       "tconst                                                                    \n",
-       "tt0000009                     Miss Jerry                     Miss Jerry   \n",
-       "tt0000147  The Corbett-Fitzsimmons Fight  The Corbett-Fitzsimmons Fight   \n",
-       "tt0000335          Soldiers of the Cross          Soldiers of the Cross   \n",
-       "tt0000574    The Story of the Kelly Gang    The Story of the Kelly Gang   \n",
-       "tt0000615             Robbery Under Arms             Robbery Under Arms   \n",
-       "...                                  ...                            ...   \n",
-       "tt9910930                    Jeg ser deg                    Jeg ser deg   \n",
-       "tt9911774      Padmavyuhathile Abhimanyu      Padmavyuhathile Abhimanyu   \n",
-       "tt9913056                   Swarm Season                   Swarm Season   \n",
-       "tt9913084               Diabolik sono io               Diabolik sono io   \n",
-       "tt9914286              Sokagin Çocuklari              Sokagin Çocuklari   \n",
-       "\n",
-       "           is_adult  year  length                  genres  imdb_rating  \\\n",
-       "tconst                                                                   \n",
-       "tt0000009     False  1894      45                 Romance          5.5   \n",
-       "tt0000147     False  1897      20  Documentary,News,Sport          5.2   \n",
-       "tt0000335     False  1900    <NA>         Biography,Drama          6.3   \n",
-       "tt0000574     False  1906      70   Biography,Crime,Drama          6.2   \n",
-       "tt0000615     False  1907    <NA>                   Drama          4.8   \n",
-       "...             ...   ...     ...                     ...          ...   \n",
-       "tt9910930     False  2019      75       Crime,Documentary          4.6   \n",
-       "tt9911774     False  2019     130                   Drama          8.5   \n",
-       "tt9913056     False  2019      86             Documentary          6.2   \n",
-       "tt9913084     False  2019      75             Documentary          6.2   \n",
-       "tt9914286     False  2019      98            Drama,Family          9.8   \n",
-       "\n",
-       "           imdb_votes  \n",
-       "tconst                 \n",
-       "tt0000009          77  \n",
-       "tt0000147         289  \n",
-       "tt0000335          39  \n",
-       "tt0000574         505  \n",
-       "tt0000615          14  \n",
-       "...               ...  \n",
-       "tt9910930           5  \n",
-       "tt9911774         363  \n",
-       "tt9913056           5  \n",
-       "tt9913084           6  \n",
-       "tt9914286          72  \n",
-       "\n",
-       "[232496 rows x 8 columns]"
-      ]
-     },
-     "execution_count": 25,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# Alternativa 1 (preferovaná)\n",
-    "movies_with_rating = movies.join(ratings, how=\"inner\")\n",
-    "movies_with_rating"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 26,
-   "metadata": {
-    "scrolled": true
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
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-       "\n",
-       "    .dataframe thead th {\n",
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-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>title</th>\n",
-       "      <th>original_title</th>\n",
-       "      <th>is_adult</th>\n",
-       "      <th>year</th>\n",
-       "      <th>length</th>\n",
-       "      <th>genres</th>\n",
-       "      <th>imdb_rating</th>\n",
-       "      <th>imdb_votes</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tconst</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>tt0000009</th>\n",
-       "      <td>Miss Jerry</td>\n",
-       "      <td>Miss Jerry</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1894</td>\n",
-       "      <td>45</td>\n",
-       "      <td>Romance</td>\n",
-       "      <td>5.5</td>\n",
-       "      <td>77</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt0000147</th>\n",
-       "      <td>The Corbett-Fitzsimmons Fight</td>\n",
-       "      <td>The Corbett-Fitzsimmons Fight</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1897</td>\n",
-       "      <td>20</td>\n",
-       "      <td>Documentary,News,Sport</td>\n",
-       "      <td>5.2</td>\n",
-       "      <td>289</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt0000335</th>\n",
-       "      <td>Soldiers of the Cross</td>\n",
-       "      <td>Soldiers of the Cross</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1900</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>Biography,Drama</td>\n",
-       "      <td>6.3</td>\n",
-       "      <td>39</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt0000574</th>\n",
-       "      <td>The Story of the Kelly Gang</td>\n",
-       "      <td>The Story of the Kelly Gang</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1906</td>\n",
-       "      <td>70</td>\n",
-       "      <td>Biography,Crime,Drama</td>\n",
-       "      <td>6.2</td>\n",
-       "      <td>505</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt0000615</th>\n",
-       "      <td>Robbery Under Arms</td>\n",
-       "      <td>Robbery Under Arms</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1907</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>Drama</td>\n",
-       "      <td>4.8</td>\n",
-       "      <td>14</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt9910930</th>\n",
-       "      <td>Jeg ser deg</td>\n",
-       "      <td>Jeg ser deg</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2019</td>\n",
-       "      <td>75</td>\n",
-       "      <td>Crime,Documentary</td>\n",
-       "      <td>4.6</td>\n",
-       "      <td>5</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt9911774</th>\n",
-       "      <td>Padmavyuhathile Abhimanyu</td>\n",
-       "      <td>Padmavyuhathile Abhimanyu</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2019</td>\n",
-       "      <td>130</td>\n",
-       "      <td>Drama</td>\n",
-       "      <td>8.5</td>\n",
-       "      <td>363</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt9913056</th>\n",
-       "      <td>Swarm Season</td>\n",
-       "      <td>Swarm Season</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2019</td>\n",
-       "      <td>86</td>\n",
-       "      <td>Documentary</td>\n",
-       "      <td>6.2</td>\n",
-       "      <td>5</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt9913084</th>\n",
-       "      <td>Diabolik sono io</td>\n",
-       "      <td>Diabolik sono io</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2019</td>\n",
-       "      <td>75</td>\n",
-       "      <td>Documentary</td>\n",
-       "      <td>6.2</td>\n",
-       "      <td>6</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt9914286</th>\n",
-       "      <td>Sokagin Çocuklari</td>\n",
-       "      <td>Sokagin Çocuklari</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2019</td>\n",
-       "      <td>98</td>\n",
-       "      <td>Drama,Family</td>\n",
-       "      <td>9.8</td>\n",
-       "      <td>72</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>232496 rows × 8 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                                   title                 original_title  \\\n",
-       "tconst                                                                    \n",
-       "tt0000009                     Miss Jerry                     Miss Jerry   \n",
-       "tt0000147  The Corbett-Fitzsimmons Fight  The Corbett-Fitzsimmons Fight   \n",
-       "tt0000335          Soldiers of the Cross          Soldiers of the Cross   \n",
-       "tt0000574    The Story of the Kelly Gang    The Story of the Kelly Gang   \n",
-       "tt0000615             Robbery Under Arms             Robbery Under Arms   \n",
-       "...                                  ...                            ...   \n",
-       "tt9910930                    Jeg ser deg                    Jeg ser deg   \n",
-       "tt9911774      Padmavyuhathile Abhimanyu      Padmavyuhathile Abhimanyu   \n",
-       "tt9913056                   Swarm Season                   Swarm Season   \n",
-       "tt9913084               Diabolik sono io               Diabolik sono io   \n",
-       "tt9914286              Sokagin Çocuklari              Sokagin Çocuklari   \n",
-       "\n",
-       "           is_adult  year  length                  genres  imdb_rating  \\\n",
-       "tconst                                                                   \n",
-       "tt0000009     False  1894      45                 Romance          5.5   \n",
-       "tt0000147     False  1897      20  Documentary,News,Sport          5.2   \n",
-       "tt0000335     False  1900    <NA>         Biography,Drama          6.3   \n",
-       "tt0000574     False  1906      70   Biography,Crime,Drama          6.2   \n",
-       "tt0000615     False  1907    <NA>                   Drama          4.8   \n",
-       "...             ...   ...     ...                     ...          ...   \n",
-       "tt9910930     False  2019      75       Crime,Documentary          4.6   \n",
-       "tt9911774     False  2019     130                   Drama          8.5   \n",
-       "tt9913056     False  2019      86             Documentary          6.2   \n",
-       "tt9913084     False  2019      75             Documentary          6.2   \n",
-       "tt9914286     False  2019      98            Drama,Family          9.8   \n",
-       "\n",
-       "           imdb_votes  \n",
-       "tconst                 \n",
-       "tt0000009          77  \n",
-       "tt0000147         289  \n",
-       "tt0000335          39  \n",
-       "tt0000574         505  \n",
-       "tt0000615          14  \n",
-       "...               ...  \n",
-       "tt9910930           5  \n",
-       "tt9911774         363  \n",
-       "tt9913056           5  \n",
-       "tt9913084           6  \n",
-       "tt9914286          72  \n",
-       "\n",
-       "[232496 rows x 8 columns]"
-      ]
-     },
-     "execution_count": 26,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# Alternativa 2 (taky dobrá)\n",
-    "pd.merge(movies, ratings, left_index=True, right_index=True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 27,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
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-       "\n",
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-       "\n",
-       "    .dataframe thead th {\n",
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-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>title</th>\n",
-       "      <th>original_title</th>\n",
-       "      <th>is_adult</th>\n",
-       "      <th>year</th>\n",
-       "      <th>length</th>\n",
-       "      <th>genres</th>\n",
-       "      <th>imdb_rating</th>\n",
-       "      <th>imdb_votes</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tconst</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>tt0000009</th>\n",
-       "      <td>Miss Jerry</td>\n",
-       "      <td>Miss Jerry</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1894</td>\n",
-       "      <td>45</td>\n",
-       "      <td>Romance</td>\n",
-       "      <td>5.5</td>\n",
-       "      <td>77</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt0000147</th>\n",
-       "      <td>The Corbett-Fitzsimmons Fight</td>\n",
-       "      <td>The Corbett-Fitzsimmons Fight</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1897</td>\n",
-       "      <td>20</td>\n",
-       "      <td>Documentary,News,Sport</td>\n",
-       "      <td>5.2</td>\n",
-       "      <td>289</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt0000335</th>\n",
-       "      <td>Soldiers of the Cross</td>\n",
-       "      <td>Soldiers of the Cross</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1900</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>Biography,Drama</td>\n",
-       "      <td>6.3</td>\n",
-       "      <td>39</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt0000574</th>\n",
-       "      <td>The Story of the Kelly Gang</td>\n",
-       "      <td>The Story of the Kelly Gang</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1906</td>\n",
-       "      <td>70</td>\n",
-       "      <td>Biography,Crime,Drama</td>\n",
-       "      <td>6.2</td>\n",
-       "      <td>505</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt0000615</th>\n",
-       "      <td>Robbery Under Arms</td>\n",
-       "      <td>Robbery Under Arms</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1907</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>Drama</td>\n",
-       "      <td>4.8</td>\n",
-       "      <td>14</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt9910930</th>\n",
-       "      <td>Jeg ser deg</td>\n",
-       "      <td>Jeg ser deg</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2019</td>\n",
-       "      <td>75</td>\n",
-       "      <td>Crime,Documentary</td>\n",
-       "      <td>4.6</td>\n",
-       "      <td>5</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt9911774</th>\n",
-       "      <td>Padmavyuhathile Abhimanyu</td>\n",
-       "      <td>Padmavyuhathile Abhimanyu</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2019</td>\n",
-       "      <td>130</td>\n",
-       "      <td>Drama</td>\n",
-       "      <td>8.5</td>\n",
-       "      <td>363</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt9913056</th>\n",
-       "      <td>Swarm Season</td>\n",
-       "      <td>Swarm Season</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2019</td>\n",
-       "      <td>86</td>\n",
-       "      <td>Documentary</td>\n",
-       "      <td>6.2</td>\n",
-       "      <td>5</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt9913084</th>\n",
-       "      <td>Diabolik sono io</td>\n",
-       "      <td>Diabolik sono io</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2019</td>\n",
-       "      <td>75</td>\n",
-       "      <td>Documentary</td>\n",
-       "      <td>6.2</td>\n",
-       "      <td>6</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tt9914286</th>\n",
-       "      <td>Sokagin Çocuklari</td>\n",
-       "      <td>Sokagin Çocuklari</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2019</td>\n",
-       "      <td>98</td>\n",
-       "      <td>Drama,Family</td>\n",
-       "      <td>9.8</td>\n",
-       "      <td>72</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>232496 rows × 8 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                                   title                 original_title  \\\n",
-       "tconst                                                                    \n",
-       "tt0000009                     Miss Jerry                     Miss Jerry   \n",
-       "tt0000147  The Corbett-Fitzsimmons Fight  The Corbett-Fitzsimmons Fight   \n",
-       "tt0000335          Soldiers of the Cross          Soldiers of the Cross   \n",
-       "tt0000574    The Story of the Kelly Gang    The Story of the Kelly Gang   \n",
-       "tt0000615             Robbery Under Arms             Robbery Under Arms   \n",
-       "...                                  ...                            ...   \n",
-       "tt9910930                    Jeg ser deg                    Jeg ser deg   \n",
-       "tt9911774      Padmavyuhathile Abhimanyu      Padmavyuhathile Abhimanyu   \n",
-       "tt9913056                   Swarm Season                   Swarm Season   \n",
-       "tt9913084               Diabolik sono io               Diabolik sono io   \n",
-       "tt9914286              Sokagin Çocuklari              Sokagin Çocuklari   \n",
-       "\n",
-       "           is_adult  year  length                  genres  imdb_rating  \\\n",
-       "tconst                                                                   \n",
-       "tt0000009     False  1894      45                 Romance          5.5   \n",
-       "tt0000147     False  1897      20  Documentary,News,Sport          5.2   \n",
-       "tt0000335     False  1900    <NA>         Biography,Drama          6.3   \n",
-       "tt0000574     False  1906      70   Biography,Crime,Drama          6.2   \n",
-       "tt0000615     False  1907    <NA>                   Drama          4.8   \n",
-       "...             ...   ...     ...                     ...          ...   \n",
-       "tt9910930     False  2019      75       Crime,Documentary          4.6   \n",
-       "tt9911774     False  2019     130                   Drama          8.5   \n",
-       "tt9913056     False  2019      86             Documentary          6.2   \n",
-       "tt9913084     False  2019      75             Documentary          6.2   \n",
-       "tt9914286     False  2019      98            Drama,Family          9.8   \n",
-       "\n",
-       "           imdb_votes  \n",
-       "tconst                 \n",
-       "tt0000009          77  \n",
-       "tt0000147         289  \n",
-       "tt0000335          39  \n",
-       "tt0000574         505  \n",
-       "tt0000615          14  \n",
-       "...               ...  \n",
-       "tt9910930           5  \n",
-       "tt9911774         363  \n",
-       "tt9913056           5  \n",
-       "tt9913084           6  \n",
-       "tt9914286          72  \n",
-       "\n",
-       "[232496 rows x 8 columns]"
-      ]
-     },
-     "execution_count": 27,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# Alternativa 3 (méně \"sémantická\")\n",
-    "pd.concat([movies, ratings], axis=\"columns\", join=\"inner\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Zkusme si zreprodukovat pořadí 250 nejlepších filmů z IMDb (viz https://www.imdb.com/chart/top/?ref_=nv_mv_250):"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 28,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
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-       "\n",
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-       "\n",
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-       "        text-align: right;\n",
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-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>title</th>\n",
-       "      <th>original_title</th>\n",
-       "      <th>is_adult</th>\n",
-       "      <th>year</th>\n",
-       "      <th>length</th>\n",
-       "      <th>genres</th>\n",
-       "      <th>imdb_rating</th>\n",
-       "      <th>imdb_votes</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>The Chaos Class</td>\n",
-       "      <td>Hababam Sinifi</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1975</td>\n",
-       "      <td>87</td>\n",
-       "      <td>Comedy,Drama</td>\n",
-       "      <td>9.4</td>\n",
-       "      <td>33394</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>The Shawshank Redemption</td>\n",
-       "      <td>The Shawshank Redemption</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1994</td>\n",
-       "      <td>142</td>\n",
-       "      <td>Drama</td>\n",
-       "      <td>9.3</td>\n",
-       "      <td>2071759</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>The Mountain II</td>\n",
-       "      <td>Dag II</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2016</td>\n",
-       "      <td>135</td>\n",
-       "      <td>Action,Drama,War</td>\n",
-       "      <td>9.3</td>\n",
-       "      <td>100095</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>CM101MMXI Fundamentals</td>\n",
-       "      <td>CM101MMXI Fundamentals</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2013</td>\n",
-       "      <td>139</td>\n",
-       "      <td>Comedy,Documentary</td>\n",
-       "      <td>9.2</td>\n",
-       "      <td>41327</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>The Godfather</td>\n",
-       "      <td>The Godfather</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1972</td>\n",
-       "      <td>175</td>\n",
-       "      <td>Crime,Drama</td>\n",
-       "      <td>9.2</td>\n",
-       "      <td>1421495</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>245</th>\n",
-       "      <td>12 Years a Slave</td>\n",
-       "      <td>12 Years a Slave</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2013</td>\n",
-       "      <td>134</td>\n",
-       "      <td>Biography,Drama,History</td>\n",
-       "      <td>8.1</td>\n",
-       "      <td>571204</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>246</th>\n",
-       "      <td>The Sixth Sense</td>\n",
-       "      <td>The Sixth Sense</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1999</td>\n",
-       "      <td>107</td>\n",
-       "      <td>Drama,Mystery,Thriller</td>\n",
-       "      <td>8.1</td>\n",
-       "      <td>836928</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>247</th>\n",
-       "      <td>The Passion of Joan of Arc</td>\n",
-       "      <td>La passion de Jeanne d'Arc</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1928</td>\n",
-       "      <td>110</td>\n",
-       "      <td>Biography,Drama,History</td>\n",
-       "      <td>8.1</td>\n",
-       "      <td>40107</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>248</th>\n",
-       "      <td>Barfi!</td>\n",
-       "      <td>Barfi!</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2012</td>\n",
-       "      <td>151</td>\n",
-       "      <td>Comedy,Drama,Romance</td>\n",
-       "      <td>8.1</td>\n",
-       "      <td>68274</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>249</th>\n",
-       "      <td>Platoon</td>\n",
-       "      <td>Platoon</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1986</td>\n",
-       "      <td>120</td>\n",
-       "      <td>Drama,War</td>\n",
-       "      <td>8.1</td>\n",
-       "      <td>348628</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>250 rows × 8 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                          title              original_title  is_adult  year  \\\n",
-       "0               The Chaos Class              Hababam Sinifi     False  1975   \n",
-       "1      The Shawshank Redemption    The Shawshank Redemption     False  1994   \n",
-       "2               The Mountain II                      Dag II     False  2016   \n",
-       "3        CM101MMXI Fundamentals      CM101MMXI Fundamentals     False  2013   \n",
-       "4                 The Godfather               The Godfather     False  1972   \n",
-       "..                          ...                         ...       ...   ...   \n",
-       "245            12 Years a Slave            12 Years a Slave     False  2013   \n",
-       "246             The Sixth Sense             The Sixth Sense     False  1999   \n",
-       "247  The Passion of Joan of Arc  La passion de Jeanne d'Arc     False  1928   \n",
-       "248                      Barfi!                      Barfi!     False  2012   \n",
-       "249                     Platoon                     Platoon     False  1986   \n",
-       "\n",
-       "     length                   genres  imdb_rating  imdb_votes  \n",
-       "0        87             Comedy,Drama          9.4       33394  \n",
-       "1       142                    Drama          9.3     2071759  \n",
-       "2       135         Action,Drama,War          9.3      100095  \n",
-       "3       139       Comedy,Documentary          9.2       41327  \n",
-       "4       175              Crime,Drama          9.2     1421495  \n",
-       "..      ...                      ...          ...         ...  \n",
-       "245     134  Biography,Drama,History          8.1      571204  \n",
-       "246     107   Drama,Mystery,Thriller          8.1      836928  \n",
-       "247     110  Biography,Drama,History          8.1       40107  \n",
-       "248     151     Comedy,Drama,Romance          8.1       68274  \n",
-       "249     120                Drama,War          8.1      348628  \n",
-       "\n",
-       "[250 rows x 8 columns]"
-      ]
-     },
-     "execution_count": 28,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# Ty nejlepší (do června 2019)\n",
-    "(movies_with_rating\n",
-    "    .query(\"imdb_votes > 25000\")                  # Berou se jen filmy s více než 25000 hlasy\n",
-    "    .sort_values(\"imdb_rating\", ascending=False)  # IMDb tu použivá i váhu jednotlivých hlasů (kterou neznáme)\n",
-    "    .reset_index(drop=True)\n",
-    ").iloc[:250]"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Do výčtu se nám dostaly filmy, které hranici hlasů nepřekračují o moc. Máme důvodné podezření, že toto kritérium dávno změnili. S požadovanými 250 000 hlasy se už blížíme:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 29,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
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-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>title</th>\n",
-       "      <th>original_title</th>\n",
-       "      <th>is_adult</th>\n",
-       "      <th>year</th>\n",
-       "      <th>length</th>\n",
-       "      <th>genres</th>\n",
-       "      <th>imdb_rating</th>\n",
-       "      <th>imdb_votes</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>The Shawshank Redemption</td>\n",
-       "      <td>The Shawshank Redemption</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1994</td>\n",
-       "      <td>142</td>\n",
-       "      <td>Drama</td>\n",
-       "      <td>9.3</td>\n",
-       "      <td>2071759</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>The Godfather</td>\n",
-       "      <td>The Godfather</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1972</td>\n",
-       "      <td>175</td>\n",
-       "      <td>Crime,Drama</td>\n",
-       "      <td>9.2</td>\n",
-       "      <td>1421495</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>The Dark Knight</td>\n",
-       "      <td>The Dark Knight</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2008</td>\n",
-       "      <td>152</td>\n",
-       "      <td>Action,Crime,Drama</td>\n",
-       "      <td>9.0</td>\n",
-       "      <td>2037678</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>The Godfather: Part II</td>\n",
-       "      <td>The Godfather: Part II</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1974</td>\n",
-       "      <td>202</td>\n",
-       "      <td>Crime,Drama</td>\n",
-       "      <td>9.0</td>\n",
-       "      <td>986451</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>Pulp Fiction</td>\n",
-       "      <td>Pulp Fiction</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1994</td>\n",
-       "      <td>154</td>\n",
-       "      <td>Crime,Drama</td>\n",
-       "      <td>8.9</td>\n",
-       "      <td>1620135</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>245</th>\n",
-       "      <td>Ocean's Eleven</td>\n",
-       "      <td>Ocean's Eleven</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2001</td>\n",
-       "      <td>116</td>\n",
-       "      <td>Crime,Thriller</td>\n",
-       "      <td>7.8</td>\n",
-       "      <td>470530</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>246</th>\n",
-       "      <td>Lost in Translation</td>\n",
-       "      <td>Lost in Translation</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2003</td>\n",
-       "      <td>102</td>\n",
-       "      <td>Drama</td>\n",
-       "      <td>7.8</td>\n",
-       "      <td>371577</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>247</th>\n",
-       "      <td>Donnie Brasco</td>\n",
-       "      <td>Donnie Brasco</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1997</td>\n",
-       "      <td>127</td>\n",
-       "      <td>Biography,Crime,Drama</td>\n",
-       "      <td>7.8</td>\n",
-       "      <td>253811</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>248</th>\n",
-       "      <td>Captain Phillips</td>\n",
-       "      <td>Captain Phillips</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2013</td>\n",
-       "      <td>134</td>\n",
-       "      <td>Biography,Drama,Thriller</td>\n",
-       "      <td>7.8</td>\n",
-       "      <td>384378</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>249</th>\n",
-       "      <td>How to Train Your Dragon 2</td>\n",
-       "      <td>How to Train Your Dragon 2</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2014</td>\n",
-       "      <td>102</td>\n",
-       "      <td>Action,Adventure,Animation</td>\n",
-       "      <td>7.8</td>\n",
-       "      <td>273406</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>250 rows × 8 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                          title              original_title  is_adult  year  \\\n",
-       "0      The Shawshank Redemption    The Shawshank Redemption     False  1994   \n",
-       "1                 The Godfather               The Godfather     False  1972   \n",
-       "2               The Dark Knight             The Dark Knight     False  2008   \n",
-       "3        The Godfather: Part II      The Godfather: Part II     False  1974   \n",
-       "4                  Pulp Fiction                Pulp Fiction     False  1994   \n",
-       "..                          ...                         ...       ...   ...   \n",
-       "245              Ocean's Eleven              Ocean's Eleven     False  2001   \n",
-       "246         Lost in Translation         Lost in Translation     False  2003   \n",
-       "247               Donnie Brasco               Donnie Brasco     False  1997   \n",
-       "248            Captain Phillips            Captain Phillips     False  2013   \n",
-       "249  How to Train Your Dragon 2  How to Train Your Dragon 2     False  2014   \n",
-       "\n",
-       "     length                      genres  imdb_rating  imdb_votes  \n",
-       "0       142                       Drama          9.3     2071759  \n",
-       "1       175                 Crime,Drama          9.2     1421495  \n",
-       "2       152          Action,Crime,Drama          9.0     2037678  \n",
-       "3       202                 Crime,Drama          9.0      986451  \n",
-       "4       154                 Crime,Drama          8.9     1620135  \n",
-       "..      ...                         ...          ...         ...  \n",
-       "245     116              Crime,Thriller          7.8      470530  \n",
-       "246     102                       Drama          7.8      371577  \n",
-       "247     127       Biography,Crime,Drama          7.8      253811  \n",
-       "248     134    Biography,Drama,Thriller          7.8      384378  \n",
-       "249     102  Action,Adventure,Animation          7.8      273406  \n",
-       "\n",
-       "[250 rows x 8 columns]"
-      ]
-     },
-     "execution_count": 29,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "(movies_with_rating\n",
-    "    .query(\"imdb_votes > 250000\")\n",
-    "    .sort_values(\"imdb_rating\", ascending=False)\n",
-    "    .reset_index(drop=True)\n",
-    ").iloc[:250]"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "#### Druhý join\n",
-    "\n",
-    "Co tabulka s výdělky (`boxoffice_raw`)?"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 30,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>rank</th>\n",
-       "      <th>title</th>\n",
-       "      <th>studio</th>\n",
-       "      <th>lifetime_gross</th>\n",
-       "      <th>year</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>1</td>\n",
-       "      <td>Star Wars: The Force Awakens</td>\n",
-       "      <td>BV</td>\n",
-       "      <td>936662225</td>\n",
-       "      <td>2015</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>2</td>\n",
-       "      <td>Avatar</td>\n",
-       "      <td>Fox</td>\n",
-       "      <td>760507625</td>\n",
-       "      <td>2009</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>3</td>\n",
-       "      <td>Black Panther</td>\n",
-       "      <td>BV</td>\n",
-       "      <td>700059566</td>\n",
-       "      <td>2018</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>4</td>\n",
-       "      <td>Avengers: Infinity War</td>\n",
-       "      <td>BV</td>\n",
-       "      <td>678815482</td>\n",
-       "      <td>2018</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>5</td>\n",
-       "      <td>Titanic</td>\n",
-       "      <td>Par.</td>\n",
-       "      <td>659363944</td>\n",
-       "      <td>1997</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>16262</th>\n",
-       "      <td>16263</td>\n",
-       "      <td>Dog Eat Dog</td>\n",
-       "      <td>IFC</td>\n",
-       "      <td>80</td>\n",
-       "      <td>2009</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>16263</th>\n",
-       "      <td>16264</td>\n",
-       "      <td>Paranoid Girls</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>78</td>\n",
-       "      <td>2015</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>16264</th>\n",
-       "      <td>16265</td>\n",
-       "      <td>Confession of a Child of the Century</td>\n",
-       "      <td>Cohen</td>\n",
-       "      <td>74</td>\n",
-       "      <td>2015</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>16265</th>\n",
-       "      <td>16266</td>\n",
-       "      <td>Storage 24</td>\n",
-       "      <td>Magn.</td>\n",
-       "      <td>72</td>\n",
-       "      <td>2013</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>16266</th>\n",
-       "      <td>16267</td>\n",
-       "      <td>Zyzzyx Road</td>\n",
-       "      <td>Reg.</td>\n",
-       "      <td>30</td>\n",
-       "      <td>2006</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>16267 rows × 5 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "        rank                                 title studio  lifetime_gross  \\\n",
-       "0          1          Star Wars: The Force Awakens     BV       936662225   \n",
-       "1          2                                Avatar    Fox       760507625   \n",
-       "2          3                         Black Panther     BV       700059566   \n",
-       "3          4                Avengers: Infinity War     BV       678815482   \n",
-       "4          5                               Titanic   Par.       659363944   \n",
-       "...      ...                                   ...    ...             ...   \n",
-       "16262  16263                           Dog Eat Dog    IFC              80   \n",
-       "16263  16264                        Paranoid Girls    NaN              78   \n",
-       "16264  16265  Confession of a Child of the Century  Cohen              74   \n",
-       "16265  16266                            Storage 24  Magn.              72   \n",
-       "16266  16267                           Zyzzyx Road   Reg.              30   \n",
-       "\n",
-       "       year  \n",
-       "0      2015  \n",
-       "1      2009  \n",
-       "2      2018  \n",
-       "3      2018  \n",
-       "4      1997  \n",
-       "...     ...  \n",
-       "16262  2009  \n",
-       "16263  2015  \n",
-       "16264  2015  \n",
-       "16265  2013  \n",
-       "16266  2006  \n",
-       "\n",
-       "[16267 rows x 5 columns]"
-      ]
-     },
-     "execution_count": 30,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "boxoffice_raw"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 31,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "rank               int64\n",
-       "title             object\n",
-       "studio            object\n",
-       "lifetime_gross     int64\n",
-       "year               int64\n",
-       "dtype: object"
-      ]
-     },
-     "execution_count": 31,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "boxoffice_raw.dtypes"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "S tím bychom v podstatně mohli být spokojení, jen přejmenujeme `rank`, abychom při joinování věděli, odkud daný sloupec pochází."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 32,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "boxoffice = (boxoffice_raw\n",
-    "    .rename({\n",
-    "        \"rank\": \"boxoffice_rank\"\n",
-    "    }, axis=\"columns\")\n",
-    ")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "A zkusíme joinovat. V tomto případě se nemůžeme opřít o index (`boxoffice` pochází z jiného zdroje a o nějakém ID filmu z IMDb nemá ani tuchy), ale explicitně specifikujeme, který sloupec (či sloupce) se musí shodovat - na to slouží argument `on`:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 33,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>title</th>\n",
-       "      <th>original_title</th>\n",
-       "      <th>is_adult</th>\n",
-       "      <th>year (imdb)</th>\n",
-       "      <th>length</th>\n",
-       "      <th>genres</th>\n",
-       "      <th>imdb_rating</th>\n",
-       "      <th>imdb_votes</th>\n",
-       "      <th>boxoffice_rank</th>\n",
-       "      <th>studio</th>\n",
-       "      <th>lifetime_gross</th>\n",
-       "      <th>year (boxoffice)</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>1643</th>\n",
-       "      <td>Pinocchio</td>\n",
-       "      <td>Pinocchio</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1940</td>\n",
-       "      <td>88</td>\n",
-       "      <td>Animation,Comedy,Family</td>\n",
-       "      <td>7.5</td>\n",
-       "      <td>114689</td>\n",
-       "      <td>885</td>\n",
-       "      <td>Dis.</td>\n",
-       "      <td>84254167</td>\n",
-       "      <td>1940</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1644</th>\n",
-       "      <td>Pinocchio</td>\n",
-       "      <td>Pinocchio</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1940</td>\n",
-       "      <td>88</td>\n",
-       "      <td>Animation,Comedy,Family</td>\n",
-       "      <td>7.5</td>\n",
-       "      <td>114689</td>\n",
-       "      <td>6108</td>\n",
-       "      <td>Mira.</td>\n",
-       "      <td>3684305</td>\n",
-       "      <td>2002</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1645</th>\n",
-       "      <td>Pinocchio</td>\n",
-       "      <td>Turlis Abenteuer</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1967</td>\n",
-       "      <td>75</td>\n",
-       "      <td>Adventure,Family,Fantasy</td>\n",
-       "      <td>7.2</td>\n",
-       "      <td>19</td>\n",
-       "      <td>885</td>\n",
-       "      <td>Dis.</td>\n",
-       "      <td>84254167</td>\n",
-       "      <td>1940</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1646</th>\n",
-       "      <td>Pinocchio</td>\n",
-       "      <td>Turlis Abenteuer</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1967</td>\n",
-       "      <td>75</td>\n",
-       "      <td>Adventure,Family,Fantasy</td>\n",
-       "      <td>7.2</td>\n",
-       "      <td>19</td>\n",
-       "      <td>6108</td>\n",
-       "      <td>Mira.</td>\n",
-       "      <td>3684305</td>\n",
-       "      <td>2002</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1647</th>\n",
-       "      <td>Pinocchio</td>\n",
-       "      <td>Pinocchio</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1971</td>\n",
-       "      <td>79</td>\n",
-       "      <td>Comedy,Fantasy</td>\n",
-       "      <td>3.5</td>\n",
-       "      <td>123</td>\n",
-       "      <td>885</td>\n",
-       "      <td>Dis.</td>\n",
-       "      <td>84254167</td>\n",
-       "      <td>1940</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1648</th>\n",
-       "      <td>Pinocchio</td>\n",
-       "      <td>Pinocchio</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1971</td>\n",
-       "      <td>79</td>\n",
-       "      <td>Comedy,Fantasy</td>\n",
-       "      <td>3.5</td>\n",
-       "      <td>123</td>\n",
-       "      <td>6108</td>\n",
-       "      <td>Mira.</td>\n",
-       "      <td>3684305</td>\n",
-       "      <td>2002</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1649</th>\n",
-       "      <td>Pinocchio</td>\n",
-       "      <td>Pinocchio</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1911</td>\n",
-       "      <td>50</td>\n",
-       "      <td>Fantasy</td>\n",
-       "      <td>5.9</td>\n",
-       "      <td>69</td>\n",
-       "      <td>885</td>\n",
-       "      <td>Dis.</td>\n",
-       "      <td>84254167</td>\n",
-       "      <td>1940</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1650</th>\n",
-       "      <td>Pinocchio</td>\n",
-       "      <td>Pinocchio</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1911</td>\n",
-       "      <td>50</td>\n",
-       "      <td>Fantasy</td>\n",
-       "      <td>5.9</td>\n",
-       "      <td>69</td>\n",
-       "      <td>6108</td>\n",
-       "      <td>Mira.</td>\n",
-       "      <td>3684305</td>\n",
-       "      <td>2002</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1651</th>\n",
-       "      <td>Pinocchio</td>\n",
-       "      <td>Pinocchio</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2002</td>\n",
-       "      <td>108</td>\n",
-       "      <td>Comedy,Family,Fantasy</td>\n",
-       "      <td>4.3</td>\n",
-       "      <td>7192</td>\n",
-       "      <td>885</td>\n",
-       "      <td>Dis.</td>\n",
-       "      <td>84254167</td>\n",
-       "      <td>1940</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1652</th>\n",
-       "      <td>Pinocchio</td>\n",
-       "      <td>Pinocchio</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2002</td>\n",
-       "      <td>108</td>\n",
-       "      <td>Comedy,Family,Fantasy</td>\n",
-       "      <td>4.3</td>\n",
-       "      <td>7192</td>\n",
-       "      <td>6108</td>\n",
-       "      <td>Mira.</td>\n",
-       "      <td>3684305</td>\n",
-       "      <td>2002</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1653</th>\n",
-       "      <td>Pinocchio</td>\n",
-       "      <td>Un burattino di nome Pinocchio</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1971</td>\n",
-       "      <td>96</td>\n",
-       "      <td>Animation,Family,Fantasy</td>\n",
-       "      <td>7.0</td>\n",
-       "      <td>117</td>\n",
-       "      <td>885</td>\n",
-       "      <td>Dis.</td>\n",
-       "      <td>84254167</td>\n",
-       "      <td>1940</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1654</th>\n",
-       "      <td>Pinocchio</td>\n",
-       "      <td>Un burattino di nome Pinocchio</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1971</td>\n",
-       "      <td>96</td>\n",
-       "      <td>Animation,Family,Fantasy</td>\n",
-       "      <td>7.0</td>\n",
-       "      <td>117</td>\n",
-       "      <td>6108</td>\n",
-       "      <td>Mira.</td>\n",
-       "      <td>3684305</td>\n",
-       "      <td>2002</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1655</th>\n",
-       "      <td>Pinocchio</td>\n",
-       "      <td>Pinocchio</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2012</td>\n",
-       "      <td>75</td>\n",
-       "      <td>Animation,Family,Fantasy</td>\n",
-       "      <td>6.3</td>\n",
-       "      <td>218</td>\n",
-       "      <td>885</td>\n",
-       "      <td>Dis.</td>\n",
-       "      <td>84254167</td>\n",
-       "      <td>1940</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1656</th>\n",
-       "      <td>Pinocchio</td>\n",
-       "      <td>Pinocchio</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2012</td>\n",
-       "      <td>75</td>\n",
-       "      <td>Animation,Family,Fantasy</td>\n",
-       "      <td>6.3</td>\n",
-       "      <td>218</td>\n",
-       "      <td>6108</td>\n",
-       "      <td>Mira.</td>\n",
-       "      <td>3684305</td>\n",
-       "      <td>2002</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1657</th>\n",
-       "      <td>Pinocchio</td>\n",
-       "      <td>Pinocchio</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2015</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>Family,Fantasy</td>\n",
-       "      <td>4.9</td>\n",
-       "      <td>43</td>\n",
-       "      <td>885</td>\n",
-       "      <td>Dis.</td>\n",
-       "      <td>84254167</td>\n",
-       "      <td>1940</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1658</th>\n",
-       "      <td>Pinocchio</td>\n",
-       "      <td>Pinocchio</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2015</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>Family,Fantasy</td>\n",
-       "      <td>4.9</td>\n",
-       "      <td>43</td>\n",
-       "      <td>6108</td>\n",
-       "      <td>Mira.</td>\n",
-       "      <td>3684305</td>\n",
-       "      <td>2002</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1659</th>\n",
-       "      <td>Pinocchio</td>\n",
-       "      <td>Pinocchio</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2015</td>\n",
-       "      <td>75</td>\n",
-       "      <td>Documentary</td>\n",
-       "      <td>6.8</td>\n",
-       "      <td>8</td>\n",
-       "      <td>885</td>\n",
-       "      <td>Dis.</td>\n",
-       "      <td>84254167</td>\n",
-       "      <td>1940</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1660</th>\n",
-       "      <td>Pinocchio</td>\n",
-       "      <td>Pinocchio</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2015</td>\n",
-       "      <td>75</td>\n",
-       "      <td>Documentary</td>\n",
-       "      <td>6.8</td>\n",
-       "      <td>8</td>\n",
-       "      <td>6108</td>\n",
-       "      <td>Mira.</td>\n",
-       "      <td>3684305</td>\n",
-       "      <td>2002</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "          title                  original_title  is_adult  year (imdb)  \\\n",
-       "1643  Pinocchio                       Pinocchio     False         1940   \n",
-       "1644  Pinocchio                       Pinocchio     False         1940   \n",
-       "1645  Pinocchio                Turlis Abenteuer     False         1967   \n",
-       "1646  Pinocchio                Turlis Abenteuer     False         1967   \n",
-       "1647  Pinocchio                       Pinocchio     False         1971   \n",
-       "1648  Pinocchio                       Pinocchio     False         1971   \n",
-       "1649  Pinocchio                       Pinocchio     False         1911   \n",
-       "1650  Pinocchio                       Pinocchio     False         1911   \n",
-       "1651  Pinocchio                       Pinocchio     False         2002   \n",
-       "1652  Pinocchio                       Pinocchio     False         2002   \n",
-       "1653  Pinocchio  Un burattino di nome Pinocchio     False         1971   \n",
-       "1654  Pinocchio  Un burattino di nome Pinocchio     False         1971   \n",
-       "1655  Pinocchio                       Pinocchio     False         2012   \n",
-       "1656  Pinocchio                       Pinocchio     False         2012   \n",
-       "1657  Pinocchio                       Pinocchio     False         2015   \n",
-       "1658  Pinocchio                       Pinocchio     False         2015   \n",
-       "1659  Pinocchio                       Pinocchio     False         2015   \n",
-       "1660  Pinocchio                       Pinocchio     False         2015   \n",
-       "\n",
-       "      length                    genres  imdb_rating  imdb_votes  \\\n",
-       "1643      88   Animation,Comedy,Family          7.5      114689   \n",
-       "1644      88   Animation,Comedy,Family          7.5      114689   \n",
-       "1645      75  Adventure,Family,Fantasy          7.2          19   \n",
-       "1646      75  Adventure,Family,Fantasy          7.2          19   \n",
-       "1647      79            Comedy,Fantasy          3.5         123   \n",
-       "1648      79            Comedy,Fantasy          3.5         123   \n",
-       "1649      50                   Fantasy          5.9          69   \n",
-       "1650      50                   Fantasy          5.9          69   \n",
-       "1651     108     Comedy,Family,Fantasy          4.3        7192   \n",
-       "1652     108     Comedy,Family,Fantasy          4.3        7192   \n",
-       "1653      96  Animation,Family,Fantasy          7.0         117   \n",
-       "1654      96  Animation,Family,Fantasy          7.0         117   \n",
-       "1655      75  Animation,Family,Fantasy          6.3         218   \n",
-       "1656      75  Animation,Family,Fantasy          6.3         218   \n",
-       "1657    <NA>            Family,Fantasy          4.9          43   \n",
-       "1658    <NA>            Family,Fantasy          4.9          43   \n",
-       "1659      75               Documentary          6.8           8   \n",
-       "1660      75               Documentary          6.8           8   \n",
-       "\n",
-       "      boxoffice_rank studio  lifetime_gross  year (boxoffice)  \n",
-       "1643             885   Dis.        84254167              1940  \n",
-       "1644            6108  Mira.         3684305              2002  \n",
-       "1645             885   Dis.        84254167              1940  \n",
-       "1646            6108  Mira.         3684305              2002  \n",
-       "1647             885   Dis.        84254167              1940  \n",
-       "1648            6108  Mira.         3684305              2002  \n",
-       "1649             885   Dis.        84254167              1940  \n",
-       "1650            6108  Mira.         3684305              2002  \n",
-       "1651             885   Dis.        84254167              1940  \n",
-       "1652            6108  Mira.         3684305              2002  \n",
-       "1653             885   Dis.        84254167              1940  \n",
-       "1654            6108  Mira.         3684305              2002  \n",
-       "1655             885   Dis.        84254167              1940  \n",
-       "1656            6108  Mira.         3684305              2002  \n",
-       "1657             885   Dis.        84254167              1940  \n",
-       "1658            6108  Mira.         3684305              2002  \n",
-       "1659             885   Dis.        84254167              1940  \n",
-       "1660            6108  Mira.         3684305              2002  "
-      ]
-     },
-     "execution_count": 33,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "pd.merge(\n",
-    "    movies_with_rating,\n",
-    "    boxoffice,\n",
-    "    suffixes=[\" (imdb)\", \" (boxoffice)\"],\n",
-    "    on=\"title\"\n",
-    ").query(\"title == 'Pinocchio'\")  # \"Jeden\" ukázkový film"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Jejda, to jsme asi nechtěli. Existuje spousta různých Pinocchiů a ke každému z nich se připojili vždy oba snímky tohoto jména z `boxoffice`. Z toho vyplývá poučení, že při joinování je dobré se zamyslet nad jedinečností hodnot ve sloupci, který používáme jako klíč. Jméno filmu takové očividně není.\n",
-    "\n",
-    "V našem konkrétním případě jsme si problému všimli sami, ale pokud bude duplikátní klíč utopen někde v milionech hodnot, rádi bychom, aby to počítač poznal za nás. K tomu slouží argument `validate` - podle toho, jaký vztah mezi tabulkami očekáš, jsou přípustné hodnoty `\"one_to_one\"`, `\"one_to_many\"`, `\"many_to_one\"` nebo `\"many_to_many\"`:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 34,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>title</th>\n",
-       "      <th>original_title</th>\n",
-       "      <th>is_adult</th>\n",
-       "      <th>year (imdb)</th>\n",
-       "      <th>length</th>\n",
-       "      <th>genres</th>\n",
-       "      <th>imdb_rating</th>\n",
-       "      <th>imdb_votes</th>\n",
-       "      <th>boxoffice_rank</th>\n",
-       "      <th>studio</th>\n",
-       "      <th>lifetime_gross</th>\n",
-       "      <th>year (boxoffice)</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>Oliver Twist</td>\n",
-       "      <td>Oliver Twist</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1912</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>Drama</td>\n",
-       "      <td>4.7</td>\n",
-       "      <td>19</td>\n",
-       "      <td>6826</td>\n",
-       "      <td>Sony</td>\n",
-       "      <td>2080321</td>\n",
-       "      <td>2005</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>Oliver Twist</td>\n",
-       "      <td>Oliver Twist</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1912</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>Drama</td>\n",
-       "      <td>4.4</td>\n",
-       "      <td>12</td>\n",
-       "      <td>6826</td>\n",
-       "      <td>Sony</td>\n",
-       "      <td>2080321</td>\n",
-       "      <td>2005</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>Oliver Twist</td>\n",
-       "      <td>Oliver Twist</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1916</td>\n",
-       "      <td>50</td>\n",
-       "      <td>Drama</td>\n",
-       "      <td>6.6</td>\n",
-       "      <td>16</td>\n",
-       "      <td>6826</td>\n",
-       "      <td>Sony</td>\n",
-       "      <td>2080321</td>\n",
-       "      <td>2005</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>Oliver Twist</td>\n",
-       "      <td>Oliver Twist</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1922</td>\n",
-       "      <td>98</td>\n",
-       "      <td>Drama</td>\n",
-       "      <td>6.8</td>\n",
-       "      <td>657</td>\n",
-       "      <td>6826</td>\n",
-       "      <td>Sony</td>\n",
-       "      <td>2080321</td>\n",
-       "      <td>2005</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>Oliver Twist</td>\n",
-       "      <td>Oliver Twist</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1933</td>\n",
-       "      <td>80</td>\n",
-       "      <td>Drama</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>292</td>\n",
-       "      <td>6826</td>\n",
-       "      <td>Sony</td>\n",
-       "      <td>2080321</td>\n",
-       "      <td>2005</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>20562</th>\n",
-       "      <td>BTS World Tour: Love Yourself in Seoul</td>\n",
-       "      <td>BTS World Tour: Love Yourself in Seoul</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2019</td>\n",
-       "      <td>112</td>\n",
-       "      <td>Documentary,Music</td>\n",
-       "      <td>8.5</td>\n",
-       "      <td>439</td>\n",
-       "      <td>6173</td>\n",
-       "      <td>Fathom</td>\n",
-       "      <td>3509917</td>\n",
-       "      <td>2019</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>20563</th>\n",
-       "      <td>Mojin: The Worm Valley</td>\n",
-       "      <td>Yun nan chong gu</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2018</td>\n",
-       "      <td>110</td>\n",
-       "      <td>Action,Fantasy</td>\n",
-       "      <td>4.7</td>\n",
-       "      <td>120</td>\n",
-       "      <td>11240</td>\n",
-       "      <td>WGUSA</td>\n",
-       "      <td>101516</td>\n",
-       "      <td>2019</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>20564</th>\n",
-       "      <td>Extreme Job</td>\n",
-       "      <td>Geukhanjikeob</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2019</td>\n",
-       "      <td>111</td>\n",
-       "      <td>Action,Comedy</td>\n",
-       "      <td>7.3</td>\n",
-       "      <td>905</td>\n",
-       "      <td>7212</td>\n",
-       "      <td>CJ</td>\n",
-       "      <td>1548816</td>\n",
-       "      <td>2019</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>20565</th>\n",
-       "      <td>Peppa Celebrates Chinese New Year</td>\n",
-       "      <td>xiao zhu pei qi guo da nian</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2019</td>\n",
-       "      <td>81</td>\n",
-       "      <td>Animation,Family</td>\n",
-       "      <td>3.4</td>\n",
-       "      <td>41</td>\n",
-       "      <td>10811</td>\n",
-       "      <td>STX</td>\n",
-       "      <td>131225</td>\n",
-       "      <td>2019</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>20566</th>\n",
-       "      <td>Avant qu'on explose</td>\n",
-       "      <td>Avant qu'on explose</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2019</td>\n",
-       "      <td>108</td>\n",
-       "      <td>Comedy</td>\n",
-       "      <td>6.9</td>\n",
-       "      <td>41</td>\n",
-       "      <td>10995</td>\n",
-       "      <td>EOne</td>\n",
-       "      <td>116576</td>\n",
-       "      <td>2019</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>20567 rows × 12 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                                        title  \\\n",
-       "0                                Oliver Twist   \n",
-       "1                                Oliver Twist   \n",
-       "2                                Oliver Twist   \n",
-       "3                                Oliver Twist   \n",
-       "4                                Oliver Twist   \n",
-       "...                                       ...   \n",
-       "20562  BTS World Tour: Love Yourself in Seoul   \n",
-       "20563                  Mojin: The Worm Valley   \n",
-       "20564                             Extreme Job   \n",
-       "20565       Peppa Celebrates Chinese New Year   \n",
-       "20566                     Avant qu'on explose   \n",
-       "\n",
-       "                               original_title  is_adult  year (imdb)  length  \\\n",
-       "0                                Oliver Twist     False         1912    <NA>   \n",
-       "1                                Oliver Twist     False         1912    <NA>   \n",
-       "2                                Oliver Twist     False         1916      50   \n",
-       "3                                Oliver Twist     False         1922      98   \n",
-       "4                                Oliver Twist     False         1933      80   \n",
-       "...                                       ...       ...          ...     ...   \n",
-       "20562  BTS World Tour: Love Yourself in Seoul     False         2019     112   \n",
-       "20563                        Yun nan chong gu     False         2018     110   \n",
-       "20564                           Geukhanjikeob     False         2019     111   \n",
-       "20565             xiao zhu pei qi guo da nian     False         2019      81   \n",
-       "20566                     Avant qu'on explose     False         2019     108   \n",
-       "\n",
-       "                  genres  imdb_rating  imdb_votes  boxoffice_rank  studio  \\\n",
-       "0                  Drama          4.7          19            6826    Sony   \n",
-       "1                  Drama          4.4          12            6826    Sony   \n",
-       "2                  Drama          6.6          16            6826    Sony   \n",
-       "3                  Drama          6.8         657            6826    Sony   \n",
-       "4                  Drama          5.0         292            6826    Sony   \n",
-       "...                  ...          ...         ...             ...     ...   \n",
-       "20562  Documentary,Music          8.5         439            6173  Fathom   \n",
-       "20563     Action,Fantasy          4.7         120           11240   WGUSA   \n",
-       "20564      Action,Comedy          7.3         905            7212      CJ   \n",
-       "20565   Animation,Family          3.4          41           10811     STX   \n",
-       "20566             Comedy          6.9          41           10995    EOne   \n",
-       "\n",
-       "       lifetime_gross  year (boxoffice)  \n",
-       "0             2080321              2005  \n",
-       "1             2080321              2005  \n",
-       "2             2080321              2005  \n",
-       "3             2080321              2005  \n",
-       "4             2080321              2005  \n",
-       "...               ...               ...  \n",
-       "20562         3509917              2019  \n",
-       "20563          101516              2019  \n",
-       "20564         1548816              2019  \n",
-       "20565          131225              2019  \n",
-       "20566          116576              2019  \n",
-       "\n",
-       "[20567 rows x 12 columns]"
-      ]
-     },
-     "execution_count": 34,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "pd.merge(\n",
-    "    movies_with_rating,\n",
-    "    boxoffice,\n",
-    "    on=\"title\",\n",
-    "    suffixes=[\" (imdb)\", \" (boxoffice)\"],\n",
-    "#    validate=\"one_to_one\"    # Odkomentuj a vyskočí chyba!\n",
-    ")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Řešení je jednoduché - budeme joinovat přes dva různé sloupce (argument `on` to unese ;-)). Při té příležitosti navíc zjišťujeme, že nedává smysl spojovat filmy, které rok vůbec uvedený nemají, a proto je vyhodíme:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 35,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>title</th>\n",
-       "      <th>original_title</th>\n",
-       "      <th>is_adult</th>\n",
-       "      <th>year</th>\n",
-       "      <th>length</th>\n",
-       "      <th>genres</th>\n",
-       "      <th>imdb_rating</th>\n",
-       "      <th>imdb_votes</th>\n",
-       "      <th>boxoffice_rank</th>\n",
-       "      <th>studio</th>\n",
-       "      <th>lifetime_gross</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>6926</th>\n",
-       "      <td>Playback</td>\n",
-       "      <td>Playback</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2012</td>\n",
-       "      <td>98</td>\n",
-       "      <td>Horror,Thriller</td>\n",
-       "      <td>4.3</td>\n",
-       "      <td>4478</td>\n",
-       "      <td>16256</td>\n",
-       "      <td>Magn.</td>\n",
-       "      <td>264</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6927</th>\n",
-       "      <td>Playback</td>\n",
-       "      <td>Playback</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2012</td>\n",
-       "      <td>113</td>\n",
-       "      <td>Drama</td>\n",
-       "      <td>4.9</td>\n",
-       "      <td>27</td>\n",
-       "      <td>16256</td>\n",
-       "      <td>Magn.</td>\n",
-       "      <td>264</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6928</th>\n",
-       "      <td>Playback</td>\n",
-       "      <td>Dur d'être Dieu</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2012</td>\n",
-       "      <td>66</td>\n",
-       "      <td>Documentary</td>\n",
-       "      <td>5.2</td>\n",
-       "      <td>8</td>\n",
-       "      <td>16256</td>\n",
-       "      <td>Magn.</td>\n",
-       "      <td>264</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "         title   original_title  is_adult  year  length           genres  \\\n",
-       "6926  Playback         Playback     False  2012      98  Horror,Thriller   \n",
-       "6927  Playback         Playback     False  2012     113            Drama   \n",
-       "6928  Playback  Dur d'être Dieu     False  2012      66      Documentary   \n",
-       "\n",
-       "      imdb_rating  imdb_votes  boxoffice_rank studio  lifetime_gross  \n",
-       "6926          4.3        4478           16256  Magn.             264  \n",
-       "6927          4.9          27           16256  Magn.             264  \n",
-       "6928          5.2           8           16256  Magn.             264  "
-      ]
-     },
-     "execution_count": 35,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "(\n",
-    "    pd.merge(\n",
-    "        movies_with_rating.dropna(subset=[\"year\"]),  # Vyhoď všechny řádky bez roku\n",
-    "        boxoffice,\n",
-    "        on=[\"title\", \"year\"],\n",
-    "        validate=\"many_to_one\",      # movies_with_rating pořád nejsou unikátní!\n",
-    "    )\n",
-    ").query(\"title == 'Playback'\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Pořád nejsou unikátní! Co s tím?\n",
-    "\n",
-    "**Hypotéza:** Vstupujeme na nebezpečnou půdu a zkusíme spekulovat, že informace o ziscích budeme mít nejspíš jen o nejpopulárnějších filmech. Možná máme pravdu, možná ne a nejspíš nějakou drobnou nepřesnost zaneseme, ale dobrat se tady skutečné pravdy je \"drahé\" (a možná i skutečně drahé), z nabízených datových sad to věrohodně možné není.\n",
-    "\n",
-    "Abychom se co nejvíc přiblížili realitě, z každé opakující se dvojice (název, rok) vybereme film s nejvyšším `imdb_votes`. Nejdříve si pomocí `sort_values` srovnáme všechny filmy a pak zavoláme `drop_duplicates(..., keep=\"first\")`, což nám ponechá vždy jen jeden z řady duplikátů:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 36,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>title</th>\n",
-       "      <th>original_title</th>\n",
-       "      <th>is_adult</th>\n",
-       "      <th>year</th>\n",
-       "      <th>length</th>\n",
-       "      <th>genres</th>\n",
-       "      <th>imdb_rating</th>\n",
-       "      <th>imdb_votes</th>\n",
-       "      <th>boxoffice_rank</th>\n",
-       "      <th>studio</th>\n",
-       "      <th>lifetime_gross</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>The Shawshank Redemption</td>\n",
-       "      <td>The Shawshank Redemption</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1994</td>\n",
-       "      <td>142</td>\n",
-       "      <td>Drama</td>\n",
-       "      <td>9.3</td>\n",
-       "      <td>2071759</td>\n",
-       "      <td>2792</td>\n",
-       "      <td>Col.</td>\n",
-       "      <td>28341469</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>The Dark Knight</td>\n",
-       "      <td>The Dark Knight</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2008</td>\n",
-       "      <td>152</td>\n",
-       "      <td>Action,Crime,Drama</td>\n",
-       "      <td>9.0</td>\n",
-       "      <td>2037678</td>\n",
-       "      <td>10</td>\n",
-       "      <td>WB</td>\n",
-       "      <td>535234033</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>Inception</td>\n",
-       "      <td>Inception</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2010</td>\n",
-       "      <td>148</td>\n",
-       "      <td>Action,Adventure,Sci-Fi</td>\n",
-       "      <td>8.8</td>\n",
-       "      <td>1816360</td>\n",
-       "      <td>85</td>\n",
-       "      <td>WB</td>\n",
-       "      <td>292576195</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>Fight Club</td>\n",
-       "      <td>Fight Club</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1999</td>\n",
-       "      <td>139</td>\n",
-       "      <td>Drama</td>\n",
-       "      <td>8.8</td>\n",
-       "      <td>1657857</td>\n",
-       "      <td>2248</td>\n",
-       "      <td>Fox</td>\n",
-       "      <td>37030102</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>Pulp Fiction</td>\n",
-       "      <td>Pulp Fiction</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1994</td>\n",
-       "      <td>154</td>\n",
-       "      <td>Crime,Drama</td>\n",
-       "      <td>8.9</td>\n",
-       "      <td>1620135</td>\n",
-       "      <td>629</td>\n",
-       "      <td>Mira.</td>\n",
-       "      <td>107928762</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8996</th>\n",
-       "      <td>Girlfriends</td>\n",
-       "      <td>Girlfriends</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1996</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>8.6</td>\n",
-       "      <td>7</td>\n",
-       "      <td>13930</td>\n",
-       "      <td>FRun</td>\n",
-       "      <td>18000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8997</th>\n",
-       "      <td>Sacred</td>\n",
-       "      <td>Sacred</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2017</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>Action,Drama,Romance</td>\n",
-       "      <td>8.2</td>\n",
-       "      <td>6</td>\n",
-       "      <td>13950</td>\n",
-       "      <td>Argo.</td>\n",
-       "      <td>17740</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8998</th>\n",
-       "      <td>The Professor: Tai Chi's Journey West</td>\n",
-       "      <td>The Professor: Tai Chi's Journey West</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2016</td>\n",
-       "      <td>72</td>\n",
-       "      <td>Documentary</td>\n",
-       "      <td>7.2</td>\n",
-       "      <td>6</td>\n",
-       "      <td>15820</td>\n",
-       "      <td>FRun</td>\n",
-       "      <td>2852</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8999</th>\n",
-       "      <td>After Love</td>\n",
-       "      <td>After Love</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2017</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>Drama,Romance,Thriller</td>\n",
-       "      <td>7.6</td>\n",
-       "      <td>5</td>\n",
-       "      <td>14299</td>\n",
-       "      <td>Distrib.</td>\n",
-       "      <td>13693</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>9000</th>\n",
-       "      <td>Still, the Children Are Here</td>\n",
-       "      <td>Still, the Children Are Here</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2004</td>\n",
-       "      <td>85</td>\n",
-       "      <td>Documentary</td>\n",
-       "      <td>6.6</td>\n",
-       "      <td>5</td>\n",
-       "      <td>15653</td>\n",
-       "      <td>Icar.</td>\n",
-       "      <td>3685</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>9001 rows × 11 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                                      title  \\\n",
-       "0                  The Shawshank Redemption   \n",
-       "1                           The Dark Knight   \n",
-       "2                                 Inception   \n",
-       "3                                Fight Club   \n",
-       "4                              Pulp Fiction   \n",
-       "...                                     ...   \n",
-       "8996                            Girlfriends   \n",
-       "8997                                 Sacred   \n",
-       "8998  The Professor: Tai Chi's Journey West   \n",
-       "8999                             After Love   \n",
-       "9000           Still, the Children Are Here   \n",
-       "\n",
-       "                             original_title  is_adult  year  length  \\\n",
-       "0                  The Shawshank Redemption     False  1994     142   \n",
-       "1                           The Dark Knight     False  2008     152   \n",
-       "2                                 Inception     False  2010     148   \n",
-       "3                                Fight Club     False  1999     139   \n",
-       "4                              Pulp Fiction     False  1994     154   \n",
-       "...                                     ...       ...   ...     ...   \n",
-       "8996                            Girlfriends     False  1996    <NA>   \n",
-       "8997                                 Sacred     False  2017    <NA>   \n",
-       "8998  The Professor: Tai Chi's Journey West     False  2016      72   \n",
-       "8999                             After Love     False  2017    <NA>   \n",
-       "9000           Still, the Children Are Here     False  2004      85   \n",
-       "\n",
-       "                       genres  imdb_rating  imdb_votes  boxoffice_rank  \\\n",
-       "0                       Drama          9.3     2071759            2792   \n",
-       "1          Action,Crime,Drama          9.0     2037678              10   \n",
-       "2     Action,Adventure,Sci-Fi          8.8     1816360              85   \n",
-       "3                       Drama          8.8     1657857            2248   \n",
-       "4                 Crime,Drama          8.9     1620135             629   \n",
-       "...                       ...          ...         ...             ...   \n",
-       "8996                      NaN          8.6           7           13930   \n",
-       "8997     Action,Drama,Romance          8.2           6           13950   \n",
-       "8998              Documentary          7.2           6           15820   \n",
-       "8999   Drama,Romance,Thriller          7.6           5           14299   \n",
-       "9000              Documentary          6.6           5           15653   \n",
-       "\n",
-       "        studio  lifetime_gross  \n",
-       "0         Col.        28341469  \n",
-       "1           WB       535234033  \n",
-       "2           WB       292576195  \n",
-       "3          Fox        37030102  \n",
-       "4        Mira.       107928762  \n",
-       "...        ...             ...  \n",
-       "8996      FRun           18000  \n",
-       "8997     Argo.           17740  \n",
-       "8998      FRun            2852  \n",
-       "8999  Distrib.           13693  \n",
-       "9000     Icar.            3685  \n",
-       "\n",
-       "[9001 rows x 11 columns]"
-      ]
-     },
-     "execution_count": 36,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "movies_with_rating_and_boxoffice = (\n",
-    "    pd.merge(\n",
-    "        movies_with_rating\n",
-    "            .dropna(subset=[\"year\"])\n",
-    "            .sort_values(\"imdb_votes\", ascending=False)\n",
-    "            .drop_duplicates(\n",
-    "                subset=[\"title\", \"year\"],\n",
-    "                keep=\"first\"\n",
-    "            ),\n",
-    "        boxoffice,\n",
-    "        on=[\"title\", \"year\"],\n",
-    "        validate=\"one_to_one\",\n",
-    "    )\n",
-    ")\n",
-    "movies_with_rating_and_boxoffice"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 37,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>title</th>\n",
-       "      <th>original_title</th>\n",
-       "      <th>is_adult</th>\n",
-       "      <th>year</th>\n",
-       "      <th>length</th>\n",
-       "      <th>genres</th>\n",
-       "      <th>imdb_rating</th>\n",
-       "      <th>imdb_votes</th>\n",
-       "      <th>boxoffice_rank</th>\n",
-       "      <th>studio</th>\n",
-       "      <th>lifetime_gross</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>5831</th>\n",
-       "      <td>Playback</td>\n",
-       "      <td>Playback</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2012</td>\n",
-       "      <td>98</td>\n",
-       "      <td>Horror,Thriller</td>\n",
-       "      <td>4.3</td>\n",
-       "      <td>4478</td>\n",
-       "      <td>16256</td>\n",
-       "      <td>Magn.</td>\n",
-       "      <td>264</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "         title original_title  is_adult  year  length           genres  \\\n",
-       "5831  Playback       Playback     False  2012      98  Horror,Thriller   \n",
-       "\n",
-       "      imdb_rating  imdb_votes  boxoffice_rank studio  lifetime_gross  \n",
-       "5831          4.3        4478           16256  Magn.             264  "
-      ]
-     },
-     "execution_count": 37,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# To už by šlo!\n",
-    "movies_with_rating_and_boxoffice.query(\"title == 'Playback'\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "**Úkol:** Seřaď filmy podle toho, kolik vydělaly (nabízí se hned dvě možnosti)."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "**Otázka:** Které filmy nám vypadly a proč?"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "#### Třetí join"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 38,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>Rank</th>\n",
-       "      <th>Title</th>\n",
-       "      <th>RatingTomatometer</th>\n",
-       "      <th>No. of Reviews</th>\n",
-       "      <th>Genres</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>1</td>\n",
-       "      <td>Black Panther (2018)</td>\n",
-       "      <td>97</td>\n",
-       "      <td>444</td>\n",
-       "      <td>action|adventure</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>2</td>\n",
-       "      <td>Mad Max: Fury Road (2015)</td>\n",
-       "      <td>97</td>\n",
-       "      <td>394</td>\n",
-       "      <td>action|adventure</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>3</td>\n",
-       "      <td>Wonder Woman (2017)</td>\n",
-       "      <td>93</td>\n",
-       "      <td>410</td>\n",
-       "      <td>action|adventure</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>4</td>\n",
-       "      <td>Metropolis (1927)</td>\n",
-       "      <td>99</td>\n",
-       "      <td>118</td>\n",
-       "      <td>action|adventure</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>5</td>\n",
-       "      <td>Coco (2017)</td>\n",
-       "      <td>97</td>\n",
-       "      <td>308</td>\n",
-       "      <td>action|adventure</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1585</th>\n",
-       "      <td>70</td>\n",
-       "      <td>Priest (2011)</td>\n",
-       "      <td>15</td>\n",
-       "      <td>97</td>\n",
-       "      <td>western</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1586</th>\n",
-       "      <td>71</td>\n",
-       "      <td>American Outlaws (2001)</td>\n",
-       "      <td>14</td>\n",
-       "      <td>103</td>\n",
-       "      <td>western</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1587</th>\n",
-       "      <td>72</td>\n",
-       "      <td>September Dawn (2007)</td>\n",
-       "      <td>15</td>\n",
-       "      <td>54</td>\n",
-       "      <td>western</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1588</th>\n",
-       "      <td>73</td>\n",
-       "      <td>Jonah Hex (2010)</td>\n",
-       "      <td>12</td>\n",
-       "      <td>147</td>\n",
-       "      <td>western</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1589</th>\n",
-       "      <td>74</td>\n",
-       "      <td>Texas Rangers (2001)</td>\n",
-       "      <td>2</td>\n",
-       "      <td>51</td>\n",
-       "      <td>western</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>1590 rows × 5 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "      Rank                      Title  RatingTomatometer  No. of Reviews  \\\n",
-       "0        1       Black Panther (2018)                 97             444   \n",
-       "1        2  Mad Max: Fury Road (2015)                 97             394   \n",
-       "2        3        Wonder Woman (2017)                 93             410   \n",
-       "3        4          Metropolis (1927)                 99             118   \n",
-       "4        5                Coco (2017)                 97             308   \n",
-       "...    ...                        ...                ...             ...   \n",
-       "1585    70              Priest (2011)                 15              97   \n",
-       "1586    71    American Outlaws (2001)                 14             103   \n",
-       "1587    72      September Dawn (2007)                 15              54   \n",
-       "1588    73           Jonah Hex (2010)                 12             147   \n",
-       "1589    74       Texas Rangers (2001)                  2              51   \n",
-       "\n",
-       "                Genres  \n",
-       "0     action|adventure  \n",
-       "1     action|adventure  \n",
-       "2     action|adventure  \n",
-       "3     action|adventure  \n",
-       "4     action|adventure  \n",
-       "...                ...  \n",
-       "1585           western  \n",
-       "1586           western  \n",
-       "1587           western  \n",
-       "1588           western  \n",
-       "1589           western  \n",
-       "\n",
-       "[1590 rows x 5 columns]"
-      ]
-     },
-     "execution_count": 38,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "rotten_tomatoes_raw"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 39,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "Title\n",
-       "Yellow Submarine (1968)                                 6\n",
-       "101 Dalmatians (1961)                                   5\n",
-       "Fantasia (1940)                                         5\n",
-       "Harry Potter and the Deathly Hallows - Part 2 (2011)    5\n",
-       "Miracle on 34th Street (1947)                           5\n",
-       "                                                       ..\n",
-       "Misery (1990)                                           1\n",
-       "The Dead Zone (1983)                                    1\n",
-       "The Conjuring (2013)                                    1\n",
-       "The Exorcist (1973)                                     1\n",
-       "Texas Rangers (2001)                                    1\n",
-       "Name: count, Length: 947, dtype: int64"
-      ]
-     },
-     "execution_count": 39,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "rotten_tomatoes_raw[\"Title\"].value_counts()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "A zase duplicity, některé názvy se nám opakují :-(\n",
-    "\n",
-    "**Otázka:** Dokážeš zjistit proč? Nápověda: podívej se na nějaký konkrétní film."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Naštěstí už víme, jak na to - použijeme metodu `drop_duplicates`, tentokrát přes sloupec `\"Title\"`. (Poznámka: druhou možností by bylo sloučit všechny různé žánry daného filmu do jedné buňky)."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 40,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>Title</th>\n",
-       "      <th>RatingTomatometer</th>\n",
-       "      <th>No. of Reviews</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>Black Panther (2018)</td>\n",
-       "      <td>97</td>\n",
-       "      <td>444</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>Mad Max: Fury Road (2015)</td>\n",
-       "      <td>97</td>\n",
-       "      <td>394</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>Wonder Woman (2017)</td>\n",
-       "      <td>93</td>\n",
-       "      <td>410</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>Metropolis (1927)</td>\n",
-       "      <td>99</td>\n",
-       "      <td>118</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>Coco (2017)</td>\n",
-       "      <td>97</td>\n",
-       "      <td>308</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1585</th>\n",
-       "      <td>Priest (2011)</td>\n",
-       "      <td>15</td>\n",
-       "      <td>97</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1586</th>\n",
-       "      <td>American Outlaws (2001)</td>\n",
-       "      <td>14</td>\n",
-       "      <td>103</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1587</th>\n",
-       "      <td>September Dawn (2007)</td>\n",
-       "      <td>15</td>\n",
-       "      <td>54</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1588</th>\n",
-       "      <td>Jonah Hex (2010)</td>\n",
-       "      <td>12</td>\n",
-       "      <td>147</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1589</th>\n",
-       "      <td>Texas Rangers (2001)</td>\n",
-       "      <td>2</td>\n",
-       "      <td>51</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>947 rows × 3 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                          Title  RatingTomatometer  No. of Reviews\n",
-       "0          Black Panther (2018)                 97             444\n",
-       "1     Mad Max: Fury Road (2015)                 97             394\n",
-       "2           Wonder Woman (2017)                 93             410\n",
-       "3             Metropolis (1927)                 99             118\n",
-       "4                   Coco (2017)                 97             308\n",
-       "...                         ...                ...             ...\n",
-       "1585              Priest (2011)                 15              97\n",
-       "1586    American Outlaws (2001)                 14             103\n",
-       "1587      September Dawn (2007)                 15              54\n",
-       "1588           Jonah Hex (2010)                 12             147\n",
-       "1589       Texas Rangers (2001)                  2              51\n",
-       "\n",
-       "[947 rows x 3 columns]"
-      ]
-     },
-     "execution_count": 40,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "rotten_tomatoes_nodup = (\n",
-    "    rotten_tomatoes_raw\n",
-    "    .drop_duplicates(\n",
-    "        subset=\"Title\",\n",
-    "        keep=\"first\"                   # Vybereme první výskyt, lze i \"last\" (anebo False => vyhodit všechny)\n",
-    "    )\n",
-    "    .drop(\"Genres\", axis=\"columns\")    # Informační hodnotu jsme už ztratili\n",
-    "    .drop(\"Rank\", axis=\"columns\")      # Mělo smysl jen v rámci žánru\n",
-    ")\n",
-    "rotten_tomatoes_nodup"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 41,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>title_type</th>\n",
-       "      <th>title</th>\n",
-       "      <th>original_title</th>\n",
-       "      <th>is_adult</th>\n",
-       "      <th>start_year</th>\n",
-       "      <th>end_year</th>\n",
-       "      <th>length</th>\n",
-       "      <th>genres</th>\n",
-       "      <th>Title</th>\n",
-       "      <th>RatingTomatometer</th>\n",
-       "      <th>No. of Reviews</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "Empty DataFrame\n",
-       "Columns: [title_type, title, original_title, is_adult, start_year, end_year, length, genres, Title, RatingTomatometer, No. of Reviews]\n",
-       "Index: []"
-      ]
-     },
-     "execution_count": 41,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# Ready to merge?\n",
-    "pd.merge(imdb_titles, rotten_tomatoes_nodup, left_on=\"title\", right_on=\"Title\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "0 řádků!\n",
-    "\n",
-    "Dosud jsme manipulovali s řádky a sloupci jako celky, nicméně teď musíme zasahovat přímo do hodnot v buňkách. I to se při slučování dat z různých zdrojů nezřídka stává. Stojíme před úkolem převést řetězce typu \"Black Panther (2018)\" na dvě hodnoty: název \"Black Panther\" a rok 2018 (jeden sloupec na dva). \n",
-    "\n",
-    "Naštěstí si ty sloupce umíme jednoduše vyrobit pomocí řetězcové metody [`.str.slice`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.slice.html), která z každého řetězce vyřízne nějakou jeho část (a zase pracuje na celém sloupci - výsledkem bude nový sloupec s funkcí aplikovanou na každou z hodnot). Budeme věřit, že předposlední čtyři znaky představují rok a zbytek, až na nějaké ty závorky, tvoří skutečný název:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 42,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>tomatoes_rating</th>\n",
-       "      <th>tomatoes_votes</th>\n",
-       "      <th>title</th>\n",
-       "      <th>year</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>97</td>\n",
-       "      <td>444</td>\n",
-       "      <td>Black Panther</td>\n",
-       "      <td>2018</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>97</td>\n",
-       "      <td>394</td>\n",
-       "      <td>Mad Max: Fury Road</td>\n",
-       "      <td>2015</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>93</td>\n",
-       "      <td>410</td>\n",
-       "      <td>Wonder Woman</td>\n",
-       "      <td>2017</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>99</td>\n",
-       "      <td>118</td>\n",
-       "      <td>Metropolis</td>\n",
-       "      <td>1927</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>97</td>\n",
-       "      <td>308</td>\n",
-       "      <td>Coco</td>\n",
-       "      <td>2017</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1585</th>\n",
-       "      <td>15</td>\n",
-       "      <td>97</td>\n",
-       "      <td>Priest</td>\n",
-       "      <td>2011</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1586</th>\n",
-       "      <td>14</td>\n",
-       "      <td>103</td>\n",
-       "      <td>American Outlaws</td>\n",
-       "      <td>2001</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1587</th>\n",
-       "      <td>15</td>\n",
-       "      <td>54</td>\n",
-       "      <td>September Dawn</td>\n",
-       "      <td>2007</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1588</th>\n",
-       "      <td>12</td>\n",
-       "      <td>147</td>\n",
-       "      <td>Jonah Hex</td>\n",
-       "      <td>2010</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1589</th>\n",
-       "      <td>2</td>\n",
-       "      <td>51</td>\n",
-       "      <td>Texas Rangers</td>\n",
-       "      <td>2001</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>947 rows × 4 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "      tomatoes_rating  tomatoes_votes               title  year\n",
-       "0                  97             444       Black Panther  2018\n",
-       "1                  97             394  Mad Max: Fury Road  2015\n",
-       "2                  93             410        Wonder Woman  2017\n",
-       "3                  99             118          Metropolis  1927\n",
-       "4                  97             308                Coco  2017\n",
-       "...               ...             ...                 ...   ...\n",
-       "1585               15              97              Priest  2011\n",
-       "1586               14             103    American Outlaws  2001\n",
-       "1587               15              54      September Dawn  2007\n",
-       "1588               12             147           Jonah Hex  2010\n",
-       "1589                2              51       Texas Rangers  2001\n",
-       "\n",
-       "[947 rows x 4 columns]"
-      ]
-     },
-     "execution_count": 42,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "rotten_tomatoes_beta = (rotten_tomatoes_nodup\n",
-    "    .assign(\n",
-    "        title=rotten_tomatoes_nodup[\"Title\"].str.slice(0, -7),             \n",
-    "        year=rotten_tomatoes_nodup[\"Title\"].str.slice(-5, -1).astype(int)\n",
-    "    )\n",
-    "    .rename({\n",
-    "        \"RatingTomatometer\": \"tomatoes_rating\",\n",
-    "        \"No. of Reviews\": \"tomatoes_votes\",\n",
-    "    }, axis=\"columns\")\n",
-    "    .drop([\"Title\"], axis=\"columns\")\n",
-    ")\n",
-    "rotten_tomatoes_beta"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Závorková odysea nekončí, někdo nám proaktivně do závorek nacpal i originální název naanglickojazyčných filmů. Pojďme se o tom přesvědčit pomocí metody [`.str.contains`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.contains.html) (protože tato metoda ve výchozím stavu používá pro vyhledávání regulární výrazy, které jsme se zatím nenaučili používat, musíme jí to explicitně zakázat argumentem `regex=False`):"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 43,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>tomatoes_rating</th>\n",
-       "      <th>tomatoes_votes</th>\n",
-       "      <th>title</th>\n",
-       "      <th>year</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>15</th>\n",
-       "      <td>100</td>\n",
-       "      <td>58</td>\n",
-       "      <td>Seven Samurai (Shichinin no Samurai)</td>\n",
-       "      <td>1956</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>51</th>\n",
-       "      <td>98</td>\n",
-       "      <td>46</td>\n",
-       "      <td>Aguirre, the Wrath of God (Aguirre, der Zorn G...</td>\n",
-       "      <td>1972</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>61</th>\n",
-       "      <td>97</td>\n",
-       "      <td>71</td>\n",
-       "      <td>Ghostbusters (1984 Original)</td>\n",
-       "      <td>1984</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>69</th>\n",
-       "      <td>98</td>\n",
-       "      <td>47</td>\n",
-       "      <td>A Fistful of Dollars (Per un Pugno di Dollari)</td>\n",
-       "      <td>1964</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>99</th>\n",
-       "      <td>96</td>\n",
-       "      <td>139</td>\n",
-       "      <td>Embrace Of The Serpent (El Abrazo De La Serpie...</td>\n",
-       "      <td>2016</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1368</th>\n",
-       "      <td>97</td>\n",
-       "      <td>59</td>\n",
-       "      <td>To Be and to Have (Etre et Avoir)</td>\n",
-       "      <td>2003</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1457</th>\n",
-       "      <td>43</td>\n",
-       "      <td>82</td>\n",
-       "      <td>Goal! The Dream Begins (Goal!: The Impossible ...</td>\n",
-       "      <td>2005</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1502</th>\n",
-       "      <td>71</td>\n",
-       "      <td>52</td>\n",
-       "      <td>Only Human (Seres queridos)</td>\n",
-       "      <td>2006</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1547</th>\n",
-       "      <td>83</td>\n",
-       "      <td>64</td>\n",
-       "      <td>The Good, the Bad, the Weird (Joheun-nom, Nabb...</td>\n",
-       "      <td>2010</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1559</th>\n",
-       "      <td>74</td>\n",
-       "      <td>62</td>\n",
-       "      <td>Fah talai jone (Tears of the Black Tiger)</td>\n",
-       "      <td>2007</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>66 rows × 4 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "      tomatoes_rating  tomatoes_votes  \\\n",
-       "15                100              58   \n",
-       "51                 98              46   \n",
-       "61                 97              71   \n",
-       "69                 98              47   \n",
-       "99                 96             139   \n",
-       "...               ...             ...   \n",
-       "1368               97              59   \n",
-       "1457               43              82   \n",
-       "1502               71              52   \n",
-       "1547               83              64   \n",
-       "1559               74              62   \n",
-       "\n",
-       "                                                  title  year  \n",
-       "15                 Seven Samurai (Shichinin no Samurai)  1956  \n",
-       "51    Aguirre, the Wrath of God (Aguirre, der Zorn G...  1972  \n",
-       "61                         Ghostbusters (1984 Original)  1984  \n",
-       "69       A Fistful of Dollars (Per un Pugno di Dollari)  1964  \n",
-       "99    Embrace Of The Serpent (El Abrazo De La Serpie...  2016  \n",
-       "...                                                 ...   ...  \n",
-       "1368                  To Be and to Have (Etre et Avoir)  2003  \n",
-       "1457  Goal! The Dream Begins (Goal!: The Impossible ...  2005  \n",
-       "1502                        Only Human (Seres queridos)  2006  \n",
-       "1547  The Good, the Bad, the Weird (Joheun-nom, Nabb...  2010  \n",
-       "1559          Fah talai jone (Tears of the Black Tiger)  2007  \n",
-       "\n",
-       "[66 rows x 4 columns]"
-      ]
-     },
-     "execution_count": 43,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "rotten_tomatoes_beta[rotten_tomatoes_beta[\"title\"].str.contains(\")\", regex=False)]"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "V rámci zjednodušení proto ještě odstraníme všechny takové závorky. K tomu pomůže funkce [`.str.rsplit`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.rsplit.html), která rozdělí zprava řetězec na několik částí podle oddělovače a vloží je do seznamu - my za ten oddělovač zvolíme levou závorku `\"(\"`, omezíme počet částí na jednu až dvě (`n=1`):"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 44,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "41            [Marvel's The Avengers]\n",
-       "61    [Ghostbusters , 1984 Original)]\n",
-       "81      [Mad Max 2: The Road Warrior]\n",
-       "Name: title, dtype: object"
-      ]
-     },
-     "execution_count": 44,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "split_title = (\n",
-    "    rotten_tomatoes_beta[\"title\"]\n",
-    "    .str.rsplit(\"(\", n=1)\n",
-    ")\n",
-    "split_title.loc[[41, 61, 81]]   # Některé seznamy obsahují jeden prvek, jiné dva"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "A jak teď vybrat první prvek z každého seznamu?\n",
-    "\n",
-    "💡 Metoda [`apply`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.apply.html) umožňuje použít libovolnou transformaci (definovanou jako funkci) na každý řádek v tabulce či hodnotu v `Series`. Obvykle se bez ní obejdeme a měli bychom (proto se jí tolik speciálně nevěnujeme), protože není příliš výpočetně efektivní. Tady nám ale usnadní pochopení, co se vlastně dělá, t.j. vybírá první prvek nějakého seznamu:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 45,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>tomatoes_rating</th>\n",
-       "      <th>tomatoes_votes</th>\n",
-       "      <th>title</th>\n",
-       "      <th>year</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>97</td>\n",
-       "      <td>444</td>\n",
-       "      <td>Black Panther</td>\n",
-       "      <td>2018</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>97</td>\n",
-       "      <td>394</td>\n",
-       "      <td>Mad Max: Fury Road</td>\n",
-       "      <td>2015</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>93</td>\n",
-       "      <td>410</td>\n",
-       "      <td>Wonder Woman</td>\n",
-       "      <td>2017</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>99</td>\n",
-       "      <td>118</td>\n",
-       "      <td>Metropolis</td>\n",
-       "      <td>1927</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>97</td>\n",
-       "      <td>308</td>\n",
-       "      <td>Coco</td>\n",
-       "      <td>2017</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1585</th>\n",
-       "      <td>15</td>\n",
-       "      <td>97</td>\n",
-       "      <td>Priest</td>\n",
-       "      <td>2011</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1586</th>\n",
-       "      <td>14</td>\n",
-       "      <td>103</td>\n",
-       "      <td>American Outlaws</td>\n",
-       "      <td>2001</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1587</th>\n",
-       "      <td>15</td>\n",
-       "      <td>54</td>\n",
-       "      <td>September Dawn</td>\n",
-       "      <td>2007</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1588</th>\n",
-       "      <td>12</td>\n",
-       "      <td>147</td>\n",
-       "      <td>Jonah Hex</td>\n",
-       "      <td>2010</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1589</th>\n",
-       "      <td>2</td>\n",
-       "      <td>51</td>\n",
-       "      <td>Texas Rangers</td>\n",
-       "      <td>2001</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>947 rows × 4 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "      tomatoes_rating  tomatoes_votes               title  year\n",
-       "0                  97             444       Black Panther  2018\n",
-       "1                  97             394  Mad Max: Fury Road  2015\n",
-       "2                  93             410        Wonder Woman  2017\n",
-       "3                  99             118          Metropolis  1927\n",
-       "4                  97             308                Coco  2017\n",
-       "...               ...             ...                 ...   ...\n",
-       "1585               15              97              Priest  2011\n",
-       "1586               14             103    American Outlaws  2001\n",
-       "1587               15              54      September Dawn  2007\n",
-       "1588               12             147           Jonah Hex  2010\n",
-       "1589                2              51       Texas Rangers  2001\n",
-       "\n",
-       "[947 rows x 4 columns]"
-      ]
-     },
-     "execution_count": 45,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "def take_first(a_list):   # Funkce, kterou použijeme v apply\n",
-    "    return a_list[0]\n",
-    "\n",
-    "rotten_tomatoes = (rotten_tomatoes_beta\n",
-    "    .assign(\n",
-    "        title=split_title.apply(take_first)\n",
-    "    )\n",
-    ")\n",
-    "rotten_tomatoes"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 46,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>tomatoes_rating</th>\n",
-       "      <th>tomatoes_votes</th>\n",
-       "      <th>title</th>\n",
-       "      <th>year</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>1539</th>\n",
-       "      <td>88</td>\n",
-       "      <td>42</td>\n",
-       "      <td>The Magnificent Seven</td>\n",
-       "      <td>1960</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1560</th>\n",
-       "      <td>63</td>\n",
-       "      <td>289</td>\n",
-       "      <td>The Magnificent Seven</td>\n",
-       "      <td>2016</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "      tomatoes_rating  tomatoes_votes                  title  year\n",
-       "1539               88              42  The Magnificent Seven  1960\n",
-       "1560               63             289  The Magnificent Seven  2016"
-      ]
-     },
-     "execution_count": 46,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# Zbavení se duplikátů hned na začátku nám zachovalo filmy se stejným jménem :-)\n",
-    "rotten_tomatoes.query(\"title == 'The Magnificent Seven'\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 47,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>title</th>\n",
-       "      <th>original_title</th>\n",
-       "      <th>is_adult</th>\n",
-       "      <th>year</th>\n",
-       "      <th>length</th>\n",
-       "      <th>genres</th>\n",
-       "      <th>tomatoes_rating</th>\n",
-       "      <th>tomatoes_votes</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>The Birth of a Nation</td>\n",
-       "      <td>The Birth of a Nation</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1915</td>\n",
-       "      <td>195</td>\n",
-       "      <td>Drama,History,War</td>\n",
-       "      <td>98</td>\n",
-       "      <td>40</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>Battleship Potemkin</td>\n",
-       "      <td>Bronenosets Potemkin</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1925</td>\n",
-       "      <td>75</td>\n",
-       "      <td>Drama,History</td>\n",
-       "      <td>100</td>\n",
-       "      <td>45</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>The Gold Rush</td>\n",
-       "      <td>The Gold Rush</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1925</td>\n",
-       "      <td>95</td>\n",
-       "      <td>Adventure,Comedy,Drama</td>\n",
-       "      <td>100</td>\n",
-       "      <td>43</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>Metropolis</td>\n",
-       "      <td>Metropolis</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1927</td>\n",
-       "      <td>153</td>\n",
-       "      <td>Drama,Sci-Fi</td>\n",
-       "      <td>99</td>\n",
-       "      <td>118</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>All Quiet on the Western Front</td>\n",
-       "      <td>All Quiet on the Western Front</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1930</td>\n",
-       "      <td>136</td>\n",
-       "      <td>Drama,War</td>\n",
-       "      <td>100</td>\n",
-       "      <td>42</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>654</th>\n",
-       "      <td>Three Identical Strangers</td>\n",
-       "      <td>Three Identical Strangers</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2018</td>\n",
-       "      <td>96</td>\n",
-       "      <td>Biography,Documentary,Drama</td>\n",
-       "      <td>96</td>\n",
-       "      <td>157</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>655</th>\n",
-       "      <td>Searching</td>\n",
-       "      <td>Searching</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2018</td>\n",
-       "      <td>102</td>\n",
-       "      <td>Drama,Mystery,Thriller</td>\n",
-       "      <td>92</td>\n",
-       "      <td>214</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>656</th>\n",
-       "      <td>Won't You Be My Neighbor?</td>\n",
-       "      <td>Won't You Be My Neighbor?</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2018</td>\n",
-       "      <td>94</td>\n",
-       "      <td>Biography,Documentary</td>\n",
-       "      <td>98</td>\n",
-       "      <td>216</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>657</th>\n",
-       "      <td>RBG</td>\n",
-       "      <td>RBG</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2018</td>\n",
-       "      <td>98</td>\n",
-       "      <td>Biography,Documentary</td>\n",
-       "      <td>95</td>\n",
-       "      <td>153</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>658</th>\n",
-       "      <td>Hereditary</td>\n",
-       "      <td>Hereditary</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2018</td>\n",
-       "      <td>127</td>\n",
-       "      <td>Drama,Horror,Mystery</td>\n",
-       "      <td>89</td>\n",
-       "      <td>317</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>659 rows × 8 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                              title                  original_title  is_adult  \\\n",
-       "0             The Birth of a Nation           The Birth of a Nation     False   \n",
-       "1               Battleship Potemkin            Bronenosets Potemkin     False   \n",
-       "2                     The Gold Rush                   The Gold Rush     False   \n",
-       "3                        Metropolis                      Metropolis     False   \n",
-       "4    All Quiet on the Western Front  All Quiet on the Western Front     False   \n",
-       "..                              ...                             ...       ...   \n",
-       "654       Three Identical Strangers       Three Identical Strangers     False   \n",
-       "655                       Searching                       Searching     False   \n",
-       "656       Won't You Be My Neighbor?       Won't You Be My Neighbor?     False   \n",
-       "657                             RBG                             RBG     False   \n",
-       "658                      Hereditary                      Hereditary     False   \n",
-       "\n",
-       "     year  length                       genres  tomatoes_rating  \\\n",
-       "0    1915     195            Drama,History,War               98   \n",
-       "1    1925      75                Drama,History              100   \n",
-       "2    1925      95       Adventure,Comedy,Drama              100   \n",
-       "3    1927     153                 Drama,Sci-Fi               99   \n",
-       "4    1930     136                    Drama,War              100   \n",
-       "..    ...     ...                          ...              ...   \n",
-       "654  2018      96  Biography,Documentary,Drama               96   \n",
-       "655  2018     102       Drama,Mystery,Thriller               92   \n",
-       "656  2018      94        Biography,Documentary               98   \n",
-       "657  2018      98        Biography,Documentary               95   \n",
-       "658  2018     127         Drama,Horror,Mystery               89   \n",
-       "\n",
-       "     tomatoes_votes  \n",
-       "0                40  \n",
-       "1                45  \n",
-       "2                43  \n",
-       "3               118  \n",
-       "4                42  \n",
-       "..              ...  \n",
-       "654             157  \n",
-       "655             214  \n",
-       "656             216  \n",
-       "657             153  \n",
-       "658             317  \n",
-       "\n",
-       "[659 rows x 8 columns]"
-      ]
-     },
-     "execution_count": 47,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "pd.merge(\n",
-    "    movies.dropna(subset=[\"year\"]),\n",
-    "    rotten_tomatoes,\n",
-    "    on=[\"title\", \"year\"],\n",
-    "    how=\"inner\"\n",
-    ")"
+    "# Pandas - vztahy mezi více proměnnými"
    ]
   },
   {
-   "cell_type": "markdown",
+   "cell_type": "code",
+   "execution_count": 1,
    "metadata": {},
+   "outputs": [],
    "source": [
-    "Když sloučíme filmy a hodnocení na Rotten Tomatoes, z 947 filmů se nám skoro tři sta ztratí. Bohužel zde je na vině především nestejnost zápisu názvu, různé uřčité členy, interpunkce, podnázvy apod. Coby řešení se tady nabízí spousta a spousta manuální práce, případně nějaká heuristika, která by na sebe pasovala \"hodně podobné\" názvy.\n",
-    "\n",
-    "*Mimochodem, obtížnost manuální práce se mezi vývojáři někdy přeceňuje: Opravit 288 názvů filmů může být práce na hodinu až dvě, zatímco psát algoritmus na \"řešení problému\" může trvat stejně dlouho, ne-li déle.*"
+    "# Importy jako obvykle\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "#### Čtvrtý (a poslední) join\n",
-    "\n",
-    "Dokončíme slučování všech čtyř tabulek:"
+    "Načteme si spojené tabulky z předchozí lekce:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 48,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>title</th>\n",
-       "      <th>original_title</th>\n",
-       "      <th>is_adult</th>\n",
-       "      <th>year</th>\n",
-       "      <th>length</th>\n",
-       "      <th>genres</th>\n",
-       "      <th>imdb_rating</th>\n",
-       "      <th>imdb_votes</th>\n",
-       "      <th>boxoffice_rank</th>\n",
-       "      <th>studio</th>\n",
-       "      <th>lifetime_gross</th>\n",
-       "      <th>tomatoes_rating</th>\n",
-       "      <th>tomatoes_votes</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>Black Panther</td>\n",
-       "      <td>Black Panther</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2018</td>\n",
-       "      <td>134</td>\n",
-       "      <td>Action,Adventure,Sci-Fi</td>\n",
-       "      <td>7.3</td>\n",
-       "      <td>489977</td>\n",
-       "      <td>3</td>\n",
-       "      <td>BV</td>\n",
-       "      <td>700059566</td>\n",
-       "      <td>97</td>\n",
-       "      <td>444</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>Avengers: Infinity War</td>\n",
-       "      <td>Avengers: Infinity War</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2018</td>\n",
-       "      <td>149</td>\n",
-       "      <td>Action,Adventure,Sci-Fi</td>\n",
-       "      <td>8.5</td>\n",
-       "      <td>616050</td>\n",
-       "      <td>4</td>\n",
-       "      <td>BV</td>\n",
-       "      <td>678815482</td>\n",
-       "      <td>84</td>\n",
-       "      <td>408</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>Titanic</td>\n",
-       "      <td>Titanic</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1997</td>\n",
-       "      <td>194</td>\n",
-       "      <td>Drama,Romance</td>\n",
-       "      <td>7.8</td>\n",
-       "      <td>945889</td>\n",
-       "      <td>5</td>\n",
-       "      <td>Par.</td>\n",
-       "      <td>659363944</td>\n",
-       "      <td>89</td>\n",
-       "      <td>184</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>Incredibles 2</td>\n",
-       "      <td>Incredibles 2</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2018</td>\n",
-       "      <td>118</td>\n",
-       "      <td>Action,Adventure,Animation</td>\n",
-       "      <td>7.7</td>\n",
-       "      <td>192301</td>\n",
-       "      <td>9</td>\n",
-       "      <td>BV</td>\n",
-       "      <td>608581744</td>\n",
-       "      <td>94</td>\n",
-       "      <td>332</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>The Dark Knight</td>\n",
-       "      <td>The Dark Knight</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2008</td>\n",
-       "      <td>152</td>\n",
-       "      <td>Action,Crime,Drama</td>\n",
-       "      <td>9.0</td>\n",
-       "      <td>2037678</td>\n",
-       "      <td>10</td>\n",
-       "      <td>WB</td>\n",
-       "      <td>535234033</td>\n",
-       "      <td>94</td>\n",
-       "      <td>332</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>469</th>\n",
-       "      <td>Boxing Gym</td>\n",
-       "      <td>Boxing Gym</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2010</td>\n",
-       "      <td>91</td>\n",
-       "      <td>Documentary</td>\n",
-       "      <td>7.1</td>\n",
-       "      <td>389</td>\n",
-       "      <td>12999</td>\n",
-       "      <td>Zipp.</td>\n",
-       "      <td>32476</td>\n",
-       "      <td>95</td>\n",
-       "      <td>42</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>470</th>\n",
-       "      <td>Red Hill</td>\n",
-       "      <td>Red Hill</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2010</td>\n",
-       "      <td>95</td>\n",
-       "      <td>Thriller,Western</td>\n",
-       "      <td>6.4</td>\n",
-       "      <td>7844</td>\n",
-       "      <td>13681</td>\n",
-       "      <td>Strand</td>\n",
-       "      <td>21087</td>\n",
-       "      <td>78</td>\n",
-       "      <td>65</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>471</th>\n",
-       "      <td>City Lights</td>\n",
-       "      <td>City Lights</td>\n",
-       "      <td>False</td>\n",
-       "      <td>1931</td>\n",
-       "      <td>87</td>\n",
-       "      <td>Comedy,Drama,Romance</td>\n",
-       "      <td>8.5</td>\n",
-       "      <td>144261</td>\n",
-       "      <td>13827</td>\n",
-       "      <td>UA</td>\n",
-       "      <td>19181</td>\n",
-       "      <td>98</td>\n",
-       "      <td>45</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>472</th>\n",
-       "      <td>Minding the Gap</td>\n",
-       "      <td>Minding the Gap</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2018</td>\n",
-       "      <td>93</td>\n",
-       "      <td>Documentary</td>\n",
-       "      <td>8.1</td>\n",
-       "      <td>4119</td>\n",
-       "      <td>14471</td>\n",
-       "      <td>Magn.</td>\n",
-       "      <td>11998</td>\n",
-       "      <td>100</td>\n",
-       "      <td>63</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>473</th>\n",
-       "      <td>The Autopsy of Jane Doe</td>\n",
-       "      <td>The Autopsy of Jane Doe</td>\n",
-       "      <td>False</td>\n",
-       "      <td>2016</td>\n",
-       "      <td>86</td>\n",
-       "      <td>Horror,Mystery,Thriller</td>\n",
-       "      <td>6.8</td>\n",
-       "      <td>73965</td>\n",
-       "      <td>14657</td>\n",
-       "      <td>IFC</td>\n",
-       "      <td>10474</td>\n",
-       "      <td>87</td>\n",
-       "      <td>98</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>474 rows × 13 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                       title           original_title  is_adult  year  length  \\\n",
-       "0              Black Panther            Black Panther     False  2018     134   \n",
-       "1     Avengers: Infinity War   Avengers: Infinity War     False  2018     149   \n",
-       "2                    Titanic                  Titanic     False  1997     194   \n",
-       "3              Incredibles 2            Incredibles 2     False  2018     118   \n",
-       "4            The Dark Knight          The Dark Knight     False  2008     152   \n",
-       "..                       ...                      ...       ...   ...     ...   \n",
-       "469               Boxing Gym               Boxing Gym     False  2010      91   \n",
-       "470                 Red Hill                 Red Hill     False  2010      95   \n",
-       "471              City Lights              City Lights     False  1931      87   \n",
-       "472          Minding the Gap          Minding the Gap     False  2018      93   \n",
-       "473  The Autopsy of Jane Doe  The Autopsy of Jane Doe     False  2016      86   \n",
-       "\n",
-       "                         genres  imdb_rating  imdb_votes  boxoffice_rank  \\\n",
-       "0       Action,Adventure,Sci-Fi          7.3      489977               3   \n",
-       "1       Action,Adventure,Sci-Fi          8.5      616050               4   \n",
-       "2                 Drama,Romance          7.8      945889               5   \n",
-       "3    Action,Adventure,Animation          7.7      192301               9   \n",
-       "4            Action,Crime,Drama          9.0     2037678              10   \n",
-       "..                          ...          ...         ...             ...   \n",
-       "469                 Documentary          7.1         389           12999   \n",
-       "470            Thriller,Western          6.4        7844           13681   \n",
-       "471        Comedy,Drama,Romance          8.5      144261           13827   \n",
-       "472                 Documentary          8.1        4119           14471   \n",
-       "473     Horror,Mystery,Thriller          6.8       73965           14657   \n",
-       "\n",
-       "     studio  lifetime_gross  tomatoes_rating  tomatoes_votes  \n",
-       "0        BV       700059566               97             444  \n",
-       "1        BV       678815482               84             408  \n",
-       "2      Par.       659363944               89             184  \n",
-       "3        BV       608581744               94             332  \n",
-       "4        WB       535234033               94             332  \n",
-       "..      ...             ...              ...             ...  \n",
-       "469   Zipp.           32476               95              42  \n",
-       "470  Strand           21087               78              65  \n",
-       "471      UA           19181               98              45  \n",
-       "472   Magn.           11998              100              63  \n",
-       "473     IFC           10474               87              98  \n",
-       "\n",
-       "[474 rows x 13 columns]"
-      ]
-     },
-     "execution_count": 48,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "movies_complete = pd.merge(\n",
-    "    movies_with_rating_and_boxoffice,\n",
-    "    rotten_tomatoes,\n",
-    "    on=[\"title\", \"year\"],\n",
-    "    how=\"inner\"\n",
-    ")\n",
-    "movies_complete.sort_values(\"boxoffice_rank\").reset_index(drop=True)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
+   "execution_count": 2,
    "metadata": {},
+   "outputs": [],
    "source": [
-    "A přišli jsme o dalších 175 filmů. \n",
-    "\n",
-    "Co dál? Pokud by toto byl skutečný úkol, museli bychom se s tím nějak vypořádat - zkoumat, proč které řádky nesedí, v čem se liší názvy stejného filmu v různých datových sadách, jinými slovy *manuální práce, práce, práce...*\n",
-    "\n",
-    "Naštěstí to je úkol jen ukázkový, a my můžeme být spokojeni, že máme sice neúplnou, ale přesto použitelnou datovou sadu :-)"
+    "movies_complete = pd.read_csv(\"./movies_complete.csv.gz\")\n",
+    "movies_with_rating = pd.read_csv(\"./movies_with_rating.csv.gz\")"
    ]
   },
   {
@@ -6125,7 +61,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 49,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
@@ -6149,6 +85,7 @@
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
+       "      <th>Unnamed: 0</th>\n",
        "      <th>year</th>\n",
        "      <th>length</th>\n",
        "      <th>imdb_rating</th>\n",
@@ -6162,8 +99,9 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>count</th>\n",
-       "      <td>474.0</td>\n",
-       "      <td>474.0</td>\n",
+       "      <td>474.000000</td>\n",
+       "      <td>474.000000</td>\n",
+       "      <td>474.000000</td>\n",
        "      <td>474.000000</td>\n",
        "      <td>4.740000e+02</td>\n",
        "      <td>474.000000</td>\n",
@@ -6173,6 +111,7 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>mean</th>\n",
+       "      <td>236.500000</td>\n",
        "      <td>2000.272152</td>\n",
        "      <td>112.529536</td>\n",
        "      <td>7.502110</td>\n",
@@ -6184,6 +123,7 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>std</th>\n",
+       "      <td>136.976275</td>\n",
        "      <td>18.099671</td>\n",
        "      <td>24.468735</td>\n",
        "      <td>0.690525</td>\n",
@@ -6195,8 +135,9 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>min</th>\n",
-       "      <td>1927.0</td>\n",
-       "      <td>63.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>1927.000000</td>\n",
+       "      <td>63.000000</td>\n",
        "      <td>2.700000</td>\n",
        "      <td>3.890000e+02</td>\n",
        "      <td>3.000000</td>\n",
@@ -6206,8 +147,9 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>25%</th>\n",
-       "      <td>1993.0</td>\n",
-       "      <td>95.0</td>\n",
+       "      <td>118.250000</td>\n",
+       "      <td>1993.000000</td>\n",
+       "      <td>95.000000</td>\n",
        "      <td>7.200000</td>\n",
        "      <td>3.088050e+04</td>\n",
        "      <td>687.250000</td>\n",
@@ -6217,8 +159,9 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>50%</th>\n",
-       "      <td>2007.0</td>\n",
-       "      <td>108.0</td>\n",
+       "      <td>236.500000</td>\n",
+       "      <td>2007.000000</td>\n",
+       "      <td>108.000000</td>\n",
        "      <td>7.600000</td>\n",
        "      <td>1.031485e+05</td>\n",
        "      <td>2343.000000</td>\n",
@@ -6228,8 +171,9 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>75%</th>\n",
-       "      <td>2013.0</td>\n",
-       "      <td>123.0</td>\n",
+       "      <td>354.750000</td>\n",
+       "      <td>2013.000000</td>\n",
+       "      <td>123.000000</td>\n",
        "      <td>7.975000</td>\n",
        "      <td>2.878735e+05</td>\n",
        "      <td>6152.500000</td>\n",
@@ -6239,8 +183,9 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>max</th>\n",
-       "      <td>2018.0</td>\n",
-       "      <td>219.0</td>\n",
+       "      <td>473.000000</td>\n",
+       "      <td>2018.000000</td>\n",
+       "      <td>219.000000</td>\n",
        "      <td>9.200000</td>\n",
        "      <td>2.037678e+06</td>\n",
        "      <td>14657.000000</td>\n",
@@ -6253,28 +198,28 @@
        "</div>"
       ],
       "text/plain": [
-       "              year      length  imdb_rating    imdb_votes  boxoffice_rank  \\\n",
-       "count        474.0       474.0   474.000000  4.740000e+02      474.000000   \n",
-       "mean   2000.272152  112.529536     7.502110  2.049621e+05     3645.890295   \n",
-       "std      18.099671   24.468735     0.690525  2.618299e+05     3452.106932   \n",
-       "min         1927.0        63.0     2.700000  3.890000e+02        3.000000   \n",
-       "25%         1993.0        95.0     7.200000  3.088050e+04      687.250000   \n",
-       "50%         2007.0       108.0     7.600000  1.031485e+05     2343.000000   \n",
-       "75%         2013.0       123.0     7.975000  2.878735e+05     6152.500000   \n",
-       "max         2018.0       219.0     9.200000  2.037678e+06    14657.000000   \n",
-       "\n",
-       "       lifetime_gross  tomatoes_rating  tomatoes_votes  \n",
-       "count    4.740000e+02       474.000000      474.000000  \n",
-       "mean     7.643727e+07        88.369198      150.299578  \n",
-       "std      1.101133e+08        15.831859       97.208147  \n",
-       "min      1.047400e+04         5.000000       39.000000  \n",
-       "25%      3.564070e+06        88.000000       65.000000  \n",
-       "50%      3.542173e+07        93.000000      120.500000  \n",
-       "75%      1.022663e+08        96.000000      221.500000  \n",
-       "max      7.000596e+08       100.000000      444.000000  "
+       "       Unnamed: 0         year      length  imdb_rating    imdb_votes  \\\n",
+       "count  474.000000   474.000000  474.000000   474.000000  4.740000e+02   \n",
+       "mean   236.500000  2000.272152  112.529536     7.502110  2.049621e+05   \n",
+       "std    136.976275    18.099671   24.468735     0.690525  2.618299e+05   \n",
+       "min      0.000000  1927.000000   63.000000     2.700000  3.890000e+02   \n",
+       "25%    118.250000  1993.000000   95.000000     7.200000  3.088050e+04   \n",
+       "50%    236.500000  2007.000000  108.000000     7.600000  1.031485e+05   \n",
+       "75%    354.750000  2013.000000  123.000000     7.975000  2.878735e+05   \n",
+       "max    473.000000  2018.000000  219.000000     9.200000  2.037678e+06   \n",
+       "\n",
+       "       boxoffice_rank  lifetime_gross  tomatoes_rating  tomatoes_votes  \n",
+       "count      474.000000    4.740000e+02       474.000000      474.000000  \n",
+       "mean      3645.890295    7.643727e+07        88.369198      150.299578  \n",
+       "std       3452.106932    1.101133e+08        15.831859       97.208147  \n",
+       "min          3.000000    1.047400e+04         5.000000       39.000000  \n",
+       "25%        687.250000    3.564070e+06        88.000000       65.000000  \n",
+       "50%       2343.000000    3.542173e+07        93.000000      120.500000  \n",
+       "75%       6152.500000    1.022663e+08        96.000000      221.500000  \n",
+       "max      14657.000000    7.000596e+08       100.000000      444.000000  "
       ]
      },
-     "execution_count": 49,
+     "execution_count": 3,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -6285,12 +230,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 50,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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GVqvFZ599hsOHD+O1117jYyrJaJikExERWZGkpCR88MEH6NWrFzZu3GjpcIiIGpXhw4fjjTfewJdffomSkhJ06NABq1evxvTp0y0dGtkQ3pNOREREREREJBO8J52IiIiIiIhIJpikExEREREREcmEVd6TrtfrceXKFTRv3hwKhcLS4RCRBQghcOvWLfj4+ECp5PeNtcXxk4g4ftYPx08iMtf4aZVJ+pUrV+Dr62vpMIhIBi5duoTWrVtbOgyrwfGTiMpw/Kwbjp9EVMbU46dVJunNmzcHcK9zNBpNjfV1Oh3279+P0NBQqFQqU4dnErbQBoDtkBNrb0NhYSF8fX2l8YBqp67jpxxY+3u1PFtqjy21BWg87eH4WT/WOH6aiq39rZgS+6pu5N5f5ho/rTJJL7vESKPR1DpJd3JygkajkeUvuzZsoQ0A2yEnttAGALzksI7qOn7Kga28V8vYUntsqS1A42sPx8+6scbx01Rs7W/FlNhXdWMt/WXq8ZM3IhERERERERHJBJN0IiIiIiIiIplgkk5EREREREQkE0zSiYiIiIiIiGSCSToRERERERGRTFjl7O711W3hPmhLzT+T6YUlo6td33bO7hq3obYTWNa/7m0wxr4bwtL7r05DYqvv78MY+zaG6vZvyd8JUHPfEBE1VjWNzxw/qS6qez/xvURkWTyTTkRERERERCQTTNKJiIiIiIiIZIJJOhEREREREZFMMEknIiIiIiIikgkm6URERERk1RYuXAiFQmHwExAQIK0vKSlBdHQ03Nzc0KxZM0RGRiIvL8+CERMRVc3oSfrBgwcxZswY+Pj4QKFQYOfOnQbrJ06cWGEQHTVqlLHDICIiIqJGpGvXrrh69ar0c+jQIWndzJkzsWvXLmzfvh3p6em4cuUKxo0bZ8ForVu3hfukf9vO2V3hh4gaxuiPYCsqKkLPnj3x7LPPVjn4jRo1CsnJydKyWq02dhhERERE1Ig0adIEXl5eFcpv3ryJDRs2YMuWLRg+fDgAIDk5GZ07d8aRI0fw4IMPmjtUIqJqGT1JDw8PR3h4eLV11Gp1pYMoEREREVF9nD17Fj4+PnBwcEBwcDASEhLg5+eHrKws6HQ6hISESHUDAgLg5+eHjIyMKpN0rVYLrVYrLRcWFgIAdDoddDqdaRtjBmo7UeW6mtqnVgqDf+v6+sakrC/YJ7Uj9/4yV1xGT9JrIy0tDR4eHmjRogWGDx+OV155BW5ublXWb+ggWVanqoHE1Goc6KoZJKU6NQyGptx3Q5Tff/k/PFPvvzoN6Zv6/j6MsW9juP9vp3wslvydALUf/OQ6eBMRkfkFBQVh48aN6NSpE65evYr4+HgMHjwYp0+fRm5uLuzt7eHi4mLwGk9PT+Tm5la5zYSEBMTHx1co379/P5ycnIzdBLNb1r/qdXv27Kn2tYsDy/7V1+v1jVFKSoqlQ7Aqcu2v4uJis+zH7En6qFGjMG7cOPj7++P8+fN4+eWXER4ejoyMDNjZ2VX6GmMNklUNJKZW00BV3SBZXl3bYMx910dV+y/7wzP1/qtjjL6p73tKTr+X8oOgJX8nQO0/2M01SBIRkfzdfxVnjx49EBQUhDZt2mDbtm1wdHSs1zbj4uIQGxsrLRcWFsLX1xehoaHQaDQNjtnSyu4rr8zphWHVvrbvor1YHKjHvONKaPWKOr++MdHpdEhJScHIkSOhUqksHY7syb2/yk4Wm5rZk/Tx48dL/+/evTt69OiB9u3bIy0tDSNGjKj0NQ0dJMt+2VUNJNZArRTVDobWgu2QD7m2obYf7OYaJImIyPq4uLjggQcewLlz5zBy5EjcuXMHBQUFBmfT8/Lyqr39Uq1WVzpvkkqlkmXyUFfa0qo/+2tqX9lxg1avqHQ7ttA/xmYr7xtzkWt/mSsmi1zufr927dqhZcuWOHfuXJVJurEGyaoGEmtiC20A2A45kVsbavs3LceBm4iI5OH27ds4f/48nn76afTt2xcqlQqpqamIjIwEAGRnZ+PixYsIDg62cKRERBVZPEn//fffcf36dXh7e1s6FCIiIiKyQrNmzcKYMWPQpk0bXLlyBQsWLICdnR2efPJJODs7Y/LkyYiNjYWrqys0Gg1mzJiB4OBgzuxORLJk9CT99u3bOHfunLSck5ODkydPwtXVFa6uroiPj0dkZCS8vLxw/vx5zJ49Gx06dEBYGO9dISIiIqK6+/333/Hkk0/i+vXrcHd3x6BBg3DkyBG4u7sDAFauXAmlUonIyEhotVqEhYVh7dq1Fo6aiKhyRk/Sjx8/jmHDhknLZfeSR0VFISkpCT/88AM2bdqEgoIC+Pj4IDQ0FIsXL+az0omIiIioXrZu3VrtegcHByQmJiIxMdFMERER1Z/Rk/ShQ4dCiKof4bRvX9UzSRIRERERUePWds7uatdfWDLaTJEQWYbS0gEQEdE9paWlmDdvHvz9/eHo6Ij27dtj8eLFBl98CiEwf/58eHt7w9HRESEhITh79qwFoyYiIiIiY2KSTkQkE0uXLkVSUhLWrFmDn376CUuXLsWyZcuwevVqqc6yZcvw1ltvYd26dcjMzETTpk0RFhaGkpISC0ZORERERMZi8dndiYjonsOHD2Ps2LEYPfreZXxt27bFRx99hKNHjwK4dxZ91apVmDt3LsaOHQsA2Lx5Mzw9PbFz506MHz/eYrETERERkXHwTDoRkUwMGDAAqamp+OWXXwAA33//PQ4dOoTw8HAA956WkZubi5CQEOk1zs7OCAoKQkZGhkViJiIiIiLj4pl0IiKZmDNnDgoLCxEQEAA7OzuUlpbi1VdfxYQJEwAAubm5AABPT0+D13l6ekrrytNqtdBqtdJyYWEhAECn00Gn05miGUZXFqe1xFsTW2qPLbUFkH971HZVT8wLVIy7qvbItX1ERHQPk3QiIpnYtm0bPvzwQ2zZsgVdu3bFyZMnERMTAx8fH0RFRdVrmwkJCYiPj69Qvn//fjg5OTU0ZLNKSUmxdAhGZUvtsaW2APJtz7L+1a/fs2dPpeXl21NcXGyskIgqxdnZiRqGSToRkUy8+OKLmDNnjnRveffu3fHbb78hISEBUVFR8PLyAgDk5eXB29tbel1eXh569epV6Tbj4uIQGxsrLRcWFsLX1xehoaHQaDSma4wR6XQ6pKSkYOTIkVCpVJYOp8FsqT221BZA/u3ptrD6x9ieXhhmsFxVe8quqCEiInlikk5EJBPFxcVQKg2nCrGzs4NerwcA+Pv7w8vLC6mpqVJSXlhYiMzMTEybNq3SbarVaqjV6grlKpVKlklIdawx5urYUntsqS2AfNujLVVUu76qmMu3R45tIyKi/2GSTkQkE2PGjMGrr74KPz8/dO3aFSdOnMCKFSvw7LPPAgAUCgViYmLwyiuvoGPHjvD398e8efPg4+ODiIgIywZPREREREbBJJ2ISCZWr16NefPm4fnnn8e1a9fg4+OD5557DvPnz5fqzJ49G0VFRZg6dSoKCgowaNAg7N27Fw4ODhaMnIiIiIiMhUk6EZFMNG/eHKtWrcKqVauqrKNQKLBo0SIsWrTIfIERERERkdkwSSciIiIiIklNs7Or7cwUCFEjpay5ChERERERERGZA5N0IiIiIiIiIplgkk5EREREREQkE0zSiYiIiIiIiGSCSToRERERERGRTHB2dyIiIiIiMpuaZo8naux4Jp2IiIiIiIhIJpikExEREZHNWLJkCRQKBWJiYqSykpISREdHw83NDc2aNUNkZCTy8vIsFyQRUTWYpBMRERGRTTh27Bjefvtt9OjRw6B85syZ2LVrF7Zv34709HRcuXIF48aNs1CURETVY5JORERERFbv9u3bmDBhAt555x20aNFCKr958yY2bNiAFStWYPjw4ejbty+Sk5Nx+PBhHDlyxIIRExFVjhPHEREREZHVi46OxujRoxESEoJXXnlFKs/KyoJOp0NISIhUFhAQAD8/P2RkZODBBx+sdHtarRZarVZaLiwsBADodDrodDoTtcJ81Hai/q9VCoN/zc2a+r8sVmuK2ZLk3l/miotJOhERERFZta1bt+K7777DsWPHKqzLzc2Fvb09XFxcDMo9PT2Rm5tb5TYTEhIQHx9foXz//v1wcnJqcMyWtqx/w7exOFDf8I3Uw549eyyy34ZISUmxdAhWRa79VVxcbJb9MEknIiIiIqt16dIlvPDCC0hJSYGDg4PRthsXF4fY2FhpubCwEL6+vggNDYVGozHafiyl28J99X6tWimwOFCPeceV0OoVRoyqdk4vDDP7PutLp9MhJSUFI0eOhEqlsnQ4sif3/iq7osbUmKQTERERkdXKysrCtWvX0KdPH6mstLQUBw8exJo1a7Bv3z7cuXMHBQUFBmfT8/Ly4OXlVeV21Wo11Gp1hXKVSiXL5KGutKUNT661eoVRtlNX1tj/tvK+MRe59pe5YmKSTkRERERWa8SIETh16pRB2aRJkxAQEICXXnoJvr6+UKlUSE1NRWRkJAAgOzsbFy9eRHBwsCVCJiKqFpN0IiIiIrJazZs3R7du3QzKmjZtCjc3N6l88uTJiI2NhaurKzQaDWbMmIHg4OAqJ40jIrIkJulEREREZNNWrlwJpVKJyMhIaLVahIWFYe3atZYOi4ioUkzSiYiIiMimpKWlGSw7ODggMTERiYmJlgmIiKgOlJYOgIiIiIiIiIjuYZJOREREREREJBNM0omIiIiIiIhkgkk6ERERERERkUwwSSciIiIiIiKSCSbpRERERERERDLBJJ2ISEYuX76Mp556Cm5ubnB0dET37t1x/Phxab0QAvPnz4e3tzccHR0REhKCs2fPWjBiIiIiIjImJulERDJx48YNDBw4ECqVCl999RXOnDmDN954Ay1atJDqLFu2DG+99RbWrVuHzMxMNG3aFGFhYSgpKbFg5ERERERkLE0sHQAREd2zdOlS+Pr6Ijk5WSrz9/eX/i+EwKpVqzB37lyMHTsWALB582Z4enpi586dGD9+vNljJiIiIiLjYpJORCQTX3zxBcLCwvDYY48hPT0drVq1wvPPP48pU6YAAHJycpCbm4uQkBDpNc7OzggKCkJGRkalSbpWq4VWq5WWCwsLAQA6nQ46nc7ELTKOsjitJd6a2FJ7bKktgPzbo7YT1a4vH3dV7ZFr+4iI6B6jJ+kHDx7E8uXLkZWVhatXr2LHjh2IiIiQ1gshsGDBArzzzjsoKCjAwIEDkZSUhI4dOxo7FCIiq/Lrr78iKSkJsbGxePnll3Hs2DH861//gr29PaKiopCbmwsA8PT0NHidp6entK68hIQExMfHVyjfv38/nJycjN8IE0pJSbF0CEZlS+2xpbYA8m3Psv7Vr9+zZ0+l5eXbU1xcbKyQiIjIBIyepBcVFaFnz5549tlnMW7cuArry+6n3LRpE/z9/TFv3jyEhYXhzJkzcHBwMHY4RERWQ6/XIzAwEK+99hoAoHfv3jh9+jTWrVuHqKioem0zLi4OsbGx0nJhYSF8fX0RGhoKjUZjlLhNTafTISUlBSNHjoRKpbJ0OA1mS+2xpbYAlm9Pt4X7GvT60wvDDJarak/ZFTVERCRPRk/Sw8PDER4eXuk63k9JRFQ1b29vdOnSxaCsc+fO+PTTTwEAXl5eAIC8vDx4e3tLdfLy8tCrV69Kt6lWq6FWqyuUq1Qqq0uqrDHm6thSe2ypLYDl2qMtVTTo9VXFXL49tvS7IiKyRWa9J70+91MCDb+nsqyOWln9vVxyVha7NbcBYDvkRK5tqO29krZ4T+XAgQORnZ1tUPbLL7+gTZs2AO5NIufl5YXU1FQpKS8sLERmZiamTZtm7nCJiIiIyATMmqTX535KwHj3VC4O1Ne6rlzZQhsAtkNO5NaGqu6pLM8W76mcOXMmBgwYgNdeew2PP/44jh49ivXr12P9+vUAAIVCgZiYGLzyyivo2LGjdMuQj4+PwdwfRERERGS9rGJ294beU1l2T9a840po9Q27lMxS1EqBxYF6q24DwHbIiVzbUP6eyqrY4j2V/fr1w44dOxAXF4dFixbB398fq1atwoQJE6Q6s2fPRlFREaZOnYqCggIMGjQIe/fu5ZweRERERDbCrEl6fe6nBIx3T6VWr2jw/V6WZgttANgOOZFbG2r7N22r91Q+/PDDePjhh6tcr1AosGjRIixatMiMURERERGRuZg1Sef9lERERNRYtZ2z29IhEBGRFTB6kn779m2cO3dOWs7JycHJkyfh6uoKPz8/3k9JREREREREVAWjJ+nHjx/HsGHDpOWye8mjoqKwceNG3k9JREREREREVAWlsTc4dOhQCCEq/GzcuBHA/+6nzM3NRUlJCb7++ms88MADxg6DiIiIiBqJpKQk9OjRAxqNBhqNBsHBwfjqq6+k9SUlJYiOjoabmxuaNWuGyMhI5OXlWTBiIqKqWcXs7kREREREVWndujWWLFmCjh07QgiBTZs2YezYsThx4gS6du2KmTNnYvfu3di+fTucnZ0xffp0jBs3Dt9++62lQzcZzoFAZL2YpBMRERGRVRszZozB8quvvoqkpCQcOXIErVu3xoYNG7BlyxYMHz4cAJCcnIzOnTvjyJEjePDBBy0RMhFRlZikExEREZHNKC0txfbt21FUVITg4GBkZWVBp9MhJCREqhMQEAA/Pz9kZGRUmaRrtVpotVppubCwEACg0+mg0+lM2wgjUNsJ021bKQz+NTdr6P8yZbFaU8yWJPf+MldcTNKJiIiIyOqdOnUKwcHBKCkpQbNmzbBjxw506dIFJ0+ehL29PVxcXAzqe3p6Ijc3t8rtJSQkID4+vkL5/v374eTkZOzwjW5Zf9PvY3Gg3vQ7qcSePXssst+GSElJsXQIVkWu/VVcXGyW/TBJJyIiIiKr16lTJ5w8eRI3b97EJ598gqioKKSnp9d7e3FxcdJTioB7Z9J9fX0RGhoKjUZjjJBNqtvCfSbbtlopsDhQj3nHldDqFSbbT1VOLwwz+z7rS6fTISUlBSNHjoRKpbJ0OLIn9/4qu6LG1JikExEREZHVs7e3R4cOHQAAffv2xbFjx/Dmm2/iiSeewJ07d1BQUGBwNj0vLw9eXl5Vbk+tVkOtVlcoV6lUskweytOWmj551uoVZtlPedbQ/+VZy/tGLuTaX+aKyeiPYCMiIiIisjS9Xg+tVou+fftCpVIhNTVVWpednY2LFy8iODjYghESEVWOZ9KJiIiIyKrFxcUhPDwcfn5+uHXrFrZs2YK0tDTs27cPzs7OmDx5MmJjY+Hq6gqNRoMZM2YgODiYM7sTkSwxSSciIiIiq3bt2jU888wzuHr1KpydndGjRw/s27cPI0eOBACsXLkSSqUSkZGR0Gq1CAsLw9q1ay0cNRFR5ZikExEREZFV27BhQ7XrHRwckJiYiMTERDNFRERUf7wnnYiIiIiIiEgmmKQTERERERERyQQvdyciIiIygrZzdls6BCIisgE8k05EREREREQkE0zSiYiIiIiIiGSCSToRERERERGRTDBJJyIiIiIiIpIJJulEREREREREMsHZ3YmIiIiIyCbU9JSFC0tGmykSovrjmXQiIiIiIiIimWCSTkQkQ0uWLIFCoUBMTIxUVlJSgujoaLi5uaFZs2aIjIxEXl6e5YIkIiIiIqNjkk5EJDPHjh3D22+/jR49ehiUz5w5E7t27cL27duRnp6OK1euYNy4cRaKkoiIiIhMgUk6EZGM3L59GxMmTMA777yDFi1aSOU3b97Ehg0bsGLFCgwfPhx9+/ZFcnIyDh8+jCNHjlgwYiIiIiIyJk4cR0QkI9HR0Rg9ejRCQkLwyiuvSOVZWVnQ6XQICQmRygICAuDn54eMjAw8+OCDlW5Pq9VCq9VKy4WFhQAAnU4HnU5nolYYV1mc1hJvTWypPbbUFqDh7VHbCWOGU2fl466qPbby+yIislVM0omIZGLr1q347rvvcOzYsQrrcnNzYW9vDxcXF4NyT09P5ObmVrnNhIQExMfHVyjfv38/nJycGhyzOaWkpFg6BKOypfbYUluA+rdnWX8jB1JHe/bsqbS8fHuKi4vNEQ4REdUTk3QiIhm4dOkSXnjhBaSkpMDBwcFo242Li0NsbKy0XFhYCF9fX4SGhkKj0RhtP6ak0+mQkpKCkSNHQqVSWTqcBrOl9thSW4CGt6fbwn0miKr2Ti8MM1iuqj1lV9QQWauaHrNGZO2YpBMRyUBWVhauXbuGPn36SGWlpaU4ePAg1qxZg3379uHOnTsoKCgwOJuel5cHLy+vKrerVquhVqsrlKtUKqtLqqwx5urYUntsqS1A/dujLVWYIJraqyrm8u2xpd8VEZEtYpJORCQDI0aMwKlTpwzKJk2ahICAALz00kvw9fWFSqVCamoqIiMjAQDZ2dm4ePEigoODLREyEREREZkAk3QiIhlo3rw5unXrZlDWtGlTuLm5SeWTJ09GbGwsXF1dodFoMGPGDAQHB1c5aRwRERERWR8+go2IyEqsXLkSDz/8MCIjI/HQQw/By8sLn332maXDIiKyuISEBPTr1w/NmzeHh4cHIiIikJ2dbVCnpKQE0dHRcHNzQ7NmzRAZGYm8vDwLRUxEVDUm6UREMpWWloZVq1ZJyw4ODkhMTER+fj6Kiorw2WefVXs/OhFRY5Geno7o6GgcOXIEKSkp0Ol0CA0NRVFRkVRn5syZ2LVrF7Zv34709HRcuXIF48aNs2DURESV4+XuRERERLXAGaXla+/evQbLGzduhIeHB7KysvDQQw/h5s2b2LBhA7Zs2YLhw4cDAJKTk9G5c2ccOXKEtw0RkazwTDoRERER2ZSbN28CAFxdXQHce4KGTqdDSEiIVCcgIAB+fn7IyMiwSIxERFXhmXQiIiIishl6vR4xMTEYOHCgNPFmbm4u7O3tDR5hCQCenp7Izc2tdDtarRZarVZaLnu+vE6ng06nM03wRqS2E6bbtlIY/GtNzP27K9ufNbxn5EDu/WWuuJikExEREZHNiI6OxunTp3Ho0KEGbSchIQHx8fEVyvfv3w8nJ6cGbdsclvU3/T4WB+pNvxMj27Nnj0X2m5KSYpH9Wiu59ldxcbFZ9sMknYiIiIhswvTp0/Hll1/i4MGDaN26tVTu5eWFO3fuoKCgwOBsel5eXpUTcMbFxSE2NlZaLiwshK+vL0JDQ6HRaEzWBmPptnCfybatVgosDtRj3nEltHqFyfZjCqcXhpl1fzqdDikpKRg5ciRUKpVZ922N5N5fZVfUmBqTdCIiIiKyakIIzJgxAzt27EBaWhr8/f0N1vft2xcqlQqpqamIjIwEAGRnZ+PixYsIDg6udJtqtRpqtbpCuUqlkmXyUJ621PTJs1avMMt+jMlSvztred/IhVz7y1wxMUknIiIiIqsWHR2NLVu24PPPP0fz5s2l+8ydnZ3h6OgIZ2dnTJ48GbGxsXB1dYVGo8GMGTMQHBxstTO782kDRLaLSToRERERWbWkpCQAwNChQw3Kk5OTMXHiRADAypUroVQqERkZCa1Wi7CwMKxdu9bMkRIR1YxJOhERERFZNSFqnmXcwcEBiYmJSExMNENERET1Z5EkfeHChRVmy+zUqRN+/vlnS4RDRERERESNQE23CVxYMtpMkRBVzWJn0rt27Yqvv/76f4E04Ul9IiIiIiIiatwslhk3adKkykdeEBERERERETVGFkvSz549Cx8fHzg4OCA4OBgJCQnw8/OrtK5Wq4VWq5WWy55Pp9PpoNPpatxXWR21sub7leSqLHZrbgPAdsiJXNtQm7/putQjIiIiIrImFknSg4KCsHHjRnTq1AlXr15FfHw8Bg8ejNOnT6N58+YV6ickJFS4hx0A9u/fDycnp1rvd3GgvkFxy4EttAFgO+REbm3Ys2dPreoVFxebOBIiIiIiIvOzSJIeHh4u/b9Hjx4ICgpCmzZtsG3bNkyePLlC/bi4OMTGxkrLhYWF8PX1RWhoKDQaTY370+l0SElJwbzjSmj1CuM0wszUSoHFgXqrbgPAdsiJXNtwemFYreqVXVFDRERERGRLZDFbm4uLCx544AGcO3eu0vVqtRpqtbpCuUqlgkqlqvV+tHoFtKXySUbqwxbaALAdciK3NtT2b7ouf/tERERERNZCaekAAOD27ds4f/48vL29LR0KERERERERkcVYJEmfNWsW0tPTceHCBRw+fBiPPPII7Ozs8OSTT1oiHCIiIiIiIiJZsMjl7r///juefPJJXL9+He7u7hg0aBCOHDkCd3d3S4RDREREREREJAsWSdK3bt1qid0SERERERERyZos7kknIiIiIiIiIibpRERERERERLLBJJ2IiIiIiIhIJmTxnHQiIiIic2g7Z3eV69R2Asv6mzEYIiKiSvBMOhEREREREZFMMEknIpKJhIQE9OvXD82bN4eHhwciIiKQnZ1tUKekpATR0dFwc3NDs2bNEBkZiby8PAtFTERERETGxiSdiEgm0tPTER0djSNHjiAlJQU6nQ6hoaEoKiqS6sycORO7du3C9u3bkZ6ejitXrmDcuHEWjJqIiIiIjIn3pBMRycTevXsNljdu3AgPDw9kZWXhoYcews2bN7FhwwZs2bIFw4cPBwAkJyejc+fOOHLkCB588EFLhE1kc7ot3AdtqcLSYRCRDFU3rwUAXFgy2kyRkC1jkk5EJFM3b94EALi6ugIAsrKyoNPpEBISItUJCAiAn58fMjIyKk3StVottFqttFxYWAgA0Ol00Ol0pgzfaMritJZ4a2JL7bHGtqjtRNXrlMLgX2tT/vdQ1e/Hmn5fRESNEZN0IiIZ0uv1iImJwcCBA9GtWzcAQG5uLuzt7eHi4mJQ19PTE7m5uZVuJyEhAfHx8RXK9+/fDycnJ6PHbUopKSmWDsGobKk91tSW2szevjhQb/pATGDPnj2Vlpf//RQXF5sjHLM6ePAgli9fjqysLFy9ehU7duxARESEtF4IgQULFuCdd95BQUEBBg4ciKSkJHTs2NFyQRMRVYFJOhGRDEVHR+P06dM4dOhQg7YTFxeH2NhYabmwsBC+vr4IDQ2FRqNpaJhmodPpkJKSgpEjR0KlUlk6nAazpfZYY1u6LdxX5Tq1UmBxoB7zjiuh1Vvf5e6nF4YZLFf1+ym7osaWFBUVoWfPnnj22Wcrnadj2bJleOutt7Bp0yb4+/tj3rx5CAsLw5kzZ+Dg4GCBiEmuarqcncgcmKQTEcnM9OnT8eWXX+LgwYNo3bq1VO7l5YU7d+6goKDA4Gx6Xl4evLy8Kt2WWq2GWq2uUK5SqawmqSpjjTFXx5baY862NPR+0Nrca67VK6zynvSqfgflfz+28r67X3h4OMLDwytdJ4TAqlWrMHfuXIwdOxYAsHnzZnh6emLnzp0YP368OUMlIqoRk3QiIpkQQmDGjBnYsWMH0tLS4O/vb7C+b9++UKlUSE1NRWRkJAAgOzsbFy9eRHBwsCVCJiKSvZycHOTm5hrM5+Hs7IygoCBkZGRUmaTLfU6P6uZXMPm+rXz+BlOq7dwQVDm595e54mKSTkQkE9HR0diyZQs+//xzNG/eXLrP3NnZGY6OjnB2dsbkyZMRGxsLV1dXaDQazJgxA8HBwZzZnYioCmVjqaenp0F5dfN5APKf06M28yuYmrXO32BKtZ0bgqon1/4y15weTNKJiGQiKSkJADB06FCD8uTkZEycOBEAsHLlSiiVSkRGRkKr1SIsLAxr1641c6RE8sX7SclY5D6nR3XzK5iatc/fYEq1nRuCKif3/jLXnB5M0omIZEKImi8bdHBwQGJiIhITE80QERGR9SubsyMvLw/e3t5SeV5eHnr16lXl6+Q+p4cc5k2w1vkbTKm2c0NQ9eTaX+aKiUk6ERERmU1DJ34jqit/f394eXkhNTVVSsoLCwuRmZmJadOmWTY4IqJKMEknIiIiIqt2+/ZtnDt3TlrOycnByZMn4erqCj8/P8TExOCVV15Bx44dpUew+fj4GDxLncgYyn8RqbYTWNb/3u0J2lIFv4ikWmGSTkRERERW7fjx4xg2bJi0XHYveVRUFDZu3IjZs2ejqKgIU6dORUFBAQYNGoS9e/fyGelEJEtM0omIiIjIqg0dOrTaeT0UCgUWLVqERYsWmTEqIqL6UVo6ACIiIiIiIiK6h0k6ERERERERkUwwSSciIiIiIiKSCSbpRERERERERDLBJJ2IiIiIiIhIJpikExEREREREckEH8FGRERERERk5drO2V3t+gtLRpspEmooJulERERkoKYDvTJqO4Fl/YFuC/dBW6owcVRERESNA5N0IiKiRqa2STgRERGZH5N0IiIiIiKZ4Zdptqmx/l55KX7dMEknIiIi2WisB7BERERlOLs7ERERERERkUwwSSciIiIiIiKSCSbpRERERERERDLBJJ2IiIiIiIhIJjhxHBERyVbbOburfRa3Lc8G25AJ1Gy5X4iIiGwdz6QTERERERERyQTPpBMREdVDfc90l10ZQERERFQZJulERERERGbWkFtaiEyhpvekKW+lKtt3Vbe4NXTf1bVNjreIMUknIqJGyZIHI0Dl99gbCw/+iYiIrJdF70lPTExE27Zt4eDggKCgIBw9etSS4RARWQWOnURE9cPxk4isgcXOpH/88ceIjY3FunXrEBQUhFWrViEsLAzZ2dnw8PCwVFhERLJma2OnnM/4yjk2Iqo7S4yfHEdIThr6frS2S8atmcWS9BUrVmDKlCmYNGkSAGDdunXYvXs33nvvPcyZM8dSYRERyZolxk5rPsi05tiJyLh47ElE1sIiSfqdO3eQlZWFuLg4qUypVCIkJAQZGRkV6mu1Wmi1Wmn55s2bAID8/HzodLoa96fT6VBcXIwmOiVK9aa5/8/UmugFiov1Vt0GgO2QE7m24fr167Wqd+vWLQCAEMKU4chKXcdOoOHjJwA0uVvUgKgbrrr3ak3vF0vHXhm5/u3Vhy21BbD+9pT/eyg7/rl+/TpUKpVUzvHznsYwfpqKtf+tmFNj6StjfR5X1V+1PT6sz/7rsm2zjZ/CAi5fviwAiMOHDxuUv/jii6J///4V6i9YsEAA4A9/+MOfCj+XLl0y19BlcXUdO4Xg+Mkf/vCn6h+Onxw/+cMf/tTvx9Tjp1XM7h4XF4fY2FhpWa/XIz8/H25ublAoav5GqrCwEL6+vrh06RI0Go0pQzUZW2gDwHbIibW3QQiBW7duwcfHx9KhyFpDx085sPb3anm21B5bagvQeNrD8bN2bGH8NBVb+1sxJfZV3ci9v8w1flokSW/ZsiXs7OyQl5dnUJ6XlwcvL68K9dVqNdRqtUGZi4tLnfer0Whk+cuuC1toA8B2yIk1t8HZ2dnSIZhVXcdOwHjjpxxY83u1MrbUHltqC9A42sPx857GMn6aiq39rZgS+6pu5Nxf5hg/LfIINnt7e/Tt2xepqalSmV6vR2pqKoKDgy0REhGR7HHsJCKqH46fRGRNLHa5e2xsLKKiohAYGIj+/ftj1apVKCoqkmbcJCKiijh2EhHVD8dPIrIWFkvSn3jiCfzxxx+YP38+cnNz0atXL+zduxeenp5G35darcaCBQsqXLJkTWyhDQDbISe20IbGyJxjp1zY2nvVltpjS20B2B5b1xjHT1Phe6v22Fd1w/66RyFEI3r+BhEREREREZGMWeSedCIiIiIiIiKqiEk6ERERERERkUwwSSciIiIiIiKSCSbpRERERERERDJh80l6YmIi2rZtCwcHBwQFBeHo0aOWDsnAwYMHMWbMGPj4+EChUGDnzp0G64UQmD9/Pry9veHo6IiQkBCcPXvWoE5+fj4mTJgAjUYDFxcXTJ48Gbdv3zZbGxISEtCvXz80b94cHh4eiIiIQHZ2tkGdkpISREdHw83NDc2aNUNkZCTy8vIM6ly8eBGjR4+Gk5MTPDw88OKLL+Lu3btma0dSUhJ69OgBjUYDjUaD4OBgfPXVV1bVhvKWLFkChUKBmJgYqcwa20HWr6axLi8vDxMnToSPjw+cnJwwatSoCmNdGSEEwsPDK92Oud67xmpPRkYGhg8fjqZNm0Kj0eChhx7CX3/9Ja03x/hujLbk5ubi6aefhpeXF5o2bYo+ffrg008/Nahjrs8qc34mpaWloU+fPlCr1ejQoQM2btwou7Z8//33ePLJJ+Hr6wtHR0d07twZb775ZoV9mbotZB1s4bjUXGrqq4kTJ0KhUBj8jBo1yqBOY+krW8kVzMmmk/SPP/4YsbGxWLBgAb777jv07NkTYWFhuHbtmqVDkxQVFaFnz55ITEysdP2yZcvw1ltvYd26dcjMzETTpk0RFhaGkpISqc6ECRPw448/IiUlBV9++SUOHjyIqVOnmqsJSE9PR3R0NI4cOYKUlBTodDqEhoaiqKhIqjNz5kzs2rUL27dvR3p6Oq5cuYJx48ZJ60tLSzF69GjcuXMHhw8fxqZNm7Bx40bMnz/fbO1o3bo1lixZgqysLBw/fhzDhw/H2LFj8eOPP1pNG+537NgxvP322+jRo4dBubW1g2xDdWOdEAIRERH49ddf8fnnn+PEiRNo06YNQkJCDMaRMqtWrYJCoahQbs73rjHak5GRgVGjRiE0NBRHjx7FsWPHMH36dCiV//toNsf4boy2PPPMM8jOzsYXX3yBU6dOYdy4cXj88cdx4sQJs7YFMN9nUk5ODkaPHo1hw4bh5MmTiImJwT//+U/s27dPVm3JysqCh4cHPvjgA/z444/4z3/+g7i4OKxZs8asbSHrYAvHpeZSU18BwKhRo3D16lXp56OPPjJY31j6ylZyBbMSNqx///4iOjpaWi4tLRU+Pj4iISHBglFVDYDYsWOHtKzX64WXl5dYvny5VFZQUCDUarX46KOPhBBCnDlzRgAQx44dk+p89dVXQqFQiMuXL5st9vtdu3ZNABDp6elSzCqVSmzfvl2q89NPPwkAIiMjQwghxJ49e4RSqRS5ublSnaSkJKHRaIRWqzVvA+7TokUL8e6771pdG27duiU6duwoUlJSxJAhQ8QLL7wghLDu3wXZjvJjXXZ2tgAgTp8+LZWVlpYKd3d38c477xi89sSJE6JVq1bi6tWrFbZjqfdufdsTFBQk5s6dW+V2LTG+17ctTZs2FZs3bzbYlqurq1THkp9VpvpMmj17tujatavBvp544gkRFhYmq7ZU5vnnnxfDhg2Tli3RFpI/WzkuNYfyfSWEEFFRUWLs2LFVvqax9pUQtpUrmIrNnkm/c+cOsrKyEBISIpUplUqEhIQgIyPDgpHVXk5ODnJzcw3a4OzsjKCgIKkNGRkZcHFxQWBgoFQnJCQESqUSmZmZZo8ZAG7evAkAcHV1BXDvW3ydTmfQjoCAAPj5+Rm0o3v37vD09JTqhIWFobCwUDqTbU6lpaXYunUrioqKEBwcbHVtiI6OxujRow3iBazzd0G2T6vVAgAcHBykMqVSCbVajUOHDkllxcXF+Mc//oHExER4eXlV2I5c3ru1ac+1a9eQmZkJDw8PDBgwAJ6enhgyZIhBe+Uwvtf2dzNgwAB8/PHHyM/Ph16vx9atW1FSUoKhQ4davC2m+kzKyMioMMaGhYWZ9BijPm2pajtl2wAs0xayPtZ6XGpJaWlp8PDwQKdOnTBt2jRcv35dWteY+8oWcgVTs9kk/c8//0RpaanBLxIAPD09kZuba6Go6qYszurakJubCw8PD4P1TZo0gaurq0XaqdfrERMTg4EDB6Jbt25SjPb29nBxcTGoW74dlbWzbJ25nDp1Cs2aNYNarcb//d//YceOHejSpYtVtWHr1q347rvvkJCQUGGdNbWDGo+yD+K4uDjcuHEDd+7cwdKlS/H777/j6tWrUr2ZM2diwIABGDt2bKXbkct7tzbt+fXXXwEACxcuxJQpU7B371706dMHI0aMkO7vlMP4XtvfzbZt26DT6eDm5ga1Wo3nnnsOO3bsQIcOHSzaFlN+JlVVp7Cw0GBeAUu3pbzDhw/j448/Nrik1txtIetkjcelljRq1Chs3rwZqampWLp0KdLT0xEeHo7S0lIAjbevrD1XMJcmlg6AbEt0dDROnz5tcIbFmnTq1AknT57EzZs38cknnyAqKgrp6emWDqvWLl26hBdeeAEpKSkGZ76I5EylUuGzzz7D5MmT4erqCjs7O4SEhCA8PBxCCADAF198gW+++cbgHme5qk179Ho9AOC5557DpEmTAAC9e/dGamoq3nvvvUq/ZLOE2rQFAObNm4eCggJ8/fXXaNmyJXbu3InHH38c//3vf9G9e3eLxW/tn0n3M0ZbTp8+jbFjx2LBggUIDQ01YnREVN748eOl/3fv3h09evRA+/btkZaWhhEjRlgwMsuypXHZlGz2THrLli1hZ2dXYVbAvLy8Si+TlKOyOKtrg5eXV4WJ8O7evYv8/Hyzt3P69On48ssvceDAAbRu3Voq9/Lywp07d1BQUGBQv3w7Kmtn2Tpzsbe3R4cOHdC3b18kJCSgZ8+eePPNN62mDVlZWbh27Rr69OmDJk2aoEmTJkhPT8dbb72FJk2awNPT0yraQY1P3759cfLkSRQUFODq1avYu3cvrl+/jnbt2gEAvvnmG5w/fx4uLi7SexsAIiMjpUuq5fTerak93t7eAIAuXboYvK5z5864ePGiFLMcxvea2nL+/HmsWbMG7733HkaMGIGePXtiwYIFCAwMlCZUskRbTP2ZVFUdjUYDR0dH2bSlzJkzZzBixAhMnToVc+fONVhnzraQ9bK241K5adeuHVq2bIlz584BaJx9ZQu5grnYbJJub2+Pvn37IjU1VSrT6/VITU1FcHCwBSOrPX9/f3h5eRm0obCwEJmZmVIbgoODUVBQgKysLKnON998A71ej6CgILPEKYTA9OnTsWPHDnzzzTfw9/c3WN+3b1+oVCqDdmRnZ+PixYsG7Th16pTBYJWSkgKNRlPhINac9Ho9tFqt1bRhxIgROHXqFE6ePCn9BAYGYsKECdL/raEd1Hg5OzvD3d0dZ8+exfHjx6VL2+fMmYMffvjB4L0NACtXrkRycjIAeb53q2pP27Zt4ePjU+ERNL/88gvatGkDQB7j+/2qaktxcTEAGMxKDwB2dnbSFQPmbIu5PpOCg4MNtlFWx5jHGMZoCwD8+OOPGDZsGKKiovDqq69W2I852kLWz1qOS+Xq999/x/Xr16UvaRtTX9lyrmAyFpy0zuS2bt0q1Gq12Lhxozhz5oyYOnWqcHFxMZgV0NJu3bolTpw4IU6cOCEAiBUrVogTJ06I3377TQghxJIlS4SLi4v4/PPPxQ8//CDGjh0r/P39xV9//SVtY9SoUaJ3794iMzNTHDp0SHTs2FE8+eSTZmvDtGnThLOzs0hLSxNXr16VfoqLi6U6//d//yf8/PzEN998I44fPy6Cg4NFcHCwtP7u3buiW7duIjQ0VJw8eVLs3btXuLu7i7i4OLO1Y86cOSI9PV3k5OSIH374QcyZM0coFAqxf/9+q2lDZe6f3V0I620HWbeaxrpt27aJAwcOiPPnz4udO3eKNm3aiHHjxlW7TZSbTdec711jtGflypVCo9GI7du3i7Nnz4q5c+cKBwcHce7cOamOOcb3hrblzp07okOHDmLw4MEiMzNTnDt3Trz++utCoVCI3bt3m7UtQpjvM+nXX38VTk5O4sUXXxQ//fSTSExMFHZ2dmLv3r2yasupU6eEu7u7eOqppwy2ce3aNbO2hayDLRyXmkt1fXXr1i0xa9YskZGRIXJycsTXX38t+vTpIzp27ChKSkqkbTSWvrKVXMGcbDpJF0KI1atXCz8/P2Fvby/69+8vjhw5YumQDBw4cEAAqPATFRUlhLj3uIt58+YJT09PoVarxYgRI0R2drbBNq5fvy6efPJJ0axZM6HRaMSkSZPErVu3zNaGyuIHIJKTk6U6f/31l3j++edFixYthJOTk3jkkUfE1atXDbZz4cIFER4eLhwdHUXLli3Fv//9b6HT6czWjmeffVa0adNG2NvbC3d3dzFixAgpQbeWNlSmfJJure0g61bTWPfmm2+K1q1bC5VKJfz8/MTcuXNrfKRK+SRdCPO9d43VnoSEBNG6dWvh5OQkgoODxX//+1+D9eYY343Rll9++UWMGzdOeHh4CCcnJ9GjR48Kj2Qz12eVOT+TDhw4IHr16iXs7e1Fu3btDPYhl7YsWLCg0m20adPGrG0h62ALx6XmUl1fFRcXi9DQUOHu7i5UKpVo06aNmDJlSoUThY2lr2wlVzAnhRD3zfxCRERERERERBZjs/ekExEREREREVkbJulEREREREREMsEknYiIiIiIiEgmmKQTERERERERyQSTdCIiIiIiIiKZYJJOREREREREJBNM0omIiIiIiIhkgkk6ERERERERkUwwSW/ENm7cCIVCgQsXLph0PxMnTkTbtm2l5QsXLkChUOD111836X6NoXzsRET34zhKRAQsXLgQCoUCf/75p6VDqdTy5cvRrl072NnZoVevXgCAu3fvYvbs2fD19YVSqURERAQAQKFQYOHChRaL1ZzS0tKgUCjwySefWDoUKqeJpQMgsrQrV65g/fr1iIiIkAZuIiKqH46pRCQn+/fvx+zZs/HUU09h4cKFaNmyJQDgvffew/LlyxETE4M+ffrAz8/PwpES/Q+T9Ebs6aefxvjx46FWqy0dikVduXIF8fHxaNu2bYUDynfeeQd6vd4ygRGR7HEcrai6MZWIyNy++eYbKJVKbNiwAfb29gblrVq1wsqVKw3q//XXX2jShCkSWRbfgY2YnZ0d7OzsLB2G0ZWUlMDe3h5KZcPv5lCpVEaIiIhsla2Oo0REtuLatWtwdHQ0SNDLyl1cXCrUd3BwMFNktVdcXAwnJydLh0FmxHvSG7Hy91K2bdsWDz/8MNLS0hAYGAhHR0d0794daWlpAIDPPvsM3bt3h4ODA/r27YsTJ05U2ObOnTvRrVs3ODg4oFu3btixY0e1MaxcuRJt2rSBo6MjhgwZgtOnT9epDWX30mzduhVz585Fq1at4OTkhMLCQuTn52PWrFno3r07mjVrBo1Gg/DwcHz//fcGr+/Xrx8AYNKkSVAoFFAoFNi4cSOA6u8DXb9+Pdq3bw+1Wo1+/frh2LFjFeLbvn07unTpYtAfvM+dyHZY+zial5eHJk2aID4+vsK67OxsKBQKrFmzRir79ddf8dhjj8HV1RVOTk548MEHsXv3bml9TWMqAGRmZmLUqFFwdnaGk5MThgwZgm+//dZg37du3UJMTAzatm0LtVoNDw8PjBw5Et99912t20ZE5vfnn3/i8ccfh0ajgZubG1544QWUlJRI6+/evYvFixdLx09t27bFyy+/DK1WCwAQQmDYsGFwd3fHtWvXpNfduXMH3bt3R/v27VFUVFSrbQH37i9PTk5GUVGRwXikUChw4MAB/Pjjj1J52Thd2T3ply9fxuTJk+Hj4wO1Wg1/f39MmzYNd+7ckeoUFBQgJiYGvr6+UKvV6NChA5YuXVrnKzKHDh2Kbt26ISsrCw899BCcnJzw8ssvAwA+//xzjB49Woqjffv2WLx4MUpLSyvdxpkzZzBs2DA4OTmhVatWWLZsWY3712q1ePjhh+Hs7IzDhw/XKXYyIkGNVnJysgAgcnJyhBBCtGnTRnTq1El4e3uLhQsXipUrV4pWrVqJZs2aiQ8++ED4+fmJJUuWiCVLlghnZ2fRoUMHUVpaKm1v3759QqlUim7duokVK1aI//znP8LZ2Vl07dpVtGnTRqqXk5MjAIju3buLtm3biqVLl4r4+Hjh6uoq3N3dRW5ubq3bcODAAQFAdOnSRfTq1UusWLFCJCQkiKKiInHs2DHRvn17MWfOHPH222+LRYsWiVatWglnZ2dx+fJlIYQQubm5YtGiRQKAmDp1qnj//ffF+++/L86fPy+EECIqKqrS2Hv37i06dOggli5dKpYtWyZatmwpWrduLe7cuSPV/fLLL4VCoRA9evQQK1asEPPmzRMtWrQQ3bp1M9gmEVkvWxhHhw8fLrp06VKhPD4+XtjZ2Unbys3NFZ6enqJ58+biP//5j1ixYoXo2bOnUCqV4rPPPpPqVDempqamCnt7exEcHCzeeOMNsXLlStGjRw9hb28vMjMzpX3/4x//EPb29iI2Nla8++67YunSpWLMmDHigw8+qHW7iMh8FixYII1JY8aMEWvWrBFPPfWUACCefvppqV5UVJQAIB599FGRmJgonnnmGQFARERESHV+/fVX0axZM/HII49IZXPmzBEKhUKkp6fXaVvvv/++GDx4sFCr1dJ4dPr0afH++++LgIAA0bp1a6m8bKwDIBYsWCBt4/Lly8LHx0c4OTmJmJgYsW7dOjFv3jzRuXNncePGDSGEEEVFRaJHjx7Czc1NvPzyy2LdunXimWeeEQqFQrzwwgt16sshQ4YILy8v4e7uLmbMmCHefvttsXPnTiGEEBEREeLxxx8Xy5cvF0lJSeKxxx4TAMSsWbMqbMPHx0f4+vqKF154Qaxdu1YMHz5cABB79uyR6pUdR2/fvl0IIURxcbEYOXKkaNGihTh69Gid4ibjYpLeiFV2cAlAHD58WKqzb98+AUA4OjqK3377TSp/++23BQBx4MABqaxXr17C29tbFBQUSGX79+8XACo9uHR0dBS///67VJ6ZmSkAiJkzZ9a6DWWDS7t27URxcbHBupKSEoOD37J9q9VqsWjRIqns2LFjAoBITk6usP2qknQ3NzeRn58vlX/++ecCgNi1a5dU1r17d9G6dWtx69YtqSwtLa1CfxCR9bKFcbQsjlOnThmUd+nSRQwfPlxajomJEQDEf//7X6ns1q1bwt/fX7Rt21Yab6saU/V6vejYsaMICwsTer1eKi8uLhb+/v5i5MiRUpmzs7OIjo6udRuIyLLKkvS///3vBuXPP/+8ACC+//57cfLkSQFA/POf/zSoM2vWLAFAfPPNN1JZ2bj0wQcfiCNHjgg7OzsRExMjra/LtqKiokTTpk0rxDxkyBDRtWvXCuXlk/RnnnlGKJVKcezYsQp1y8ayxYsXi6ZNm4pffvnFYP2cOXOEnZ2duHjxYoXXVmXIkCECgFi3bl2FdeWPdYUQ4rnnnhNOTk6ipKSkwjY2b94slWm1WuHl5SUiIyOlsvuT9Fu3bokhQ4aIli1bihMnTtQ6XjINXu5OBrp06YLg4GBpOSgoCAAwfPhwg1kvy8p//fVXAMDVq1dx8uRJREVFwdnZWao3cuRIdOnSpdJ9RUREoFWrVtJy//79ERQUhD179tQ57qioKDg6OhqUqdVq6b700tJSXL9+Hc2aNUOnTp0afMnkE088gRYtWkjLgwcPBvC//rhy5QpOnTqFZ555Bs2aNZPqDRkyBN27d2/QvolI3qxtHB03bhyaNGmCjz/+WCo7ffo0zpw5gyeeeEIq27NnD/r3749BgwZJZc2aNcPUqVNx4cIFnDlzptr9nDx5EmfPnsU//vEPXL9+HX/++Sf+/PNPFBUVYcSIETh48KB0WaiLiwsyMzNx5cqVWreDiCwvOjraYHnGjBkA7o0fZeNSbGysQZ1///vfAGBw68zUqVMRFhaGGTNm4Omnn0b79u3x2muvSevrsq2G0Ov12LlzJ8aMGYPAwMAK6xUKBYB7tzcOHjwYLVq0kMa2P//8EyEhISgtLcXBgwfrtF+1Wo1JkyZVKL//WPfWrVv4888/MXjwYBQXF+Pnn382qNusWTM89dRT0rK9vT369+8vfebc7+bNmwgNDcXPP/+MtLQ0TvopA0zSyUD5x0+UHSj6+vpWWn7jxg0AwG+//QYA6NixY4VtdurUqdJ9VVb3gQceqNfzhv39/SuU6fV6rFy5Eh07doRarUbLli3h7u6OH374ATdv3qzzPu5Xvp/KEvby/dGhQ4cKr62sjIhsh7WNoy1btsSIESOwbds2qezjjz9GkyZNMG7cOKnst99+qzSOzp07G8RflbNnzwK496Wqu7u7wc+7774LrVYrjc3Lli3D6dOn4evri/79+2PhwoWVHlgSkbyUH5Pat28PpVKJCxcu4LfffoNSqaxwHOTl5QUXF5cKY8iGDRtQXFyMs2fPYuPGjQYJal23VV9//PEHCgsL0a1bt2rrnT17Fnv37q0wtoWEhACAwf31tdGqVasKE90BwI8//ohHHnkEzs7O0Gg0cHd3lxLx8se2rVu3lr5EKNOiRQvpM+d+MTExOHbsGL7++mt07dq1TrGSaXB2dzJQ1SzFVZULIUwZTq2VP4sOAK+99hrmzZuHZ599FosXL4arqyuUSiViYmIa/Fg1ufcHEVmONY6j48ePx6RJk3Dy5En06tUL27Ztw4gRI6TnCRtD2bi7fPnyKs/SlF159Pjjj2Pw4MHYsWMH9u/fj+XLl2Pp0qX47LPPEB4ebrSYiMi0yieJVZVVJi0tTZoE7tSpUwZXKNV1W6am1+sxcuRIzJ49u9L1DzzwQJ22V9lxbUFBAYYMGQKNRoNFixahffv2cHBwwHfffYeXXnqpwrFtXT5zxo4di61bt2LJkiXYvHmzUZ6QRA3DJJ2Mok2bNgD+d6bkftnZ2ZW+prK6v/zyi9FmPv/kk08wbNgwbNiwwaC8oKDA4MDTFAN8WX+cO3euwrrKyoiILDmORkRE4LnnnpMuef/ll18QFxdXIb7K4ii7xLIs/qrG1Pbt2wMANBqNdHapOt7e3nj++efx/PPP49q1a+jTpw9effVVJulEMnb27FmDqxvPnTsHvV6Ptm3bQggBvV6Ps2fPSlfgAPeeMlFQUCCNIcC9239mzJiB0NBQ2NvbY9asWQgLC5PqtGnTptbbagh3d3doNJoan5rRvn173L59u1ZjW32lpaXh+vXr+Oyzz/DQQw9J5Tk5OQ3edkREBEJDQzFx4kQ0b94cSUlJDd4mNQy/JiGj8Pb2Rq9evbBp0yaDy21SUlKqvE9x586duHz5srR89OhRZGZmGu0AzM7OrsK3hdu3bzfYJwA0bdoUwL3k3Vh8fHzQrVs3bN68Gbdv35bK09PTcerUKaPth4hshyXHURcXF4SFhWHbtm3YunUr7O3tERERYVDnb3/7G44ePYqMjAyprKioCOvXr0fbtm2l++arGlP79u2L9u3b4/XXXzcYF8v88ccfAO7NIVL+sk0PDw/4+PgYPFqJiOQnMTHRYHn16tUAgPDwcPztb38DAKxatcqgzooVKwAAo0ePlsqmTJkCvV6PDRs2YP369WjSpAkmT54sHdfVZVsNoVQqERERgV27duH48eMV1pfF8/jjjyMjIwP79u2rUKegoAB3795tcCxlZ8bvP7a9c+cO1q5d2+BtA8AzzzyDt956C+vWrcNLL71klG1S/fFMOhlNQkICRo8ejUGDBuHZZ59Ffn4+Vq9eja5du1Z6QNahQwcMGjQI06ZNg1arxapVq+Dm5lblpUJ19fDDD2PRokWYNGkSBgwYgFOnTuHDDz9Eu3btDOq1b98eLi4uWLduHZo3b46mTZsiKCio0vvc6+K1117D2LFjMXDgQEyaNAk3btzAmjVr0K1bt0r7g4jIkuPoE088gaeeegpr165FWFgYXFxcDNbPmTMHH330EcLDw/Gvf/0Lrq6u2LRpE3JycvDpp59Kl0dWN6a+++67CA8PR9euXTFp0iS0atUKly9fxoEDB6DRaLBr1y7cunULrVu3xqOPPoqePXuiWbNm+Prrr3Hs2DG88cYb9epXIjKPnJwc/P3vf8eoUaOQkZGBDz74AP/4xz/Qs2dPAPfmpFi/fr106fbRo0exadMmREREYNiwYQCA5ORk7N69Gxs3bkTr1q0B3Ev2n3rqKSQlJeH5559Hz549a7UtY3jttdewf/9+DBkyBFOnTkXnzp1x9epVbN++HYcOHYKLiwtefPFFfPHFF3j44YcxceJE9O3bF0VFRTh16hQ++eQTXLhwocG3Dw0YMAAtWrRAVFQU/vWvf0GhUOD999836i1T06dPR2FhIf7zn//A2dlZej47WYClppUny6vs0UGjR4+uUA9AhUfhlD3+Z/ny5Qbln376qejcubNQq9WiS5cu4rPPPqvyMWbLly8Xb7zxhvD19RVqtVoMHjxYfP/993VqQ/nnO96vpKRE/Pvf/xbe3t7C0dFRDBw4UGRkZIghQ4aIIUOGGNT9/PPPRZcuXUSTJk0MHh1UXeyV9dP9j+wQQoitW7eKgIAAoVarRbdu3cQXX3whIiMjRUBAQJ3aSUTyZAvjaJnCwkLh6OgoPfaoMufPnxePPvqocHFxEQ4ODqJ///7iyy+/rFCvqjFVCCFOnDghxo0bJ9zc3IRarRZt2rQRjz/+uEhNTRVC3HtM0Isvvih69uwpmjdvLpo2bSp69uwp1q5dW692EZHplT2C7cyZM+LRRx8VzZs3Fy1atBDTp08Xf/31l1RPp9OJ+Ph44e/vL1QqlfD19RVxcXHS48MuXboknJ2dxZgxYyrs45FHHhFNmzYVv/76a622Vaahj2ATQojffvtNPPPMM8Ld3V2o1WrRrl07ER0dLbRarVTn1q1bIi4uTnTo0EHY29uLli1bigEDBojXX39d3Llzp9Z9WVVcQgjx7bffigcffFA4OjoKHx8fMXv2bOkxn/c/zrOqbZT/LKnqOHr27NkCgFizZk2t4ybjUgghgxlriBqRXr16wd3dHSkpKZYOhYiIiIiIZIb3pBOZiE6nq3APUlpaGr7//nsMHTrUMkEREREREZGs8Uw6ydKdO3eQn59fbR1nZ+dKH1EhFxcuXEBISAieeuop+Pj44Oeff8a6devg7OyM06dPw83NzdIhEpENs4VxlIjIVuTn5+POnTtVrrezs4O7u7sZIyI548RxJEuHDx+ucdKP5ORkTJw40TwB1UOLFi3Qt29fvPvuu/jjjz/QtGlTjB49GkuWLGGCTkQmZwvjKBGRrRg3bhzS09OrXN+mTRtcuHDBfAGRrPFMOsnSjRs3kJWVVW2drl27wtvb20wRETVMQkICPvvsM/z8889wdHTEgAEDsHTpUnTq1EmqU1JSgn//+9/YunUrtFotwsLCsHbtWnh6ekp1Ll68iGnTpuHAgQNo1qwZoqKikJCQgCZN+J0rGeI4SkQkH1lZWbhx40aV6x0dHTFw4EAzRkRyVuck/eDBg1i+fDmysrJw9epV7Nixw+BZqkIILFiwAO+88w4KCgowcOBAJCUloWPHjlKd/Px8zJgxA7t27YJSqURkZCTefPNNNGvWzGgNIyKSk1GjRmH8+PHo168f7t69i5dffhmnT5/GmTNnpOdKT5s2TXrsjLOzM6ZPnw6lUolvv/0WwL3nR/fq1QteXl5Yvnw5rl69imeeeQZTpkzBa6+9ZsnmEREREZGR1DlJ/+qrr/Dtt9+ib9++GDduXIUkfenSpUhISMCmTZvg7++PefPm4dSpUzhz5gwcHBwAAOHh4bh69Srefvtt6HQ6TJo0Cf369cOWLVuM2jgiIrn6448/4OHhgfT0dDz00EO4efMm3N3dsWXLFjz66KMAgJ9//hmdO3dGRkYGHnzwQXz11Vd4+OGHceXKFens+rp16/DSSy/hjz/+gL29vSWbRERERERGUOfrI8PDwxEeHl7pOiEEVq1ahblz52Ls2LEAgM2bN8PT0xM7d+7E+PHj8dNPP2Hv3r04duwYAgMDAQCrV6/G3/72N7z++uvw8fGpMQa9Xo8rV66gefPmUCgUdW0CEdkAIQRu3boFHx8fKJXW96CKmzdvAgBcXV0B3LsMTqfTISQkRKoTEBAAPz8/KUnPyMhA9+7dDS5/DwsLw7Rp0/Djjz+id+/eFfaj1Wqh1WqlZb1ej/z8fLi5uXH8JGqkrH38tBQefxKRucZPo97EmJOTg9zcXIODTGdnZwQFBSEjIwPjx49HRkYGXFxcpAQdAEJCQqBUKpGZmYlHHnmkwnbLH2RevnwZXbp0MWboRGSlLl26hNatW1s6jDrR6/WIiYnBwIED0a1bNwBAbm4u7O3t4eLiYlDX09MTubm5Up37E/Sy9WXrKpOQkID4+Hgjt4CIbIE1jp+WdOXKFfj6+lo6DCKSAVOPn0ZN0ssOEis7iLz/INPDw8MwiCZN4OrqWueDzHfffRdOTk7GCJ2IrExxcTH++c9/onnz5pYOpc6io6Nx+vRpHDp0yOT7iouLQ2xsrLR88+ZN+Pn5IScnp1Z9p9PpcODAAQwbNgwqlcqUoVpMY2gjwHbakoa28datW/D397fK8dOSyvrr0qVL0Gg01dbV6XTYv38/QkNDbfZ9aGrsw4Zh/zVMVf1XWFgIX19fk4+fVjEdcPmDzLLOiYiIqHGQtHY6nQ4pKSkYOXIk/8Aqwf6pni33T2FhIf75z39a3SWH06dPx5dffomDBw8afAPr5eWFO3fuoKCgwOBsel5eHry8vKQ6R48eNdheXl6etK4yarUaarW6Qrmrq2utxk+dTgcnJye4ubnZ3HuoTGNoI8B22pKGtrHsNdY2flpaWX9pNJpaJelOTk7QaDQ2+z40NfZhw7D/Gqam/jP1+GnUJL3sIDEvL8/gkS55eXno1auXVOfatWsGr7t79y7y8/PrfJCpUqkazZuuMbW1Ptg/1bPF/rG29gghMGPGDOzYsQNpaWnw9/c3WN+3b1+oVCqkpqYiMjISAJCdnY2LFy8iODgYABAcHIxXX30V165dk65ISklJgUaj4S1ARERERDbCqHe7+/v7w8vLC6mpqVJZYWEhMjMzDQ4yCwoKDJ7d+s0330Cv1yMoKMiY4RARyUZ0dDQ++OADbNmyBc2bN0dubi5yc3Px119/Abg3f8fkyZMRGxuLAwcOICsrC5MmTUJwcDAefPBBAEBoaCi6dOmCp59+Gt9//z327duHuXPnIjo6utIvMomIiIjI+tT5TPrt27dx7tw5aTknJwcnT56Eq6sr/Pz8EBMTg1deeQUdO3aUHsHm4+MjPaatc+fOGDVqFKZMmYJ169ZBp9Nh+vTpGD9+fK1mdiciskZJSUkAgKFDhxqUJycnY+LEiQCAlStXQqlUIjIyElqtFmFhYVi7dq1U187ODl9++SWmTZuG4OBgNG3aFFFRUVi0aJG5mkFEREREJlbnJP348eMYNmyYtFx2r3hUVBQ2btyI2bNno6ioCFOnTkVBQQEGDRqEvXv3Ss9IB4APP/wQ06dPx4gRI6QD0rfeessIzSEikichRI11HBwckJiYiMTExCrrtGnTBnv27DFmaEREREQkI3VO0ocOHVrtwaZCocCiRYuqPbPj6uqKLVu21HXXRERERERERDbNKmZ3J6K6aTtnNwBAbSewrD/QbeE+aEv/NwvlhSWjLRUaWany76H78f1ERFQ5jp1EVB9GnTiOiIiIiIiIiOqPSToRERERERGRTDBJJyIiIiIiIpIJJulEREREREREMsEknYiIiIiIiEgmmKQTERERERERyQSTdCIiIiIiIiKZYJJOREREREREJBNM0omIiIiIiIhkgkk6ERERERERkUwwSSciIiIiIiKSCSbpRERERERERDLBJJ2IiIiIiIhIJpikExEREREREckEk3QiIiIiIiIimWCSTkRERERERCQTTNKJiIiIiIiIZIJJOhERERFZrdLSUsybNw/+/v5wdHRE+/btsXjxYgghpDpCCMyfPx/e3t5wdHRESEgIzp49a8GoiYiqxiSdiIiIiKzW0qVLkZSUhDVr1uCnn37C0qVLsWzZMqxevVqqs2zZMrz11ltYt24dMjMz0bRpU4SFhaGkpMSCkRMRVa6JpQMgIiIiIqqvw4cPY+zYsRg9ejQAoG3btvjoo49w9OhRAPfOoq9atQpz587F2LFjAQCbN2+Gp6cndu7cifHjx1ssdiKiyjBJJyIiIiKrNWDAAKxfvx6//PILHnjgAXz//fc4dOgQVqxYAQDIyclBbm4uQkJCpNc4OzsjKCgIGRkZVSbpWq0WWq1WWi4sLAQA6HQ66HS6amMqW69WihrrUOXK+of9VD/sv4apqv/M1Z9M0omIiIjIas2ZMweFhYUICAiAnZ0dSktL8eqrr2LChAkAgNzcXACAp6enwes8PT2ldZVJSEhAfHx8hfL9+/fDycmpVrEtDtRXuW7Pnj212kZjl5KSYukQrBr7r2HK919xcbFZ9mv0JL20tBQLFy7EBx98gNzcXPj4+GDixImYO3cuFAoFgHuXHS1YsADvvPMOCgoKMHDgQCQlJaFjx47GDoeIiIiIbNi2bdvw4YcfYsuWLejatStOnjyJmJgY+Pj4ICoqqt7bjYuLQ2xsrLRcWFgIX19fhIaGQqPRVPtanU6HlJQUzDuuhFavqLTO6YVh9Y6tMSjrw5EjR0KlUlk6HKvD/muYqvqv7IoaUzN6kl42ecemTZvQtWtXHD9+HJMmTYKzszP+9a9/Afjf5B2bNm2Cv78/5s2bh7CwMJw5cwYODg7GDomIiIiIbNSLL76IOXPmSJetd+/eHb/99hsSEhIQFRUFLy8vAEBeXh68vb2l1+Xl5aFXr15VbletVkOtVlcoV6lUtU56tHoFtKWVJ+lMnGqnLv1NFbH/GqZ8/5mrL40+u/v9k3e0bdsWjz76KEJDQ6ucvKNHjx7YvHkzrly5gp07dxo7HCIiIiKyYcXFxVAqDQ9p7ezsoNffu9Tc398fXl5eSE1NldYXFhYiMzMTwcHBZo2ViKg2jH4m3RSTdzRk4g5rx0kfqsf+qZza7t5ENWUT1pSfuMYW+ssW2kBERA03ZswYvPrqq/Dz80PXrl1x4sQJrFixAs8++ywAQKFQICYmBq+88go6duwoXcXp4+ODiIgIywZPRFQJoyfpppi8wxgTd1g7TvpQPfaPoWX9DZfLT1xjC5PVmGviDiIikrfVq1dj3rx5eP7553Ht2jX4+Pjgueeew/z586U6s2fPRlFREaZOnYqCggIMGjQIe/fu5W2WRCRLRk/STTF5R0Mm7rB2nPSheuyfynVbuA/AvTPoiwP1FSausYXJasw1cQcREclb8+bNsWrVKqxatarKOgqFAosWLcKiRYvMFxgRUT0ZPUk3xeQdxpi4w9o1prbWB/vHUPlJaspPXGMLfWULbSAiIiIiKs/oE8dx8g4ioooOHjyIMWPGwMfHBwqFosJEmRMnToRCoTD4GTVqlEGd/Px8TJgwARqNBi4uLpg8eTJu375txlYQERERkakZ/Uw6J+8gIqqoqKgIPXv2xLPPPotx48ZVWmfUqFFITk6WlstfQTRhwgRcvXoVKSkp0Ol0mDRpEqZOnYotW7aYNHYiIiIiMh+jJ+mcvIOIqKLw8HCEh4dXW0etVku3BJX3008/Ye/evTh27BgCAwMB3Btv//a3v+H111+Hj4+P0WMmIiIiIvMz+uXuZZN3/Pbbb/jrr79w/vx5vPLKK7C3t5fqlE3ekZubi5KSEnz99dd44IEHjB0KEZFVSUtLg4eHBzp16oRp06bh+vXr0rqMjAy4uLhICToAhISEQKlUIjMz0xLhEhEREZEJGP1MOhE1XNs5u6tdf2HJaDNFQuYyatQojBs3Dv7+/jh//jxefvllhIeHIyMjA3Z2dsjNzYWHh4fBa5o0aQJXV9cqH18JAFqtFlqtVloumxVfp9PV6lnzZXXUSlFjHWtVFr+1t6MmbKftaGgbbblviIhsAZN0IiIZKHsiBnDvqRg9evRA+/btkZaWhhEjRtR7uwkJCYiPj69Qvn//fjg5OdV6O4sD9VWu27NnT71ik5uUlBRLh2AWbKftqG8bi4uLjRwJEREZE5N0IiIZateuHVq2bIlz585hxIgR8PLywrVr1wzq3L17F/n5+VXexw4AcXFxiI2NlZYLCwvh6+uL0NBQaDSaGuPQ6XRISUnBvONKaPWKSuucXhhWy1bJU1kbR44cadOP9mM7bUdD21h2RQ0REckTk3QiIhn6/fffcf36dXh7ewMAgoODUVBQgKysLPTt2xcA8M0330Cv1yMoKKjK7ajV6gqzxAP3njNfl4N7rV4BbWnlSbqtJEJ17RNrxXbajvq20db7hYjI2jFJJyIyg9u3b+PcuXPSck5ODk6ePAlXV1e4uroiPj4ekZGR8PLywvnz5zF79mx06NABYWH3zlJ37twZo0aNwpQpU7Bu3TrodDpMnz4d48eP58zuRERERDbE6LO7ExFRRcePH0fv3r3Ru3dvAEBsbCx69+6N+fPnw87ODj/88AP+/ve/44EHHsDkyZPRt29f/Pe//zU4C/7hhx8iICAAI0aMwN/+9jcMGjQI69evt1STiIiIiMgEeCadiMgMhg4dCiGqniF93759NW7D1dUVW7ZsMWZYRERERCQzPJNOREREREREJBNM0omIiIiIiIhkgkk6ERERERERkUwwSSciIiIiIiKSCSbpRERERERERDLBJJ2IiIiIiIhIJpikExEREREREckEk3QiIiIiIiIimWCSTkRERERERCQTTNKJiIiIiIiIZKKJpQMgorprO2e3pUMgIiIiIiIT4Jl0IiIiIiIiIplgkk5EREREVu3y5ct46qmn4ObmBkdHR3Tv3h3Hjx+X1gshMH/+fHh7e8PR0REhISE4e/asBSMmIqoak3QiIiIislo3btzAwIEDoVKp8NVXX+HMmTN444030KJFC6nOsmXL8NZbb2HdunXIzMxE06ZNERYWhpKSEgtGTkRUOd6TTkRERERWa+nSpfD19UVycrJU5u/vL/1fCIFVq1Zh7ty5GDt2LABg8+bN8PT0xM6dOzF+/Hizx0xEVB2eSSciIiIiq/XFF18gMDAQjz32GDw8PNC7d2+888470vqcnBzk5uYiJCREKnN2dkZQUBAyMjIsETIRUbVMcib98uXLeOmll/DVV1+huLgYHTp0QHJyMgIDAwHc+0ZzwYIFeOedd1BQUICBAwciKSkJHTt2NEU4RERERGSjfv31VyQlJSE2NhYvv/wyjh07hn/961+wt7dHVFQUcnNzAQCenp4Gr/P09JTWVUar1UKr1UrLhYWFAACdTgedTldtTGXr1UpRYx2qXFn/sJ/qh/3XMFX1n7n60+hJetl9QcOGDcNXX30Fd3d3nD17ttL7gjZt2gR/f3/MmzcPYWFhOHPmDBwcHIwdEhERERHZKL1ej8DAQLz22msAgN69e+P06dNYt24doqKi6r3dhIQExMfHVyjfv38/nJycarWNxYH6Ktft2bOn3rE1JikpKZYOwaqx/xqmfP8VFxebZb9GT9J5XxARERERmYu3tze6dOliUNa5c2d8+umnAAAvLy8AQF5eHry9vaU6eXl56NWrV5XbjYuLQ2xsrLRcWFgIX19fhIaGQqPRVBuTTqdDSkoK5h1XQqtXVFrn9MKwarfR2JX14ciRI6FSqSwdjtVh/zVMVf1XdkWNqRk9Sf/iiy8QFhaGxx57DOnp6WjVqhWef/55TJkyBUDN9wVVlqQ35HIja8dLVapnq/2jtqv68rg6bef/X2ZX/nI7W+gvW2gDERE13MCBA5GdnW1Q9ssvv6BNmzYA7p0s8vLyQmpqqpSUFxYWIjMzE9OmTatyu2q1Gmq1ukK5SqWqddKj1SugLa08SWfiVDt16W+qiP3XMOX7z1x9afQk3RT3BRnjciNrx0tVqmdr/bOsv3G3V/5yO1u4xM5clxsREZG8zZw5EwMGDMBrr72Gxx9/HEePHsX69euxfv16AIBCoUBMTAxeeeUVdOzYUbrV0sfHBxEREZYNnoioEkZP0k1xX1BDLjeydrxUpXq22j/dFu4zynbUSoHFgfoKl9vZwiV25rrciIiI5K1fv37YsWMH4uLisGjRIvj7+2PVqlWYMGGCVGf27NkoKirC1KlTUVBQgEGDBmHv3r2cC4mIZMnoSbop7gsyxuVG1q4xtbU+bK1/qro0rt7bK3e5nS30lS20gYiIjOPhhx/Gww8/XOV6hUKBRYsWYdGiRWaMioiofoz+nPS63BdUpuy+oODgYGOHQ0RERERERGQ1jH4mnfcFEREREREREdWP0ZN03hdERERERFS9tnN2V7v+wpLRZoqEiOTG6Ek6wPuCiIiIiIiIiOrD6PekExEREREREVH9MEknIiIiIiIikgkm6UREREREREQywSSdiIiIiIiISCaYpBMRERERERHJBJN0IiIzOHjwIMaMGQMfHx8oFArs3LnTYL0QAvPnz4e3tzccHR0REhKCs2fPGtTJz8/HhAkToNFo4OLigsmTJ+P27dtmbAURERERmRqTdCIiMygqKkLPnj2RmJhY6fply5bhrbfewrp165CZmYmmTZsiLCwMJSUlUp0JEybgxx9/REpKCr788kscPHgQU6dONVcTiIiIiMgMTPKcdCIiMhQeHo7w8PBK1wkhsGrVKsydOxdjx44FAGzevBmenp7YuXMnxo8fj59++gl79+7FsWPHEBgYCABYvXo1/va3v+H111+Hj4+P2dpCRERERKbDJJ2IyMJycnKQm5uLkJAQqczZ2RlBQUHIyMjA+PHjkZGRARcXFylBB4CQkBAolUpkZmbikUceqXTbWq0WWq1WWi4sLAQA6HQ66HS6GmMrq6NWihrrWKuy+K29HTVhO21HQ9toy31DRGQLmKQTEVlYbm4uAMDT09Og3NPTU1qXm5sLDw8Pg/VNmjSBq6urVKcyCQkJiI+Pr1C+f/9+ODk51TrGxYH6Ktft2bOn1tuRs5SUFEuHYBZsp+2obxuLi4uNHAkRERkTk3QiIhsWFxeH2NhYabmwsBC+vr4IDQ2FRqOp8fU6nQ4pKSmYd1wJrV5RaZ3TC8OMFq8llLVx5MiRUKlUlg7HZNhO29HQNpZdUUNERPLEJJ3IAtrO2W3pEEhGvLy8AAB5eXnw9vaWyvPy8tCrVy+pzrVr1wxed/fuXeTn50uvr4xarYZara5QrlKp6nRwr9UroC2tPEm3lUSorn1irdhO21HfNtp6vxARWTvO7k5EZGH+/v7w8vJCamqqVFZYWIjMzEwEBwcDAIKDg1FQUICsrCypzjfffAO9Xo+goCCzx0xEREREpsEz6UREZnD79m2cO3dOWs7JycHJkyfh6uoKPz8/xMTE4JVXXkHHjh3h7++PefPmwcfHBxEREQCAzp07Y9SoUZgyZQrWrVsHnU6H6dOnY/z48ZzZnYiIiMiGMEknIjKD48ePY9iwYdJy2X3iUVFR2LhxI2bPno2ioiJMnToVBQUFGDRoEPbu3QsHBwfpNR9++CGmT5+OESNGQKlUIjIyEm+99ZbZ20JEREREpsMkncgEeM85lTd06FAIUfVjzBQKBRYtWoRFixZVWcfV1RVbtmwxRXhEREREJBO8J52IiIiIiIhIJpikExEREREREckEk3QiIiIiIiIimWCSTkRERERERCQTTNKJiIiIyGYsWbIECoUCMTExUllJSQmio6Ph5uaGZs2aITIyEnl5eZYLkoioGkzSiYiIiMgmHDt2DG+//TZ69OhhUD5z5kzs2rUL27dvR3p6Oq5cuYJx48ZZKEoiouqZPEnnt5lEREREZGq3b9/GhAkT8M4776BFixZS+c2bN7FhwwasWLECw4cPR9++fZGcnIzDhw/jyJEjFoyYiKhyJk3S+W0mEREREZlDdHQ0Ro8ejZCQEIPyrKws6HQ6g/KAgAD4+fkhIyPD3GESEdWoiak2fP+3ma+88opUXvZt5pYtWzB8+HAAQHJyMjp37owjR47gwQcfNFVIRERERGSDtm7diu+++w7Hjh2rsC43Nxf29vZwcXExKPf09ERubm6V29RqtdBqtdJyYWEhAECn00Gn01UbT9l6tVLUtglVbqOxKmt/Y++H+mL/NUxV/Weu/jRZkn7/t5n3J+k1fZvJJJ2IiIiIauvSpUt44YUXkJKSAgcHB6NtNyEhAfHx8RXK9+/fDycnp1ptY3Ggvt7737NnT71fa0tSUlIsHYJVY/81TPn+Ky4uNst+TZKkG/vbzIZ8k2nt+C1Y9eTaP2q7+n9zbkxl3+CX/yZfbv1VH7bQBiIiarisrCxcu3YNffr0kcpKS0tx8OBBrFmzBvv27cOdO3dQUFBgcPyZl5cHLy+vKrcbFxeH2NhYabmwsBC+vr4IDQ2FRqOpNiadToeUlBTMO66EVq+oV7tOLwyr1+tsRVkfjhw5EiqVytLhWB32X8NU1X9leaipGT1JN8W3mcb4JtPa8Vuw6smtf5b1t3QEhsp/k28L386b65tMIiKStxEjRuDUqVMGZZMmTUJAQABeeukl+Pr6QqVSITU1FZGRkQCA7OxsXLx4EcHBwVVuV61WQ61WVyhXqVS1Tnq0egW0pfVL0plY3VOX/qaK2H8NU77/zNWXRk/STfFtZkO+ybR2/BasenLtn24L91k6BAD3zqAvDtRX+CbfFr6dN9c3mUREJG/NmzdHt27dDMqaNm0KNzc3qXzy5MmIjY2Fq6srNBoNZsyYgeDgYN5mSUSyZPQk3RTfZhrjm0xr15jaWh9y65/6fmtuKuW/yZdTX9WXLbTBVrSds7vKdReWjDZjJERElVu5ciWUSiUiIyOh1WoRFhaGtWvXWjosIqJKGT1J57eZRERERGRJaWlpBssODg5ITExEYmKiZQIiIqoDk83uXh1+m0lERERERERUkVmSdH6bSURERERERFQzi5xJJyIiIiKi+qtuPhCAc4IQWTOlpQMgIiIiIiIionuYpBMRERERERHJBJN0IiIiIiIiIpngPelERERERDJT0z3nRGS7eCadiIiIiIiISCaYpBMRERERERHJBJN0IiIiIiIiIplgkk5EREREREQkE0zSiYiIiIiIiGSCSToRERERERGRTDBJJyIiIiIiIpIJPiedqBGq7tmrF5aMNmMkZOtqes4v329EREREhngmnYiIiIiIiEgmmKQTERERERERyQSTdCIimVi4cCEUCoXBT0BAgLS+pKQE0dHRcHNzQ7NmzRAZGYm8vDwLRkxERERExsYknYhIRrp27YqrV69KP4cOHZLWzZw5E7t27cL27duRnp6OK1euYNy4cRaMloiIiIiMjRPHERHJSJMmTeDl5VWh/ObNm9iwYQO2bNmC4cOHAwCSk5PRuXNnHDlyBA8++KC5QyUiIiIiE2CSTkQkI2fPnoWPjw8cHBwQHByMhIQE+Pn5ISsrCzqdDiEhIVLdgIAA+Pn5ISMjo8okXavVQqvVSsuFhYUAAJ1OB51OV2M8ZXXUStGQZtW4fUsqi0EOsZgS22k7GtpGW+4bIiJbwCSdiEgmgoKCsHHjRnTq1AlXr15FfHw8Bg8ejNOnTyM3Nxf29vZwcXExeI2npydyc3Or3GZCQgLi4+MrlO/fvx9OTk61jm1xoL7Wdetiz549JtlufaSkpFg6BLNgO21HfdtYXFxs5EiIiMiYmKQTEclEeHi49P8ePXogKCgIbdq0wbZt2+Do6FivbcbFxSE2NlZaLiwshK+vL0JDQ6HRaGp8vU6nQ0pKCuYdV0KrV9QrhuqcXhhm9G3WVVkbR44cCZVKZelwTIbttB0NbWPZFTXUuLWds7vKdReWjDZjJERUHpN0IiKZcnFxwQMPPIBz585h5MiRuHPnDgoKCgzOpufl5VV6D3sZtVoNtVpdoVylUtXp4F6rV0BbavwkXU5JVF37xFqxnbajvm209X6he6pLwolI3ji7OxGRTN2+fRvnz5+Ht7c3+vbtC5VKhdTUVGl9dnY2Ll68iODgYAtGSURkeQkJCejXrx+aN28ODw8PREREIDs726AOH2NJRNbC6GfSExIS8Nlnn+Hnn3+Go6MjBgwYgKVLl6JTp05SnZKSEvz73//G1q1bodVqERYWhrVr18LT09PY4RDVW03fQPNSMDK2WbNmYcyYMWjTpg2uXLmCBQsWwM7ODk8++SScnZ0xefJkxMbGwtXVFRqNBjNmzEBwcDBndieiRi89PR3R0dHo168f7t69i5dffhmhoaE4c+YMmjZtCuDeYyx3796N7du3w9nZGdOnT8e4cePw7bffWjh6IiJDRk/SOUhSY8HLyMjYfv/9dzz55JO4fv063N3dMWjQIBw5cgTu7u4AgJUrV0KpVCIyMtLgC04iosZu7969BssbN26Eh4cHsrKy8NBDD/ExlkRkVYyepHOQJCKqn61bt1a73sHBAYmJiUhMTDRTRERE1unmzZsAAFdXVwCo92MsiYgsweQTx3GQJCIiIiJz0ev1iImJwcCBA9GtWzcAqNdjLLVaLbRarbRcNiu+Tqer8VnzZevVSlHfZlhUTe0zZwxyiMUasf8apqr+M1d/mjRJl8Mgae34B1Y9U/aP2s46P1jvV3ZwUJeDBGt5r1lLnEREZF7R0dE4ffo0Dh061KDtJCQkID4+vkL5/v374eTkVKttLA7UNygGS9mzZ4+lQ5CkpKRYOgSrxv5rmPL9V1xcbJb9mjRJl9Mgae34B1Y9U/TPsv5G36TF1OUgQU4fzNUx1yBJRETWY/r06fjyyy9x8OBBtG7dWir38vKq82Ms4+LiEBsbKy0XFhbC19cXoaGh0Gg01cZR9iz7eceV0OqN//hKSzu9MMzk+yjrw5EjR9bpsYHdFu6rdr05YpeD+vYf3VNV/5WdLDY1kyXpchkkrR3/wKpnyv6paZC3BmqlwOJAfZ0OEqzlw8tcgyQREcmfEAIzZszAjh07kJaWBn9/f4P19z/GMjIyEkDNj7FUq9VQq9UVyuvyfHqtXgFtqe0l6eY8Jq1LfwOosb8b2/F0XfuPDJXvP3P1pdGTdLkOktauMbW1PkzRP7b0oVqXgwRreZ9ZS5xERGR60dHR2LJlCz7//HM0b95cuoXS2dkZjo6OfIwlEVkVoyfpHCSJiIiIyJySkpIAAEOHDjUoT05OxsSJEwHwMZZEZD2MnqRzkCQiIiIicxKi5glS+RhL82k7Z3e16y8sGW2mSIisk0kud68JB0ki+eIHKxERERGR5Zj8OelERERERES11XbObqjtBJb1vzeRb/l5dXjCgGwdk3RqtGo6Y0xEREREtqWhx3/8goDMQWnpAIiIiIiIiIjoHibpRERERERERDLBJJ2IiIiIiIhIJnhPOhERERERWY3GOq8Qn8DTeDBJJyIii+EBBxEREZEhJulERERERERmUN2X0/ximsowSSciItnimXYiIiJqbDhxHBEREREREZFM8Ew6ERERERGRhTXWCfGoIibpRERktXg5PBEREdkaJulERNQolSX4ajuBZf2Bbgv3QVuqkNYzwSciImty/xfXlX228XPNevCedCIiIiIiIiKZ4Jl0slm8r4eIiIhIfqz5GM2aY68JbyGTDybpRERERERUa7acqBLJAS93JyIiIiIiIpIJnkknq9V2zu4qJ3wiIgIadraHl/0RERGRJfBMOhEREREREZFM8Ew6ERFRPfBMOxEREZkCz6QTERERERERyQTPpBNRnfDsIRERERGR6fBMOhEREREREZFMWPRMemJiIpYvX47c3Fz07NkTq1evRv/+/S0ZEpkZn7NJVHccO62DKcc3XrFCVD8cP4nIGlgsSf/4448RGxuLdevWISgoCKtWrUJYWBiys7Ph4eFhqbCIqIEampgw+agex04iovrh+EmNXUOP0eT85XNDYpPjsafFkvQVK1ZgypQpmDRpEgBg3bp12L17N9577z3MmTPHUmEREckax04CODcEUX1w/CQia2GRJP3OnTvIyspCXFycVKZUKhESEoKMjAyT7LMhBzS2fDBk6rOevJydyHgsMXZS42TLn3vUOHH8JJI3fu4YskiS/ueff6K0tBSenp4G5Z6envj5558r1NdqtdBqtdLyzZs3AQD5+fnQ6XS12meTu0XVrr9+/bpJXttQOp0OxcXFuH79OlQqldG3X1PbalJT2xu6/Zo00QsUF+vRRKdEqV5h0n1ZI2vsn9r+Pd26dQsAIIQwZTiyUtexE2j4+Fk2BlnTe6iurPHvpCaV/R3d/3ky6PWD1b6+poODDrO2Vbs+M25EleuCElJr2HrDHJr1kEk/Ny2prO/USoG5vfXo9Z/PoL3vPVtdv9+P4+f/mGr8bAxjp6nZ4thsTrbWf6bMOWr6zLz/s8Rc46dVPIItISEB8fHxFcr9/f2Nto+Wb1jmtdZODm3/h6UDkDlr65+6vqdu3boFZ2dn0wRjA8wxftoCa/s7qYmlx2ZL7t9bBp9L5lDZe5bjp3Fx/LQ8Wxubzc2W+s+Unyv12bapx0+LJOktW7aEnZ0d8vLyDMrz8vLg5eVVoX5cXBxiY2OlZb1ej/z8fLi5uUGhsP5vhqpTWFgIX19fXLp0CRqNxtLhyA77p3q23D9CCNy6dQs+Pj6WDsVs6jp2Ag0fP235PVSmMbQRYDttSUPbyPHzf0w1fjaG96GpsQ8bhv3XMFX1n7nGT4sk6fb29ujbty9SU1MREREB4N7Al5qaiunTp1eor1aroVarDcpcXFzMEKl8aDQa/oFVg/1TPVvtn8Z2BqiuYydgvPHTVt9D92sMbQTYTlvSkDZy/DTP+NkY3oemxj5sGPZfw1TWf+YYPy12uXtsbCyioqIQGBiI/v37Y9WqVSgqKpJm3CQiooo4dhIR1Q/HTyKyFhZL0p944gn88ccfmD9/PnJzc9GrVy/s3bu3woQeRET0Pxw7iYjqh+MnEVkLi04cN3369CovMaJ71Go1FixYUOFyK7qH/VM99o9tMufY2RjeQ42hjQDbaUsaQxtNxVzjJ39HDcc+bBj2X8NYuv8UojE9f4OIiIiIiIhIxpSWDoCIiIiIiIiI7mGSTkRERERERCQTTNKJiIiIiIiIZIJJOhEREREREZFMMEm3AkuWLIFCoUBMTIylQ5GVy5cv46mnnoKbmxscHR3RvXt3HD9+3NJhyUJpaSnmzZsHf39/ODo6on379li8eDE4TyRVJjExEW3btoWDgwOCgoJw9OjRautv374dAQEBcHBwQPfu3bFnzx4zRVp/dWnjxo0boVAoDH4cHBzMGG3dHTx4EGPGjIGPjw8UCgV27txZ42vS0tLQp08fqNVqdOjQARs3bjR5nA1V13ampaVV+F0qFArk5uaaJ+B6SEhIQL9+/dC8eXN4eHggIiIC2dnZNb7OGv8ubVldx1VbtHDhwgp/ewEBAdL6kpISREdHw83NDc2aNUNkZCTy8vIMtnHx4kWMHj0aTk5O8PDwwIsvvoi7d+8a1LHGsawyNY1vQgjMnz8f3t7ecHR0REhICM6ePWtQJz8/HxMmTIBGo4GLiwsmT56M27dvG9T54YcfMHjwYDg4OMDX1xfLli2rEIs1jic19d/EiRMrvB9HjRplUEdO/cckXeaOHTuGt99+Gz169LB0KLJy48YNDBw4ECqVCl999RXOnDmDN954Ay1atLB0aLKwdOlSJCUlYc2aNfjpp5+wdOlSLFu2DKtXr7Z0aCQzH3/8MWJjY7FgwQJ899136NmzJ8LCwnDt2rVK6x8+fBhPPvkkJk+ejBMnTiAiIgIRERE4ffq0mSOvvbq2EQA0Gg2uXr0q/fz2229mjLjuioqK0LNnTyQmJtaqfk5ODkaPHo1hw4bh5MmTiImJwT//+U/s27fPxJE2TF3bWSY7O9vg9+nh4WGiCBsuPT0d0dHROHLkCFJSUqDT6RAaGoqioqIqX2ONf5e2rD5jjq3q2rWrwd/eoUOHpHUzZ87Erl27sH37dqSnp+PKlSsYN26ctL60tBSjR4/GnTt3cPjwYWzatAkbN27E/PnzpTrWOpZVpqbxbdmyZXjrrbewbt06ZGZmomnTpggLC0NJSYlUZ8KECfjxxx+RkpKCL7/8EgcPHsTUqVOl9YWFhQgNDUWbNm2QlZWF5cuXY+HChVi/fr1Ux1rHk9p8PowaNcrg/fjRRx8ZrJdV/wmSrVu3bomOHTuKlJQUMWTIEPHCCy9YOiTZeOmll8SgQYMsHYZsjR49Wjz77LMGZePGjRMTJkywUEQkV/379xfR0dHScmlpqfDx8REJCQmV1n/88cfF6NGjDcqCgoLEc889Z9I4G6KubUxOThbOzs5mis74AIgdO3ZUW2f27Nmia9euBmVPPPGECAsLM2FkxlWbdh44cEAAEDdu3DBLTKZw7do1AUCkp6dXWcca/y5tWV3HHFu1YMEC0bNnz0rXFRQUCJVKJbZv3y6V/fTTTwKAyMjIEEIIsWfPHqFUKkVubq5UJykpSWg0GqHVaoUQtjGWVab8+KbX64WXl5dYvny5VFZQUCDUarX46KOPhBBCnDlzRgAQx44dk+p89dVXQqFQiMuXLwshhFi7dq1o0aKF1H9C3Dum7tSpk7RsC+NJZZ8PUVFRYuzYsVW+Rm79xzPpMhYdHY3Ro0cjJCTE0qHIzhdffIHAwEA89thj8PDwQO/evfHOO+9YOizZGDBgAFJTU/HLL78AAL7//nscOnQI4eHhFo6M5OTOnTvIysoyGGOUSiVCQkKQkZFR6WsyMjIqjElhYWFV1re0+rQRAG7fvo02bdrA19cXY8eOxY8//miOcM3G2n6PDdWrVy94e3tj5MiR+Pbbby0dTp3cvHkTAODq6lplncb2+5Sz+o45turs2bPw8fFBu3btMGHCBFy8eBEAkJWVBZ1OZ9BPAQEB8PPzk/opIyMD3bt3h6enp1QnLCwMhYWF0pjcWN77OTk5yM3NNWirs7MzgoKCDPrLxcUFgYGBUp2QkBAolUpkZmZKdR566CHY29tLdcLCwpCdnY0bN25IdWy1T9PS0uDh4YFOnTph2rRpuH79urRObv3HJF2mtm7diu+++w4JCQmWDkWWfv31VyQlJaFjx47Yt28fpk2bhn/961/YtGmTpUOThTlz5mD8+PEICAiASqVC7969ERMTgwkTJlg6NJKRP//8E6WlpQYHQADg6elZ5T27ubm5dapvafVpY6dOnfDee+/h888/xwcffAC9Xo8BAwbg999/N0fIZlHV77GwsBB//fWXhaIyPm9vb6xbtw6ffvopPv30U/j6+mLo0KH47rvvLB1arej1esTExGDgwIHo1q1blfWs7e/SltVnzLFVQUFB2LhxI/bu3YukpCTk5ORg8ODBuHXrFnJzc2Fvbw8XFxeD19zfT1W9r8vWVVfH1saysvZW977Kzc2tcCtPkyZN4OrqapQ+tfb376hRo7B582akpqZi6dKlSE9PR3h4OEpLSwHIr/+a1Kk2mcWlS5fwwgsvICUlRfaTFVmKXq9HYGAgXnvtNQBA7969cfr0aaxbtw5RUVEWjs7ytm3bhg8//BBbtmxB165dpfu0fHx82D9ENQgODkZwcLC0PGDAAHTu3Blvv/02Fi9ebMHIqK46deqETp06ScsDBgzA+fPnsXLlSrz//vsWjKx2oqOjcfr0aYP7eImsxf1X7/Xo0QNBQUFo06YNtm3bBkdHRwtGRo3R+PHjpf93794dPXr0QPv27ZGWloYRI0ZYMLLK8Uy6DGVlZeHatWvo06cPmjRpgiZNmiA9PR1vvfUWmjRpIn3j05h5e3ujS5cuBmWdO3eWLqNq7F588UXpbHr37t3x9NNPY+bMmbwygwy0bNkSdnZ2FWbTzcvLg5eXV6Wv8fLyqlN9S6tPG8sruxrl3LlzpgjRIqr6PWo0Gps/eO7fv79V/C6nT5+OL7/8EgcOHEDr1q3/X3t3HhdV2f+P/8UyDCAOiAgDioimqeEWJs6NqQmCaKZJuUSFZdoCpmKWVC6YSZql34y07vppi6Z53y5ppoyocJu4keQaomGUCpaGKMQ4MtfvDz8cG9kGGJgz4+v5eMzjwbnONWfe74vhGt5zthr7WtvfpS0zx5xjqzw8PNCpUyecOXMGarUaN27cQFFRkVGff45Tde/rinU19bG1uawi35reV2q1utLFCW/evIkrV66YZUxt7f3bvn17eHl5SZ8Hchs/FukyFBYWhmPHjiE7O1t69O7dGzExMcjOzoaDg4OlQ7S40NDQSrekOX36NAICAiwUkbyUlpbC3t74z9vBwQEGg8FCEZEcOTk5ITg4GGlpaVKbwWBAWlqa0Z7kf9JoNEb9AUCr1Vbb39Lqk+OdysvLcezYMfj6+jZWmE3O2n6P5pSdnS3r36UQAvHx8di4cSN27dqFwMDAWp9zN/8+5cYcc46tun79Os6ePQtfX18EBwdDoVAYjVNOTg7y8/OlcdJoNDh27JhR4aTVaqFSqaQdNXfLez8wMBBqtdoo1+LiYhw4cMBovIqKipCVlSX12bVrFwwGA0JCQqQ+GRkZ0Ov1Uh+tVot7771XukPS3TKmv//+Oy5fvix9Hshu/Op0mTmyGF7d3djBgweFo6OjePvtt0Vubq5YvXq1cHV1FV999ZWlQ5OF2NhY0bp1a7F161aRl5cnNmzYILy8vMSrr75q6dBIZtauXSuUSqVYtWqVOHnypJg0aZLw8PCQrqb71FNPiZkzZ0r9f/jhB+Ho6CgWL14sTp06JebMmSMUCoU4duyYpVKoVV1zTEpKEjt27BBnz54VWVlZYuzYscLZ2VmcOHHCUinU6tq1a+LIkSPiyJEjAoB4//33xZEjR8Svv/4qhBBi5syZ4qmnnpL6//LLL8LV1VXMmDFDnDp1SqSkpAgHBwexfft2S6VgkrrmuWTJErFp0yaRm5srjh07JqZMmSLs7e3Fzp07LZVCrV588UXh7u4u9uzZIy5evCg9SktLpT628Hdpy2qbc+4W06dPF3v27BF5eXnihx9+EOHh4cLLy0tcunRJCCHECy+8INq2bSt27dolDh8+LDQajdBoNNLzb968KYKCgkRERITIzs4W27dvF61atRKJiYlSH2udy6pS2/z2zjvvCA8PD7F582Zx9OhRMWLECBEYGCj+/vtvaRtDhgwRvXr1EgcOHBB79+4VHTt2FOPGjZPWFxUVCR8fH/HUU0+J48ePi7Vr1wpXV1fx8ccfS32sdT6pafyuXbsmXnnlFZGZmSny8vLEzp07xf333y86duwoysrKpG3IafxYpFsJFumVbdmyRQQFBQmlUik6d+4sPvnkE0uHJBvFxcViypQpom3btsLZ2Vm0b99evPHGG0a3jCCqsGzZMtG2bVvh5OQk+vTpI/bv3y+tGzBggIiNjTXq/80334hOnToJJycncd9994nvvvuuiSOuu7rkOHXqVKmvj4+PGDp0qPjxxx8tELXpKm41duejIq/Y2FgxYMCASs/p2bOncHJyEu3btxcrV65s8rjrqq55Lly4UHTo0EE4OzsLT09PMXDgQLFr1y7LBG+iqvIDYPT7sZW/S1tW05xztxgzZozw9fUVTk5OonXr1mLMmDHizJkz0vq///5bvPTSS6JFixbC1dVVPProo+LixYtG2zh37pyIiooSLi4uwsvLS0yfPl3o9XqjPtY4l1WltvnNYDCIWbNmCR8fH6FUKkVYWJjIyckx2sbly5fFuHHjhJubm1CpVOKZZ54R165dM+rz008/iX79+gmlUilat24t3nnnnUqxWON8UtP4lZaWioiICNGqVSuhUChEQECAmDhxYqUvzuQ0fnZCCFG3fe9ERERERERE1Bh4TjoRERERERGRTLBIJyIiIiIiIpIJFulEREREREREMsEinYiIiIiIiEgmWKQTERERERERyQSLdCIiIiIiIiKZYJFOREREREREJBMs0m3YqlWrYGdnh3PnzgEABg4ciIEDBxr1KSwsxGOPPYaWLVvCzs4OS5cuNctrz507F3Z2dmbZFhER3d3atWuH8ePHWzqMJpWRkYHhw4fDz88PdnZ22LRpU523IYTA4sWL0alTJyiVSrRu3Rpvv/22+YMlIiKzYpF+l5s2bRp27NiBxMREfPnllxgyZIjJzy0tLcXcuXOxZ8+exguQiMiM9u3bh7lz56KoqMjSodTIWuI0p7sx55qUlJSgR48eSElJqfc2pkyZgk8//RSLFy/Gzz//jG+//RZ9+vQxY5R0t7GWv1NribOx3O352wRBNmvlypUCgMjLyxNCCKHT6YROpzPq4+PjI2JiYuq1/T/++EMAEHPmzKm0Tq/Xi7///rte2yUiaizvvvuu0bwoV9YSpznVlHNZWZm4ceNG0wclEwDExo0bjdrKysrE9OnThZ+fn3B1dRV9+vQRu3fvltafPHlSODo6ip9//rlpgyWbZi1zk7XE2Vju9vxtAfek30WcnJzg5ORk1Hbp0iV4eHiY/bUcHR3h7Oxs9u3KQUlJiaVDICKSPXPOlUqlEgqFwmzbswXx8fHIzMzE2rVrcfToUTz++OMYMmQIcnNzAQBbtmxB+/btsXXrVgQGBqJdu3Z47rnncOXKFQtHTkREtbL0twTUeO7ckz5gwAAxYMAAo3V3Pir89ddfYsqUKaJNmzbCyclJdOjQQbzzzjuivLxcCCFEXl5elc+v2Ks+Z84ccefbC4CIi4sT33zzjejSpYtwdnYWffv2FUePHhVCCLFixQrRoUMHoVQqxYABA6r89m///v0iMjJSqFQq4eLiIvr37y/27t1b57H5888/xZNPPimaN28u3N3dxdNPPy2ys7MFALFy5UqpX2xsrGjWrJk4c+aMiIqKEm5ubmLEiBFCCCGuX78uEhISpDHq1KmTePfdd4XBYDB6rdTUVBEaGirc3d1Fs2bNRKdOnURiYqJRnw8++EB07dpVuLi4CA8PDxEcHCxWr15d57yIqHoV89Kdj7y8PKHX68W8efNE+/bthZOTkwgICBCJiYmirKzMaBsBAQFi2LBhYvfu3SI4OFg4OzuLoKAgaQ/mf//7XxEUFCSUSqW4//77xY8//mj0/J9++knExsaKwMBAoVQqhY+Pj3jmmWfEn3/+aVKcQgiTYxVCiG3btol+/foJV1dX4ebmJoYOHSqOHz9u1OfixYti/PjxonXr1sLJyUmo1WrxyCOP1GkPTEXMJ06cEOPGjRMeHh6iZ8+eZss5ICBAxMbGSv0rPsP27t0rpk2bJry8vISrq6sYOXKkuHTpklFs5eXlYs6cOcLX11e4uLiIgQMHihMnTlTappzhjj3pv/76q3BwcBDnz5836hcWFiZ9vjz//PNCqVSKkJAQkZGRIXbv3i169uwpHnrooaYMnWwI59DGmUPXr18vAIg9e/ZUWrdixQoBQBw7dkxqS0tLk2Jyd3cXjzzyiDh58qTJ+QshxJdffinuv/9+4ezsLFq0aCHGjBkj8vPzjV779OnTYtSoUcLHx0colUrRunVrMWbMGFFUVGRSXtQwjmav+skq9O/fH19++SWeeuopDB48GE8//bS0rrS0FAMGDMD58+fx/PPPo23btti3bx8SExNx8eJFLF26FK1atcLy5cvx4osv4tFHH8WoUaMAAN27d6/xdf/3v//h22+/RVxcHAAgOTkZDz/8MF599VV89NFHeOmll/DXX39h0aJFePbZZ7Fr1y7pubt27UJUVBSCg4MxZ84c2NvbY+XKlRg0aBD+97//mXyencFgwPDhw3Hw4EG8+OKL6Ny5MzZv3ozY2Ngq+9+8eRORkZHo168fFi9eDFdXVwgh8Mgjj2D37t2YMGECevbsiR07dmDGjBk4f/48lixZAgA4ceIEHn74YXTv3h3z5s2DUqnEmTNn8MMPP0jb//e//42XX34Zjz32GKZMmYKysjIcPXoUBw4cwBNPPGFSTkRUu1GjRuH06dP4+uuvsWTJEnh5eQEAWrVqheeeew6ff/45HnvsMUyfPh0HDhxAcnIyTp06hY0bNxpt58yZM3jiiSfw/PPP48knn8TixYsxfPhwrFixAq+//jpeeuklALfmt9GjRyMnJwf29rcOXNNqtfjll1/wzDPPQK1W48SJE/jkk09w4sQJ7N+/H3Z2djXGCcDkWL/88kvExsYiMjISCxcuRGlpKZYvX45+/frhyJEjaNeuHQAgOjoaJ06cwOTJk9GuXTtcunQJWq0W+fn5Uh9TPf744+jYsSMWLFgAIYTZcq7O5MmT0aJFC8yZMwfnzp3D0qVLER8fj3Xr1kl9EhMTsWjRIgwfPhyRkZH46aefEBkZibKysjrlJifHjh1DeXk5OnXqZNSu0+nQsmVLALc+63Q6Hb744gup32effYbg4GDk5OTg3nvvbfK4ybpxDm2cOXTYsGFwc3PDN998gwEDBhitW7duHe677z4EBQUBAHbu3ImoqCi0b98ec+fOxd9//41ly5YhNDQUP/74I9q1a1dr/m+//TZmzZqF0aNH47nnnsMff/yBZcuWoX///jhy5Ag8PDxw48YNREZGQqfTYfLkyVCr1Th//jy2bt2KoqIiuLu7m/y+oXqy9LcE1Hhq2pNeAf+3d/uf3nrrLdGsWTNx+vRpo/aZM2cKBwcH6Zu2ms5Jr25PulKpNPom7+OPPxYAhFqtFsXFxVJ7YmKiUewGg0F07NhRREZGGu2pLi0tFYGBgWLw4MGmDIkQ4ta3tADE0qVLpbby8nIxaNCgKvekAxAzZ8402samTZsEADF//nyj9scee0zY2dmJM2fOCCGEWLJkiQAg/vjjj2rjGTFihLjvvvtMjp+I6q+q8/QqjqJ57rnnjPq+8sorAoDYtWuX1BYQECAAiH379kltO3bsEACEi4uL+PXXX6X2ivntn+cJl5aWVorp66+/FgBERkZGjXHWJdZr164JDw8PMXHiRKN+BQUFwt3dXWr/66+/BADx7rvvVjVcJquY88eNG1dpXUNzFqL6Penh4eFGnwnTpk0TDg4O0p6egoIC4ejoKEaOHGm0vblz5woAVrsnfe3atcLBwUH8/PPPIjc31+hx8eJFIYQQs2fPFo6OjkbbKS0tFQBEampqU4ZPNoRzaOPMoePGjRPe3t7i5s2bUtvFixeFvb29mDdvntTWs2dP4e3tLS5fviy1/fTTT8Le3l48/fTTteZ/7tw54eDgIN5++22j9mPHjglHR0ep/ciRIwKAWL9+fYPyovrjOelUyfr16/Hggw+iRYsW+PPPP6VHeHg4ysvLkZGRUe9th4WFGX2rGBISAuDWt5DNmzev1P7LL78AALKzs5Gbm4snnngCly9flmIqKSlBWFgYMjIyYDAYTIph+/btUCgUmDhxotRmb28v7d2vyosvvmi0vG3bNjg4OODll182ap8+fTqEEPj+++8BQDrff/PmzdXG5+Hhgd9//x2HDh0yKX4iMq9t27YBABISEozap0+fDgD47rvvjNq7du0KjUYjLVfMV4MGDULbtm0rtVfMYwDg4uIi/VxWVoY///wTffv2BQD8+OOPZotVq9WiqKgI48aNM5rHHRwcEBISgt27d0vxODk5Yc+ePfjrr79qff3avPDCC5XaGppzTSZNmmR0u88HH3wQ5eXl+PXXXwEAaWlpuHnzprRnrsLkyZMb9LqW1qtXL5SXl+PSpUu45557jB5qtRoAEBoaips3b+Ls2bPS806fPg0ACAgIsEjcZJs4hzZ8Dh0zZgwuXbpkdMek//znPzAYDBgzZgwA4OLFi8jOzsb48ePh6ekp9evevTsGDx4s5VaTDRs2wGAwYPTo0UZ5qdVqdOzYUcqrYk/5jh07UFpaWu+8qP5YpFMlubm52L59O1q1amX0CA8PB3DrYnP19c/JF7g9Cfj7+1fZXjHhVVwIJzY2tlJcn376KXQ6Ha5evWpSDL/++it8fX3h6upq1H7PPfdU2d/R0RFt2rSptA0/Pz+jLxYAoEuXLtJ64NakGxoaiueeew4+Pj4YO3YsvvnmG6OC/bXXXoObmxv69OmDjh07Ii4uzuhweCJqXL/++ivs7e0rzQFqtRoeHh7S33OF+s5jAHDlyhVMmTIFPj4+cHFxQatWrRAYGAgAJs1hpsZaMWcOGjSo0pyZmpoqzeNKpRILFy7E999/Dx8fH/Tv3x+LFi1CQUFBrbFUpSKXf2pozjW583fRokULALfHvGI87hwvT09Pqa9cXb9+HdnZ2cjOzgYA5OXlITs7G/n5+ejUqRNiYmLw9NNPY8OGDcjLy8PBgweRnJwsFRnh4eG4//778eyzz+LIkSPIysrC888/j8GDB1c6TJ6oITiHNnwOHTJkCNzd3Y1O1Vm3bh169uwp/b1WxFbVqSpdunSRdl7VJDc3F0IIdOzYsVJep06dkvIKDAxEQkICPv30U3h5eSEyMhIpKSkNnrPJdDwnnSoxGAwYPHgwXn311SrXN+TD3cHBoU7t4v/Oaawoat9991307Nmzyr5ubm71jqsmSqVSOheqrlxcXJCRkYHdu3fju+++w/bt27Fu3ToMGjQIqampcHBwQJcuXZCTk4OtW7di+/bt+O9//4uPPvoIs2fPRlJSkpmzIaLq/HOPbE3qO48BwOjRo7Fv3z7MmDEDPXv2hJubGwwGA4YMGWLy0UCmxFqxrS+//FLas/pPjo63P/6nTp2K4cOHY9OmTdixYwdmzZqF5ORk7Nq1C7169TI5JsB4L1cFc+VcFVPG3FodPnwYDz30kLRcsecvNjYWq1atwsqVKzF//nxMnz4d58+fh5eXF/r27YuHH34YwK0jxLZs2YLJkyejf//+aNasGaKiovDee+9ZJB+yfZxD6z+HKpVKjBw5Ehs3bsRHH32EwsJC/PDDD1iwYIHJOZnCYDDAzs4O33//fZXj/c//pd977z2MHz8emzdvRmpqKl5++WUkJydj//79lXZekfmxSKdKOnTogOvXr0t7zqtj6mRsDh06dAAAqFSqWuOqTUBAAHbv3o3S0lKjvelnzpyp0zZ27tyJa9euGe1N//nnn6X1Fezt7REWFoawsDC8//77WLBgAd544w3s3r1byqVZs2YYM2YMxowZgxs3bmDUqFF4++23kZiYaLO3siOyhKrmrYCAABgMBuTm5kpHwwBAYWEhioqKzHZo8F9//YW0tDQkJSVh9uzZUnvFHpva4qxLrBVzpre3t0lzZocOHTB9+nRMnz4dubm56NmzJ9577z189dVXdcrxTubIuSEqxuPMmTNGe/kvX75slsP7G9PAgQNr/LJBoVAgKSmpxi9z/fz88N///rcxwqO7FOfQqpljDh0zZgw+//xzpKWl4dSpUxBCSIe6V8QOADk5OZWe+/PPP8PLywvNmjUDUH3+HTp0gBACgYGBJu1069atG7p164Y333wT+/btQ2hoKFasWIH58+ebnBfVDw93p0pGjx6NzMxM7Nixo9K6oqIi3Lx5EwCkAreoqKjRYwoODkaHDh2wePFiXL9+vdL6P/74w+RtRUZGQq/X49///rfUZjAYkJKSYvI2hg4divLycnz44YdG7UuWLIGdnR2ioqIAoMr70VYcCaDT6QDc+mfxn5ycnNC1a1cIIaDX602OiYhqV/EPzD/nraFDhwIAli5datT3/fffB3DryrvmULHX4s7C687XrS5OwPRYIyMjoVKpsGDBgirnkYo5s7S0tNJVzjt06IDmzZtLc1RDmCPnhggLC4OjoyOWL19u1H7n3E1EpuEcektjzKHh4eHw9PTEunXrsG7dOvTp08foy0VfX1/07NkTn3/+uVFex48fR2pqqpQbUH3+o0aNgoODA5KSkiqNoxBC+p+0uLhY+n+/Qrdu3WBvb2+WzwaqHfekUyUzZszAt99+i4cffhjjx49HcHAwSkpKcOzYMfznP//BuXPn4OXlBRcXF3Tt2hXr1q1Dp06d4OnpiaCgIOk2EeZkb2+PTz/9FFFRUbjvvvvwzDPPoHXr1jh//jx2794NlUqFLVu2mLStkSNHok+fPpg+fTrOnDmDzp0749tvv5UKalP25gwfPhwPPfQQ3njjDZw7dw49evRAamoqNm/ejKlTp0rfwM6bNw8ZGRkYNmwYAgICcOnSJXz00Udo06YN+vXrBwCIiIiAWq1GaGgofHx8cOrUKXz44YcYNmxYpXPeiahhgoODAQBvvPEGxo4dC4VCgeHDhyM2NhaffPIJioqKMGDAABw8eBCff/45Ro4caXTIcUOoVCrpfEW9Xo/WrVsjNTUVeXl5JsfZo0cPk2JVqVRYvnw5nnrqKdx///0YO3YsWrVqhfz8fHz33XcIDQ3Fhx9+iNOnTyMsLAyjR49G165d4ejoiI0bN6KwsBBjx46VRc4V/2zWh4+PD6ZMmYL33nsPjzzyCIYMGYKffvoJ33//Pby8vJr0iDAiW8A5tPHmUIVCgVGjRmHt2rUoKSnB4sWLK/V59913ERUVBY1GgwkTJki3YHN3d8fcuXNrzb9Dhw6YP38+EhMTce7cOYwcORLNmzdHXl4eNm7ciEmTJuGVV17Brl27EB8fj8cffxydOnXCzZs38eWXX8LBwQHR0dF1yovqyQJXlKcmUt9bsAlx69YTiYmJ4p577hFOTk7Cy8tL/Otf/xKLFy8WN27ckPrt27dPBAcHCycnJ6PbsVV3C7Y7XysvL6/KW1fs3r27yls/HDlyRIwaNUq0bNlSKJVKERAQIEaPHi3S0tLqMjTijz/+EE888YRo3ry5cHd3F+PHjxc//PCDACDWrl0r9YuNjRXNmjWrchvXrl0T06ZNE35+fkKhUIiOHTuKd9991+h2QGlpaWLEiBHCz89PODk5CT8/PzFu3Dij29t9/PHHon///lJOHTp0EDNmzBBXr16tU05EZJq33npLtG7dWtjb20tzpF6vF0lJSSIwMFAoFArh7+8vEhMTRVlZmdFzAwICxLBhwypt09T57ffffxePPvqo8PDwEO7u7uLxxx8XFy5cqPJ2llXFKYQwOVYhbs2lkZGRwt3dXTg7O4sOHTqI8ePHi8OHDwshhPjzzz9FXFyc6Ny5s2jWrJlwd3cXISEh4ptvvqnTmFbM+VXdbtIcOVd3C7ZDhw5Vyhd33LLp5s2bYtasWUKtVgsXFxcxaNAgcerUKdGyZUvxwgsv1ClPIuIc2hhzaAWtVisACDs7O/Hbb79V2Wfnzp0iNDRUuLi4CJVKJYYPHy5OnjxZqV91+Qtx63bE/fr1E82aNRPNmjUTnTt3FnFxcSInJ0cIIcQvv/winn32WdGhQwfh7OwsPD09xUMPPSR27txZr7yo7uyEsIGrqxCZwaZNm/Doo49i7969CA0NtXQ4RETUSIqKitCiRQvMnz8fb7zxhqXDISIiMsJz0umu9Pfffxstl5eXY9myZVCpVLj//vstFBUREZnbnfM9cPt81IEDBzZtMERERCbgOelkM8rLy2u9gJybmxvc3NwwefJk/P3339BoNNDpdNiwYQP27duHBQsWVHkLISKiu9H169ervFjnP7Vq1araWyfJwbp167Bq1SoMHToUbm5u2Lt3L77++mtERETwqCkialS2MIeSZbBIJ5vx22+/GV0Fsypz5szB3LlzMWjQILz33nvYunUrysrKcM8992DZsmWIj49vomiJiORv8eLFNd7iCwDy8vLQrl27pgmoHrp37w5HR0csWrQIxcXF0sXkeAshImpstjCHkmXwnHSyGWVlZdi7d2+Nfdq3b4/27ds3UURERNbtl19+wS+//FJjn379+sHZ2bmJIiIish6cQ6m+WKQTERERERERyQQvHEdEREREREQkE1Z5TrrBYMCFCxfQvHlz2NnZWTocIrIAIQSuXbsGPz8/2Nvz+0ZTcf4kIs6f9cP5k4iaav60yiL9woUL8Pf3t3QYRCQDv/32G9q0aWPpMKwG508iqsD5s244fxJRhcaeP62ySG/evDmAW4OjUqlq7a/X65GamoqIiAgoFIrGDk/WOBa3cSxus8axKC4uhr+/vzQfkGnqOn/KkTW+X+9kCzkAtpGHLeQA1C0Pzp/1Y83zp628z2vDPG2LHPNsqvnTKov0ikOMVCqVyUW6q6srVCqVbH7BlsKxuI1jcZs1jwUPOaybus6fcmTN79cKtpADYBt52EIOQP3y4PxZN9Y8f9rK+7w2zNO2yDnPxp4/eSISERERERERkUywSCciIiIiIiKSiToV6cnJyXjggQfQvHlzeHt7Y+TIkcjJyTHqU1ZWhri4OLRs2RJubm6Ijo5GYWGhUZ/8/HwMGzYMrq6u8Pb2xowZM3Dz5s2GZ0NERERERERkxepUpKenpyMuLg779++HVquFXq9HREQESkpKpD7Tpk3Dli1bsH79eqSnp+PChQsYNWqUtL68vBzDhg3DjRs3sG/fPnz++edYtWoVZs+ebb6siIiIiIiIiKxQnS4ct337dqPlVatWwdvbG1lZWejfvz+uXr2Kzz77DGvWrMGgQYMAACtXrkSXLl2wf/9+9O3bF6mpqTh58iR27twJHx8f9OzZE2+99RZee+01zJ07F05OTubLjoiIiIiIiMiKNOjq7levXgUAeHp6AgCysrKg1+sRHh4u9encuTPatm2LzMxM9O3bF5mZmejWrRt8fHykPpGRkXjxxRdx4sQJ9OrVq9Lr6HQ66HQ6abm4uBjArSv+6fX6WuOs6BM8bzt0hqqvxHd8bmSt27EFFWNhyrjZOo7FbdY4FtYUKxGRKdrN/K7G9efeGdZEkVBT4O+biKpT7yLdYDBg6tSpCA0NRVBQEACgoKAATk5O8PDwMOrr4+ODgoICqc8/C/SK9RXrqpKcnIykpKRK7ampqXB1dTU55rd6G6pdt23bNpO3Ywu0Wq2lQ5ANjsVt1jQWpaWllg6BiIiIiMjs6l2kx8XF4fjx49i7d68546lSYmIiEhISpOWKm8hHRESYfJ90rVaLWYftuSf9/8Zi8ODBsrvfYFPjWNxmjWNRcUQNEREREZEtqVeRHh8fj61btyIjIwNt2rSR2tVqNW7cuIGioiKjvemFhYVQq9VSn4MHDxptr+Lq7xV97qRUKqFUKiu1KxSKOhUUOoMddOVVF+nWUpiYS13HzpZxLG6zprGwljiJiIiIiOqiTld3F0IgPj4eGzduxK5duxAYGGi0Pjg4GAqFAmlpaVJbTk4O8vPzodFoAAAajQbHjh3DpUuXpD5arRYqlQpdu3ZtSC5EREREREREVq1Oe9Lj4uKwZs0abN68Gc2bN5fOIXd3d4eLiwvc3d0xYcIEJCQkwNPTEyqVCpMnT4ZGo0Hfvn0BABEREejatSueeuopLFq0CAUFBXjzzTcRFxdX5d5yIiIiIiIiortFnfakL1++HFevXsXAgQPh6+srPdatWyf1WbJkCR5++GFER0ejf//+UKvV2LBhg7TewcEBW7duhYODAzQaDZ588kk8/fTTmDdvnvmyIiIiIqK7xvnz5/Hkk0+iZcuWcHFxQbdu3XD48GFpvRACs2fPhq+vL1xcXBAeHo7c3FwLRkxEVL067UkXQtTax9nZGSkpKUhJSam2T0BAwF13NXUiIiIiMr+//voLoaGheOihh/D999+jVatWyM3NRYsWLaQ+ixYtwgcffIDPP/8cgYGBmDVrFiIjI3Hy5Ek4OztbMHoiosoadJ90IiIiIiJLWrhwIfz9/bFy5Uqp7Z/XTRJCYOnSpXjzzTcxYsQIAMAXX3wBHx8fbNq0CWPHjm202Gq7FzoRUVVYpBMRERGR1fr2228RGRmJxx9/HOnp6WjdujVeeuklTJw4EQCQl5eHgoIChIeHS89xd3dHSEgIMjMzqy3SdToddDqdtFxx60+9Xg+9Xm9SbEqH2o9CrY6pr1GXbZlzm3LEPG2LHPNsqlhYpBMRERGR1frll1+wfPlyJCQk4PXXX8ehQ4fw8ssvw8nJCbGxsdKFjn18fIye5+PjI62rSnJyMpKSkiq1p6amwtXV1aTYFvWpQyJ3aIxTQ7Vardm3KUfM07bIKc/S0tImeR0W6URERERWoKZDp5UOokEFoTUzGAzo3bs3FixYAADo1asXjh8/jhUrViA2Nrbe201MTERCQoK0XFxcDH9/f0REREClUpm0jaC5O+r9+sfnRtb7uXfS6/XQarUYPHgwFAqF2bYrN8zTtsgxz4ojahobi3QiIiIislq+vr7o2rWrUVuXLl3w3//+FwCgVqsBAIWFhfD19ZX6FBYWomfPntVuV6lUVnl7YIVCYXLBoCu3M6lfVRqjKKlL7NaMedoWOeXZVHHU6RZsRERERERyEhoaipycHKO206dPIyAgAMCti8ip1WqkpaVJ64uLi3HgwAFoNJomjZWIyBTck05EREREVmvatGn417/+hQULFmD06NE4ePAgPvnkE3zyyScAADs7O0ydOhXz589Hx44dpVuw+fn5YeTIkZYNnoioCizSiYiIiMhqPfDAA9i4cSMSExMxb948BAYGYunSpYiJiZH6vPrqqygpKcGkSZNQVFSEfv36Yfv27bxHOhHJEot0IiIiIrJqDz/8MB5++OFq19vZ2WHevHmYN29eE0ZFRFQ/PCediIiIiIiISCZYpBMRERERERHJBIt0IiIiIiIiIplgkU5EREREREQkEyzSiYiaQEZGBoYPHw4/Pz/Y2dlh06ZNRuuFEJg9ezZ8fX3h4uKC8PBw5ObmGvW5cuUKYmJioFKp4OHhgQkTJuD69etNmAURERERNTYW6URETaCkpAQ9evRASkpKlesXLVqEDz74ACtWrMCBAwfQrFkzREZGoqysTOoTExODEydOQKvVYuvWrcjIyMCkSZOaKgUiIiIiagK8BRsRUROIiopCVFRUleuEEFi6dCnefPNNjBgxAgDwxRdfwMfHB5s2bcLYsWNx6tQpbN++HYcOHULv3r0BAMuWLcPQoUOxePFi+Pn5NVkuRERERNR4WKQTEVlYXl4eCgoKEB4eLrW5u7sjJCQEmZmZGDt2LDIzM+Hh4SEV6AAQHh4Oe3t7HDhwAI8++miV29bpdNDpdNJycXExAECv10Ov1zdSRo2rIm5rjR+wjRwA28hDTjkoHUT9n2t/67mm5CGHXImIqHos0omILKygoAAA4OPjY9Tu4+MjrSsoKIC3t7fRekdHR3h6ekp9qpKcnIykpKRK7ampqXB1dW1o6Bal1WotHUKD2UIOgG3kIYccFvVp+DZMyaO0tLThL0RERI2GRToRkQ1LTExEQkKCtFxcXAx/f39ERERApVJZMLL60+v10Gq1GDx4MBQKhaXDqRdbyAGwjTzklEPQ3B31fq7SXuCt3gaT8qg4ooaIiOSJRToRkYWp1WoAQGFhIXx9faX2wsJC9OzZU+pz6dIlo+fdvHkTV65ckZ5fFaVSCaVSWaldoVBYvCBpKOYgH7aQhxxy0JXbNXgbpuRh6TyJiKhmvLo7EZGFBQYGQq1WIy0tTWorLi7GgQMHoNFoAAAajQZFRUXIysqS+uzatQsGgwEhISFNHjMRERERNQ7uSSciagLXr1/HmTNnpOW8vDxkZ2fD09MTbdu2xdSpUzF//nx07NgRgYGBmDVrFvz8/DBy5EgAQJcuXTBkyBBMnDgRK1asgF6vR3x8PMaOHcsruxMRERHZEBbpRERN4PDhw3jooYek5YrzxGNjY7Fq1Sq8+uqrKCkpwaRJk1BUVIR+/fph+/btcHZ2lp6zevVqxMfHIywsDPb29oiOjsYHH3zQ5LkQERERUeNhkU5E1AQGDhwIIaq/vZKdnR3mzZuHefPmVdvH09MTa9asaYzwiIiIiEgmeE46ERERERERkUywSCciIiIiIiKSCRbpRERERERERDLBIp2IiIiIiIhIJlikExEREREREclEnYv0jIwMDB8+HH5+frCzs8OmTZuM1o8fPx52dnZGjyFDhhj1uXLlCmJiYqBSqeDh4YEJEybg+vXrDUqEiIiIiIiIyNrVuUgvKSlBjx49kJKSUm2fIUOG4OLFi9Lj66+/NlofExODEydOQKvVYuvWrcjIyMCkSZPqHj0RERERERGRDanzfdKjoqIQFRVVYx+lUgm1Wl3lulOnTmH79u04dOgQevfuDQBYtmwZhg4disWLF8PPz6+uIRERERERERHZhDoX6abYs2cPvL290aJFCwwaNAjz589Hy5YtAQCZmZnw8PCQCnQACA8Ph729PQ4cOIBHH3200vZ0Oh10Op20XFxcDADQ6/XQ6/W1xlPRR2kvau1j6yryvFvyrQnH4jZrHAtripWIiIiIyFRmL9KHDBmCUaNGITAwEGfPnsXrr7+OqKgoZGZmwsHBAQUFBfD29jYOwtERnp6eKCgoqHKbycnJSEpKqtSempoKV1dXk2N7q7eh2nXbtm0zeTu2QKvVWjoE2eBY3GZNY1FaWmrpEIiIiIiIzM7sRfrYsWOln7t164bu3bujQ4cO2LNnD8LCwuq1zcTERCQkJEjLxcXF8Pf3R0REBFQqVa3P1+v10Gq1mHXYHjqDXZV9js+NrFds1qZiLAYPHgyFQmHpcCyKY3GbNY5FxRE1RERERES2pFEOd/+n9u3bw8vLC2fOnEFYWBjUajUuXbpk1OfmzZu4cuVKteexK5VKKJXKSu0KhaJOBYXOYAddedVFurUUJuZS17GzZRyL26xpLKwlTiIiIiKiumj0Iv3333/H5cuX4evrCwDQaDQoKipCVlYWgoODAQC7du2CwWBASEhIY4dDREREZBHtZn5n6RCIiMgK1LlIv379Os6cOSMt5+XlITs7G56envD09ERSUhKio6OhVqtx9uxZvPrqq7jnnnsQGXnrcPIuXbpgyJAhmDhxIlasWAG9Xo/4+HiMHTuWV3YnIiIiIiKiu1qd75N++PBh9OrVC7169QIAJCQkoFevXpg9ezYcHBxw9OhRPPLII+jUqRMmTJiA4OBg/O9//zM6XH316tXo3LkzwsLCMHToUPTr1w+ffPKJ+bIiIiIiIiIiskJ13pM+cOBACFH9rcx27NhR6zY8PT2xZs2aur40ERERERERkU2r8550IiIiIiIiImocLNKJiIiIiIiIZIJFOhEREREREZFMsEgnIiIiIiIikgkW6UREREREREQywSKdiIiIiIiISCZYpBMRERERERHJBIt0IiKZaNeuHezs7Co94uLiAAADBw6stO6FF16wcNREREREZE6Olg6AiIhuOXToEMrLy6Xl48ePY/DgwXj88celtokTJ2LevHnSsqura5PGSERERESNi3vSiYhkolWrVlCr1dJj69at6NChAwYMGCD1cXV1NeqjUqksGDERkfy88847sLOzw9SpU6W2srIyxMXFoWXLlnBzc0N0dDQKCwstFyQRUQ1YpBMRydCNGzfw1Vdf4dlnn4WdnZ3Uvnr1anh5eSEoKAiJiYkoLS21YJRERPJy6NAhfPzxx+jevbtR+7Rp07BlyxasX78e6enpuHDhAkaNGmWhKImIasbD3YmIZGjTpk0oKirC+PHjpbYnnngCAQEB8PPzw9GjR/Haa68hJycHGzZsqHY7Op0OOp1OWi4uLgYA6PV66PX6Rou/MVXEba3xA7aRA2AbeTRlDkoH0Xjbtr+1bVPysObfV02uX7+OmJgY/Pvf/8b8+fOl9qtXr+Kzzz7DmjVrMGjQIADAypUr0aVLF+zfvx99+/a1VMhERFVikU5EJEOfffYZoqKi4OfnJ7VNmjRJ+rlbt27w9fVFWFgYzp49iw4dOlS5neTkZCQlJVVqT01Ntfrz2bVaraVDaDBbyAGwjTyaIodFfRr9JUzKw1aPwImLi8OwYcMQHh5uVKRnZWVBr9cjPDxcauvcuTPatm2LzMzMaot0c3zJ2ZAvZsz5ZYotfKFmCuZpW+SYZ1PFwiKdiEhmfv31V+zcubPGPeQAEBISAgA4c+ZMtUV6YmIiEhISpOXi4mL4+/sjIiLCas9n1+v10Gq1GDx4MBQKhaXDqRdbyAGwjTyaMoeguTsabdtKe4G3ehtMyqOi2LQla9euxY8//ohDhw5VWldQUAAnJyd4eHgYtfv4+KCgoKDabZrjS86GfDGzbdu2+j+5GrbwhZopmKdtkVOeTfUlJ4t0IiKZWblyJby9vTFs2LAa+2VnZwMAfH19q+2jVCqhVCortSsUCqstqiowB/mwhTyaIgdduV3tnRrIlDys/Xd1p99++w1TpkyBVquFs7Oz2bZrji85G/LFzPG5kfV+7p1s4Qs1UzBP2yLHPJvqS04W6UREMmIwGLBy5UrExsbC0fH2FH327FmsWbMGQ4cORcuWLXH06FFMmzYN/fv3r3SBJCKiu0lWVhYuXbqE+++/X2orLy9HRkYGPvzwQ+zYsQM3btxAUVGR0d70wsJCqNXqardrji85G/LFTGMUJbbwhZopmKdtkVOeTRUHi3QiIhnZuXMn8vPz8eyzzxq1Ozk5YefOnVi6dClKSkrg7++P6OhovPnmmxaKlIhIHsLCwnDs2DGjtmeeeQadO3fGa6+9Bn9/fygUCqSlpSE6OhoAkJOTg/z8fGg0GkuEbJJ2M7+rcf25d2o+2oqIrBeLdCIiGYmIiIAQlS805O/vj/T0dAtEREQkb82bN0dQUJBRW7NmzdCyZUupfcKECUhISICnpydUKhUmT54MjUbDK7sTkSyxSCciIiIim7ZkyRLY29sjOjoaOp0OkZGR+OijjywdFhFRlVikExEREZFN2bNnj9Gys7MzUlJSkJKSYpmAiIjqwN7SARARERERERHRLSzSiYiIiIiIiGSCRToRERERERGRTLBIJyIiIiIiIpIJFulEREREREREMsEinYiIiIiIiEgmWKQTERERERERyQSLdCIiIiIiIiKZYJFOREREREREJBMs0omIiIiIiIhkos5FekZGBoYPHw4/Pz/Y2dlh06ZNRuuFEJg9ezZ8fX3h4uKC8PBw5ObmGvW5cuUKYmJioFKp4OHhgQkTJuD69esNSoSIiIiIiIjI2tW5SC8pKUGPHj2QkpJS5fpFixbhgw8+wIoVK3DgwAE0a9YMkZGRKCsrk/rExMTgxIkT0Gq12Lp1KzIyMjBp0qT6Z0FERERERERkAxzr+oSoqChERUVVuU4IgaVLl+LNN9/EiBEjAABffPEFfHx8sGnTJowdOxanTp3C9u3bcejQIfTu3RsAsGzZMgwdOhSLFy+Gn59fA9IhIiIiIiIisl51LtJrkpeXh4KCAoSHh0tt7u7uCAkJQWZmJsaOHYvMzEx4eHhIBToAhIeHw97eHgcOHMCjjz5aabs6nQ46nU5aLi4uBgDo9Xro9fpa46roo7QXtfaxdRV53i351oRjcZs1joU1xUpEREREZCqzFukFBQUAAB8fH6N2Hx8faV1BQQG8vb2Ng3B0hKenp9TnTsnJyUhKSqrUnpqaCldXV5Pje6u3odp127ZtM3k7tkCr1Vo6BNngWNxmTWNRWlpq6RCIiIiIiMzOrEV6Y0lMTERCQoK0XFxcDH9/f0REREClUtX6fL1eD61Wi1mH7aEz2FXZ5/jcSLPFK2cVYzF48GAoFApLh2NRHIvbrHEsKo6oISIiIiKyJWYt0tVqNQCgsLAQvr6+UnthYSF69uwp9bl06ZLR827evIkrV65Iz7+TUqmEUqms1K5QKOpUUOgMdtCVV12kW0thYi51HTtbxrG4zZrGwlriJCIiIiKqC7PeJz0wMBBqtRppaWlSW3FxMQ4cOACNRgMA0Gg0KCoqQlZWltRn165dMBgMCAkJMWc4RERERERERFalznvSr1+/jjNnzkjLeXl5yM7OhqenJ9q2bYupU6di/vz56NixIwIDAzFr1iz4+flh5MiRAIAuXbpgyJAhmDhxIlasWAG9Xo/4+HiMHTuWV3YnIiIiIiKiu1qdi/TDhw/joYcekpYrzhWPjY3FqlWr8Oqrr6KkpASTJk1CUVER+vXrh+3bt8PZ2Vl6zurVqxEfH4+wsDDY29sjOjoaH3zwgRnSISIiIiIiIrJedS7SBw4cCCGqv5WZnZ0d5s2bh3nz5lXbx9PTE2vWrKnrSxMRERERERHZNLOek05ERERERERE9ccinYhIJubOnQs7OzujR+fOnaX1ZWVliIuLQ8uWLeHm5obo6GgUFhZaMGIiIiIiMjeruE86EdHd4r777sPOnTulZUfH29P0tGnT8N1332H9+vVwd3dHfHw8Ro0ahR9++MESoRLRHdrN/M7SIRARkQ1gkU5EJCOOjo5Qq9WV2q9evYrPPvsMa9aswaBBgwAAK1euRJcuXbB//3707du3qUMlIiIiokbAIp2ISEZyc3Ph5+cHZ2dnaDQaJCcno23btsjKyoJer0d4eLjUt3Pnzmjbti0yMzOrLdJ1Oh10Op20XFxcDADQ6/XQ6/WNm0wjqYjbWuMHbCMHwDbyMGcOSofqL6zb2JT2t17blDys+fdFRHQ3YJFORCQTISEhWLVqFe69915cvHgRSUlJePDBB3H8+HEUFBTAyckJHh4eRs/x8fFBQUFBtdtMTk5GUlJSpfbU1FS4urqaO4UmpdVqLR1Cg9lCDoBt5GGOHBb1MUMgDWRKHqWlpU0QCTW22k6vOPfOsCaKhIjMjUU6EZFMREVFST93794dISEhCAgIwDfffAMXF5d6bTMxMREJCQnScnFxMfz9/REREQGVStXgmC1Br9dDq9Vi8ODBUCgUlg6nXmwhB8A28jBnDkFzd5gpqrpT2gu81dtgUh4VR9QQEZE8sUgnIpIpDw8PdOrUCWfOnMHgwYNx48YNFBUVGe1NLywsrPIc9gpKpRJKpbJSu0KhsNqiqgJzkA9byMMcOejK7cwUTf2Zkoe1/66IiGwdb8FGRCRT169fx9mzZ+Hr64vg4GAoFAqkpaVJ63NycpCfnw+NRmPBKImIiIjInLgnnYhIJl555RUMHz4cAQEBuHDhAubMmQMHBweMGzcO7u7umDBhAhISEuDp6QmVSoXJkydDo9Hwyu5ERERENoRFOhGRTPz+++8YN24cLl++jFatWqFfv37Yv38/WrVqBQBYsmQJ7O3tER0dDZ1Oh8jISHz00UcWjpqIiIiIzIlFOhGRTKxdu7bG9c7OzkhJSUFKSkoTRURERERETY3npBMRERERERHJBPekExERERHdZWq6zzrvsU5kWdyTTkRERERERCQTLNKJiIiIiIiIZIJFOhEREREREZFM8Jz0/8PzcoiIiIiIiMjSuCediIiIiIiISCZYpBMRERGRVUtOTsYDDzyA5s2bw9vbGyNHjkROTo5Rn7KyMsTFxaFly5Zwc3NDdHQ0CgsLLRQxEVH1WKQTERERkVVLT09HXFwc9u/fD61WC71ej4iICJSUlEh9pk2bhi1btmD9+vVIT0/HhQsXMGrUKAtGTURUNZ6TTkRERERWbfv27UbLq1atgre3N7KystC/f39cvXoVn332GdasWYNBgwYBAFauXIkuXbpg//796Nu3ryXCJiKqEot0IiIiIrIpV69eBQB4enoCALKysqDX6xEeHi716dy5M9q2bYvMzMwqi3SdTgedTictFxcXAwD0ej30er1JcSgdRL1zaKh/xljx8z/baorN1Pzkpqo8bRHztJymioVFOhERERHZDIPBgKlTpyI0NBRBQUEAgIKCAjg5OcHDw8Oor4+PDwoKCqrcTnJyMpKSkiq1p6amwtXV1aRYFvWpW+zmtG3btkptWq1W+rmm2Kp6rjX5Z562jHk2vdLS0iZ5HRbpRERERGQz4uLicPz4cezdu7dB20lMTERCQoK0XFxcDH9/f0REREClUpm0jaC5OxoUg7ko7QXe6m3ArMP20Bnsau1/fG5kg16vtrwbuv3q6PV6aLVaDB48GAqFolFeQw6Yp+VUHFHT2FikExEREZFNiI+Px9atW5GRkYE2bdpI7Wq1Gjdu3EBRUZHR3vTCwkKo1eoqt6VUKqFUKiu1KxQKkwsGXXntBXFT0hnsTIqpoQVRba/R2AVXXX5H1ox5Nr2mioNXdyciIiIiqyaEQHx8PDZu3Ihdu3YhMDDQaH1wcDAUCgXS0tKktpycHOTn50Oj0TR1uERENeKedCIiIiKyanFxcVizZg02b96M5s2bS+eZu7u7w8XFBe7u7pgwYQISEhLg6ekJlUqFyZMnQ6PR8MruRCQ7LNKJiIiIyKotX74cADBw4ECj9pUrV2L8+PEAgCVLlsDe3h7R0dHQ6XSIjIzERx991MSRWod2M7+rcf25d4Y1USTmZ8u5ke0we5E+d+7cSlfCvPfee/Hzzz8DAMrKyjB9+nSsXbvWaIL08fExdyhEREREZlPbP/dkOULUfqszZ2dnpKSkICUlpQkiIiKqv0Y5J/2+++7DxYsXpcc/r645bdo0bNmyBevXr0d6ejouXLiAUaNGNUYYRERERERERFalUQ53d3R0rPJKmVevXsVnn32GNWvWYNCgQQBuHYbUpUsX7N+/n+cEERERERER0V2tUfak5+bmws/PD+3bt0dMTAzy8/MBAFlZWdDr9QgPD5f6du7cGW3btkVmZmZjhEJERERERERkNcy+Jz0kJASrVq3Cvffei4sXLyIpKQkPPvggjh8/joKCAjg5ORndnxIAfHx8pKtwVkWn00Gn00nLFTeR1+v10Ov1tcZU0UdpX/v5SjU93xZU5GJLOdUXx+I2axwLa4qViIjIljT0+gy8eBtRzcxepEdFRUk/d+/eHSEhIQgICMA333wDFxeXem0zOTm50sXoACA1NRWurq4mb+et3oZ6vf62bdvq9Tw502q1lg5BNjgWt1nTWJSWllo6BCIiIiIis2v0W7B5eHigU6dOOHPmDAYPHowbN26gqKjIaG96YWFhleewV0hMTERCQoK0XFxcDH9/f0REREClUtUag16vh1arxazD9tAZ7Oqcw/G5kXV+jlxVjMXgwYOhUCgsHY5FcSxus8axqDiixpYkJydjw4YN+Pnnn+Hi4oJ//etfWLhwIe69916pz8CBA5Genm70vOeffx4rVqxo6nCJiIiIqBE0epF+/fp1nD17Fk899RSCg4OhUCiQlpaG6OhoAEBOTg7y8/Oh0Wiq3YZSqYRSqazUrlAo6lRQ6Ax20JXXvUi3lqKlLuo6draMY3GbNY2FtcRZF+np6YiLi8MDDzyAmzdv4vXXX0dERAROnjyJZs2aSf0mTpyIefPmSct1OaKIiIjI1gXN3VGv//lN0dBD/XkoP5nC7EX6K6+8guHDhyMgIAAXLlzAnDlz4ODggHHjxsHd3R0TJkxAQkICPD09oVKpMHnyZGg0Gl7ZnYjuetu3bzdaXrVqFby9vZGVlYX+/ftL7a6urjUefURERERE1svsRfrvv/+OcePG4fLly2jVqhX69euH/fv3o1WrVgCAJUuWwN7eHtHR0dDpdIiMjMRHH31k7jCIiKze1atXAQCenp5G7atXr8ZXX30FtVqN4cOHY9asWdybTkREZAYN3VNOZA5mL9LXrl1b43pnZ2ekpKQgJSXF3C9NRGQzDAYDpk6ditDQUAQFBUntTzzxBAICAuDn54ejR4/itddeQ05ODjZs2FDldhp6dww5ssa7EdzJFnIAbCOPuuSgdKjfXWKaQsUdbOpy1xsiIpKnRj8n3RbwNhFE1NTi4uJw/Phx7N2716h90qRJ0s/dunWDr68vwsLCcPbsWXTo0KHSdsx1dww5sqa7EVTHFnIAbCMPU3JY1KcJAmkgU/Lg3TGIiOSNRToRkczEx8dj69atyMjIQJs2bWrsGxISAgA4c+ZMlUV6Q++OIUfWeDeCO9lCDoBt5FGXHILm7miiqOpOaS/wVm+DSXnY4t0xyLbY8g6ymnKz5rzIvFikExHJhBACkydPxsaNG7Fnzx4EBgbW+pzs7GwAgK+vb5XrzXV3DDliDvJhC3mYkkNjXS3anEzJw9p/V0REto5FOhGRTMTFxWHNmjXYvHkzmjdvjoKCAgCAu7s7XFxccPbsWaxZswZDhw5Fy5YtcfToUUybNg39+/dH9+7dLRw9EREREZkDi3QiIplYvnw5AGDgwIFG7StXrsT48ePh5OSEnTt3YunSpSgpKYG/vz+io6Px5ptvWiBaIiIiImoMLNKJiGRCiJqvHO3v74/09PQmioaIiIiILIFFOhERERERWY3qLr6mdBBWcRcGubLlC/ZZGxbpTYBveCIiIiIiIjKFvaUDICIiIiIiIqJbuCediIiIiIhI5iqOzq04rD9o7g6jW0Py6FzbwT3pRERERERERDLBPelmUNs550RERERERDVhTUEVuCediIiIiIiISCa4J52IiIjo/3BPFhERWRr3pBMRERERERHJBIt0IiIiIiIiIplgkU5EREREREQkEyzSiYiIiIiIiGSCRToRERERERGRTPDq7kRERERERDaOd6+wHtyTTkRERERERCQTLNKJiIiIiIiIZIKHu1uB2g5NOffOsCaKhIiIiIiIiBoTi3QZ4PkhRERETePOz1ylg8CiPkDQ3B3QldtZKCoiIqLbWKTf5biXnoiIiIiIGqKxa4q7rWZhkW4DanrT2tobloiIiIiIyJaxSCciIiIj1rzHgqeQEdHdSs7znzV/rlgCi3QiIiKyGnL+J5SIiMgceAs2IiIiIiIiIpngnnQb19hXseWhK0TUEJxDLIN7o4mIqK4a87Ojqm3/s24B7q67b1i0SE9JScG7776LgoIC9OjRA8uWLUOfPn0sGRLdwZL/yDX2P+9Bc3fU+IUFiwOSK2uaO625GOQXCI2D40qWZE3zJxHdvSxWpK9btw4JCQlYsWIFQkJCsHTpUkRGRiInJwfe3t6WCovMjP+MEZkX507zkcMXCI11b+7Gnlsrxq4x7jEuh98L2SbOn0RkLSxWpL///vuYOHEinnnmGQDAihUr8N133+H/+//+P8ycOdNSYVETa+rDZv5J6dCw5/MLhvrhuDYM504iovrh/El097K2W1ZbpEi/ceMGsrKykJiYKLXZ29sjPDwcmZmZlfrrdDrodDpp+erVqwCAK1euQK/X1/p6er0epaWlcNTbo9xwd53PcCdHg0BpqcEmxuKeV76pcX1tb+6GjsXly5erXReSnFbjcw8khtW4vqHPr6uKv5HLly+j3+KMBr12bbHX9nupaVz/6dq1awAAIYRJ/W1BXedOoOHzJ9Cw96PjzRKTXqM6Vb0fzPV+bWhstc1BNb12Y38uNXR+NJUtfKbYQg7A7TwuX74MhUJRY1/On7c0xfzZ0HnGXGzlfV4b5mlb6pJnbf8/1vS3aOr/nkATzp/CAs6fPy8AiH379hm1z5gxQ/Tp06dS/zlz5ggAfPDBBx+VHr/99ltTTV0WV9e5UwjOn3zwwUf1D86fnD/54IOP+j0ae/60iqu7JyYmIiEhQVo2GAy4cuUKWrZsCTu72r89Ki4uhr+/P3777TeoVKrGDFX2OBa3cSxus8axEELg2rVr8PPzs3QostbQ+VOOrPH9eidbyAGwjTxsIQegbnlw/jSNLc2ftvI+rw3ztC1yzLOp5k+LFOleXl5wcHBAYWGhUXthYSHUanWl/kqlEkql0qjNw8Ojzq+rUqlk8wu2NI7FbRyL26xtLNzd3S0dQpOq69wJmG/+lCNre79WxRZyAGwjD1vIATA9D86ft9xt86etvM9rwzxti9zybIr5077RX6EKTk5OCA4ORlra7fMcDQYD0tLSoNFoLBESEZHsce4kIqofzp9EZE0sdrh7QkICYmNj0bt3b/Tp0wdLly5FSUmJdMVNIiKqjHMnEVH9cP4kImthsSJ9zJgx+OOPPzB79mwUFBSgZ8+e2L59O3x8fMz+WkqlEnPmzKl0yNLdiGNxG8fiNo6F9WjKuVOubOH9ags5ALaRhy3kANhOHo3pbp4/75b3B/O0LXdLnlWxE+Iuuv8GERERERERkYxZ5Jx0IiIiIiIiIqqMRToRERERERGRTLBIJyIiIiIiIpIJFulEREREREREMmHzRXpKSgratWsHZ2dnhISE4ODBg5YOySKSk5PxwAMPoHnz5vD29sbIkSORk5Nj6bAs7p133oGdnR2mTp1q6VAs5vz583jyySfRsmVLuLi4oFu3bjh8+LClw6K7nClzVllZGeLi4tCyZUu4ubkhOjoahYWFFoq4dlXNN9aSQ23zhBACs2fPhq+vL1xcXBAeHo7c3FwLRmysvLwcs2bNQmBgIFxcXNChQwe89dZb+Oe1c+WYQ0ZGBoYPHw4/Pz/Y2dlh06ZNRutNifnKlSuIiYmBSqWCh4cHJkyYgOvXrzdhFtRY7pb3h7k+D/Lz8zFs2DC4urrC29sbM2bMwM2bN5sylRotX74c3bt3h0qlgkqlgkajwffffy+tt4Uc71Tfz0Vry7M+bLpIX7duHRISEjBnzhz8+OOP6NGjByIjI3Hp0iVLh9bk0tPTERcXh/3790Or1UKv1yMiIgIlJSWWDs1iDh06hI8//hjdu3e3dCgW89dffyE0NBQKhQLff/89Tp48iffeew8tWrSwdGh0lzNlzpo2bRq2bNmC9evXIz09HRcuXMCoUaMsGHX1qptvrCEHU+aJRYsW4YMPPsCKFStw4MABNGvWDJGRkSgrK7Ng5LctXLgQy5cvx4cffohTp05h4cKFWLRoEZYtWyb1kWMOJSUl6NGjB1JSUqpcb0rMMTExOHHiBLRaLbZu3YqMjAxMmjSpqVKgRnS3vD/M8XlQXl6OYcOG4caNG9i3bx8+//xzrFq1CrNnz7ZESlVq06YN3nnnHWRlZeHw4cMYNGgQRowYgRMnTgCwjRz/qb6fi9aWZ70JG9anTx8RFxcnLZeXlws/Pz+RnJxswajk4dKlSwKASE9Pt3QoFnHt2jXRsWNHodVqxYABA8SUKVMsHZJFvPbaa6Jfv36WDoOoVnfOWUVFRUKhUIj169dLfU6dOiUAiMzMTEuFWaXq5htryaG2ecJgMAi1Wi3effddqa2oqEgolUrx9ddfN0WItRo2bJh49tlnjdpGjRolYmJihBDWkQMAsXHjRmnZlJhPnjwpAIhDhw5Jfb7//nthZ2cnzp8/32SxU+O7m94f9fk82LZtm7C3txcFBQVSn+XLlwuVSiV0Ol3TJlAHLVq0EJ9++qnN5diQz0VryrMhbHZP+o0bN5CVlYXw8HCpzd7eHuHh4cjMzLRgZPJw9epVAICnp6eFI7GMuLg4DBs2zOj9cTf69ttv0bt3bzz++OPw9vZGr1698O9//9vSYRFVcueclZWVBb1eb/Q33LlzZ7Rt21Z2c3x184215FDbPJGXl4eCggKjPNzd3RESEiKbPP71r38hLS0Np0+fBgD89NNP2Lt3L6KiogBYRw53MiXmzMxMeHh4oHfv3lKf8PBw2Nvb48CBA00eMzUdW35/1OfzIDMzE926dYOPj4/UJzIyEsXFxdKeajkpLy/H2rVrUVJSAo1GY3M5NuRz0ZrybAhHSwfQWP7880+Ul5cb/QIBwMfHBz///LOFopIHg8GAqVOnIjQ0FEFBQZYOp8mtXbsWP/74Iw4dOmTpUCzul19+wfLly5GQkIDXX38dhw4dwssvvwwnJyfExsZaOjwiAFXPWQUFBXBycoKHh4dRXx8fHxQUFFggyqrVNN9YSw61zRMVsVb1eSuXPGbOnIni4mJ07twZDg4OKC8vx9tvv42YmBgAsIoc7mRKzAUFBfD29jZa7+joCE9PT9nmReZhq++P+n4eFBQUVDkWFevk4tixY9BoNCgrK4Obmxs2btyIrl27Ijs722ZybOjnorXk2VA2W6RT9eLi4nD8+HHs3bvX0qE0ud9++w1TpkyBVquFs7OzpcOxOIPBgN69e2PBggUAgF69euH48eNYsWIFi3SSDWuds2xlvrGFeeKbb77B6tWrsWbNGtx3333Izs7G1KlT4efnZzU5EJH1fh6Y6t5770V2djauXr2K//znP4iNjUV6erqlwzIbW/lcbAo2e7i7l5cXHBwcKl0NsLCwEGq12kJRWV58fDy2bt2K3bt3o02bNpYOp8llZWXh0qVLuP/+++Ho6AhHR0ekp6fjgw8+gKOjI8rLyy0dYpPy9fVF165djdq6dOmC/Px8C0VEZKy6OUutVuPGjRsoKioy6i+nOb62+cbHx0f2OQC1zxMVscr583bGjBmYOXMmxo4di27duuGpp57CtGnTkJycDMA6criTKTGr1epKF8u9efMmrly5Itu8yDxs8f3RkM8DtVpd5VhUrJMLJycn3HPPPQgODkZycjJ69OiB//f//p/N5GiOz0VryNMcbLZId3JyQnBwMNLS0qQ2g8GAtLQ0aDQaC0ZmGUIIxMfHY+PGjdi1axcCAwMtHZJFhIWF4dixY8jOzpYevXv3RkxMDLKzs+Hg4GDpEJtUaGhopduYnD59GgEBARaKiOiW2uas4OBgKBQKozk+JycH+fn5spnja5tvevfuLfscgNrnicDAQKjVaqM8iouLceDAAdnkUVpaCnt74395HBwcYDAYAFhHDncyJWaNRoOioiJkZWVJfXbt2gWDwYCQkJAmj5maji29P8zxeaDRaHDs2DGjLyW0Wi1UKlWlLyHlxGAwQKfT2UyO5vhctIY8zcLCF65rVGvXrhVKpVKsWrVKnDx5UkyaNEl4eHgYXQ3wbvHiiy8Kd3d3sWfPHnHx4kXpUVpaaunQLO5uvrr7wYMHhaOjo3j77bdFbm6uWL16tXB1dRVfffWVpUOju5wpc9YLL7wg2rZtK3bt2iUOHz4sNBqN0Gg0Foy6dnfON9aQgynzxDvvvCM8PDzE5s2bxdGjR8WIESNEYGCg+Pvvvy0Y+W2xsbGidevWYuvWrSIvL09s2LBBeHl5iVdffVXqI8ccrl27Jo4cOSKOHDkiAIj3339fHDlyRPz6668mxzxkyBDRq1cvceDAAbF3717RsWNHMW7cOEulRGZ0t7w/zPF5cPPmTREUFCQiIiJEdna22L59u2jVqpVITEy0REpVmjlzpkhPTxd5eXni6NGjYubMmcLOzk6kpqYKIWwjx6rU9XPRWvOsK5su0oUQYtmyZaJt27bCyclJ9OnTR+zfv9/SIVkEgCofK1eutHRoFnc3F+lCCLFlyxYRFBQklEql6Ny5s/jkk08sHRKRSXPW33//LV566SXRokUL4erqKh599FFx8eJFywVtgjvnG2vJobZ5wmAwiFmzZgkfHx+hVCpFWFiYyMnJsVC0lRUXF4spU6aItm3bCmdnZ9G+fXvxxhtvGN2uR4457N69u8q/g9jYWJNjvnz5shg3bpxwc3MTKpVKPPPMM+LatWsWyIbM7W55f5jr8+DcuXMiKipKuLi4CC8vLzF9+nSh1+ubOJvqPfvssyIgIEA4OTmJVq1aibCwMKlAF8I2cqxKfT4XrTHPurITQoim2GNPRERERERERDWz2XPSiYiIiIiIiKwNi3QiIiIiIiIimWCRTkRERERERCQTLNKJiIiIiIiIZIJFOhEREREREZFMsEgnIiIiIiIikgkW6UREREREREQywSKdiBpNRkYGhg8fDj8/P9jZ2WHTpk113saOHTvQt29fNG/eHK1atUJ0dDTOnTtn9liJiIiIiOSARToRNZqSkhL06NEDKSkp9Xp+Xl4eRowYgUGDBiE7Oxs7duzAn3/+iVGjRpk5UiIiIiIiebATQghLB0FEts/Ozg4bN27EyJEjpTadToc33ngDX3/9NYqKihAUFISFCxdi4MCBAID//Oc/GDduHHQ6Heztb32nuGXLFowYMQI6nQ4KhcICmRARERERNR7uSScii4mPj0dmZibWrl2Lo0eP4vHHH8eQIUOQm5sLAAgODoa9vT1WrlyJ8vJyXL16FV9++SXCw8NZoBMRERGRTeKedCJqEnfuSc/Pz0f79u2Rn58PPz8/qV94eDj69OmDBQsWAADS09MxevRoXL58GeXl5dBoNNi2bRs8PDwskAURERERUePinnQisohjx46hvLwcnTp1gpubm/RIT0/H2bNnAQAFBQWYOHEiYmNjcejQIaSnp8PJyQmPPfYY+P0iEREREdkiR0sHQER3p+vXr8PBwQFZWVlwcHAwWufm5gYASElJgbu7OxYtWiSt++qrr+Dv748DBw6gb9++TRozEREREVFjY5FORBbRq1cvlJeX49KlS3jwwQer7FNaWipdMK5CRUFvMBgaPUYiIiIioqbGw92JqNFcv34d2dnZyM7OBnDrlmrZ2dnIz89Hp06dEBMTg6effhobNmxAXl4eDh48iOTkZHz33XcAgGHDhuHQoUOYN28ecnNz8eOPP+KZZ55BQEAAevXqZcHMiIiIiIgaBy8cR0SNZs+ePXjooYcqtcfGxmLVqlXQ6/WYP38+vvjiC5w/fx5eXl7o27cvkpKS0K1bNwDA2rVrsWjRIpw+fRqurq7QaDRYuHAhOnfu3NTpEBERERE1OhbpRERERERERDLBw92JiIiIiIiIZIJFOhEREREREZFMsEgnIiIiIiIikgkW6UREREREREQywSKdiIiIiIiISCZYpBMRERERERHJBIt0IiIiIiIiIplgkU5EREREREQkEyzSiYiIiIiIiGSCRToRERERERGRTLBIJyIiIiIiIpIJFulEREREREREMvH/AxuAd1iuozb8AAAAAElFTkSuQmCC",
       "text/plain": [
        "<Figure size 1200x800 with 9 Axes>"
       ]
@@ -6312,7 +257,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 51,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
@@ -6352,7 +297,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 52,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
@@ -6386,7 +331,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 53,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -6449,7 +394,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 54,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
@@ -6470,10 +415,10 @@
        "        9.05]),\n",
        " array([ 79.5,  81.5,  83.5,  85.5,  87.5,  89.5,  91.5,  93.5,  95.5,\n",
        "         97.5,  99.5, 101.5]),\n",
-       " <matplotlib.collections.QuadMesh at 0x2409f93e850>)"
+       " <matplotlib.collections.QuadMesh at 0x2514d0c8e90>)"
       ]
      },
-     "execution_count": 54,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -6530,7 +475,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 55,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
@@ -6539,7 +484,7 @@
        "<Axes: xlabel='imdb_rating', ylabel='tomatoes_rating'>"
       ]
      },
-     "execution_count": 55,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -6587,7 +532,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 56,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
@@ -6653,7 +598,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 57,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
@@ -6704,7 +649,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 58,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
@@ -6810,7 +755,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 59,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
@@ -6819,7 +764,7 @@
        "0.6673272196886042"
       ]
      },
-     "execution_count": 59,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -6839,7 +784,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 60,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
@@ -6863,6 +808,7 @@
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
+       "      <th>Unnamed: 0</th>\n",
        "      <th>is_adult</th>\n",
        "      <th>year</th>\n",
        "      <th>length</th>\n",
@@ -6876,6 +822,19 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
+       "      <th>Unnamed: 0</th>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.111334</td>\n",
+       "      <td>-0.271571</td>\n",
+       "      <td>-0.411800</td>\n",
+       "      <td>-0.818634</td>\n",
+       "      <td>0.733054</td>\n",
+       "      <td>-0.626876</td>\n",
+       "      <td>-0.182300</td>\n",
+       "      <td>-0.528328</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
        "      <th>is_adult</th>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -6886,9 +845,11 @@
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>year</th>\n",
+       "      <td>0.111334</td>\n",
        "      <td>NaN</td>\n",
        "      <td>1.000000</td>\n",
        "      <td>-0.164026</td>\n",
@@ -6901,6 +862,7 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>length</th>\n",
+       "      <td>-0.271571</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-0.164026</td>\n",
        "      <td>1.000000</td>\n",
@@ -6913,6 +875,7 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>imdb_rating</th>\n",
+       "      <td>-0.411800</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-0.258788</td>\n",
        "      <td>0.264138</td>\n",
@@ -6925,6 +888,7 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>imdb_votes</th>\n",
+       "      <td>-0.818634</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-0.020599</td>\n",
        "      <td>0.325280</td>\n",
@@ -6937,6 +901,7 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>boxoffice_rank</th>\n",
+       "      <td>0.733054</td>\n",
        "      <td>NaN</td>\n",
        "      <td>0.024687</td>\n",
        "      <td>-0.227022</td>\n",
@@ -6949,6 +914,7 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>lifetime_gross</th>\n",
+       "      <td>-0.626876</td>\n",
        "      <td>NaN</td>\n",
        "      <td>0.105194</td>\n",
        "      <td>0.211506</td>\n",
@@ -6961,6 +927,7 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>tomatoes_rating</th>\n",
+       "      <td>-0.182300</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-0.143181</td>\n",
        "      <td>0.001890</td>\n",
@@ -6973,6 +940,7 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>tomatoes_votes</th>\n",
+       "      <td>-0.528328</td>\n",
        "      <td>NaN</td>\n",
        "      <td>0.583895</td>\n",
        "      <td>0.141379</td>\n",
@@ -6988,29 +956,32 @@
        "</div>"
       ],
       "text/plain": [
-       "                 is_adult      year    length  imdb_rating  imdb_votes  \\\n",
-       "is_adult              NaN       NaN       NaN          NaN         NaN   \n",
-       "year                  NaN  1.000000 -0.164026    -0.258788   -0.020599   \n",
-       "length                NaN -0.164026  1.000000     0.264138    0.325280   \n",
-       "imdb_rating           NaN -0.258788  0.264138     1.000000    0.465902   \n",
-       "imdb_votes            NaN -0.020599  0.325280     0.465902    1.000000   \n",
-       "boxoffice_rank        NaN  0.024687 -0.227022    -0.107621   -0.529907   \n",
-       "lifetime_gross        NaN  0.105194  0.211506     0.202497    0.649080   \n",
-       "tomatoes_rating       NaN -0.143181  0.001890     0.667327    0.167706   \n",
-       "tomatoes_votes        NaN  0.583895  0.141379     0.075651    0.434226   \n",
-       "\n",
-       "                 boxoffice_rank  lifetime_gross  tomatoes_rating  \\\n",
-       "is_adult                    NaN             NaN              NaN   \n",
-       "year                   0.024687        0.105194        -0.143181   \n",
-       "length                -0.227022        0.211506         0.001890   \n",
-       "imdb_rating           -0.107621        0.202497         0.667327   \n",
-       "imdb_votes            -0.529907        0.649080         0.167706   \n",
-       "boxoffice_rank         1.000000       -0.612221         0.028940   \n",
-       "lifetime_gross        -0.612221        1.000000         0.077516   \n",
-       "tomatoes_rating        0.028940        0.077516         1.000000   \n",
-       "tomatoes_votes        -0.432609        0.499844         0.059786   \n",
+       "                 Unnamed: 0  is_adult      year    length  imdb_rating  \\\n",
+       "Unnamed: 0         1.000000       NaN  0.111334 -0.271571    -0.411800   \n",
+       "is_adult                NaN       NaN       NaN       NaN          NaN   \n",
+       "year               0.111334       NaN  1.000000 -0.164026    -0.258788   \n",
+       "length            -0.271571       NaN -0.164026  1.000000     0.264138   \n",
+       "imdb_rating       -0.411800       NaN -0.258788  0.264138     1.000000   \n",
+       "imdb_votes        -0.818634       NaN -0.020599  0.325280     0.465902   \n",
+       "boxoffice_rank     0.733054       NaN  0.024687 -0.227022    -0.107621   \n",
+       "lifetime_gross    -0.626876       NaN  0.105194  0.211506     0.202497   \n",
+       "tomatoes_rating   -0.182300       NaN -0.143181  0.001890     0.667327   \n",
+       "tomatoes_votes    -0.528328       NaN  0.583895  0.141379     0.075651   \n",
+       "\n",
+       "                 imdb_votes  boxoffice_rank  lifetime_gross  tomatoes_rating  \\\n",
+       "Unnamed: 0        -0.818634        0.733054       -0.626876        -0.182300   \n",
+       "is_adult                NaN             NaN             NaN              NaN   \n",
+       "year              -0.020599        0.024687        0.105194        -0.143181   \n",
+       "length             0.325280       -0.227022        0.211506         0.001890   \n",
+       "imdb_rating        0.465902       -0.107621        0.202497         0.667327   \n",
+       "imdb_votes         1.000000       -0.529907        0.649080         0.167706   \n",
+       "boxoffice_rank    -0.529907        1.000000       -0.612221         0.028940   \n",
+       "lifetime_gross     0.649080       -0.612221        1.000000         0.077516   \n",
+       "tomatoes_rating    0.167706        0.028940        0.077516         1.000000   \n",
+       "tomatoes_votes     0.434226       -0.432609        0.499844         0.059786   \n",
        "\n",
        "                 tomatoes_votes  \n",
+       "Unnamed: 0            -0.528328  \n",
        "is_adult                    NaN  \n",
        "year                   0.583895  \n",
        "length                 0.141379  \n",
@@ -7022,7 +993,7 @@
        "tomatoes_votes         1.000000  "
       ]
      },
-     "execution_count": 60,
+     "execution_count": 14,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -7064,7 +1035,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 61,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [
     {
@@ -7099,6 +1070,8 @@
       "  if pd.api.types.is_categorical_dtype(vector):\n",
       "c:\\Users\\janpi\\Documents\\code\\collaboration\\pyladies-kurz\\.venv\\Lib\\site-packages\\seaborn\\_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
       "  if pd.api.types.is_categorical_dtype(vector):\n",
+      "c:\\Users\\janpi\\Documents\\code\\collaboration\\pyladies-kurz\\.venv\\Lib\\site-packages\\seaborn\\_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
+      "  if pd.api.types.is_categorical_dtype(vector):\n",
       "c:\\Users\\janpi\\Documents\\code\\collaboration\\pyladies-kurz\\.venv\\Lib\\site-packages\\seaborn\\_oldcore.py:1119: FutureWarning: use_inf_as_na option is deprecated and will be removed in a future version. Convert inf values to NaN before operating instead.\n",
       "  with pd.option_context('mode.use_inf_as_na', True):\n",
       "c:\\Users\\janpi\\Documents\\code\\collaboration\\pyladies-kurz\\.venv\\Lib\\site-packages\\seaborn\\_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
@@ -7204,10 +1177,10 @@
     {
      "data": {
       "text/plain": [
-       "<seaborn.axisgrid.PairGrid at 0x2409f8d80d0>"
+       "<seaborn.axisgrid.PairGrid at 0x25146755810>"
       ]
      },
-     "execution_count": 61,
+     "execution_count": 15,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -7247,29 +1220,28 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 62,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "tconst\n",
-       "tt0000009    (1890, 1900]\n",
-       "tt0000147    (1890, 1900]\n",
-       "tt0000335    (1890, 1900]\n",
-       "tt0000574    (1900, 1910]\n",
-       "tt0000615    (1900, 1910]\n",
-       "                 ...     \n",
-       "tt9910930    (2010, 2020]\n",
-       "tt9911774    (2010, 2020]\n",
-       "tt9913056    (2010, 2020]\n",
-       "tt9913084    (2010, 2020]\n",
-       "tt9914286    (2010, 2020]\n",
+       "0         (1890, 1900]\n",
+       "1         (1890, 1900]\n",
+       "2         (1890, 1900]\n",
+       "3         (1900, 1910]\n",
+       "4         (1900, 1910]\n",
+       "              ...     \n",
+       "232491    (2010, 2020]\n",
+       "232492    (2010, 2020]\n",
+       "232493    (2010, 2020]\n",
+       "232494    (2010, 2020]\n",
+       "232495    (2010, 2020]\n",
        "Name: year, Length: 232496, dtype: category\n",
        "Categories (13, interval[int64, right]): [(1890, 1900] < (1900, 1910] < (1910, 1920] < (1920, 1930] ... (1980, 1990] < (1990, 2000] < (2000, 2010] < (2010, 2020]]"
       ]
      },
-     "execution_count": 62,
+     "execution_count": 16,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -7290,29 +1262,28 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 63,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "tconst\n",
-       "tt0000009    1890s\n",
-       "tt0000147    1890s\n",
-       "tt0000335    1890s\n",
-       "tt0000574    1900s\n",
-       "tt0000615    1900s\n",
-       "             ...  \n",
-       "tt9910930    2010s\n",
-       "tt9911774    2010s\n",
-       "tt9913056    2010s\n",
-       "tt9913084    2010s\n",
-       "tt9914286    2010s\n",
+       "0         1890s\n",
+       "1         1890s\n",
+       "2         1890s\n",
+       "3         1900s\n",
+       "4         1900s\n",
+       "          ...  \n",
+       "232491    2010s\n",
+       "232492    2010s\n",
+       "232493    2010s\n",
+       "232494    2010s\n",
+       "232495    2010s\n",
        "Name: year, Length: 232496, dtype: category\n",
        "Categories (13, object): ['1890s' < '1900s' < '1910s' < '1920s' ... '1980s' < '1990s' < '2000s' < '2010s']"
       ]
      },
-     "execution_count": 63,
+     "execution_count": 17,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -7346,28 +1317,27 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 64,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "tconst\n",
-       "tt0000009        Romance\n",
-       "tt0000147    Documentary\n",
-       "tt0000147           News\n",
-       "tt0000147          Sport\n",
-       "tt0000335      Biography\n",
-       "                ...     \n",
-       "tt9911774          Drama\n",
-       "tt9913056    Documentary\n",
-       "tt9913084    Documentary\n",
-       "tt9914286          Drama\n",
-       "tt9914286         Family\n",
+       "0             Romance\n",
+       "1         Documentary\n",
+       "1                News\n",
+       "1               Sport\n",
+       "2           Biography\n",
+       "             ...     \n",
+       "232492          Drama\n",
+       "232493    Documentary\n",
+       "232494    Documentary\n",
+       "232495          Drama\n",
+       "232495         Family\n",
        "Name: genres, Length: 397539, dtype: object"
       ]
      },
-     "execution_count": 64,
+     "execution_count": 18,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -7388,7 +1358,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 65,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [
     {
@@ -7418,18 +1388,10 @@
        "      <th>imdb_rating</th>\n",
        "      <th>imdb_votes</th>\n",
        "    </tr>\n",
-       "    <tr>\n",
-       "      <th>tconst</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>tt0000009</th>\n",
+       "      <th>0</th>\n",
        "      <td>Miss Jerry</td>\n",
        "      <td>Romance</td>\n",
        "      <td>1890s</td>\n",
@@ -7437,7 +1399,7 @@
        "      <td>77</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>tt0000147</th>\n",
+       "      <th>1</th>\n",
        "      <td>The Corbett-Fitzsimmons Fight</td>\n",
        "      <td>Documentary</td>\n",
        "      <td>1890s</td>\n",
@@ -7445,7 +1407,7 @@
        "      <td>289</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>tt0000147</th>\n",
+       "      <th>1</th>\n",
        "      <td>The Corbett-Fitzsimmons Fight</td>\n",
        "      <td>News</td>\n",
        "      <td>1890s</td>\n",
@@ -7453,7 +1415,7 @@
        "      <td>289</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>tt0000147</th>\n",
+       "      <th>1</th>\n",
        "      <td>The Corbett-Fitzsimmons Fight</td>\n",
        "      <td>Sport</td>\n",
        "      <td>1890s</td>\n",
@@ -7461,7 +1423,7 @@
        "      <td>289</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>tt0000335</th>\n",
+       "      <th>2</th>\n",
        "      <td>Soldiers of the Cross</td>\n",
        "      <td>Biography</td>\n",
        "      <td>1890s</td>\n",
@@ -7477,7 +1439,7 @@
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>tt9911774</th>\n",
+       "      <th>232492</th>\n",
        "      <td>Padmavyuhathile Abhimanyu</td>\n",
        "      <td>Drama</td>\n",
        "      <td>2010s</td>\n",
@@ -7485,7 +1447,7 @@
        "      <td>363</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>tt9913056</th>\n",
+       "      <th>232493</th>\n",
        "      <td>Swarm Season</td>\n",
        "      <td>Documentary</td>\n",
        "      <td>2010s</td>\n",
@@ -7493,7 +1455,7 @@
        "      <td>5</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>tt9913084</th>\n",
+       "      <th>232494</th>\n",
        "      <td>Diabolik sono io</td>\n",
        "      <td>Documentary</td>\n",
        "      <td>2010s</td>\n",
@@ -7501,7 +1463,7 @@
        "      <td>6</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>tt9914286</th>\n",
+       "      <th>232495</th>\n",
        "      <td>Sokagin Çocuklari</td>\n",
        "      <td>Drama</td>\n",
        "      <td>2010s</td>\n",
@@ -7509,7 +1471,7 @@
        "      <td>72</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>tt9914286</th>\n",
+       "      <th>232495</th>\n",
        "      <td>Sokagin Çocuklari</td>\n",
        "      <td>Family</td>\n",
        "      <td>2010s</td>\n",
@@ -7522,38 +1484,36 @@
        "</div>"
       ],
       "text/plain": [
-       "                                   title        genre decade  imdb_rating  \\\n",
-       "tconst                                                                      \n",
-       "tt0000009                     Miss Jerry      Romance  1890s          5.5   \n",
-       "tt0000147  The Corbett-Fitzsimmons Fight  Documentary  1890s          5.2   \n",
-       "tt0000147  The Corbett-Fitzsimmons Fight         News  1890s          5.2   \n",
-       "tt0000147  The Corbett-Fitzsimmons Fight        Sport  1890s          5.2   \n",
-       "tt0000335          Soldiers of the Cross    Biography  1890s          6.3   \n",
-       "...                                  ...          ...    ...          ...   \n",
-       "tt9911774      Padmavyuhathile Abhimanyu        Drama  2010s          8.5   \n",
-       "tt9913056                   Swarm Season  Documentary  2010s          6.2   \n",
-       "tt9913084               Diabolik sono io  Documentary  2010s          6.2   \n",
-       "tt9914286              Sokagin Çocuklari        Drama  2010s          9.8   \n",
-       "tt9914286              Sokagin Çocuklari       Family  2010s          9.8   \n",
-       "\n",
-       "           imdb_votes  \n",
-       "tconst                 \n",
-       "tt0000009          77  \n",
-       "tt0000147         289  \n",
-       "tt0000147         289  \n",
-       "tt0000147         289  \n",
-       "tt0000335          39  \n",
-       "...               ...  \n",
-       "tt9911774         363  \n",
-       "tt9913056           5  \n",
-       "tt9913084           6  \n",
-       "tt9914286          72  \n",
-       "tt9914286          72  \n",
+       "                                title        genre decade  imdb_rating  \\\n",
+       "0                          Miss Jerry      Romance  1890s          5.5   \n",
+       "1       The Corbett-Fitzsimmons Fight  Documentary  1890s          5.2   \n",
+       "1       The Corbett-Fitzsimmons Fight         News  1890s          5.2   \n",
+       "1       The Corbett-Fitzsimmons Fight        Sport  1890s          5.2   \n",
+       "2               Soldiers of the Cross    Biography  1890s          6.3   \n",
+       "...                               ...          ...    ...          ...   \n",
+       "232492      Padmavyuhathile Abhimanyu        Drama  2010s          8.5   \n",
+       "232493                   Swarm Season  Documentary  2010s          6.2   \n",
+       "232494               Diabolik sono io  Documentary  2010s          6.2   \n",
+       "232495              Sokagin Çocuklari        Drama  2010s          9.8   \n",
+       "232495              Sokagin Çocuklari       Family  2010s          9.8   \n",
+       "\n",
+       "        imdb_votes  \n",
+       "0               77  \n",
+       "1              289  \n",
+       "1              289  \n",
+       "1              289  \n",
+       "2               39  \n",
+       "...            ...  \n",
+       "232492         363  \n",
+       "232493           5  \n",
+       "232494           6  \n",
+       "232495          72  \n",
+       "232495          72  \n",
        "\n",
        "[397539 rows x 5 columns]"
       ]
      },
-     "execution_count": 65,
+     "execution_count": 19,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -7583,7 +1543,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 66,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -7604,7 +1564,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 67,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [
     {
@@ -7725,7 +1685,7 @@
        "2010s      7.350307  5.061069"
       ]
      },
-     "execution_count": 67,
+     "execution_count": 21,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -7750,7 +1710,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 68,
+   "execution_count": 22,
    "metadata": {
     "scrolled": false
    },
@@ -7779,7 +1739,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 69,
+   "execution_count": 23,
    "metadata": {},
    "outputs": [
     {
@@ -7838,7 +1798,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 70,
+   "execution_count": 24,
    "metadata": {},
    "outputs": [
     {
@@ -7857,7 +1817,7 @@
        "<Axes: xlabel='decade', ylabel='imdb_rating'>"
       ]
      },
-     "execution_count": 70,
+     "execution_count": 24,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -7889,7 +1849,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 71,
+   "execution_count": 25,
    "metadata": {},
    "outputs": [
     {
@@ -7908,7 +1868,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 1200x500 with 1 Axes>"
       ]
@@ -7936,7 +1896,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 72,
+   "execution_count": 26,
    "metadata": {},
    "outputs": [
     {
@@ -7955,7 +1915,7 @@
        "<Axes: xlabel='decade', ylabel='imdb_rating'>"
       ]
      },
-     "execution_count": 72,
+     "execution_count": 26,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -8008,7 +1968,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 73,
+   "execution_count": 27,
    "metadata": {},
    "outputs": [
     {
@@ -8038,7 +1998,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 74,
+   "execution_count": 28,
    "metadata": {},
    "outputs": [
     {
@@ -8111,7 +2071,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 76,
+   "execution_count": 30,
    "metadata": {},
    "outputs": [
     {
diff --git a/lessons/pydata/pandas_correlations/movies_complete.csv.gz b/lessons/pydata/pandas_correlations/movies_complete.csv.gz
new file mode 100644
index 0000000..589ffc3
Binary files /dev/null and b/lessons/pydata/pandas_correlations/movies_complete.csv.gz differ
diff --git a/lessons/pydata/pandas_correlations/movies_with_rating.csv.gz b/lessons/pydata/pandas_correlations/movies_with_rating.csv.gz
new file mode 100644
index 0000000..cfdb7eb
Binary files /dev/null and b/lessons/pydata/pandas_correlations/movies_with_rating.csv.gz differ
diff --git a/lessons/pydata/pandas_correlations/boxoffice_march_2019.csv.gz b/lessons/pydata/pandas_joins/boxoffice_march_2019.csv.gz
similarity index 100%
rename from lessons/pydata/pandas_correlations/boxoffice_march_2019.csv.gz
rename to lessons/pydata/pandas_joins/boxoffice_march_2019.csv.gz
diff --git a/lessons/pydata/pandas_joins/index.ipynb b/lessons/pydata/pandas_joins/index.ipynb
new file mode 100644
index 0000000..5c3a49d
--- /dev/null
+++ b/lessons/pydata/pandas_joins/index.ipynb
@@ -0,0 +1,6118 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Pandas - spojování tabulek\n",
+    "\n",
+    "Tato lekce se nese ve znamení mnohosti a propojování - naučíš se  pracovat s více tabulkami najednou. Při tom společně projdeme (ne poprvé a ne naposledy) čištění reálných datových sad."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Importy jako obvykle\n",
+    "import pandas as pd"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "toc-hr-collapsed": false
+   },
+   "source": [
+    "## Spojování tabulek\n",
+    "\n",
+    "V lekci, kde jsme zpracovávali data o počasí, jsme ti ukázali, že je pomocí funkce `concat` možné slepit dohromady několik objektů `DataFrame` či `Series`, pokud mají \"kompatibilní\" index. Nyní se na problematiku podíváme trochu blíže a ukážeme si, jak spojovat tabulky na základě různých sloupců, a co dělat, když řádky z jedné tabulky nepasují přesně na tabulku druhou.\n",
+    "\n",
+    "Obecně pro spojování `pandas` nabízí tři funkce / metody, z nichž každá má svoje typické využití (možnostmi se ovšem překrývají):\n",
+    "\n",
+    "- [`concat`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.concat.html) je univerzální funkce pro slepování dvou či více tabulek / sloupců - pod sebe, vedle sebe, s přihlédnutím k indexům i bez něj. \n",
+    "- [`merge`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.merge.html) je univerzální funkce pro spojování tabulek na základě vazby mezi indexy nebo sloupci.\n",
+    "- [`join`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.join.html) (metoda) zjednodušuje práci, když chceš spojit dvě tabulky na základě indexu.\n",
+    "\n",
+    "Detailní rozbor toho, co která umí, najdeš v [dokumentaci](https://pandas.pydata.org/pandas-docs/stable/user_guide/merging.html). My si je také postupně ukážeme."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Jednoduché skládání"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Pod sebou\n",
+    "\n",
+    "To je asi ten nejjednodušší případ - máme dva objekty `Series` nebo dva kusy tabulky se stejnými sloupci a chceme je spojit pod sebou. Na to se používá funkce [`concat`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.concat.html):"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "a = pd.Series([\"jedna\", \"dvě\", \"tři\"])\n",
+    "b = pd.Series([\"čtyři\", \"pět\", \"šest\"])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0    jedna\n",
+       "1      dvě\n",
+       "2      tři\n",
+       "0    čtyři\n",
+       "1      pět\n",
+       "2     šest\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pd.concat([a, b])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "💡 Vidíš, že se index opakuje? Vytvořili jsme dvě `Series`, u kterých jsme index neřešili. Jenže `pandas` na rozdíl od nás ano, a tak poslušně oba indexy spojil, i za cenu duplicitních hodnot. Za cenu použití dodatečného argumentu `ignore_index=True` se tomu lze vyhnout, což si ukážeme na příklady spojování dvou tabulek o stejných sloupcích:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0     jedna\n",
+       "1       dvě\n",
+       "2       tři\n",
+       "3     jedna\n",
+       "4       dvě\n",
+       "5       tři\n",
+       "6     jedna\n",
+       "7       dvě\n",
+       "8       tři\n",
+       "9     jedna\n",
+       "10      dvě\n",
+       "11      tři\n",
+       "12    jedna\n",
+       "13      dvě\n",
+       "14      tři\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pd.concat([a, a, a, a, a], ignore_index=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Vedle sebe\n",
+    "\n",
+    "Toto asi použijete zřídka, ale když chceme \"lepit\" doprava (třeba deset `Series`), stačí přidat nám dobře známý argument `axis`:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>0</th>\n",
+       "      <th>1</th>\n",
+       "      <th>2</th>\n",
+       "      <th>3</th>\n",
+       "      <th>4</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>jedna</td>\n",
+       "      <td>jedna</td>\n",
+       "      <td>jedna</td>\n",
+       "      <td>jedna</td>\n",
+       "      <td>jedna</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>dvě</td>\n",
+       "      <td>dvě</td>\n",
+       "      <td>dvě</td>\n",
+       "      <td>dvě</td>\n",
+       "      <td>dvě</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>tři</td>\n",
+       "      <td>tři</td>\n",
+       "      <td>tři</td>\n",
+       "      <td>tři</td>\n",
+       "      <td>tři</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       0      1      2      3      4\n",
+       "0  jedna  jedna  jedna  jedna  jedna\n",
+       "1    dvě    dvě    dvě    dvě    dvě\n",
+       "2    tři    tři    tři    tři    tři"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pd.concat([a, a, a, a, a], axis=\"columns\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Příklad:** Jak co nejrychleji \"nakreslit prázdnou šachovnici\" (obě slova jsou v uvozovkách)?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>A</th>\n",
+       "      <th>B</th>\n",
+       "      <th>C</th>\n",
+       "      <th>D</th>\n",
+       "      <th>E</th>\n",
+       "      <th>F</th>\n",
+       "      <th>G</th>\n",
+       "      <th>H</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>⬜</td>\n",
+       "      <td>⬛</td>\n",
+       "      <td>⬜</td>\n",
+       "      <td>⬛</td>\n",
+       "      <td>⬜</td>\n",
+       "      <td>⬛</td>\n",
+       "      <td>⬜</td>\n",
+       "      <td>⬛</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>⬛</td>\n",
+       "      <td>⬜</td>\n",
+       "      <td>⬛</td>\n",
+       "      <td>⬜</td>\n",
+       "      <td>⬛</td>\n",
+       "      <td>⬜</td>\n",
+       "      <td>⬛</td>\n",
+       "      <td>⬜</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>⬜</td>\n",
+       "      <td>⬛</td>\n",
+       "      <td>⬜</td>\n",
+       "      <td>⬛</td>\n",
+       "      <td>⬜</td>\n",
+       "      <td>⬛</td>\n",
+       "      <td>⬜</td>\n",
+       "      <td>⬛</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>⬛</td>\n",
+       "      <td>⬜</td>\n",
+       "      <td>⬛</td>\n",
+       "      <td>⬜</td>\n",
+       "      <td>⬛</td>\n",
+       "      <td>⬜</td>\n",
+       "      <td>⬛</td>\n",
+       "      <td>⬜</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>⬜</td>\n",
+       "      <td>⬛</td>\n",
+       "      <td>⬜</td>\n",
+       "      <td>⬛</td>\n",
+       "      <td>⬜</td>\n",
+       "      <td>⬛</td>\n",
+       "      <td>⬜</td>\n",
+       "      <td>⬛</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>⬛</td>\n",
+       "      <td>⬜</td>\n",
+       "      <td>⬛</td>\n",
+       "      <td>⬜</td>\n",
+       "      <td>⬛</td>\n",
+       "      <td>⬜</td>\n",
+       "      <td>⬛</td>\n",
+       "      <td>⬜</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>⬜</td>\n",
+       "      <td>⬛</td>\n",
+       "      <td>⬜</td>\n",
+       "      <td>⬛</td>\n",
+       "      <td>⬜</td>\n",
+       "      <td>⬛</td>\n",
+       "      <td>⬜</td>\n",
+       "      <td>⬛</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>⬛</td>\n",
+       "      <td>⬜</td>\n",
+       "      <td>⬛</td>\n",
+       "      <td>⬜</td>\n",
+       "      <td>⬛</td>\n",
+       "      <td>⬜</td>\n",
+       "      <td>⬛</td>\n",
+       "      <td>⬜</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   A  B  C  D  E  F  G  H\n",
+       "8  ⬜  ⬛  ⬜  ⬛  ⬜  ⬛  ⬜  ⬛\n",
+       "7  ⬛  ⬜  ⬛  ⬜  ⬛  ⬜  ⬛  ⬜\n",
+       "6  ⬜  ⬛  ⬜  ⬛  ⬜  ⬛  ⬜  ⬛\n",
+       "5  ⬛  ⬜  ⬛  ⬜  ⬛  ⬜  ⬛  ⬜\n",
+       "4  ⬜  ⬛  ⬜  ⬛  ⬜  ⬛  ⬜  ⬛\n",
+       "3  ⬛  ⬜  ⬛  ⬜  ⬛  ⬜  ⬛  ⬜\n",
+       "2  ⬜  ⬛  ⬜  ⬛  ⬜  ⬛  ⬜  ⬛\n",
+       "1  ⬛  ⬜  ⬛  ⬜  ⬛  ⬜  ⬛  ⬜"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sachy = pd.concat(\n",
+    "    [\n",
+    "        pd.concat(   \n",
+    "            [pd.DataFrame([[\"⬜\", \"⬛\"], [\"⬛\", \"⬜\"]])] * 4,\n",
+    "            axis=1)\n",
+    "    ] * 4\n",
+    ")\n",
+    "sachy.index = list(range(8, 0, -1))\n",
+    "sachy.columns = list(\"ABCDEFGH\")\n",
+    "sachy"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Spojování různorodých tabulek"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "🎦 Pro spojování heterogenních dat (v datové hantýrce \"joinování\") sáhneme po trochu komplexnějších filmových datech..."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Máme staženo několik souborů, načteme si je (zatím hrubě, \"raw\") - s přihlédnutím k tomu, že první dva nejsou v pravém slova smyslu \"comma-separated\", ale používají k oddělení hodnot tabulátor (tady pomůže argument `sep`). Také zohledníme, že v nich řetězec `\"\\N\"` představuje chybějící hodnoty (pomůže argument `na_values`):"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "imdb_titles_raw = pd.read_csv(\"title.basics.tsv.gz\", sep=\"\\t\", na_values=\"\\\\N\")\n",
+    "imdb_ratings_raw = pd.read_csv(\"title.ratings.tsv.gz\", sep=\"\\t\", na_values=\"\\\\N\")\n",
+    "boxoffice_raw = pd.read_csv(\"boxoffice_march_2019.csv.gz\")\n",
+    "rotten_tomatoes_raw = pd.read_csv(\"rotten_tomatoes_top_movies_2019-01-15.csv\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Co který soubor obsahuje? \n",
+    "\n",
+    "- První dva soubory obsahují volně dostupná (byť \"jen\" pro nekomerční použití) data o filmech z IMDb (Internet Movie Database). My jsme si zvolili obecné informace a uživatelská (číselná) hodnocení. Detailní popis souborů, stejně jako odkazy na další soubory, najdeš na https://www.imdb.com/interfaces/. Z důvodů paměťové náročnosti jsme datovou sadu ořezali o epizody seriálů, protože nás nebudou zajímat a s trochu štěstí přežijeme i na počítačích s menší operační pamětí.\n",
+    "\n",
+    "- Soubor `boxoffice_march_2019.csv.gz` obsahuje informace o výdělcích jednotlivých filmů. Pochází z ukázkového datasetu pro soutěž \"TMDB Box Office Prediction\" na serveru Kaggle: https://www.kaggle.com/c/tmdb-box-office-prediction/data\n",
+    "\n",
+    "- Soubor `rotten_tomatoes_top_movies_2019-01-15.csv` obsahuje procentuální hodnocení filmů ze serveru Rotten Tomatoes, které se počítá jako podíl pozitivních hodnoceních od filmových kritiku (je to tedy jiný princip než na IMDb). Staženo z: https://data.world/prasert/rotten-tomatoes-top-movies-by-genre\n",
+    "\n",
+    "Pojďme se podívat na nedostatky těchto souborů a postupně je skládat dohromady. Zajímalo by nás (a snad i tebe!), jak souvisí hodnocení s komerční úspěšností filmu, jak se liší hodnocení rotten tomatoes od těch na IMDb."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>tconst</th>\n",
+       "      <th>titleType</th>\n",
+       "      <th>primaryTitle</th>\n",
+       "      <th>originalTitle</th>\n",
+       "      <th>isAdult</th>\n",
+       "      <th>startYear</th>\n",
+       "      <th>endYear</th>\n",
+       "      <th>runtimeMinutes</th>\n",
+       "      <th>genres</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>tt0000001</td>\n",
+       "      <td>short</td>\n",
+       "      <td>Carmencita</td>\n",
+       "      <td>Carmencita</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1894.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>Documentary,Short</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>tt0000002</td>\n",
+       "      <td>short</td>\n",
+       "      <td>Le clown et ses chiens</td>\n",
+       "      <td>Le clown et ses chiens</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1892.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>Animation,Short</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>tt0000003</td>\n",
+       "      <td>short</td>\n",
+       "      <td>Pauvre Pierrot</td>\n",
+       "      <td>Pauvre Pierrot</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1892.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>Animation,Comedy,Romance</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>tt0000004</td>\n",
+       "      <td>short</td>\n",
+       "      <td>Un bon bock</td>\n",
+       "      <td>Un bon bock</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1892.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Animation,Short</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>tt0000005</td>\n",
+       "      <td>short</td>\n",
+       "      <td>Blacksmith Scene</td>\n",
+       "      <td>Blacksmith Scene</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1893.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>Comedy,Short</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1783511</th>\n",
+       "      <td>tt9916734</td>\n",
+       "      <td>video</td>\n",
+       "      <td>Manca: Peleo</td>\n",
+       "      <td>Manca: Peleo</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2018.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Music,Short</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1783512</th>\n",
+       "      <td>tt9916754</td>\n",
+       "      <td>movie</td>\n",
+       "      <td>Chico Albuquerque - Revelações</td>\n",
+       "      <td>Chico Albuquerque - Revelações</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2013.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Documentary</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1783513</th>\n",
+       "      <td>tt9916756</td>\n",
+       "      <td>short</td>\n",
+       "      <td>Pretty Pretty Black Girl</td>\n",
+       "      <td>Pretty Pretty Black Girl</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2019.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Short</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1783514</th>\n",
+       "      <td>tt9916764</td>\n",
+       "      <td>short</td>\n",
+       "      <td>38</td>\n",
+       "      <td>38</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2018.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Short</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1783515</th>\n",
+       "      <td>tt9916856</td>\n",
+       "      <td>short</td>\n",
+       "      <td>The Wind</td>\n",
+       "      <td>The Wind</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2015.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>27.0</td>\n",
+       "      <td>Short</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1783516 rows × 9 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            tconst titleType                    primaryTitle  \\\n",
+       "0        tt0000001     short                      Carmencita   \n",
+       "1        tt0000002     short          Le clown et ses chiens   \n",
+       "2        tt0000003     short                  Pauvre Pierrot   \n",
+       "3        tt0000004     short                     Un bon bock   \n",
+       "4        tt0000005     short                Blacksmith Scene   \n",
+       "...            ...       ...                             ...   \n",
+       "1783511  tt9916734     video                    Manca: Peleo   \n",
+       "1783512  tt9916754     movie  Chico Albuquerque - Revelações   \n",
+       "1783513  tt9916756     short        Pretty Pretty Black Girl   \n",
+       "1783514  tt9916764     short                              38   \n",
+       "1783515  tt9916856     short                        The Wind   \n",
+       "\n",
+       "                          originalTitle  isAdult  startYear  endYear  \\\n",
+       "0                            Carmencita        0     1894.0      NaN   \n",
+       "1                Le clown et ses chiens        0     1892.0      NaN   \n",
+       "2                        Pauvre Pierrot        0     1892.0      NaN   \n",
+       "3                           Un bon bock        0     1892.0      NaN   \n",
+       "4                      Blacksmith Scene        0     1893.0      NaN   \n",
+       "...                                 ...      ...        ...      ...   \n",
+       "1783511                    Manca: Peleo        0     2018.0      NaN   \n",
+       "1783512  Chico Albuquerque - Revelações        0     2013.0      NaN   \n",
+       "1783513        Pretty Pretty Black Girl        0     2019.0      NaN   \n",
+       "1783514                              38        0     2018.0      NaN   \n",
+       "1783515                        The Wind        0     2015.0      NaN   \n",
+       "\n",
+       "         runtimeMinutes                    genres  \n",
+       "0                   1.0         Documentary,Short  \n",
+       "1                   5.0           Animation,Short  \n",
+       "2                   4.0  Animation,Comedy,Romance  \n",
+       "3                   NaN           Animation,Short  \n",
+       "4                   1.0              Comedy,Short  \n",
+       "...                 ...                       ...  \n",
+       "1783511             NaN               Music,Short  \n",
+       "1783512             NaN               Documentary  \n",
+       "1783513             NaN                     Short  \n",
+       "1783514             NaN                     Short  \n",
+       "1783515            27.0                     Short  \n",
+       "\n",
+       "[1783516 rows x 9 columns]"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "imdb_titles_raw"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "648.8971881866455"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Kolik tabulka zabírá megabajtů paměti? (1 MB = 2**20 bajtů)\n",
+    "imdb_titles_raw.memory_usage(deep=True).sum() / 2**20 "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Jistě budeme chtít převést sloupce na správné typy. Jaké jsou v základu?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "tconst             object\n",
+       "titleType          object\n",
+       "primaryTitle       object\n",
+       "originalTitle      object\n",
+       "isAdult             int64\n",
+       "startYear         float64\n",
+       "endYear           float64\n",
+       "runtimeMinutes    float64\n",
+       "genres             object\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "imdb_titles_raw.dtypes"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Na co budeme převádět?\n",
+    "\n",
+    "- `tconst` je řetězec, který posléze použijeme jako index, protože představuje unikátní identifikátor v databázi IMDb.\n",
+    "- `titleType`:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "titleType\n",
+       "short           676930\n",
+       "movie           514654\n",
+       "video           227582\n",
+       "tvSeries        162781\n",
+       "tvMovie         126507\n",
+       "tvMiniSeries     25574\n",
+       "videoGame        23310\n",
+       "tvSpecial        17007\n",
+       "tvShort           9171\n",
+       "Name: count, dtype: int64"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "imdb_titles_raw[\"titleType\"].value_counts()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Jen devět různých hodnot ve skoro 2 milionech řádků? To je ideální kandidát na převedení na typ `\"category\"`.\n",
+    "\n",
+    "- `primaryTitle` a `originalTitle` vypadají jako obyčejné řetězce (pokud možno anglický a pokud možno původní název)\n",
+    "- `isAdult` určuje, zda se jedná o dílo pro dospělé. Tento sloupec bychom nejspíše měli převést na `bool`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "isAdult\n",
+       "0    1692292\n",
+       "1      91224\n",
+       "Name: count, dtype: int64"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "imdb_titles_raw[\"isAdult\"].value_counts()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "- `startYear` a `endYear` obsahují roky, t.j. celá čísla, ovšem kvůli chybějícím hodnotám je pro ně zvolen typ `float64`. V `pandas` raději zvolíme tzv. \"nullable integer\", který se zapisuje s velkým \"I\". Když nevíš, jaký podtyp konkrétně, sáhni po `Int64`.\n",
+    "- totéž platí pro `runtimeMinutes`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "startYear           2115.0\n",
+       "endYear             2027.0\n",
+       "runtimeMinutes    125156.0\n",
+       "dtype: float64"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "imdb_titles_raw[[\"startYear\", \"endYear\", \"runtimeMinutes\"]].max()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Mimochodem všimli jste si, že máme díla z budoucnosti (rok 2115)?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "startYear\n",
+       "2020.0    340\n",
+       "2021.0     36\n",
+       "2022.0     14\n",
+       "2023.0      1\n",
+       "2024.0      2\n",
+       "2025.0      1\n",
+       "2115.0      1\n",
+       "Name: count, dtype: int64"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "imdb_titles_raw[\"startYear\"].plot.hist()\n",
+    "imdb_titles_raw.query(\"startYear > 2019\")[\"startYear\"].value_counts().sort_index()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Takhle nějak by přetypování mohlo vypadat:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "tconst              object\n",
+       "titleType         category\n",
+       "primaryTitle        object\n",
+       "originalTitle       object\n",
+       "isAdult               bool\n",
+       "startYear            Int64\n",
+       "endYear              Int64\n",
+       "runtimeMinutes       Int64\n",
+       "genres              object\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "(\n",
+    "    imdb_titles_raw\n",
+    "    .assign(\n",
+    "        titleType=imdb_titles_raw[\"titleType\"].astype(\"category\"),\n",
+    "        startYear=imdb_titles_raw[\"startYear\"].astype(\"Int64\"),\n",
+    "        endYear=imdb_titles_raw[\"endYear\"].astype(\"Int64\"),\n",
+    "        isAdult=imdb_titles_raw[\"isAdult\"].astype(bool),\n",
+    "        runtimeMinutes=imdb_titles_raw[\"runtimeMinutes\"].astype(\"Int64\")\n",
+    "    )\n",
+    ").dtypes"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Takhle už by to mohlo být. Jen si ještě:\n",
+    "\n",
+    "- pro přehlednost přejmenujeme některé sloupce (pomocí metody [`rename`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.rename.html))\n",
+    "- použijeme `tconst` jako index\n",
+    "\n",
+    "A tabulka `imdb_titles` bude připravená k použití!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>title_type</th>\n",
+       "      <th>title</th>\n",
+       "      <th>original_title</th>\n",
+       "      <th>is_adult</th>\n",
+       "      <th>start_year</th>\n",
+       "      <th>end_year</th>\n",
+       "      <th>length</th>\n",
+       "      <th>genres</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tconst</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>tt0000001</th>\n",
+       "      <td>short</td>\n",
+       "      <td>Carmencita</td>\n",
+       "      <td>Carmencita</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1894</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Documentary,Short</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt0000002</th>\n",
+       "      <td>short</td>\n",
+       "      <td>Le clown et ses chiens</td>\n",
+       "      <td>Le clown et ses chiens</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1892</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>5</td>\n",
+       "      <td>Animation,Short</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt0000003</th>\n",
+       "      <td>short</td>\n",
+       "      <td>Pauvre Pierrot</td>\n",
+       "      <td>Pauvre Pierrot</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1892</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>4</td>\n",
+       "      <td>Animation,Comedy,Romance</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt0000004</th>\n",
+       "      <td>short</td>\n",
+       "      <td>Un bon bock</td>\n",
+       "      <td>Un bon bock</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1892</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>Animation,Short</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt0000005</th>\n",
+       "      <td>short</td>\n",
+       "      <td>Blacksmith Scene</td>\n",
+       "      <td>Blacksmith Scene</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1893</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Comedy,Short</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt9916734</th>\n",
+       "      <td>video</td>\n",
+       "      <td>Manca: Peleo</td>\n",
+       "      <td>Manca: Peleo</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>Music,Short</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt9916754</th>\n",
+       "      <td>movie</td>\n",
+       "      <td>Chico Albuquerque - Revelações</td>\n",
+       "      <td>Chico Albuquerque - Revelações</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2013</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>Documentary</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt9916756</th>\n",
+       "      <td>short</td>\n",
+       "      <td>Pretty Pretty Black Girl</td>\n",
+       "      <td>Pretty Pretty Black Girl</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>Short</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt9916764</th>\n",
+       "      <td>short</td>\n",
+       "      <td>38</td>\n",
+       "      <td>38</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>Short</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt9916856</th>\n",
+       "      <td>short</td>\n",
+       "      <td>The Wind</td>\n",
+       "      <td>The Wind</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2015</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>27</td>\n",
+       "      <td>Short</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1783516 rows × 8 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          title_type                           title  \\\n",
+       "tconst                                                 \n",
+       "tt0000001      short                      Carmencita   \n",
+       "tt0000002      short          Le clown et ses chiens   \n",
+       "tt0000003      short                  Pauvre Pierrot   \n",
+       "tt0000004      short                     Un bon bock   \n",
+       "tt0000005      short                Blacksmith Scene   \n",
+       "...              ...                             ...   \n",
+       "tt9916734      video                    Manca: Peleo   \n",
+       "tt9916754      movie  Chico Albuquerque - Revelações   \n",
+       "tt9916756      short        Pretty Pretty Black Girl   \n",
+       "tt9916764      short                              38   \n",
+       "tt9916856      short                        The Wind   \n",
+       "\n",
+       "                           original_title  is_adult  start_year  end_year  \\\n",
+       "tconst                                                                      \n",
+       "tt0000001                      Carmencita     False        1894      <NA>   \n",
+       "tt0000002          Le clown et ses chiens     False        1892      <NA>   \n",
+       "tt0000003                  Pauvre Pierrot     False        1892      <NA>   \n",
+       "tt0000004                     Un bon bock     False        1892      <NA>   \n",
+       "tt0000005                Blacksmith Scene     False        1893      <NA>   \n",
+       "...                                   ...       ...         ...       ...   \n",
+       "tt9916734                    Manca: Peleo     False        2018      <NA>   \n",
+       "tt9916754  Chico Albuquerque - Revelações     False        2013      <NA>   \n",
+       "tt9916756        Pretty Pretty Black Girl     False        2019      <NA>   \n",
+       "tt9916764                              38     False        2018      <NA>   \n",
+       "tt9916856                        The Wind     False        2015      <NA>   \n",
+       "\n",
+       "           length                    genres  \n",
+       "tconst                                       \n",
+       "tt0000001       1         Documentary,Short  \n",
+       "tt0000002       5           Animation,Short  \n",
+       "tt0000003       4  Animation,Comedy,Romance  \n",
+       "tt0000004    <NA>           Animation,Short  \n",
+       "tt0000005       1              Comedy,Short  \n",
+       "...           ...                       ...  \n",
+       "tt9916734    <NA>               Music,Short  \n",
+       "tt9916754    <NA>               Documentary  \n",
+       "tt9916756    <NA>                     Short  \n",
+       "tt9916764    <NA>                     Short  \n",
+       "tt9916856      27                     Short  \n",
+       "\n",
+       "[1783516 rows x 8 columns]"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "imdb_titles = (\n",
+    "    imdb_titles_raw\n",
+    "    .assign(\n",
+    "        titleType=imdb_titles_raw[\"titleType\"].astype(\"category\"),\n",
+    "        startYear=imdb_titles_raw[\"startYear\"].astype(\"Int64\"),\n",
+    "        endYear=imdb_titles_raw[\"endYear\"].astype(\"Int64\"),\n",
+    "        isAdult=imdb_titles_raw[\"isAdult\"].astype(bool),\n",
+    "        runtimeMinutes=imdb_titles_raw[\"runtimeMinutes\"].astype(\"Int64\")\n",
+    "    )\n",
+    "    .rename({\n",
+    "        \"primaryTitle\": \"title\",\n",
+    "        \"originalTitle\": \"original_title\",\n",
+    "        \"titleType\": \"title_type\",\n",
+    "        \"runtimeMinutes\": \"length\",\n",
+    "        \"startYear\": \"start_year\",\n",
+    "        \"endYear\": \"end_year\",\n",
+    "        \"isAdult\": \"is_adult\",\n",
+    "    }, axis=\"columns\")\n",
+    "    .set_index(\"tconst\")\n",
+    ")\n",
+    "imdb_titles"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "537.2908029556274"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Kolik tabulka zabírá megabajtů paměti?\n",
+    "imdb_titles.memory_usage(deep=True).sum() / 2**20   # O chlup méně, zase tolik jsme si ale nepomohli."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Připravíme si ještě speciální tabulku jenom pro filmy, protože další datové sady se zabývají jenom jimi.\n",
+    "\n",
+    "U této tabulky navíc vyhodíme zbytečné sloupce `title_type`, `end_year` a přejmenujeme `start_year` prostě na `year`:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>title</th>\n",
+       "      <th>original_title</th>\n",
+       "      <th>is_adult</th>\n",
+       "      <th>year</th>\n",
+       "      <th>length</th>\n",
+       "      <th>genres</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tconst</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>tt0000009</th>\n",
+       "      <td>Miss Jerry</td>\n",
+       "      <td>Miss Jerry</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1894</td>\n",
+       "      <td>45</td>\n",
+       "      <td>Romance</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt0000147</th>\n",
+       "      <td>The Corbett-Fitzsimmons Fight</td>\n",
+       "      <td>The Corbett-Fitzsimmons Fight</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1897</td>\n",
+       "      <td>20</td>\n",
+       "      <td>Documentary,News,Sport</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt0000335</th>\n",
+       "      <td>Soldiers of the Cross</td>\n",
+       "      <td>Soldiers of the Cross</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1900</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>Biography,Drama</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt0000502</th>\n",
+       "      <td>Bohemios</td>\n",
+       "      <td>Bohemios</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1905</td>\n",
+       "      <td>100</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt0000574</th>\n",
+       "      <td>The Story of the Kelly Gang</td>\n",
+       "      <td>The Story of the Kelly Gang</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1906</td>\n",
+       "      <td>70</td>\n",
+       "      <td>Biography,Crime,Drama</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt9916622</th>\n",
+       "      <td>Rodolpho Teóphilo - O Legado de um Pioneiro</td>\n",
+       "      <td>Rodolpho Teóphilo - O Legado de um Pioneiro</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2015</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>Documentary</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt9916680</th>\n",
+       "      <td>De la ilusión al desconcierto: cine colombiano...</td>\n",
+       "      <td>De la ilusión al desconcierto: cine colombiano...</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2007</td>\n",
+       "      <td>100</td>\n",
+       "      <td>Documentary</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt9916706</th>\n",
+       "      <td>Dankyavar Danka</td>\n",
+       "      <td>Dankyavar Danka</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2013</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>Comedy</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt9916730</th>\n",
+       "      <td>6 Gunn</td>\n",
+       "      <td>6 Gunn</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>116</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt9916754</th>\n",
+       "      <td>Chico Albuquerque - Revelações</td>\n",
+       "      <td>Chico Albuquerque - Revelações</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2013</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>Documentary</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>514654 rows × 6 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                                       title  \\\n",
+       "tconst                                                         \n",
+       "tt0000009                                         Miss Jerry   \n",
+       "tt0000147                      The Corbett-Fitzsimmons Fight   \n",
+       "tt0000335                              Soldiers of the Cross   \n",
+       "tt0000502                                           Bohemios   \n",
+       "tt0000574                        The Story of the Kelly Gang   \n",
+       "...                                                      ...   \n",
+       "tt9916622        Rodolpho Teóphilo - O Legado de um Pioneiro   \n",
+       "tt9916680  De la ilusión al desconcierto: cine colombiano...   \n",
+       "tt9916706                                    Dankyavar Danka   \n",
+       "tt9916730                                             6 Gunn   \n",
+       "tt9916754                     Chico Albuquerque - Revelações   \n",
+       "\n",
+       "                                              original_title  is_adult  year  \\\n",
+       "tconst                                                                         \n",
+       "tt0000009                                         Miss Jerry     False  1894   \n",
+       "tt0000147                      The Corbett-Fitzsimmons Fight     False  1897   \n",
+       "tt0000335                              Soldiers of the Cross     False  1900   \n",
+       "tt0000502                                           Bohemios     False  1905   \n",
+       "tt0000574                        The Story of the Kelly Gang     False  1906   \n",
+       "...                                                      ...       ...   ...   \n",
+       "tt9916622        Rodolpho Teóphilo - O Legado de um Pioneiro     False  2015   \n",
+       "tt9916680  De la ilusión al desconcierto: cine colombiano...     False  2007   \n",
+       "tt9916706                                    Dankyavar Danka     False  2013   \n",
+       "tt9916730                                             6 Gunn     False  2017   \n",
+       "tt9916754                     Chico Albuquerque - Revelações     False  2013   \n",
+       "\n",
+       "           length                  genres  \n",
+       "tconst                                     \n",
+       "tt0000009      45                 Romance  \n",
+       "tt0000147      20  Documentary,News,Sport  \n",
+       "tt0000335    <NA>         Biography,Drama  \n",
+       "tt0000502     100                     NaN  \n",
+       "tt0000574      70   Biography,Crime,Drama  \n",
+       "...           ...                     ...  \n",
+       "tt9916622    <NA>             Documentary  \n",
+       "tt9916680     100             Documentary  \n",
+       "tt9916706    <NA>                  Comedy  \n",
+       "tt9916730     116                     NaN  \n",
+       "tt9916754    <NA>             Documentary  \n",
+       "\n",
+       "[514654 rows x 6 columns]"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "movies = (\n",
+    "    imdb_titles\n",
+    "    .query(\"title_type == 'movie'\")\n",
+    "    .drop([\"title_type\", \"end_year\"], axis=\"columns\")\n",
+    "    .rename({\"start_year\": \"year\"}, axis=\"columns\")\n",
+    ")\n",
+    "movies"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(514654, 6)\n",
+      "title             object\n",
+      "original_title    object\n",
+      "is_adult            bool\n",
+      "year               Int64\n",
+      "length             Int64\n",
+      "genres            object\n",
+      "dtype: object\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(movies.shape)\n",
+    "print(movies.dtypes)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Nyní se podíváme na zoubek hodnocením z IMDb, na tabulky `imdb_ratings_raw`:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>tconst</th>\n",
+       "      <th>averageRating</th>\n",
+       "      <th>numVotes</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>tt0000001</td>\n",
+       "      <td>5.8</td>\n",
+       "      <td>1486</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>tt0000002</td>\n",
+       "      <td>6.4</td>\n",
+       "      <td>179</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>tt0000003</td>\n",
+       "      <td>6.6</td>\n",
+       "      <td>1117</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>tt0000004</td>\n",
+       "      <td>6.4</td>\n",
+       "      <td>109</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>tt0000005</td>\n",
+       "      <td>6.2</td>\n",
+       "      <td>1820</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>923691</th>\n",
+       "      <td>tt9916380</td>\n",
+       "      <td>9.7</td>\n",
+       "      <td>58</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>923692</th>\n",
+       "      <td>tt9916420</td>\n",
+       "      <td>7.0</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>923693</th>\n",
+       "      <td>tt9916460</td>\n",
+       "      <td>9.2</td>\n",
+       "      <td>12</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>923694</th>\n",
+       "      <td>tt9916720</td>\n",
+       "      <td>5.2</td>\n",
+       "      <td>11</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>923695</th>\n",
+       "      <td>tt9916766</td>\n",
+       "      <td>7.2</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>923696 rows × 3 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "           tconst  averageRating  numVotes\n",
+       "0       tt0000001            5.8      1486\n",
+       "1       tt0000002            6.4       179\n",
+       "2       tt0000003            6.6      1117\n",
+       "3       tt0000004            6.4       109\n",
+       "4       tt0000005            6.2      1820\n",
+       "...           ...            ...       ...\n",
+       "923691  tt9916380            9.7        58\n",
+       "923692  tt9916420            7.0         5\n",
+       "923693  tt9916460            9.2        12\n",
+       "923694  tt9916720            5.2        11\n",
+       "923695  tt9916766            7.2         5\n",
+       "\n",
+       "[923696 rows x 3 columns]"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "imdb_ratings_raw"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "tconst            object\n",
+       "averageRating    float64\n",
+       "numVotes           int64\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "imdb_ratings_raw.dtypes"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "To by vlastně skoro mohlo být!\n",
+    "\n",
+    "Tak jen nastavíme index (opět `tconst`) a přejmenujeme sloupce:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>imdb_rating</th>\n",
+       "      <th>imdb_votes</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tconst</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>tt0000001</th>\n",
+       "      <td>5.8</td>\n",
+       "      <td>1486</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt0000002</th>\n",
+       "      <td>6.4</td>\n",
+       "      <td>179</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt0000003</th>\n",
+       "      <td>6.6</td>\n",
+       "      <td>1117</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt0000004</th>\n",
+       "      <td>6.4</td>\n",
+       "      <td>109</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt0000005</th>\n",
+       "      <td>6.2</td>\n",
+       "      <td>1820</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt9916380</th>\n",
+       "      <td>9.7</td>\n",
+       "      <td>58</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt9916420</th>\n",
+       "      <td>7.0</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt9916460</th>\n",
+       "      <td>9.2</td>\n",
+       "      <td>12</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt9916720</th>\n",
+       "      <td>5.2</td>\n",
+       "      <td>11</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt9916766</th>\n",
+       "      <td>7.2</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>923696 rows × 2 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "           imdb_rating  imdb_votes\n",
+       "tconst                            \n",
+       "tt0000001          5.8        1486\n",
+       "tt0000002          6.4         179\n",
+       "tt0000003          6.6        1117\n",
+       "tt0000004          6.4         109\n",
+       "tt0000005          6.2        1820\n",
+       "...                ...         ...\n",
+       "tt9916380          9.7          58\n",
+       "tt9916420          7.0           5\n",
+       "tt9916460          9.2          12\n",
+       "tt9916720          5.2          11\n",
+       "tt9916766          7.2           5\n",
+       "\n",
+       "[923696 rows x 2 columns]"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ratings = (imdb_ratings_raw\n",
+    "    .rename({\n",
+    "        \"averageRating\": \"imdb_rating\",\n",
+    "        \"numVotes\": \"imdb_votes\"\n",
+    "    }, axis=\"columns\")\n",
+    "    .set_index(\"tconst\")\n",
+    ")\n",
+    "ratings"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### První join\n",
+    "\n",
+    "Máme připravené dvě krásné tabulky, které sdílejí stejný index, a můžeme vesele spojovat. Protože pomocí `join`, `merge` a `concat` lze volbou vhodných parametrů dosáhnout identického výsledku (což je jedním z nešvarů knihovny `pandas`), ukážeme si všechny tři alternativy podle subjektivního pořadí vhodnosti."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>title</th>\n",
+       "      <th>original_title</th>\n",
+       "      <th>is_adult</th>\n",
+       "      <th>year</th>\n",
+       "      <th>length</th>\n",
+       "      <th>genres</th>\n",
+       "      <th>imdb_rating</th>\n",
+       "      <th>imdb_votes</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tconst</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>tt0000009</th>\n",
+       "      <td>Miss Jerry</td>\n",
+       "      <td>Miss Jerry</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1894</td>\n",
+       "      <td>45</td>\n",
+       "      <td>Romance</td>\n",
+       "      <td>5.5</td>\n",
+       "      <td>77.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt0000147</th>\n",
+       "      <td>The Corbett-Fitzsimmons Fight</td>\n",
+       "      <td>The Corbett-Fitzsimmons Fight</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1897</td>\n",
+       "      <td>20</td>\n",
+       "      <td>Documentary,News,Sport</td>\n",
+       "      <td>5.2</td>\n",
+       "      <td>289.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt0000335</th>\n",
+       "      <td>Soldiers of the Cross</td>\n",
+       "      <td>Soldiers of the Cross</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1900</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>Biography,Drama</td>\n",
+       "      <td>6.3</td>\n",
+       "      <td>39.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt0000502</th>\n",
+       "      <td>Bohemios</td>\n",
+       "      <td>Bohemios</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1905</td>\n",
+       "      <td>100</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt0000574</th>\n",
+       "      <td>The Story of the Kelly Gang</td>\n",
+       "      <td>The Story of the Kelly Gang</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1906</td>\n",
+       "      <td>70</td>\n",
+       "      <td>Biography,Crime,Drama</td>\n",
+       "      <td>6.2</td>\n",
+       "      <td>505.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt9916622</th>\n",
+       "      <td>Rodolpho Teóphilo - O Legado de um Pioneiro</td>\n",
+       "      <td>Rodolpho Teóphilo - O Legado de um Pioneiro</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2015</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>Documentary</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt9916680</th>\n",
+       "      <td>De la ilusión al desconcierto: cine colombiano...</td>\n",
+       "      <td>De la ilusión al desconcierto: cine colombiano...</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2007</td>\n",
+       "      <td>100</td>\n",
+       "      <td>Documentary</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt9916706</th>\n",
+       "      <td>Dankyavar Danka</td>\n",
+       "      <td>Dankyavar Danka</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2013</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>Comedy</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt9916730</th>\n",
+       "      <td>6 Gunn</td>\n",
+       "      <td>6 Gunn</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>116</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt9916754</th>\n",
+       "      <td>Chico Albuquerque - Revelações</td>\n",
+       "      <td>Chico Albuquerque - Revelações</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2013</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>Documentary</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>514654 rows × 8 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                                       title  \\\n",
+       "tconst                                                         \n",
+       "tt0000009                                         Miss Jerry   \n",
+       "tt0000147                      The Corbett-Fitzsimmons Fight   \n",
+       "tt0000335                              Soldiers of the Cross   \n",
+       "tt0000502                                           Bohemios   \n",
+       "tt0000574                        The Story of the Kelly Gang   \n",
+       "...                                                      ...   \n",
+       "tt9916622        Rodolpho Teóphilo - O Legado de um Pioneiro   \n",
+       "tt9916680  De la ilusión al desconcierto: cine colombiano...   \n",
+       "tt9916706                                    Dankyavar Danka   \n",
+       "tt9916730                                             6 Gunn   \n",
+       "tt9916754                     Chico Albuquerque - Revelações   \n",
+       "\n",
+       "                                              original_title  is_adult  year  \\\n",
+       "tconst                                                                         \n",
+       "tt0000009                                         Miss Jerry     False  1894   \n",
+       "tt0000147                      The Corbett-Fitzsimmons Fight     False  1897   \n",
+       "tt0000335                              Soldiers of the Cross     False  1900   \n",
+       "tt0000502                                           Bohemios     False  1905   \n",
+       "tt0000574                        The Story of the Kelly Gang     False  1906   \n",
+       "...                                                      ...       ...   ...   \n",
+       "tt9916622        Rodolpho Teóphilo - O Legado de um Pioneiro     False  2015   \n",
+       "tt9916680  De la ilusión al desconcierto: cine colombiano...     False  2007   \n",
+       "tt9916706                                    Dankyavar Danka     False  2013   \n",
+       "tt9916730                                             6 Gunn     False  2017   \n",
+       "tt9916754                     Chico Albuquerque - Revelações     False  2013   \n",
+       "\n",
+       "           length                  genres  imdb_rating  imdb_votes  \n",
+       "tconst                                                              \n",
+       "tt0000009      45                 Romance          5.5        77.0  \n",
+       "tt0000147      20  Documentary,News,Sport          5.2       289.0  \n",
+       "tt0000335    <NA>         Biography,Drama          6.3        39.0  \n",
+       "tt0000502     100                     NaN          NaN         NaN  \n",
+       "tt0000574      70   Biography,Crime,Drama          6.2       505.0  \n",
+       "...           ...                     ...          ...         ...  \n",
+       "tt9916622    <NA>             Documentary          NaN         NaN  \n",
+       "tt9916680     100             Documentary          NaN         NaN  \n",
+       "tt9916706    <NA>                  Comedy          NaN         NaN  \n",
+       "tt9916730     116                     NaN          NaN         NaN  \n",
+       "tt9916754    <NA>             Documentary          NaN         NaN  \n",
+       "\n",
+       "[514654 rows x 8 columns]"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "movies.join(ratings)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "K tabulce se nenápadně přidaly dva sloupce z tabulky `ratings`, a to takovým způsobem, že se porovnaly hodnoty indexu (tedy `tconst`) a spárovaly se ty části řádku, kde se tento index shoduje.\n",
+    "\n",
+    "💡 Uvědom si (ačkoliv z volání funkcí v `pandas` to není úplně zřejmé), že se tady děje něco fundamentálně odlišného od \"nalepení doprava\" - tabulky tu nejsou chápány jako čtverečky, které jde skládat jako lego, nýbrž jako zdroj údajů o jednotlivých objektech, které je potřeba spojit sémanticky.\n",
+    "\n",
+    "Jak ale vidíš, tabulka obsahuje spoustu řádků, kde ve sloupcích s hodnocením chybí hodnoty (respektive nachází se `NaN`). To vychází ze způsobu, jakým metoda `join` ve výchozím nastavení \"joinuje\" - použije všechny řádky z levé tabulky bez ohledu na to, jestli jim odpovídá nějaký protějšek v tabulce pravé. Naštěstí lze pomocí argumentu `how` specifikovat i jiné způsoby spojování:\n",
+    "\n",
+    "- `left` (výchozí pro metodu `join`) - vezmou se všechny prvky z levé tabulky a jim odpovídající prvky z pravé tabulky (kde nejsou, doplní se `NaN`)\n",
+    "- `right` - vezmou se všechny prvky z pravé tabulky a jim odpovídající prvky z levé tabulky (kde nejsou, doplní se `NaN`)\n",
+    "- `inner` (výchozí pro funkci `merge`) - vezmou se jen ty prvky, které jsou v levé i pravé tabulce.\n",
+    "- `outer` (výchozí pro funkci `concat`) - vezmou se všechny prvky, z levé i pravé tabulky, kde něco chybí, doplní se `NaN`.\n",
+    "\n",
+    "V podobě Vennově diagramu, kde kruhy představují množiny řádků v obou zdrojových tabulkách a modrou barvou jsou zvýrazněny řádky v tabulce cílové:\n",
+    "\n",
+    "![Typy joinů](static/joins.svg)\n",
+    "\n",
+    "*Obrázek adaptován z https://upload.wikimedia.org/wikipedia/commons/9/9d/SQL_Joins.svg (autor: Arbeck)*\n",
+    "\n",
+    "💡 Až budeme probírat databáze, tyto čtyři typu joinů se nám znovu vynoří.\n",
+    "\n",
+    "Následující výpis ukáže, kolik řádků bychom dostali při použití různých hodnot `how`:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "movies.join(ratings, how=\"left\"): 514654 řádků.\n",
+      "movies.join(ratings, how=\"right\"): 923696 řádků.\n",
+      "movies.join(ratings, how=\"inner\"): 232496 řádků.\n",
+      "movies.join(ratings, how=\"outer\"): 1205854 řádků.\n"
+     ]
+    }
+   ],
+   "source": [
+    "for how in [\"left\", \"right\", \"inner\", \"outer\"]:\n",
+    "    print(f\"movies.join(ratings, how=\\\"{how}\\\"):\", movies.join(ratings, how=how).shape[0], \"řádků.\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "A teď tedy ty tři alternativy:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>title</th>\n",
+       "      <th>original_title</th>\n",
+       "      <th>is_adult</th>\n",
+       "      <th>year</th>\n",
+       "      <th>length</th>\n",
+       "      <th>genres</th>\n",
+       "      <th>imdb_rating</th>\n",
+       "      <th>imdb_votes</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tconst</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>tt0000009</th>\n",
+       "      <td>Miss Jerry</td>\n",
+       "      <td>Miss Jerry</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1894</td>\n",
+       "      <td>45</td>\n",
+       "      <td>Romance</td>\n",
+       "      <td>5.5</td>\n",
+       "      <td>77</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt0000147</th>\n",
+       "      <td>The Corbett-Fitzsimmons Fight</td>\n",
+       "      <td>The Corbett-Fitzsimmons Fight</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1897</td>\n",
+       "      <td>20</td>\n",
+       "      <td>Documentary,News,Sport</td>\n",
+       "      <td>5.2</td>\n",
+       "      <td>289</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt0000335</th>\n",
+       "      <td>Soldiers of the Cross</td>\n",
+       "      <td>Soldiers of the Cross</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1900</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>Biography,Drama</td>\n",
+       "      <td>6.3</td>\n",
+       "      <td>39</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt0000574</th>\n",
+       "      <td>The Story of the Kelly Gang</td>\n",
+       "      <td>The Story of the Kelly Gang</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1906</td>\n",
+       "      <td>70</td>\n",
+       "      <td>Biography,Crime,Drama</td>\n",
+       "      <td>6.2</td>\n",
+       "      <td>505</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt0000615</th>\n",
+       "      <td>Robbery Under Arms</td>\n",
+       "      <td>Robbery Under Arms</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1907</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>Drama</td>\n",
+       "      <td>4.8</td>\n",
+       "      <td>14</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt9910930</th>\n",
+       "      <td>Jeg ser deg</td>\n",
+       "      <td>Jeg ser deg</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>75</td>\n",
+       "      <td>Crime,Documentary</td>\n",
+       "      <td>4.6</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt9911774</th>\n",
+       "      <td>Padmavyuhathile Abhimanyu</td>\n",
+       "      <td>Padmavyuhathile Abhimanyu</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>130</td>\n",
+       "      <td>Drama</td>\n",
+       "      <td>8.5</td>\n",
+       "      <td>363</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt9913056</th>\n",
+       "      <td>Swarm Season</td>\n",
+       "      <td>Swarm Season</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>86</td>\n",
+       "      <td>Documentary</td>\n",
+       "      <td>6.2</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt9913084</th>\n",
+       "      <td>Diabolik sono io</td>\n",
+       "      <td>Diabolik sono io</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>75</td>\n",
+       "      <td>Documentary</td>\n",
+       "      <td>6.2</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt9914286</th>\n",
+       "      <td>Sokagin Çocuklari</td>\n",
+       "      <td>Sokagin Çocuklari</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>98</td>\n",
+       "      <td>Drama,Family</td>\n",
+       "      <td>9.8</td>\n",
+       "      <td>72</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>232496 rows × 8 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                   title                 original_title  \\\n",
+       "tconst                                                                    \n",
+       "tt0000009                     Miss Jerry                     Miss Jerry   \n",
+       "tt0000147  The Corbett-Fitzsimmons Fight  The Corbett-Fitzsimmons Fight   \n",
+       "tt0000335          Soldiers of the Cross          Soldiers of the Cross   \n",
+       "tt0000574    The Story of the Kelly Gang    The Story of the Kelly Gang   \n",
+       "tt0000615             Robbery Under Arms             Robbery Under Arms   \n",
+       "...                                  ...                            ...   \n",
+       "tt9910930                    Jeg ser deg                    Jeg ser deg   \n",
+       "tt9911774      Padmavyuhathile Abhimanyu      Padmavyuhathile Abhimanyu   \n",
+       "tt9913056                   Swarm Season                   Swarm Season   \n",
+       "tt9913084               Diabolik sono io               Diabolik sono io   \n",
+       "tt9914286              Sokagin Çocuklari              Sokagin Çocuklari   \n",
+       "\n",
+       "           is_adult  year  length                  genres  imdb_rating  \\\n",
+       "tconst                                                                   \n",
+       "tt0000009     False  1894      45                 Romance          5.5   \n",
+       "tt0000147     False  1897      20  Documentary,News,Sport          5.2   \n",
+       "tt0000335     False  1900    <NA>         Biography,Drama          6.3   \n",
+       "tt0000574     False  1906      70   Biography,Crime,Drama          6.2   \n",
+       "tt0000615     False  1907    <NA>                   Drama          4.8   \n",
+       "...             ...   ...     ...                     ...          ...   \n",
+       "tt9910930     False  2019      75       Crime,Documentary          4.6   \n",
+       "tt9911774     False  2019     130                   Drama          8.5   \n",
+       "tt9913056     False  2019      86             Documentary          6.2   \n",
+       "tt9913084     False  2019      75             Documentary          6.2   \n",
+       "tt9914286     False  2019      98            Drama,Family          9.8   \n",
+       "\n",
+       "           imdb_votes  \n",
+       "tconst                 \n",
+       "tt0000009          77  \n",
+       "tt0000147         289  \n",
+       "tt0000335          39  \n",
+       "tt0000574         505  \n",
+       "tt0000615          14  \n",
+       "...               ...  \n",
+       "tt9910930           5  \n",
+       "tt9911774         363  \n",
+       "tt9913056           5  \n",
+       "tt9913084           6  \n",
+       "tt9914286          72  \n",
+       "\n",
+       "[232496 rows x 8 columns]"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Alternativa 1 (preferovaná)\n",
+    "movies_with_rating = movies.join(ratings, how=\"inner\")\n",
+    "movies_with_rating"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>title</th>\n",
+       "      <th>original_title</th>\n",
+       "      <th>is_adult</th>\n",
+       "      <th>year</th>\n",
+       "      <th>length</th>\n",
+       "      <th>genres</th>\n",
+       "      <th>imdb_rating</th>\n",
+       "      <th>imdb_votes</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tconst</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>tt0000009</th>\n",
+       "      <td>Miss Jerry</td>\n",
+       "      <td>Miss Jerry</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1894</td>\n",
+       "      <td>45</td>\n",
+       "      <td>Romance</td>\n",
+       "      <td>5.5</td>\n",
+       "      <td>77</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt0000147</th>\n",
+       "      <td>The Corbett-Fitzsimmons Fight</td>\n",
+       "      <td>The Corbett-Fitzsimmons Fight</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1897</td>\n",
+       "      <td>20</td>\n",
+       "      <td>Documentary,News,Sport</td>\n",
+       "      <td>5.2</td>\n",
+       "      <td>289</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt0000335</th>\n",
+       "      <td>Soldiers of the Cross</td>\n",
+       "      <td>Soldiers of the Cross</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1900</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>Biography,Drama</td>\n",
+       "      <td>6.3</td>\n",
+       "      <td>39</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt0000574</th>\n",
+       "      <td>The Story of the Kelly Gang</td>\n",
+       "      <td>The Story of the Kelly Gang</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1906</td>\n",
+       "      <td>70</td>\n",
+       "      <td>Biography,Crime,Drama</td>\n",
+       "      <td>6.2</td>\n",
+       "      <td>505</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt0000615</th>\n",
+       "      <td>Robbery Under Arms</td>\n",
+       "      <td>Robbery Under Arms</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1907</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>Drama</td>\n",
+       "      <td>4.8</td>\n",
+       "      <td>14</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt9910930</th>\n",
+       "      <td>Jeg ser deg</td>\n",
+       "      <td>Jeg ser deg</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>75</td>\n",
+       "      <td>Crime,Documentary</td>\n",
+       "      <td>4.6</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt9911774</th>\n",
+       "      <td>Padmavyuhathile Abhimanyu</td>\n",
+       "      <td>Padmavyuhathile Abhimanyu</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>130</td>\n",
+       "      <td>Drama</td>\n",
+       "      <td>8.5</td>\n",
+       "      <td>363</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt9913056</th>\n",
+       "      <td>Swarm Season</td>\n",
+       "      <td>Swarm Season</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>86</td>\n",
+       "      <td>Documentary</td>\n",
+       "      <td>6.2</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt9913084</th>\n",
+       "      <td>Diabolik sono io</td>\n",
+       "      <td>Diabolik sono io</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>75</td>\n",
+       "      <td>Documentary</td>\n",
+       "      <td>6.2</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt9914286</th>\n",
+       "      <td>Sokagin Çocuklari</td>\n",
+       "      <td>Sokagin Çocuklari</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>98</td>\n",
+       "      <td>Drama,Family</td>\n",
+       "      <td>9.8</td>\n",
+       "      <td>72</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>232496 rows × 8 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                   title                 original_title  \\\n",
+       "tconst                                                                    \n",
+       "tt0000009                     Miss Jerry                     Miss Jerry   \n",
+       "tt0000147  The Corbett-Fitzsimmons Fight  The Corbett-Fitzsimmons Fight   \n",
+       "tt0000335          Soldiers of the Cross          Soldiers of the Cross   \n",
+       "tt0000574    The Story of the Kelly Gang    The Story of the Kelly Gang   \n",
+       "tt0000615             Robbery Under Arms             Robbery Under Arms   \n",
+       "...                                  ...                            ...   \n",
+       "tt9910930                    Jeg ser deg                    Jeg ser deg   \n",
+       "tt9911774      Padmavyuhathile Abhimanyu      Padmavyuhathile Abhimanyu   \n",
+       "tt9913056                   Swarm Season                   Swarm Season   \n",
+       "tt9913084               Diabolik sono io               Diabolik sono io   \n",
+       "tt9914286              Sokagin Çocuklari              Sokagin Çocuklari   \n",
+       "\n",
+       "           is_adult  year  length                  genres  imdb_rating  \\\n",
+       "tconst                                                                   \n",
+       "tt0000009     False  1894      45                 Romance          5.5   \n",
+       "tt0000147     False  1897      20  Documentary,News,Sport          5.2   \n",
+       "tt0000335     False  1900    <NA>         Biography,Drama          6.3   \n",
+       "tt0000574     False  1906      70   Biography,Crime,Drama          6.2   \n",
+       "tt0000615     False  1907    <NA>                   Drama          4.8   \n",
+       "...             ...   ...     ...                     ...          ...   \n",
+       "tt9910930     False  2019      75       Crime,Documentary          4.6   \n",
+       "tt9911774     False  2019     130                   Drama          8.5   \n",
+       "tt9913056     False  2019      86             Documentary          6.2   \n",
+       "tt9913084     False  2019      75             Documentary          6.2   \n",
+       "tt9914286     False  2019      98            Drama,Family          9.8   \n",
+       "\n",
+       "           imdb_votes  \n",
+       "tconst                 \n",
+       "tt0000009          77  \n",
+       "tt0000147         289  \n",
+       "tt0000335          39  \n",
+       "tt0000574         505  \n",
+       "tt0000615          14  \n",
+       "...               ...  \n",
+       "tt9910930           5  \n",
+       "tt9911774         363  \n",
+       "tt9913056           5  \n",
+       "tt9913084           6  \n",
+       "tt9914286          72  \n",
+       "\n",
+       "[232496 rows x 8 columns]"
+      ]
+     },
+     "execution_count": 26,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Alternativa 2 (taky dobrá)\n",
+    "pd.merge(movies, ratings, left_index=True, right_index=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>title</th>\n",
+       "      <th>original_title</th>\n",
+       "      <th>is_adult</th>\n",
+       "      <th>year</th>\n",
+       "      <th>length</th>\n",
+       "      <th>genres</th>\n",
+       "      <th>imdb_rating</th>\n",
+       "      <th>imdb_votes</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tconst</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>tt0000009</th>\n",
+       "      <td>Miss Jerry</td>\n",
+       "      <td>Miss Jerry</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1894</td>\n",
+       "      <td>45</td>\n",
+       "      <td>Romance</td>\n",
+       "      <td>5.5</td>\n",
+       "      <td>77</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt0000147</th>\n",
+       "      <td>The Corbett-Fitzsimmons Fight</td>\n",
+       "      <td>The Corbett-Fitzsimmons Fight</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1897</td>\n",
+       "      <td>20</td>\n",
+       "      <td>Documentary,News,Sport</td>\n",
+       "      <td>5.2</td>\n",
+       "      <td>289</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt0000335</th>\n",
+       "      <td>Soldiers of the Cross</td>\n",
+       "      <td>Soldiers of the Cross</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1900</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>Biography,Drama</td>\n",
+       "      <td>6.3</td>\n",
+       "      <td>39</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt0000574</th>\n",
+       "      <td>The Story of the Kelly Gang</td>\n",
+       "      <td>The Story of the Kelly Gang</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1906</td>\n",
+       "      <td>70</td>\n",
+       "      <td>Biography,Crime,Drama</td>\n",
+       "      <td>6.2</td>\n",
+       "      <td>505</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt0000615</th>\n",
+       "      <td>Robbery Under Arms</td>\n",
+       "      <td>Robbery Under Arms</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1907</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>Drama</td>\n",
+       "      <td>4.8</td>\n",
+       "      <td>14</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt9910930</th>\n",
+       "      <td>Jeg ser deg</td>\n",
+       "      <td>Jeg ser deg</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>75</td>\n",
+       "      <td>Crime,Documentary</td>\n",
+       "      <td>4.6</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt9911774</th>\n",
+       "      <td>Padmavyuhathile Abhimanyu</td>\n",
+       "      <td>Padmavyuhathile Abhimanyu</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>130</td>\n",
+       "      <td>Drama</td>\n",
+       "      <td>8.5</td>\n",
+       "      <td>363</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt9913056</th>\n",
+       "      <td>Swarm Season</td>\n",
+       "      <td>Swarm Season</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>86</td>\n",
+       "      <td>Documentary</td>\n",
+       "      <td>6.2</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt9913084</th>\n",
+       "      <td>Diabolik sono io</td>\n",
+       "      <td>Diabolik sono io</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>75</td>\n",
+       "      <td>Documentary</td>\n",
+       "      <td>6.2</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tt9914286</th>\n",
+       "      <td>Sokagin Çocuklari</td>\n",
+       "      <td>Sokagin Çocuklari</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>98</td>\n",
+       "      <td>Drama,Family</td>\n",
+       "      <td>9.8</td>\n",
+       "      <td>72</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>232496 rows × 8 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                   title                 original_title  \\\n",
+       "tconst                                                                    \n",
+       "tt0000009                     Miss Jerry                     Miss Jerry   \n",
+       "tt0000147  The Corbett-Fitzsimmons Fight  The Corbett-Fitzsimmons Fight   \n",
+       "tt0000335          Soldiers of the Cross          Soldiers of the Cross   \n",
+       "tt0000574    The Story of the Kelly Gang    The Story of the Kelly Gang   \n",
+       "tt0000615             Robbery Under Arms             Robbery Under Arms   \n",
+       "...                                  ...                            ...   \n",
+       "tt9910930                    Jeg ser deg                    Jeg ser deg   \n",
+       "tt9911774      Padmavyuhathile Abhimanyu      Padmavyuhathile Abhimanyu   \n",
+       "tt9913056                   Swarm Season                   Swarm Season   \n",
+       "tt9913084               Diabolik sono io               Diabolik sono io   \n",
+       "tt9914286              Sokagin Çocuklari              Sokagin Çocuklari   \n",
+       "\n",
+       "           is_adult  year  length                  genres  imdb_rating  \\\n",
+       "tconst                                                                   \n",
+       "tt0000009     False  1894      45                 Romance          5.5   \n",
+       "tt0000147     False  1897      20  Documentary,News,Sport          5.2   \n",
+       "tt0000335     False  1900    <NA>         Biography,Drama          6.3   \n",
+       "tt0000574     False  1906      70   Biography,Crime,Drama          6.2   \n",
+       "tt0000615     False  1907    <NA>                   Drama          4.8   \n",
+       "...             ...   ...     ...                     ...          ...   \n",
+       "tt9910930     False  2019      75       Crime,Documentary          4.6   \n",
+       "tt9911774     False  2019     130                   Drama          8.5   \n",
+       "tt9913056     False  2019      86             Documentary          6.2   \n",
+       "tt9913084     False  2019      75             Documentary          6.2   \n",
+       "tt9914286     False  2019      98            Drama,Family          9.8   \n",
+       "\n",
+       "           imdb_votes  \n",
+       "tconst                 \n",
+       "tt0000009          77  \n",
+       "tt0000147         289  \n",
+       "tt0000335          39  \n",
+       "tt0000574         505  \n",
+       "tt0000615          14  \n",
+       "...               ...  \n",
+       "tt9910930           5  \n",
+       "tt9911774         363  \n",
+       "tt9913056           5  \n",
+       "tt9913084           6  \n",
+       "tt9914286          72  \n",
+       "\n",
+       "[232496 rows x 8 columns]"
+      ]
+     },
+     "execution_count": 27,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Alternativa 3 (méně \"sémantická\")\n",
+    "pd.concat([movies, ratings], axis=\"columns\", join=\"inner\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Zkusme si zreprodukovat pořadí 250 nejlepších filmů z IMDb (viz https://www.imdb.com/chart/top/?ref_=nv_mv_250):"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>title</th>\n",
+       "      <th>original_title</th>\n",
+       "      <th>is_adult</th>\n",
+       "      <th>year</th>\n",
+       "      <th>length</th>\n",
+       "      <th>genres</th>\n",
+       "      <th>imdb_rating</th>\n",
+       "      <th>imdb_votes</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>The Chaos Class</td>\n",
+       "      <td>Hababam Sinifi</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1975</td>\n",
+       "      <td>87</td>\n",
+       "      <td>Comedy,Drama</td>\n",
+       "      <td>9.4</td>\n",
+       "      <td>33394</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>The Shawshank Redemption</td>\n",
+       "      <td>The Shawshank Redemption</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1994</td>\n",
+       "      <td>142</td>\n",
+       "      <td>Drama</td>\n",
+       "      <td>9.3</td>\n",
+       "      <td>2071759</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>The Mountain II</td>\n",
+       "      <td>Dag II</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2016</td>\n",
+       "      <td>135</td>\n",
+       "      <td>Action,Drama,War</td>\n",
+       "      <td>9.3</td>\n",
+       "      <td>100095</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>CM101MMXI Fundamentals</td>\n",
+       "      <td>CM101MMXI Fundamentals</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2013</td>\n",
+       "      <td>139</td>\n",
+       "      <td>Comedy,Documentary</td>\n",
+       "      <td>9.2</td>\n",
+       "      <td>41327</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>The Godfather</td>\n",
+       "      <td>The Godfather</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1972</td>\n",
+       "      <td>175</td>\n",
+       "      <td>Crime,Drama</td>\n",
+       "      <td>9.2</td>\n",
+       "      <td>1421495</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>245</th>\n",
+       "      <td>12 Years a Slave</td>\n",
+       "      <td>12 Years a Slave</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2013</td>\n",
+       "      <td>134</td>\n",
+       "      <td>Biography,Drama,History</td>\n",
+       "      <td>8.1</td>\n",
+       "      <td>571204</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>246</th>\n",
+       "      <td>The Sixth Sense</td>\n",
+       "      <td>The Sixth Sense</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1999</td>\n",
+       "      <td>107</td>\n",
+       "      <td>Drama,Mystery,Thriller</td>\n",
+       "      <td>8.1</td>\n",
+       "      <td>836928</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>247</th>\n",
+       "      <td>The Passion of Joan of Arc</td>\n",
+       "      <td>La passion de Jeanne d'Arc</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1928</td>\n",
+       "      <td>110</td>\n",
+       "      <td>Biography,Drama,History</td>\n",
+       "      <td>8.1</td>\n",
+       "      <td>40107</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>248</th>\n",
+       "      <td>Barfi!</td>\n",
+       "      <td>Barfi!</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>151</td>\n",
+       "      <td>Comedy,Drama,Romance</td>\n",
+       "      <td>8.1</td>\n",
+       "      <td>68274</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>249</th>\n",
+       "      <td>Platoon</td>\n",
+       "      <td>Platoon</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1986</td>\n",
+       "      <td>120</td>\n",
+       "      <td>Drama,War</td>\n",
+       "      <td>8.1</td>\n",
+       "      <td>348628</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>250 rows × 8 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                          title              original_title  is_adult  year  \\\n",
+       "0               The Chaos Class              Hababam Sinifi     False  1975   \n",
+       "1      The Shawshank Redemption    The Shawshank Redemption     False  1994   \n",
+       "2               The Mountain II                      Dag II     False  2016   \n",
+       "3        CM101MMXI Fundamentals      CM101MMXI Fundamentals     False  2013   \n",
+       "4                 The Godfather               The Godfather     False  1972   \n",
+       "..                          ...                         ...       ...   ...   \n",
+       "245            12 Years a Slave            12 Years a Slave     False  2013   \n",
+       "246             The Sixth Sense             The Sixth Sense     False  1999   \n",
+       "247  The Passion of Joan of Arc  La passion de Jeanne d'Arc     False  1928   \n",
+       "248                      Barfi!                      Barfi!     False  2012   \n",
+       "249                     Platoon                     Platoon     False  1986   \n",
+       "\n",
+       "     length                   genres  imdb_rating  imdb_votes  \n",
+       "0        87             Comedy,Drama          9.4       33394  \n",
+       "1       142                    Drama          9.3     2071759  \n",
+       "2       135         Action,Drama,War          9.3      100095  \n",
+       "3       139       Comedy,Documentary          9.2       41327  \n",
+       "4       175              Crime,Drama          9.2     1421495  \n",
+       "..      ...                      ...          ...         ...  \n",
+       "245     134  Biography,Drama,History          8.1      571204  \n",
+       "246     107   Drama,Mystery,Thriller          8.1      836928  \n",
+       "247     110  Biography,Drama,History          8.1       40107  \n",
+       "248     151     Comedy,Drama,Romance          8.1       68274  \n",
+       "249     120                Drama,War          8.1      348628  \n",
+       "\n",
+       "[250 rows x 8 columns]"
+      ]
+     },
+     "execution_count": 28,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Ty nejlepší (do června 2019)\n",
+    "(movies_with_rating\n",
+    "    .query(\"imdb_votes > 25000\")                  # Berou se jen filmy s více než 25000 hlasy\n",
+    "    .sort_values(\"imdb_rating\", ascending=False)  # IMDb tu použivá i váhu jednotlivých hlasů (kterou neznáme)\n",
+    "    .reset_index(drop=True)\n",
+    ").iloc[:250]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Do výčtu se nám dostaly filmy, které hranici hlasů nepřekračují o moc. Máme důvodné podezření, že toto kritérium dávno změnili. S požadovanými 250 000 hlasy se už blížíme:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>title</th>\n",
+       "      <th>original_title</th>\n",
+       "      <th>is_adult</th>\n",
+       "      <th>year</th>\n",
+       "      <th>length</th>\n",
+       "      <th>genres</th>\n",
+       "      <th>imdb_rating</th>\n",
+       "      <th>imdb_votes</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>The Shawshank Redemption</td>\n",
+       "      <td>The Shawshank Redemption</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1994</td>\n",
+       "      <td>142</td>\n",
+       "      <td>Drama</td>\n",
+       "      <td>9.3</td>\n",
+       "      <td>2071759</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>The Godfather</td>\n",
+       "      <td>The Godfather</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1972</td>\n",
+       "      <td>175</td>\n",
+       "      <td>Crime,Drama</td>\n",
+       "      <td>9.2</td>\n",
+       "      <td>1421495</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>The Dark Knight</td>\n",
+       "      <td>The Dark Knight</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2008</td>\n",
+       "      <td>152</td>\n",
+       "      <td>Action,Crime,Drama</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>2037678</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>The Godfather: Part II</td>\n",
+       "      <td>The Godfather: Part II</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1974</td>\n",
+       "      <td>202</td>\n",
+       "      <td>Crime,Drama</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>986451</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Pulp Fiction</td>\n",
+       "      <td>Pulp Fiction</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1994</td>\n",
+       "      <td>154</td>\n",
+       "      <td>Crime,Drama</td>\n",
+       "      <td>8.9</td>\n",
+       "      <td>1620135</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>245</th>\n",
+       "      <td>Ocean's Eleven</td>\n",
+       "      <td>Ocean's Eleven</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2001</td>\n",
+       "      <td>116</td>\n",
+       "      <td>Crime,Thriller</td>\n",
+       "      <td>7.8</td>\n",
+       "      <td>470530</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>246</th>\n",
+       "      <td>Lost in Translation</td>\n",
+       "      <td>Lost in Translation</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2003</td>\n",
+       "      <td>102</td>\n",
+       "      <td>Drama</td>\n",
+       "      <td>7.8</td>\n",
+       "      <td>371577</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>247</th>\n",
+       "      <td>Donnie Brasco</td>\n",
+       "      <td>Donnie Brasco</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1997</td>\n",
+       "      <td>127</td>\n",
+       "      <td>Biography,Crime,Drama</td>\n",
+       "      <td>7.8</td>\n",
+       "      <td>253811</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>248</th>\n",
+       "      <td>Captain Phillips</td>\n",
+       "      <td>Captain Phillips</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2013</td>\n",
+       "      <td>134</td>\n",
+       "      <td>Biography,Drama,Thriller</td>\n",
+       "      <td>7.8</td>\n",
+       "      <td>384378</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>249</th>\n",
+       "      <td>How to Train Your Dragon 2</td>\n",
+       "      <td>How to Train Your Dragon 2</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2014</td>\n",
+       "      <td>102</td>\n",
+       "      <td>Action,Adventure,Animation</td>\n",
+       "      <td>7.8</td>\n",
+       "      <td>273406</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>250 rows × 8 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                          title              original_title  is_adult  year  \\\n",
+       "0      The Shawshank Redemption    The Shawshank Redemption     False  1994   \n",
+       "1                 The Godfather               The Godfather     False  1972   \n",
+       "2               The Dark Knight             The Dark Knight     False  2008   \n",
+       "3        The Godfather: Part II      The Godfather: Part II     False  1974   \n",
+       "4                  Pulp Fiction                Pulp Fiction     False  1994   \n",
+       "..                          ...                         ...       ...   ...   \n",
+       "245              Ocean's Eleven              Ocean's Eleven     False  2001   \n",
+       "246         Lost in Translation         Lost in Translation     False  2003   \n",
+       "247               Donnie Brasco               Donnie Brasco     False  1997   \n",
+       "248            Captain Phillips            Captain Phillips     False  2013   \n",
+       "249  How to Train Your Dragon 2  How to Train Your Dragon 2     False  2014   \n",
+       "\n",
+       "     length                      genres  imdb_rating  imdb_votes  \n",
+       "0       142                       Drama          9.3     2071759  \n",
+       "1       175                 Crime,Drama          9.2     1421495  \n",
+       "2       152          Action,Crime,Drama          9.0     2037678  \n",
+       "3       202                 Crime,Drama          9.0      986451  \n",
+       "4       154                 Crime,Drama          8.9     1620135  \n",
+       "..      ...                         ...          ...         ...  \n",
+       "245     116              Crime,Thriller          7.8      470530  \n",
+       "246     102                       Drama          7.8      371577  \n",
+       "247     127       Biography,Crime,Drama          7.8      253811  \n",
+       "248     134    Biography,Drama,Thriller          7.8      384378  \n",
+       "249     102  Action,Adventure,Animation          7.8      273406  \n",
+       "\n",
+       "[250 rows x 8 columns]"
+      ]
+     },
+     "execution_count": 29,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "(movies_with_rating\n",
+    "    .query(\"imdb_votes > 250000\")\n",
+    "    .sort_values(\"imdb_rating\", ascending=False)\n",
+    "    .reset_index(drop=True)\n",
+    ").iloc[:250]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Druhý join\n",
+    "\n",
+    "Co tabulka s výdělky (`boxoffice_raw`)?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>rank</th>\n",
+       "      <th>title</th>\n",
+       "      <th>studio</th>\n",
+       "      <th>lifetime_gross</th>\n",
+       "      <th>year</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>Star Wars: The Force Awakens</td>\n",
+       "      <td>BV</td>\n",
+       "      <td>936662225</td>\n",
+       "      <td>2015</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>Avatar</td>\n",
+       "      <td>Fox</td>\n",
+       "      <td>760507625</td>\n",
+       "      <td>2009</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>Black Panther</td>\n",
+       "      <td>BV</td>\n",
+       "      <td>700059566</td>\n",
+       "      <td>2018</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>Avengers: Infinity War</td>\n",
+       "      <td>BV</td>\n",
+       "      <td>678815482</td>\n",
+       "      <td>2018</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>Titanic</td>\n",
+       "      <td>Par.</td>\n",
+       "      <td>659363944</td>\n",
+       "      <td>1997</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16262</th>\n",
+       "      <td>16263</td>\n",
+       "      <td>Dog Eat Dog</td>\n",
+       "      <td>IFC</td>\n",
+       "      <td>80</td>\n",
+       "      <td>2009</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16263</th>\n",
+       "      <td>16264</td>\n",
+       "      <td>Paranoid Girls</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>78</td>\n",
+       "      <td>2015</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16264</th>\n",
+       "      <td>16265</td>\n",
+       "      <td>Confession of a Child of the Century</td>\n",
+       "      <td>Cohen</td>\n",
+       "      <td>74</td>\n",
+       "      <td>2015</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16265</th>\n",
+       "      <td>16266</td>\n",
+       "      <td>Storage 24</td>\n",
+       "      <td>Magn.</td>\n",
+       "      <td>72</td>\n",
+       "      <td>2013</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16266</th>\n",
+       "      <td>16267</td>\n",
+       "      <td>Zyzzyx Road</td>\n",
+       "      <td>Reg.</td>\n",
+       "      <td>30</td>\n",
+       "      <td>2006</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>16267 rows × 5 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        rank                                 title studio  lifetime_gross  \\\n",
+       "0          1          Star Wars: The Force Awakens     BV       936662225   \n",
+       "1          2                                Avatar    Fox       760507625   \n",
+       "2          3                         Black Panther     BV       700059566   \n",
+       "3          4                Avengers: Infinity War     BV       678815482   \n",
+       "4          5                               Titanic   Par.       659363944   \n",
+       "...      ...                                   ...    ...             ...   \n",
+       "16262  16263                           Dog Eat Dog    IFC              80   \n",
+       "16263  16264                        Paranoid Girls    NaN              78   \n",
+       "16264  16265  Confession of a Child of the Century  Cohen              74   \n",
+       "16265  16266                            Storage 24  Magn.              72   \n",
+       "16266  16267                           Zyzzyx Road   Reg.              30   \n",
+       "\n",
+       "       year  \n",
+       "0      2015  \n",
+       "1      2009  \n",
+       "2      2018  \n",
+       "3      2018  \n",
+       "4      1997  \n",
+       "...     ...  \n",
+       "16262  2009  \n",
+       "16263  2015  \n",
+       "16264  2015  \n",
+       "16265  2013  \n",
+       "16266  2006  \n",
+       "\n",
+       "[16267 rows x 5 columns]"
+      ]
+     },
+     "execution_count": 30,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "boxoffice_raw"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "rank               int64\n",
+       "title             object\n",
+       "studio            object\n",
+       "lifetime_gross     int64\n",
+       "year               int64\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 31,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "boxoffice_raw.dtypes"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "S tím bychom v podstatně mohli být spokojení, jen přejmenujeme `rank`, abychom při joinování věděli, odkud daný sloupec pochází."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "boxoffice = (boxoffice_raw\n",
+    "    .rename({\n",
+    "        \"rank\": \"boxoffice_rank\"\n",
+    "    }, axis=\"columns\")\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "A zkusíme joinovat. V tomto případě se nemůžeme opřít o index (`boxoffice` pochází z jiného zdroje a o nějakém ID filmu z IMDb nemá ani tuchy), ale explicitně specifikujeme, který sloupec (či sloupce) se musí shodovat - na to slouží argument `on`:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>title</th>\n",
+       "      <th>original_title</th>\n",
+       "      <th>is_adult</th>\n",
+       "      <th>year (imdb)</th>\n",
+       "      <th>length</th>\n",
+       "      <th>genres</th>\n",
+       "      <th>imdb_rating</th>\n",
+       "      <th>imdb_votes</th>\n",
+       "      <th>boxoffice_rank</th>\n",
+       "      <th>studio</th>\n",
+       "      <th>lifetime_gross</th>\n",
+       "      <th>year (boxoffice)</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1643</th>\n",
+       "      <td>Pinocchio</td>\n",
+       "      <td>Pinocchio</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1940</td>\n",
+       "      <td>88</td>\n",
+       "      <td>Animation,Comedy,Family</td>\n",
+       "      <td>7.5</td>\n",
+       "      <td>114689</td>\n",
+       "      <td>885</td>\n",
+       "      <td>Dis.</td>\n",
+       "      <td>84254167</td>\n",
+       "      <td>1940</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1644</th>\n",
+       "      <td>Pinocchio</td>\n",
+       "      <td>Pinocchio</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1940</td>\n",
+       "      <td>88</td>\n",
+       "      <td>Animation,Comedy,Family</td>\n",
+       "      <td>7.5</td>\n",
+       "      <td>114689</td>\n",
+       "      <td>6108</td>\n",
+       "      <td>Mira.</td>\n",
+       "      <td>3684305</td>\n",
+       "      <td>2002</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1645</th>\n",
+       "      <td>Pinocchio</td>\n",
+       "      <td>Turlis Abenteuer</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1967</td>\n",
+       "      <td>75</td>\n",
+       "      <td>Adventure,Family,Fantasy</td>\n",
+       "      <td>7.2</td>\n",
+       "      <td>19</td>\n",
+       "      <td>885</td>\n",
+       "      <td>Dis.</td>\n",
+       "      <td>84254167</td>\n",
+       "      <td>1940</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1646</th>\n",
+       "      <td>Pinocchio</td>\n",
+       "      <td>Turlis Abenteuer</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1967</td>\n",
+       "      <td>75</td>\n",
+       "      <td>Adventure,Family,Fantasy</td>\n",
+       "      <td>7.2</td>\n",
+       "      <td>19</td>\n",
+       "      <td>6108</td>\n",
+       "      <td>Mira.</td>\n",
+       "      <td>3684305</td>\n",
+       "      <td>2002</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1647</th>\n",
+       "      <td>Pinocchio</td>\n",
+       "      <td>Pinocchio</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1971</td>\n",
+       "      <td>79</td>\n",
+       "      <td>Comedy,Fantasy</td>\n",
+       "      <td>3.5</td>\n",
+       "      <td>123</td>\n",
+       "      <td>885</td>\n",
+       "      <td>Dis.</td>\n",
+       "      <td>84254167</td>\n",
+       "      <td>1940</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1648</th>\n",
+       "      <td>Pinocchio</td>\n",
+       "      <td>Pinocchio</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1971</td>\n",
+       "      <td>79</td>\n",
+       "      <td>Comedy,Fantasy</td>\n",
+       "      <td>3.5</td>\n",
+       "      <td>123</td>\n",
+       "      <td>6108</td>\n",
+       "      <td>Mira.</td>\n",
+       "      <td>3684305</td>\n",
+       "      <td>2002</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1649</th>\n",
+       "      <td>Pinocchio</td>\n",
+       "      <td>Pinocchio</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1911</td>\n",
+       "      <td>50</td>\n",
+       "      <td>Fantasy</td>\n",
+       "      <td>5.9</td>\n",
+       "      <td>69</td>\n",
+       "      <td>885</td>\n",
+       "      <td>Dis.</td>\n",
+       "      <td>84254167</td>\n",
+       "      <td>1940</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1650</th>\n",
+       "      <td>Pinocchio</td>\n",
+       "      <td>Pinocchio</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1911</td>\n",
+       "      <td>50</td>\n",
+       "      <td>Fantasy</td>\n",
+       "      <td>5.9</td>\n",
+       "      <td>69</td>\n",
+       "      <td>6108</td>\n",
+       "      <td>Mira.</td>\n",
+       "      <td>3684305</td>\n",
+       "      <td>2002</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1651</th>\n",
+       "      <td>Pinocchio</td>\n",
+       "      <td>Pinocchio</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2002</td>\n",
+       "      <td>108</td>\n",
+       "      <td>Comedy,Family,Fantasy</td>\n",
+       "      <td>4.3</td>\n",
+       "      <td>7192</td>\n",
+       "      <td>885</td>\n",
+       "      <td>Dis.</td>\n",
+       "      <td>84254167</td>\n",
+       "      <td>1940</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1652</th>\n",
+       "      <td>Pinocchio</td>\n",
+       "      <td>Pinocchio</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2002</td>\n",
+       "      <td>108</td>\n",
+       "      <td>Comedy,Family,Fantasy</td>\n",
+       "      <td>4.3</td>\n",
+       "      <td>7192</td>\n",
+       "      <td>6108</td>\n",
+       "      <td>Mira.</td>\n",
+       "      <td>3684305</td>\n",
+       "      <td>2002</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1653</th>\n",
+       "      <td>Pinocchio</td>\n",
+       "      <td>Un burattino di nome Pinocchio</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1971</td>\n",
+       "      <td>96</td>\n",
+       "      <td>Animation,Family,Fantasy</td>\n",
+       "      <td>7.0</td>\n",
+       "      <td>117</td>\n",
+       "      <td>885</td>\n",
+       "      <td>Dis.</td>\n",
+       "      <td>84254167</td>\n",
+       "      <td>1940</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1654</th>\n",
+       "      <td>Pinocchio</td>\n",
+       "      <td>Un burattino di nome Pinocchio</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1971</td>\n",
+       "      <td>96</td>\n",
+       "      <td>Animation,Family,Fantasy</td>\n",
+       "      <td>7.0</td>\n",
+       "      <td>117</td>\n",
+       "      <td>6108</td>\n",
+       "      <td>Mira.</td>\n",
+       "      <td>3684305</td>\n",
+       "      <td>2002</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1655</th>\n",
+       "      <td>Pinocchio</td>\n",
+       "      <td>Pinocchio</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>75</td>\n",
+       "      <td>Animation,Family,Fantasy</td>\n",
+       "      <td>6.3</td>\n",
+       "      <td>218</td>\n",
+       "      <td>885</td>\n",
+       "      <td>Dis.</td>\n",
+       "      <td>84254167</td>\n",
+       "      <td>1940</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1656</th>\n",
+       "      <td>Pinocchio</td>\n",
+       "      <td>Pinocchio</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>75</td>\n",
+       "      <td>Animation,Family,Fantasy</td>\n",
+       "      <td>6.3</td>\n",
+       "      <td>218</td>\n",
+       "      <td>6108</td>\n",
+       "      <td>Mira.</td>\n",
+       "      <td>3684305</td>\n",
+       "      <td>2002</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1657</th>\n",
+       "      <td>Pinocchio</td>\n",
+       "      <td>Pinocchio</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2015</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>Family,Fantasy</td>\n",
+       "      <td>4.9</td>\n",
+       "      <td>43</td>\n",
+       "      <td>885</td>\n",
+       "      <td>Dis.</td>\n",
+       "      <td>84254167</td>\n",
+       "      <td>1940</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1658</th>\n",
+       "      <td>Pinocchio</td>\n",
+       "      <td>Pinocchio</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2015</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>Family,Fantasy</td>\n",
+       "      <td>4.9</td>\n",
+       "      <td>43</td>\n",
+       "      <td>6108</td>\n",
+       "      <td>Mira.</td>\n",
+       "      <td>3684305</td>\n",
+       "      <td>2002</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1659</th>\n",
+       "      <td>Pinocchio</td>\n",
+       "      <td>Pinocchio</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2015</td>\n",
+       "      <td>75</td>\n",
+       "      <td>Documentary</td>\n",
+       "      <td>6.8</td>\n",
+       "      <td>8</td>\n",
+       "      <td>885</td>\n",
+       "      <td>Dis.</td>\n",
+       "      <td>84254167</td>\n",
+       "      <td>1940</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1660</th>\n",
+       "      <td>Pinocchio</td>\n",
+       "      <td>Pinocchio</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2015</td>\n",
+       "      <td>75</td>\n",
+       "      <td>Documentary</td>\n",
+       "      <td>6.8</td>\n",
+       "      <td>8</td>\n",
+       "      <td>6108</td>\n",
+       "      <td>Mira.</td>\n",
+       "      <td>3684305</td>\n",
+       "      <td>2002</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          title                  original_title  is_adult  year (imdb)  \\\n",
+       "1643  Pinocchio                       Pinocchio     False         1940   \n",
+       "1644  Pinocchio                       Pinocchio     False         1940   \n",
+       "1645  Pinocchio                Turlis Abenteuer     False         1967   \n",
+       "1646  Pinocchio                Turlis Abenteuer     False         1967   \n",
+       "1647  Pinocchio                       Pinocchio     False         1971   \n",
+       "1648  Pinocchio                       Pinocchio     False         1971   \n",
+       "1649  Pinocchio                       Pinocchio     False         1911   \n",
+       "1650  Pinocchio                       Pinocchio     False         1911   \n",
+       "1651  Pinocchio                       Pinocchio     False         2002   \n",
+       "1652  Pinocchio                       Pinocchio     False         2002   \n",
+       "1653  Pinocchio  Un burattino di nome Pinocchio     False         1971   \n",
+       "1654  Pinocchio  Un burattino di nome Pinocchio     False         1971   \n",
+       "1655  Pinocchio                       Pinocchio     False         2012   \n",
+       "1656  Pinocchio                       Pinocchio     False         2012   \n",
+       "1657  Pinocchio                       Pinocchio     False         2015   \n",
+       "1658  Pinocchio                       Pinocchio     False         2015   \n",
+       "1659  Pinocchio                       Pinocchio     False         2015   \n",
+       "1660  Pinocchio                       Pinocchio     False         2015   \n",
+       "\n",
+       "      length                    genres  imdb_rating  imdb_votes  \\\n",
+       "1643      88   Animation,Comedy,Family          7.5      114689   \n",
+       "1644      88   Animation,Comedy,Family          7.5      114689   \n",
+       "1645      75  Adventure,Family,Fantasy          7.2          19   \n",
+       "1646      75  Adventure,Family,Fantasy          7.2          19   \n",
+       "1647      79            Comedy,Fantasy          3.5         123   \n",
+       "1648      79            Comedy,Fantasy          3.5         123   \n",
+       "1649      50                   Fantasy          5.9          69   \n",
+       "1650      50                   Fantasy          5.9          69   \n",
+       "1651     108     Comedy,Family,Fantasy          4.3        7192   \n",
+       "1652     108     Comedy,Family,Fantasy          4.3        7192   \n",
+       "1653      96  Animation,Family,Fantasy          7.0         117   \n",
+       "1654      96  Animation,Family,Fantasy          7.0         117   \n",
+       "1655      75  Animation,Family,Fantasy          6.3         218   \n",
+       "1656      75  Animation,Family,Fantasy          6.3         218   \n",
+       "1657    <NA>            Family,Fantasy          4.9          43   \n",
+       "1658    <NA>            Family,Fantasy          4.9          43   \n",
+       "1659      75               Documentary          6.8           8   \n",
+       "1660      75               Documentary          6.8           8   \n",
+       "\n",
+       "      boxoffice_rank studio  lifetime_gross  year (boxoffice)  \n",
+       "1643             885   Dis.        84254167              1940  \n",
+       "1644            6108  Mira.         3684305              2002  \n",
+       "1645             885   Dis.        84254167              1940  \n",
+       "1646            6108  Mira.         3684305              2002  \n",
+       "1647             885   Dis.        84254167              1940  \n",
+       "1648            6108  Mira.         3684305              2002  \n",
+       "1649             885   Dis.        84254167              1940  \n",
+       "1650            6108  Mira.         3684305              2002  \n",
+       "1651             885   Dis.        84254167              1940  \n",
+       "1652            6108  Mira.         3684305              2002  \n",
+       "1653             885   Dis.        84254167              1940  \n",
+       "1654            6108  Mira.         3684305              2002  \n",
+       "1655             885   Dis.        84254167              1940  \n",
+       "1656            6108  Mira.         3684305              2002  \n",
+       "1657             885   Dis.        84254167              1940  \n",
+       "1658            6108  Mira.         3684305              2002  \n",
+       "1659             885   Dis.        84254167              1940  \n",
+       "1660            6108  Mira.         3684305              2002  "
+      ]
+     },
+     "execution_count": 33,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pd.merge(\n",
+    "    movies_with_rating,\n",
+    "    boxoffice,\n",
+    "    suffixes=[\" (imdb)\", \" (boxoffice)\"],\n",
+    "    on=\"title\"\n",
+    ").query(\"title == 'Pinocchio'\")  # \"Jeden\" ukázkový film"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Jejda, to jsme asi nechtěli. Existuje spousta různých Pinocchiů a ke každému z nich se připojili vždy oba snímky tohoto jména z `boxoffice`. Z toho vyplývá poučení, že při joinování je dobré se zamyslet nad jedinečností hodnot ve sloupci, který používáme jako klíč. Jméno filmu takové očividně není.\n",
+    "\n",
+    "V našem konkrétním případě jsme si problému všimli sami, ale pokud bude duplikátní klíč utopen někde v milionech hodnot, rádi bychom, aby to počítač poznal za nás. K tomu slouží argument `validate` - podle toho, jaký vztah mezi tabulkami očekáš, jsou přípustné hodnoty `\"one_to_one\"`, `\"one_to_many\"`, `\"many_to_one\"` nebo `\"many_to_many\"`:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>title</th>\n",
+       "      <th>original_title</th>\n",
+       "      <th>is_adult</th>\n",
+       "      <th>year (imdb)</th>\n",
+       "      <th>length</th>\n",
+       "      <th>genres</th>\n",
+       "      <th>imdb_rating</th>\n",
+       "      <th>imdb_votes</th>\n",
+       "      <th>boxoffice_rank</th>\n",
+       "      <th>studio</th>\n",
+       "      <th>lifetime_gross</th>\n",
+       "      <th>year (boxoffice)</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Oliver Twist</td>\n",
+       "      <td>Oliver Twist</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1912</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>Drama</td>\n",
+       "      <td>4.7</td>\n",
+       "      <td>19</td>\n",
+       "      <td>6826</td>\n",
+       "      <td>Sony</td>\n",
+       "      <td>2080321</td>\n",
+       "      <td>2005</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Oliver Twist</td>\n",
+       "      <td>Oliver Twist</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1912</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>Drama</td>\n",
+       "      <td>4.4</td>\n",
+       "      <td>12</td>\n",
+       "      <td>6826</td>\n",
+       "      <td>Sony</td>\n",
+       "      <td>2080321</td>\n",
+       "      <td>2005</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Oliver Twist</td>\n",
+       "      <td>Oliver Twist</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1916</td>\n",
+       "      <td>50</td>\n",
+       "      <td>Drama</td>\n",
+       "      <td>6.6</td>\n",
+       "      <td>16</td>\n",
+       "      <td>6826</td>\n",
+       "      <td>Sony</td>\n",
+       "      <td>2080321</td>\n",
+       "      <td>2005</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Oliver Twist</td>\n",
+       "      <td>Oliver Twist</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1922</td>\n",
+       "      <td>98</td>\n",
+       "      <td>Drama</td>\n",
+       "      <td>6.8</td>\n",
+       "      <td>657</td>\n",
+       "      <td>6826</td>\n",
+       "      <td>Sony</td>\n",
+       "      <td>2080321</td>\n",
+       "      <td>2005</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Oliver Twist</td>\n",
+       "      <td>Oliver Twist</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1933</td>\n",
+       "      <td>80</td>\n",
+       "      <td>Drama</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>292</td>\n",
+       "      <td>6826</td>\n",
+       "      <td>Sony</td>\n",
+       "      <td>2080321</td>\n",
+       "      <td>2005</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20562</th>\n",
+       "      <td>BTS World Tour: Love Yourself in Seoul</td>\n",
+       "      <td>BTS World Tour: Love Yourself in Seoul</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>112</td>\n",
+       "      <td>Documentary,Music</td>\n",
+       "      <td>8.5</td>\n",
+       "      <td>439</td>\n",
+       "      <td>6173</td>\n",
+       "      <td>Fathom</td>\n",
+       "      <td>3509917</td>\n",
+       "      <td>2019</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20563</th>\n",
+       "      <td>Mojin: The Worm Valley</td>\n",
+       "      <td>Yun nan chong gu</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>110</td>\n",
+       "      <td>Action,Fantasy</td>\n",
+       "      <td>4.7</td>\n",
+       "      <td>120</td>\n",
+       "      <td>11240</td>\n",
+       "      <td>WGUSA</td>\n",
+       "      <td>101516</td>\n",
+       "      <td>2019</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20564</th>\n",
+       "      <td>Extreme Job</td>\n",
+       "      <td>Geukhanjikeob</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>111</td>\n",
+       "      <td>Action,Comedy</td>\n",
+       "      <td>7.3</td>\n",
+       "      <td>905</td>\n",
+       "      <td>7212</td>\n",
+       "      <td>CJ</td>\n",
+       "      <td>1548816</td>\n",
+       "      <td>2019</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20565</th>\n",
+       "      <td>Peppa Celebrates Chinese New Year</td>\n",
+       "      <td>xiao zhu pei qi guo da nian</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>81</td>\n",
+       "      <td>Animation,Family</td>\n",
+       "      <td>3.4</td>\n",
+       "      <td>41</td>\n",
+       "      <td>10811</td>\n",
+       "      <td>STX</td>\n",
+       "      <td>131225</td>\n",
+       "      <td>2019</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20566</th>\n",
+       "      <td>Avant qu'on explose</td>\n",
+       "      <td>Avant qu'on explose</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>108</td>\n",
+       "      <td>Comedy</td>\n",
+       "      <td>6.9</td>\n",
+       "      <td>41</td>\n",
+       "      <td>10995</td>\n",
+       "      <td>EOne</td>\n",
+       "      <td>116576</td>\n",
+       "      <td>2019</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>20567 rows × 12 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                        title  \\\n",
+       "0                                Oliver Twist   \n",
+       "1                                Oliver Twist   \n",
+       "2                                Oliver Twist   \n",
+       "3                                Oliver Twist   \n",
+       "4                                Oliver Twist   \n",
+       "...                                       ...   \n",
+       "20562  BTS World Tour: Love Yourself in Seoul   \n",
+       "20563                  Mojin: The Worm Valley   \n",
+       "20564                             Extreme Job   \n",
+       "20565       Peppa Celebrates Chinese New Year   \n",
+       "20566                     Avant qu'on explose   \n",
+       "\n",
+       "                               original_title  is_adult  year (imdb)  length  \\\n",
+       "0                                Oliver Twist     False         1912    <NA>   \n",
+       "1                                Oliver Twist     False         1912    <NA>   \n",
+       "2                                Oliver Twist     False         1916      50   \n",
+       "3                                Oliver Twist     False         1922      98   \n",
+       "4                                Oliver Twist     False         1933      80   \n",
+       "...                                       ...       ...          ...     ...   \n",
+       "20562  BTS World Tour: Love Yourself in Seoul     False         2019     112   \n",
+       "20563                        Yun nan chong gu     False         2018     110   \n",
+       "20564                           Geukhanjikeob     False         2019     111   \n",
+       "20565             xiao zhu pei qi guo da nian     False         2019      81   \n",
+       "20566                     Avant qu'on explose     False         2019     108   \n",
+       "\n",
+       "                  genres  imdb_rating  imdb_votes  boxoffice_rank  studio  \\\n",
+       "0                  Drama          4.7          19            6826    Sony   \n",
+       "1                  Drama          4.4          12            6826    Sony   \n",
+       "2                  Drama          6.6          16            6826    Sony   \n",
+       "3                  Drama          6.8         657            6826    Sony   \n",
+       "4                  Drama          5.0         292            6826    Sony   \n",
+       "...                  ...          ...         ...             ...     ...   \n",
+       "20562  Documentary,Music          8.5         439            6173  Fathom   \n",
+       "20563     Action,Fantasy          4.7         120           11240   WGUSA   \n",
+       "20564      Action,Comedy          7.3         905            7212      CJ   \n",
+       "20565   Animation,Family          3.4          41           10811     STX   \n",
+       "20566             Comedy          6.9          41           10995    EOne   \n",
+       "\n",
+       "       lifetime_gross  year (boxoffice)  \n",
+       "0             2080321              2005  \n",
+       "1             2080321              2005  \n",
+       "2             2080321              2005  \n",
+       "3             2080321              2005  \n",
+       "4             2080321              2005  \n",
+       "...               ...               ...  \n",
+       "20562         3509917              2019  \n",
+       "20563          101516              2019  \n",
+       "20564         1548816              2019  \n",
+       "20565          131225              2019  \n",
+       "20566          116576              2019  \n",
+       "\n",
+       "[20567 rows x 12 columns]"
+      ]
+     },
+     "execution_count": 34,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pd.merge(\n",
+    "    movies_with_rating,\n",
+    "    boxoffice,\n",
+    "    on=\"title\",\n",
+    "    suffixes=[\" (imdb)\", \" (boxoffice)\"],\n",
+    "#    validate=\"one_to_one\"    # Odkomentuj a vyskočí chyba!\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Řešení je jednoduché - budeme joinovat přes dva různé sloupce (argument `on` to unese ;-)). Při té příležitosti navíc zjišťujeme, že nedává smysl spojovat filmy, které rok vůbec uvedený nemají, a proto je vyhodíme:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>title</th>\n",
+       "      <th>original_title</th>\n",
+       "      <th>is_adult</th>\n",
+       "      <th>year</th>\n",
+       "      <th>length</th>\n",
+       "      <th>genres</th>\n",
+       "      <th>imdb_rating</th>\n",
+       "      <th>imdb_votes</th>\n",
+       "      <th>boxoffice_rank</th>\n",
+       "      <th>studio</th>\n",
+       "      <th>lifetime_gross</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>6926</th>\n",
+       "      <td>Playback</td>\n",
+       "      <td>Playback</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>98</td>\n",
+       "      <td>Horror,Thriller</td>\n",
+       "      <td>4.3</td>\n",
+       "      <td>4478</td>\n",
+       "      <td>16256</td>\n",
+       "      <td>Magn.</td>\n",
+       "      <td>264</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6927</th>\n",
+       "      <td>Playback</td>\n",
+       "      <td>Playback</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>113</td>\n",
+       "      <td>Drama</td>\n",
+       "      <td>4.9</td>\n",
+       "      <td>27</td>\n",
+       "      <td>16256</td>\n",
+       "      <td>Magn.</td>\n",
+       "      <td>264</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6928</th>\n",
+       "      <td>Playback</td>\n",
+       "      <td>Dur d'être Dieu</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>66</td>\n",
+       "      <td>Documentary</td>\n",
+       "      <td>5.2</td>\n",
+       "      <td>8</td>\n",
+       "      <td>16256</td>\n",
+       "      <td>Magn.</td>\n",
+       "      <td>264</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "         title   original_title  is_adult  year  length           genres  \\\n",
+       "6926  Playback         Playback     False  2012      98  Horror,Thriller   \n",
+       "6927  Playback         Playback     False  2012     113            Drama   \n",
+       "6928  Playback  Dur d'être Dieu     False  2012      66      Documentary   \n",
+       "\n",
+       "      imdb_rating  imdb_votes  boxoffice_rank studio  lifetime_gross  \n",
+       "6926          4.3        4478           16256  Magn.             264  \n",
+       "6927          4.9          27           16256  Magn.             264  \n",
+       "6928          5.2           8           16256  Magn.             264  "
+      ]
+     },
+     "execution_count": 35,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "(\n",
+    "    pd.merge(\n",
+    "        movies_with_rating.dropna(subset=[\"year\"]),  # Vyhoď všechny řádky bez roku\n",
+    "        boxoffice,\n",
+    "        on=[\"title\", \"year\"],\n",
+    "        validate=\"many_to_one\",      # movies_with_rating pořád nejsou unikátní!\n",
+    "    )\n",
+    ").query(\"title == 'Playback'\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Pořád nejsou unikátní! Co s tím?\n",
+    "\n",
+    "**Hypotéza:** Vstupujeme na nebezpečnou půdu a zkusíme spekulovat, že informace o ziscích budeme mít nejspíš jen o nejpopulárnějších filmech. Možná máme pravdu, možná ne a nejspíš nějakou drobnou nepřesnost zaneseme, ale dobrat se tady skutečné pravdy je \"drahé\" (a možná i skutečně drahé), z nabízených datových sad to věrohodně možné není.\n",
+    "\n",
+    "Abychom se co nejvíc přiblížili realitě, z každé opakující se dvojice (název, rok) vybereme film s nejvyšším `imdb_votes`. Nejdříve si pomocí `sort_values` srovnáme všechny filmy a pak zavoláme `drop_duplicates(..., keep=\"first\")`, což nám ponechá vždy jen jeden z řady duplikátů:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>title</th>\n",
+       "      <th>original_title</th>\n",
+       "      <th>is_adult</th>\n",
+       "      <th>year</th>\n",
+       "      <th>length</th>\n",
+       "      <th>genres</th>\n",
+       "      <th>imdb_rating</th>\n",
+       "      <th>imdb_votes</th>\n",
+       "      <th>boxoffice_rank</th>\n",
+       "      <th>studio</th>\n",
+       "      <th>lifetime_gross</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>The Shawshank Redemption</td>\n",
+       "      <td>The Shawshank Redemption</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1994</td>\n",
+       "      <td>142</td>\n",
+       "      <td>Drama</td>\n",
+       "      <td>9.3</td>\n",
+       "      <td>2071759</td>\n",
+       "      <td>2792</td>\n",
+       "      <td>Col.</td>\n",
+       "      <td>28341469</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>The Dark Knight</td>\n",
+       "      <td>The Dark Knight</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2008</td>\n",
+       "      <td>152</td>\n",
+       "      <td>Action,Crime,Drama</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>2037678</td>\n",
+       "      <td>10</td>\n",
+       "      <td>WB</td>\n",
+       "      <td>535234033</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Inception</td>\n",
+       "      <td>Inception</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2010</td>\n",
+       "      <td>148</td>\n",
+       "      <td>Action,Adventure,Sci-Fi</td>\n",
+       "      <td>8.8</td>\n",
+       "      <td>1816360</td>\n",
+       "      <td>85</td>\n",
+       "      <td>WB</td>\n",
+       "      <td>292576195</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Fight Club</td>\n",
+       "      <td>Fight Club</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1999</td>\n",
+       "      <td>139</td>\n",
+       "      <td>Drama</td>\n",
+       "      <td>8.8</td>\n",
+       "      <td>1657857</td>\n",
+       "      <td>2248</td>\n",
+       "      <td>Fox</td>\n",
+       "      <td>37030102</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Pulp Fiction</td>\n",
+       "      <td>Pulp Fiction</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1994</td>\n",
+       "      <td>154</td>\n",
+       "      <td>Crime,Drama</td>\n",
+       "      <td>8.9</td>\n",
+       "      <td>1620135</td>\n",
+       "      <td>629</td>\n",
+       "      <td>Mira.</td>\n",
+       "      <td>107928762</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8996</th>\n",
+       "      <td>Girlfriends</td>\n",
+       "      <td>Girlfriends</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1996</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8.6</td>\n",
+       "      <td>7</td>\n",
+       "      <td>13930</td>\n",
+       "      <td>FRun</td>\n",
+       "      <td>18000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8997</th>\n",
+       "      <td>Sacred</td>\n",
+       "      <td>Sacred</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>Action,Drama,Romance</td>\n",
+       "      <td>8.2</td>\n",
+       "      <td>6</td>\n",
+       "      <td>13950</td>\n",
+       "      <td>Argo.</td>\n",
+       "      <td>17740</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8998</th>\n",
+       "      <td>The Professor: Tai Chi's Journey West</td>\n",
+       "      <td>The Professor: Tai Chi's Journey West</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2016</td>\n",
+       "      <td>72</td>\n",
+       "      <td>Documentary</td>\n",
+       "      <td>7.2</td>\n",
+       "      <td>6</td>\n",
+       "      <td>15820</td>\n",
+       "      <td>FRun</td>\n",
+       "      <td>2852</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8999</th>\n",
+       "      <td>After Love</td>\n",
+       "      <td>After Love</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>Drama,Romance,Thriller</td>\n",
+       "      <td>7.6</td>\n",
+       "      <td>5</td>\n",
+       "      <td>14299</td>\n",
+       "      <td>Distrib.</td>\n",
+       "      <td>13693</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9000</th>\n",
+       "      <td>Still, the Children Are Here</td>\n",
+       "      <td>Still, the Children Are Here</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2004</td>\n",
+       "      <td>85</td>\n",
+       "      <td>Documentary</td>\n",
+       "      <td>6.6</td>\n",
+       "      <td>5</td>\n",
+       "      <td>15653</td>\n",
+       "      <td>Icar.</td>\n",
+       "      <td>3685</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>9001 rows × 11 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                      title  \\\n",
+       "0                  The Shawshank Redemption   \n",
+       "1                           The Dark Knight   \n",
+       "2                                 Inception   \n",
+       "3                                Fight Club   \n",
+       "4                              Pulp Fiction   \n",
+       "...                                     ...   \n",
+       "8996                            Girlfriends   \n",
+       "8997                                 Sacred   \n",
+       "8998  The Professor: Tai Chi's Journey West   \n",
+       "8999                             After Love   \n",
+       "9000           Still, the Children Are Here   \n",
+       "\n",
+       "                             original_title  is_adult  year  length  \\\n",
+       "0                  The Shawshank Redemption     False  1994     142   \n",
+       "1                           The Dark Knight     False  2008     152   \n",
+       "2                                 Inception     False  2010     148   \n",
+       "3                                Fight Club     False  1999     139   \n",
+       "4                              Pulp Fiction     False  1994     154   \n",
+       "...                                     ...       ...   ...     ...   \n",
+       "8996                            Girlfriends     False  1996    <NA>   \n",
+       "8997                                 Sacred     False  2017    <NA>   \n",
+       "8998  The Professor: Tai Chi's Journey West     False  2016      72   \n",
+       "8999                             After Love     False  2017    <NA>   \n",
+       "9000           Still, the Children Are Here     False  2004      85   \n",
+       "\n",
+       "                       genres  imdb_rating  imdb_votes  boxoffice_rank  \\\n",
+       "0                       Drama          9.3     2071759            2792   \n",
+       "1          Action,Crime,Drama          9.0     2037678              10   \n",
+       "2     Action,Adventure,Sci-Fi          8.8     1816360              85   \n",
+       "3                       Drama          8.8     1657857            2248   \n",
+       "4                 Crime,Drama          8.9     1620135             629   \n",
+       "...                       ...          ...         ...             ...   \n",
+       "8996                      NaN          8.6           7           13930   \n",
+       "8997     Action,Drama,Romance          8.2           6           13950   \n",
+       "8998              Documentary          7.2           6           15820   \n",
+       "8999   Drama,Romance,Thriller          7.6           5           14299   \n",
+       "9000              Documentary          6.6           5           15653   \n",
+       "\n",
+       "        studio  lifetime_gross  \n",
+       "0         Col.        28341469  \n",
+       "1           WB       535234033  \n",
+       "2           WB       292576195  \n",
+       "3          Fox        37030102  \n",
+       "4        Mira.       107928762  \n",
+       "...        ...             ...  \n",
+       "8996      FRun           18000  \n",
+       "8997     Argo.           17740  \n",
+       "8998      FRun            2852  \n",
+       "8999  Distrib.           13693  \n",
+       "9000     Icar.            3685  \n",
+       "\n",
+       "[9001 rows x 11 columns]"
+      ]
+     },
+     "execution_count": 36,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "movies_with_rating_and_boxoffice = (\n",
+    "    pd.merge(\n",
+    "        movies_with_rating\n",
+    "            .dropna(subset=[\"year\"])\n",
+    "            .sort_values(\"imdb_votes\", ascending=False)\n",
+    "            .drop_duplicates(\n",
+    "                subset=[\"title\", \"year\"],\n",
+    "                keep=\"first\"\n",
+    "            ),\n",
+    "        boxoffice,\n",
+    "        on=[\"title\", \"year\"],\n",
+    "        validate=\"one_to_one\",\n",
+    "    )\n",
+    ")\n",
+    "movies_with_rating_and_boxoffice"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>title</th>\n",
+       "      <th>original_title</th>\n",
+       "      <th>is_adult</th>\n",
+       "      <th>year</th>\n",
+       "      <th>length</th>\n",
+       "      <th>genres</th>\n",
+       "      <th>imdb_rating</th>\n",
+       "      <th>imdb_votes</th>\n",
+       "      <th>boxoffice_rank</th>\n",
+       "      <th>studio</th>\n",
+       "      <th>lifetime_gross</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>5831</th>\n",
+       "      <td>Playback</td>\n",
+       "      <td>Playback</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>98</td>\n",
+       "      <td>Horror,Thriller</td>\n",
+       "      <td>4.3</td>\n",
+       "      <td>4478</td>\n",
+       "      <td>16256</td>\n",
+       "      <td>Magn.</td>\n",
+       "      <td>264</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "         title original_title  is_adult  year  length           genres  \\\n",
+       "5831  Playback       Playback     False  2012      98  Horror,Thriller   \n",
+       "\n",
+       "      imdb_rating  imdb_votes  boxoffice_rank studio  lifetime_gross  \n",
+       "5831          4.3        4478           16256  Magn.             264  "
+      ]
+     },
+     "execution_count": 37,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# To už by šlo!\n",
+    "movies_with_rating_and_boxoffice.query(\"title == 'Playback'\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Úkol:** Seřaď filmy podle toho, kolik vydělaly (nabízí se hned dvě možnosti)."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Otázka:** Které filmy nám vypadly a proč?"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Třetí join"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Rank</th>\n",
+       "      <th>Title</th>\n",
+       "      <th>RatingTomatometer</th>\n",
+       "      <th>No. of Reviews</th>\n",
+       "      <th>Genres</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>Black Panther (2018)</td>\n",
+       "      <td>97</td>\n",
+       "      <td>444</td>\n",
+       "      <td>action|adventure</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>Mad Max: Fury Road (2015)</td>\n",
+       "      <td>97</td>\n",
+       "      <td>394</td>\n",
+       "      <td>action|adventure</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>Wonder Woman (2017)</td>\n",
+       "      <td>93</td>\n",
+       "      <td>410</td>\n",
+       "      <td>action|adventure</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>Metropolis (1927)</td>\n",
+       "      <td>99</td>\n",
+       "      <td>118</td>\n",
+       "      <td>action|adventure</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>Coco (2017)</td>\n",
+       "      <td>97</td>\n",
+       "      <td>308</td>\n",
+       "      <td>action|adventure</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1585</th>\n",
+       "      <td>70</td>\n",
+       "      <td>Priest (2011)</td>\n",
+       "      <td>15</td>\n",
+       "      <td>97</td>\n",
+       "      <td>western</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1586</th>\n",
+       "      <td>71</td>\n",
+       "      <td>American Outlaws (2001)</td>\n",
+       "      <td>14</td>\n",
+       "      <td>103</td>\n",
+       "      <td>western</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1587</th>\n",
+       "      <td>72</td>\n",
+       "      <td>September Dawn (2007)</td>\n",
+       "      <td>15</td>\n",
+       "      <td>54</td>\n",
+       "      <td>western</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1588</th>\n",
+       "      <td>73</td>\n",
+       "      <td>Jonah Hex (2010)</td>\n",
+       "      <td>12</td>\n",
+       "      <td>147</td>\n",
+       "      <td>western</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1589</th>\n",
+       "      <td>74</td>\n",
+       "      <td>Texas Rangers (2001)</td>\n",
+       "      <td>2</td>\n",
+       "      <td>51</td>\n",
+       "      <td>western</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1590 rows × 5 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      Rank                      Title  RatingTomatometer  No. of Reviews  \\\n",
+       "0        1       Black Panther (2018)                 97             444   \n",
+       "1        2  Mad Max: Fury Road (2015)                 97             394   \n",
+       "2        3        Wonder Woman (2017)                 93             410   \n",
+       "3        4          Metropolis (1927)                 99             118   \n",
+       "4        5                Coco (2017)                 97             308   \n",
+       "...    ...                        ...                ...             ...   \n",
+       "1585    70              Priest (2011)                 15              97   \n",
+       "1586    71    American Outlaws (2001)                 14             103   \n",
+       "1587    72      September Dawn (2007)                 15              54   \n",
+       "1588    73           Jonah Hex (2010)                 12             147   \n",
+       "1589    74       Texas Rangers (2001)                  2              51   \n",
+       "\n",
+       "                Genres  \n",
+       "0     action|adventure  \n",
+       "1     action|adventure  \n",
+       "2     action|adventure  \n",
+       "3     action|adventure  \n",
+       "4     action|adventure  \n",
+       "...                ...  \n",
+       "1585           western  \n",
+       "1586           western  \n",
+       "1587           western  \n",
+       "1588           western  \n",
+       "1589           western  \n",
+       "\n",
+       "[1590 rows x 5 columns]"
+      ]
+     },
+     "execution_count": 38,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rotten_tomatoes_raw"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Title\n",
+       "Yellow Submarine (1968)                                 6\n",
+       "101 Dalmatians (1961)                                   5\n",
+       "Fantasia (1940)                                         5\n",
+       "Harry Potter and the Deathly Hallows - Part 2 (2011)    5\n",
+       "Miracle on 34th Street (1947)                           5\n",
+       "                                                       ..\n",
+       "Misery (1990)                                           1\n",
+       "The Dead Zone (1983)                                    1\n",
+       "The Conjuring (2013)                                    1\n",
+       "The Exorcist (1973)                                     1\n",
+       "Texas Rangers (2001)                                    1\n",
+       "Name: count, Length: 947, dtype: int64"
+      ]
+     },
+     "execution_count": 39,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rotten_tomatoes_raw[\"Title\"].value_counts()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "A zase duplicity, některé názvy se nám opakují :-(\n",
+    "\n",
+    "**Otázka:** Dokážeš zjistit proč? Nápověda: podívej se na nějaký konkrétní film."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Naštěstí už víme, jak na to - použijeme metodu `drop_duplicates`, tentokrát přes sloupec `\"Title\"`. (Poznámka: druhou možností by bylo sloučit všechny různé žánry daného filmu do jedné buňky)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Title</th>\n",
+       "      <th>RatingTomatometer</th>\n",
+       "      <th>No. of Reviews</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Black Panther (2018)</td>\n",
+       "      <td>97</td>\n",
+       "      <td>444</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Mad Max: Fury Road (2015)</td>\n",
+       "      <td>97</td>\n",
+       "      <td>394</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Wonder Woman (2017)</td>\n",
+       "      <td>93</td>\n",
+       "      <td>410</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Metropolis (1927)</td>\n",
+       "      <td>99</td>\n",
+       "      <td>118</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Coco (2017)</td>\n",
+       "      <td>97</td>\n",
+       "      <td>308</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1585</th>\n",
+       "      <td>Priest (2011)</td>\n",
+       "      <td>15</td>\n",
+       "      <td>97</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1586</th>\n",
+       "      <td>American Outlaws (2001)</td>\n",
+       "      <td>14</td>\n",
+       "      <td>103</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1587</th>\n",
+       "      <td>September Dawn (2007)</td>\n",
+       "      <td>15</td>\n",
+       "      <td>54</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1588</th>\n",
+       "      <td>Jonah Hex (2010)</td>\n",
+       "      <td>12</td>\n",
+       "      <td>147</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1589</th>\n",
+       "      <td>Texas Rangers (2001)</td>\n",
+       "      <td>2</td>\n",
+       "      <td>51</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>947 rows × 3 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                          Title  RatingTomatometer  No. of Reviews\n",
+       "0          Black Panther (2018)                 97             444\n",
+       "1     Mad Max: Fury Road (2015)                 97             394\n",
+       "2           Wonder Woman (2017)                 93             410\n",
+       "3             Metropolis (1927)                 99             118\n",
+       "4                   Coco (2017)                 97             308\n",
+       "...                         ...                ...             ...\n",
+       "1585              Priest (2011)                 15              97\n",
+       "1586    American Outlaws (2001)                 14             103\n",
+       "1587      September Dawn (2007)                 15              54\n",
+       "1588           Jonah Hex (2010)                 12             147\n",
+       "1589       Texas Rangers (2001)                  2              51\n",
+       "\n",
+       "[947 rows x 3 columns]"
+      ]
+     },
+     "execution_count": 40,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rotten_tomatoes_nodup = (\n",
+    "    rotten_tomatoes_raw\n",
+    "    .drop_duplicates(\n",
+    "        subset=\"Title\",\n",
+    "        keep=\"first\"                   # Vybereme první výskyt, lze i \"last\" (anebo False => vyhodit všechny)\n",
+    "    )\n",
+    "    .drop(\"Genres\", axis=\"columns\")    # Informační hodnotu jsme už ztratili\n",
+    "    .drop(\"Rank\", axis=\"columns\")      # Mělo smysl jen v rámci žánru\n",
+    ")\n",
+    "rotten_tomatoes_nodup"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>title_type</th>\n",
+       "      <th>title</th>\n",
+       "      <th>original_title</th>\n",
+       "      <th>is_adult</th>\n",
+       "      <th>start_year</th>\n",
+       "      <th>end_year</th>\n",
+       "      <th>length</th>\n",
+       "      <th>genres</th>\n",
+       "      <th>Title</th>\n",
+       "      <th>RatingTomatometer</th>\n",
+       "      <th>No. of Reviews</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "Empty DataFrame\n",
+       "Columns: [title_type, title, original_title, is_adult, start_year, end_year, length, genres, Title, RatingTomatometer, No. of Reviews]\n",
+       "Index: []"
+      ]
+     },
+     "execution_count": 41,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Ready to merge?\n",
+    "pd.merge(imdb_titles, rotten_tomatoes_nodup, left_on=\"title\", right_on=\"Title\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "0 řádků!\n",
+    "\n",
+    "Dosud jsme manipulovali s řádky a sloupci jako celky, nicméně teď musíme zasahovat přímo do hodnot v buňkách. I to se při slučování dat z různých zdrojů nezřídka stává. Stojíme před úkolem převést řetězce typu \"Black Panther (2018)\" na dvě hodnoty: název \"Black Panther\" a rok 2018 (jeden sloupec na dva). \n",
+    "\n",
+    "Naštěstí si ty sloupce umíme jednoduše vyrobit pomocí řetězcové metody [`.str.slice`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.slice.html), která z každého řetězce vyřízne nějakou jeho část (a zase pracuje na celém sloupci - výsledkem bude nový sloupec s funkcí aplikovanou na každou z hodnot). Budeme věřit, že předposlední čtyři znaky představují rok a zbytek, až na nějaké ty závorky, tvoří skutečný název:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>tomatoes_rating</th>\n",
+       "      <th>tomatoes_votes</th>\n",
+       "      <th>title</th>\n",
+       "      <th>year</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>97</td>\n",
+       "      <td>444</td>\n",
+       "      <td>Black Panther</td>\n",
+       "      <td>2018</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>97</td>\n",
+       "      <td>394</td>\n",
+       "      <td>Mad Max: Fury Road</td>\n",
+       "      <td>2015</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>93</td>\n",
+       "      <td>410</td>\n",
+       "      <td>Wonder Woman</td>\n",
+       "      <td>2017</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>99</td>\n",
+       "      <td>118</td>\n",
+       "      <td>Metropolis</td>\n",
+       "      <td>1927</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>97</td>\n",
+       "      <td>308</td>\n",
+       "      <td>Coco</td>\n",
+       "      <td>2017</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1585</th>\n",
+       "      <td>15</td>\n",
+       "      <td>97</td>\n",
+       "      <td>Priest</td>\n",
+       "      <td>2011</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1586</th>\n",
+       "      <td>14</td>\n",
+       "      <td>103</td>\n",
+       "      <td>American Outlaws</td>\n",
+       "      <td>2001</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1587</th>\n",
+       "      <td>15</td>\n",
+       "      <td>54</td>\n",
+       "      <td>September Dawn</td>\n",
+       "      <td>2007</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1588</th>\n",
+       "      <td>12</td>\n",
+       "      <td>147</td>\n",
+       "      <td>Jonah Hex</td>\n",
+       "      <td>2010</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1589</th>\n",
+       "      <td>2</td>\n",
+       "      <td>51</td>\n",
+       "      <td>Texas Rangers</td>\n",
+       "      <td>2001</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>947 rows × 4 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      tomatoes_rating  tomatoes_votes               title  year\n",
+       "0                  97             444       Black Panther  2018\n",
+       "1                  97             394  Mad Max: Fury Road  2015\n",
+       "2                  93             410        Wonder Woman  2017\n",
+       "3                  99             118          Metropolis  1927\n",
+       "4                  97             308                Coco  2017\n",
+       "...               ...             ...                 ...   ...\n",
+       "1585               15              97              Priest  2011\n",
+       "1586               14             103    American Outlaws  2001\n",
+       "1587               15              54      September Dawn  2007\n",
+       "1588               12             147           Jonah Hex  2010\n",
+       "1589                2              51       Texas Rangers  2001\n",
+       "\n",
+       "[947 rows x 4 columns]"
+      ]
+     },
+     "execution_count": 42,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rotten_tomatoes_beta = (rotten_tomatoes_nodup\n",
+    "    .assign(\n",
+    "        title=rotten_tomatoes_nodup[\"Title\"].str.slice(0, -7),             \n",
+    "        year=rotten_tomatoes_nodup[\"Title\"].str.slice(-5, -1).astype(int)\n",
+    "    )\n",
+    "    .rename({\n",
+    "        \"RatingTomatometer\": \"tomatoes_rating\",\n",
+    "        \"No. of Reviews\": \"tomatoes_votes\",\n",
+    "    }, axis=\"columns\")\n",
+    "    .drop([\"Title\"], axis=\"columns\")\n",
+    ")\n",
+    "rotten_tomatoes_beta"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Závorková odysea nekončí, někdo nám proaktivně do závorek nacpal i originální název naanglickojazyčných filmů. Pojďme se o tom přesvědčit pomocí metody [`.str.contains`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.contains.html) (protože tato metoda ve výchozím stavu používá pro vyhledávání regulární výrazy, které jsme se zatím nenaučili používat, musíme jí to explicitně zakázat argumentem `regex=False`):"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>tomatoes_rating</th>\n",
+       "      <th>tomatoes_votes</th>\n",
+       "      <th>title</th>\n",
+       "      <th>year</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>100</td>\n",
+       "      <td>58</td>\n",
+       "      <td>Seven Samurai (Shichinin no Samurai)</td>\n",
+       "      <td>1956</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>51</th>\n",
+       "      <td>98</td>\n",
+       "      <td>46</td>\n",
+       "      <td>Aguirre, the Wrath of God (Aguirre, der Zorn G...</td>\n",
+       "      <td>1972</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>61</th>\n",
+       "      <td>97</td>\n",
+       "      <td>71</td>\n",
+       "      <td>Ghostbusters (1984 Original)</td>\n",
+       "      <td>1984</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>69</th>\n",
+       "      <td>98</td>\n",
+       "      <td>47</td>\n",
+       "      <td>A Fistful of Dollars (Per un Pugno di Dollari)</td>\n",
+       "      <td>1964</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>99</th>\n",
+       "      <td>96</td>\n",
+       "      <td>139</td>\n",
+       "      <td>Embrace Of The Serpent (El Abrazo De La Serpie...</td>\n",
+       "      <td>2016</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1368</th>\n",
+       "      <td>97</td>\n",
+       "      <td>59</td>\n",
+       "      <td>To Be and to Have (Etre et Avoir)</td>\n",
+       "      <td>2003</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1457</th>\n",
+       "      <td>43</td>\n",
+       "      <td>82</td>\n",
+       "      <td>Goal! The Dream Begins (Goal!: The Impossible ...</td>\n",
+       "      <td>2005</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1502</th>\n",
+       "      <td>71</td>\n",
+       "      <td>52</td>\n",
+       "      <td>Only Human (Seres queridos)</td>\n",
+       "      <td>2006</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1547</th>\n",
+       "      <td>83</td>\n",
+       "      <td>64</td>\n",
+       "      <td>The Good, the Bad, the Weird (Joheun-nom, Nabb...</td>\n",
+       "      <td>2010</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1559</th>\n",
+       "      <td>74</td>\n",
+       "      <td>62</td>\n",
+       "      <td>Fah talai jone (Tears of the Black Tiger)</td>\n",
+       "      <td>2007</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>66 rows × 4 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      tomatoes_rating  tomatoes_votes  \\\n",
+       "15                100              58   \n",
+       "51                 98              46   \n",
+       "61                 97              71   \n",
+       "69                 98              47   \n",
+       "99                 96             139   \n",
+       "...               ...             ...   \n",
+       "1368               97              59   \n",
+       "1457               43              82   \n",
+       "1502               71              52   \n",
+       "1547               83              64   \n",
+       "1559               74              62   \n",
+       "\n",
+       "                                                  title  year  \n",
+       "15                 Seven Samurai (Shichinin no Samurai)  1956  \n",
+       "51    Aguirre, the Wrath of God (Aguirre, der Zorn G...  1972  \n",
+       "61                         Ghostbusters (1984 Original)  1984  \n",
+       "69       A Fistful of Dollars (Per un Pugno di Dollari)  1964  \n",
+       "99    Embrace Of The Serpent (El Abrazo De La Serpie...  2016  \n",
+       "...                                                 ...   ...  \n",
+       "1368                  To Be and to Have (Etre et Avoir)  2003  \n",
+       "1457  Goal! The Dream Begins (Goal!: The Impossible ...  2005  \n",
+       "1502                        Only Human (Seres queridos)  2006  \n",
+       "1547  The Good, the Bad, the Weird (Joheun-nom, Nabb...  2010  \n",
+       "1559          Fah talai jone (Tears of the Black Tiger)  2007  \n",
+       "\n",
+       "[66 rows x 4 columns]"
+      ]
+     },
+     "execution_count": 43,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rotten_tomatoes_beta[rotten_tomatoes_beta[\"title\"].str.contains(\")\", regex=False)]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "V rámci zjednodušení proto ještě odstraníme všechny takové závorky. K tomu pomůže funkce [`.str.rsplit`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.rsplit.html), která rozdělí zprava řetězec na několik částí podle oddělovače a vloží je do seznamu - my za ten oddělovač zvolíme levou závorku `\"(\"`, omezíme počet částí na jednu až dvě (`n=1`):"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "41            [Marvel's The Avengers]\n",
+       "61    [Ghostbusters , 1984 Original)]\n",
+       "81      [Mad Max 2: The Road Warrior]\n",
+       "Name: title, dtype: object"
+      ]
+     },
+     "execution_count": 44,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "split_title = (\n",
+    "    rotten_tomatoes_beta[\"title\"]\n",
+    "    .str.rsplit(\"(\", n=1)\n",
+    ")\n",
+    "split_title.loc[[41, 61, 81]]   # Některé seznamy obsahují jeden prvek, jiné dva"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "A jak teď vybrat první prvek z každého seznamu?\n",
+    "\n",
+    "💡 Metoda [`apply`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.apply.html) umožňuje použít libovolnou transformaci (definovanou jako funkci) na každý řádek v tabulce či hodnotu v `Series`. Obvykle se bez ní obejdeme a měli bychom (proto se jí tolik speciálně nevěnujeme), protože není příliš výpočetně efektivní. Tady nám ale usnadní pochopení, co se vlastně dělá, t.j. vybírá první prvek nějakého seznamu:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>tomatoes_rating</th>\n",
+       "      <th>tomatoes_votes</th>\n",
+       "      <th>title</th>\n",
+       "      <th>year</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>97</td>\n",
+       "      <td>444</td>\n",
+       "      <td>Black Panther</td>\n",
+       "      <td>2018</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>97</td>\n",
+       "      <td>394</td>\n",
+       "      <td>Mad Max: Fury Road</td>\n",
+       "      <td>2015</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>93</td>\n",
+       "      <td>410</td>\n",
+       "      <td>Wonder Woman</td>\n",
+       "      <td>2017</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>99</td>\n",
+       "      <td>118</td>\n",
+       "      <td>Metropolis</td>\n",
+       "      <td>1927</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>97</td>\n",
+       "      <td>308</td>\n",
+       "      <td>Coco</td>\n",
+       "      <td>2017</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1585</th>\n",
+       "      <td>15</td>\n",
+       "      <td>97</td>\n",
+       "      <td>Priest</td>\n",
+       "      <td>2011</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1586</th>\n",
+       "      <td>14</td>\n",
+       "      <td>103</td>\n",
+       "      <td>American Outlaws</td>\n",
+       "      <td>2001</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1587</th>\n",
+       "      <td>15</td>\n",
+       "      <td>54</td>\n",
+       "      <td>September Dawn</td>\n",
+       "      <td>2007</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1588</th>\n",
+       "      <td>12</td>\n",
+       "      <td>147</td>\n",
+       "      <td>Jonah Hex</td>\n",
+       "      <td>2010</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1589</th>\n",
+       "      <td>2</td>\n",
+       "      <td>51</td>\n",
+       "      <td>Texas Rangers</td>\n",
+       "      <td>2001</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>947 rows × 4 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      tomatoes_rating  tomatoes_votes               title  year\n",
+       "0                  97             444       Black Panther  2018\n",
+       "1                  97             394  Mad Max: Fury Road  2015\n",
+       "2                  93             410        Wonder Woman  2017\n",
+       "3                  99             118          Metropolis  1927\n",
+       "4                  97             308                Coco  2017\n",
+       "...               ...             ...                 ...   ...\n",
+       "1585               15              97              Priest  2011\n",
+       "1586               14             103    American Outlaws  2001\n",
+       "1587               15              54      September Dawn  2007\n",
+       "1588               12             147           Jonah Hex  2010\n",
+       "1589                2              51       Texas Rangers  2001\n",
+       "\n",
+       "[947 rows x 4 columns]"
+      ]
+     },
+     "execution_count": 45,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "def take_first(a_list):   # Funkce, kterou použijeme v apply\n",
+    "    return a_list[0]\n",
+    "\n",
+    "rotten_tomatoes = (rotten_tomatoes_beta\n",
+    "    .assign(\n",
+    "        title=split_title.apply(take_first)\n",
+    "    )\n",
+    ")\n",
+    "rotten_tomatoes"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>tomatoes_rating</th>\n",
+       "      <th>tomatoes_votes</th>\n",
+       "      <th>title</th>\n",
+       "      <th>year</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1539</th>\n",
+       "      <td>88</td>\n",
+       "      <td>42</td>\n",
+       "      <td>The Magnificent Seven</td>\n",
+       "      <td>1960</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1560</th>\n",
+       "      <td>63</td>\n",
+       "      <td>289</td>\n",
+       "      <td>The Magnificent Seven</td>\n",
+       "      <td>2016</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      tomatoes_rating  tomatoes_votes                  title  year\n",
+       "1539               88              42  The Magnificent Seven  1960\n",
+       "1560               63             289  The Magnificent Seven  2016"
+      ]
+     },
+     "execution_count": 46,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Zbavení se duplikátů hned na začátku nám zachovalo filmy se stejným jménem :-)\n",
+    "rotten_tomatoes.query(\"title == 'The Magnificent Seven'\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>title</th>\n",
+       "      <th>original_title</th>\n",
+       "      <th>is_adult</th>\n",
+       "      <th>year</th>\n",
+       "      <th>length</th>\n",
+       "      <th>genres</th>\n",
+       "      <th>tomatoes_rating</th>\n",
+       "      <th>tomatoes_votes</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>The Birth of a Nation</td>\n",
+       "      <td>The Birth of a Nation</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1915</td>\n",
+       "      <td>195</td>\n",
+       "      <td>Drama,History,War</td>\n",
+       "      <td>98</td>\n",
+       "      <td>40</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Battleship Potemkin</td>\n",
+       "      <td>Bronenosets Potemkin</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1925</td>\n",
+       "      <td>75</td>\n",
+       "      <td>Drama,History</td>\n",
+       "      <td>100</td>\n",
+       "      <td>45</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>The Gold Rush</td>\n",
+       "      <td>The Gold Rush</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1925</td>\n",
+       "      <td>95</td>\n",
+       "      <td>Adventure,Comedy,Drama</td>\n",
+       "      <td>100</td>\n",
+       "      <td>43</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Metropolis</td>\n",
+       "      <td>Metropolis</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1927</td>\n",
+       "      <td>153</td>\n",
+       "      <td>Drama,Sci-Fi</td>\n",
+       "      <td>99</td>\n",
+       "      <td>118</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>All Quiet on the Western Front</td>\n",
+       "      <td>All Quiet on the Western Front</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1930</td>\n",
+       "      <td>136</td>\n",
+       "      <td>Drama,War</td>\n",
+       "      <td>100</td>\n",
+       "      <td>42</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>654</th>\n",
+       "      <td>Three Identical Strangers</td>\n",
+       "      <td>Three Identical Strangers</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>96</td>\n",
+       "      <td>Biography,Documentary,Drama</td>\n",
+       "      <td>96</td>\n",
+       "      <td>157</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>655</th>\n",
+       "      <td>Searching</td>\n",
+       "      <td>Searching</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>102</td>\n",
+       "      <td>Drama,Mystery,Thriller</td>\n",
+       "      <td>92</td>\n",
+       "      <td>214</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>656</th>\n",
+       "      <td>Won't You Be My Neighbor?</td>\n",
+       "      <td>Won't You Be My Neighbor?</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>94</td>\n",
+       "      <td>Biography,Documentary</td>\n",
+       "      <td>98</td>\n",
+       "      <td>216</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>657</th>\n",
+       "      <td>RBG</td>\n",
+       "      <td>RBG</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>98</td>\n",
+       "      <td>Biography,Documentary</td>\n",
+       "      <td>95</td>\n",
+       "      <td>153</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>658</th>\n",
+       "      <td>Hereditary</td>\n",
+       "      <td>Hereditary</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>127</td>\n",
+       "      <td>Drama,Horror,Mystery</td>\n",
+       "      <td>89</td>\n",
+       "      <td>317</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>659 rows × 8 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                              title                  original_title  is_adult  \\\n",
+       "0             The Birth of a Nation           The Birth of a Nation     False   \n",
+       "1               Battleship Potemkin            Bronenosets Potemkin     False   \n",
+       "2                     The Gold Rush                   The Gold Rush     False   \n",
+       "3                        Metropolis                      Metropolis     False   \n",
+       "4    All Quiet on the Western Front  All Quiet on the Western Front     False   \n",
+       "..                              ...                             ...       ...   \n",
+       "654       Three Identical Strangers       Three Identical Strangers     False   \n",
+       "655                       Searching                       Searching     False   \n",
+       "656       Won't You Be My Neighbor?       Won't You Be My Neighbor?     False   \n",
+       "657                             RBG                             RBG     False   \n",
+       "658                      Hereditary                      Hereditary     False   \n",
+       "\n",
+       "     year  length                       genres  tomatoes_rating  \\\n",
+       "0    1915     195            Drama,History,War               98   \n",
+       "1    1925      75                Drama,History              100   \n",
+       "2    1925      95       Adventure,Comedy,Drama              100   \n",
+       "3    1927     153                 Drama,Sci-Fi               99   \n",
+       "4    1930     136                    Drama,War              100   \n",
+       "..    ...     ...                          ...              ...   \n",
+       "654  2018      96  Biography,Documentary,Drama               96   \n",
+       "655  2018     102       Drama,Mystery,Thriller               92   \n",
+       "656  2018      94        Biography,Documentary               98   \n",
+       "657  2018      98        Biography,Documentary               95   \n",
+       "658  2018     127         Drama,Horror,Mystery               89   \n",
+       "\n",
+       "     tomatoes_votes  \n",
+       "0                40  \n",
+       "1                45  \n",
+       "2                43  \n",
+       "3               118  \n",
+       "4                42  \n",
+       "..              ...  \n",
+       "654             157  \n",
+       "655             214  \n",
+       "656             216  \n",
+       "657             153  \n",
+       "658             317  \n",
+       "\n",
+       "[659 rows x 8 columns]"
+      ]
+     },
+     "execution_count": 47,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pd.merge(\n",
+    "    movies.dropna(subset=[\"year\"]),\n",
+    "    rotten_tomatoes,\n",
+    "    on=[\"title\", \"year\"],\n",
+    "    how=\"inner\"\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Když sloučíme filmy a hodnocení na Rotten Tomatoes, z 947 filmů se nám skoro tři sta ztratí. Bohužel zde je na vině především nestejnost zápisu názvu, různé uřčité členy, interpunkce, podnázvy apod. Coby řešení se tady nabízí spousta a spousta manuální práce, případně nějaká heuristika, která by na sebe pasovala \"hodně podobné\" názvy.\n",
+    "\n",
+    "*Mimochodem, obtížnost manuální práce se mezi vývojáři někdy přeceňuje: Opravit 288 názvů filmů může být práce na hodinu až dvě, zatímco psát algoritmus na \"řešení problému\" může trvat stejně dlouho, ne-li déle.*"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Čtvrtý (a poslední) join\n",
+    "\n",
+    "Dokončíme slučování všech čtyř tabulek:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>title</th>\n",
+       "      <th>original_title</th>\n",
+       "      <th>is_adult</th>\n",
+       "      <th>year</th>\n",
+       "      <th>length</th>\n",
+       "      <th>genres</th>\n",
+       "      <th>imdb_rating</th>\n",
+       "      <th>imdb_votes</th>\n",
+       "      <th>boxoffice_rank</th>\n",
+       "      <th>studio</th>\n",
+       "      <th>lifetime_gross</th>\n",
+       "      <th>tomatoes_rating</th>\n",
+       "      <th>tomatoes_votes</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Black Panther</td>\n",
+       "      <td>Black Panther</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>134</td>\n",
+       "      <td>Action,Adventure,Sci-Fi</td>\n",
+       "      <td>7.3</td>\n",
+       "      <td>489977</td>\n",
+       "      <td>3</td>\n",
+       "      <td>BV</td>\n",
+       "      <td>700059566</td>\n",
+       "      <td>97</td>\n",
+       "      <td>444</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Avengers: Infinity War</td>\n",
+       "      <td>Avengers: Infinity War</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>149</td>\n",
+       "      <td>Action,Adventure,Sci-Fi</td>\n",
+       "      <td>8.5</td>\n",
+       "      <td>616050</td>\n",
+       "      <td>4</td>\n",
+       "      <td>BV</td>\n",
+       "      <td>678815482</td>\n",
+       "      <td>84</td>\n",
+       "      <td>408</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Titanic</td>\n",
+       "      <td>Titanic</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1997</td>\n",
+       "      <td>194</td>\n",
+       "      <td>Drama,Romance</td>\n",
+       "      <td>7.8</td>\n",
+       "      <td>945889</td>\n",
+       "      <td>5</td>\n",
+       "      <td>Par.</td>\n",
+       "      <td>659363944</td>\n",
+       "      <td>89</td>\n",
+       "      <td>184</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Incredibles 2</td>\n",
+       "      <td>Incredibles 2</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>118</td>\n",
+       "      <td>Action,Adventure,Animation</td>\n",
+       "      <td>7.7</td>\n",
+       "      <td>192301</td>\n",
+       "      <td>9</td>\n",
+       "      <td>BV</td>\n",
+       "      <td>608581744</td>\n",
+       "      <td>94</td>\n",
+       "      <td>332</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>The Dark Knight</td>\n",
+       "      <td>The Dark Knight</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2008</td>\n",
+       "      <td>152</td>\n",
+       "      <td>Action,Crime,Drama</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>2037678</td>\n",
+       "      <td>10</td>\n",
+       "      <td>WB</td>\n",
+       "      <td>535234033</td>\n",
+       "      <td>94</td>\n",
+       "      <td>332</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>469</th>\n",
+       "      <td>Boxing Gym</td>\n",
+       "      <td>Boxing Gym</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2010</td>\n",
+       "      <td>91</td>\n",
+       "      <td>Documentary</td>\n",
+       "      <td>7.1</td>\n",
+       "      <td>389</td>\n",
+       "      <td>12999</td>\n",
+       "      <td>Zipp.</td>\n",
+       "      <td>32476</td>\n",
+       "      <td>95</td>\n",
+       "      <td>42</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>470</th>\n",
+       "      <td>Red Hill</td>\n",
+       "      <td>Red Hill</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2010</td>\n",
+       "      <td>95</td>\n",
+       "      <td>Thriller,Western</td>\n",
+       "      <td>6.4</td>\n",
+       "      <td>7844</td>\n",
+       "      <td>13681</td>\n",
+       "      <td>Strand</td>\n",
+       "      <td>21087</td>\n",
+       "      <td>78</td>\n",
+       "      <td>65</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>471</th>\n",
+       "      <td>City Lights</td>\n",
+       "      <td>City Lights</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1931</td>\n",
+       "      <td>87</td>\n",
+       "      <td>Comedy,Drama,Romance</td>\n",
+       "      <td>8.5</td>\n",
+       "      <td>144261</td>\n",
+       "      <td>13827</td>\n",
+       "      <td>UA</td>\n",
+       "      <td>19181</td>\n",
+       "      <td>98</td>\n",
+       "      <td>45</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>472</th>\n",
+       "      <td>Minding the Gap</td>\n",
+       "      <td>Minding the Gap</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>93</td>\n",
+       "      <td>Documentary</td>\n",
+       "      <td>8.1</td>\n",
+       "      <td>4119</td>\n",
+       "      <td>14471</td>\n",
+       "      <td>Magn.</td>\n",
+       "      <td>11998</td>\n",
+       "      <td>100</td>\n",
+       "      <td>63</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>473</th>\n",
+       "      <td>The Autopsy of Jane Doe</td>\n",
+       "      <td>The Autopsy of Jane Doe</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2016</td>\n",
+       "      <td>86</td>\n",
+       "      <td>Horror,Mystery,Thriller</td>\n",
+       "      <td>6.8</td>\n",
+       "      <td>73965</td>\n",
+       "      <td>14657</td>\n",
+       "      <td>IFC</td>\n",
+       "      <td>10474</td>\n",
+       "      <td>87</td>\n",
+       "      <td>98</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>474 rows × 13 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                       title           original_title  is_adult  year  length  \\\n",
+       "0              Black Panther            Black Panther     False  2018     134   \n",
+       "1     Avengers: Infinity War   Avengers: Infinity War     False  2018     149   \n",
+       "2                    Titanic                  Titanic     False  1997     194   \n",
+       "3              Incredibles 2            Incredibles 2     False  2018     118   \n",
+       "4            The Dark Knight          The Dark Knight     False  2008     152   \n",
+       "..                       ...                      ...       ...   ...     ...   \n",
+       "469               Boxing Gym               Boxing Gym     False  2010      91   \n",
+       "470                 Red Hill                 Red Hill     False  2010      95   \n",
+       "471              City Lights              City Lights     False  1931      87   \n",
+       "472          Minding the Gap          Minding the Gap     False  2018      93   \n",
+       "473  The Autopsy of Jane Doe  The Autopsy of Jane Doe     False  2016      86   \n",
+       "\n",
+       "                         genres  imdb_rating  imdb_votes  boxoffice_rank  \\\n",
+       "0       Action,Adventure,Sci-Fi          7.3      489977               3   \n",
+       "1       Action,Adventure,Sci-Fi          8.5      616050               4   \n",
+       "2                 Drama,Romance          7.8      945889               5   \n",
+       "3    Action,Adventure,Animation          7.7      192301               9   \n",
+       "4            Action,Crime,Drama          9.0     2037678              10   \n",
+       "..                          ...          ...         ...             ...   \n",
+       "469                 Documentary          7.1         389           12999   \n",
+       "470            Thriller,Western          6.4        7844           13681   \n",
+       "471        Comedy,Drama,Romance          8.5      144261           13827   \n",
+       "472                 Documentary          8.1        4119           14471   \n",
+       "473     Horror,Mystery,Thriller          6.8       73965           14657   \n",
+       "\n",
+       "     studio  lifetime_gross  tomatoes_rating  tomatoes_votes  \n",
+       "0        BV       700059566               97             444  \n",
+       "1        BV       678815482               84             408  \n",
+       "2      Par.       659363944               89             184  \n",
+       "3        BV       608581744               94             332  \n",
+       "4        WB       535234033               94             332  \n",
+       "..      ...             ...              ...             ...  \n",
+       "469   Zipp.           32476               95              42  \n",
+       "470  Strand           21087               78              65  \n",
+       "471      UA           19181               98              45  \n",
+       "472   Magn.           11998              100              63  \n",
+       "473     IFC           10474               87              98  \n",
+       "\n",
+       "[474 rows x 13 columns]"
+      ]
+     },
+     "execution_count": 48,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "movies_complete = pd.merge(\n",
+    "    movies_with_rating_and_boxoffice,\n",
+    "    rotten_tomatoes,\n",
+    "    on=[\"title\", \"year\"],\n",
+    "    how=\"inner\"\n",
+    ")\n",
+    "movies_complete.sort_values(\"boxoffice_rank\").reset_index(drop=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "A přišli jsme o dalších 175 filmů. \n",
+    "\n",
+    "Co dál? Pokud by toto byl skutečný úkol, museli bychom se s tím nějak vypořádat - zkoumat, proč které řádky nesedí, v čem se liší názvy stejného filmu v různých datových sadách, jinými slovy *manuální práce, práce, práce...*\n",
+    "\n",
+    "Naštěstí to je úkol jen ukázkový, a my můžeme být spokojeni, že máme sice neúplnou, ale přesto použitelnou datovou sadu :-)"
+   ]
+  }
+ ],
+ "metadata": {
+  "interpreter": {
+   "hash": "31f2aee4e71d21fbe5cf8b01ff0e069b9275f58929596ceb00d14d90e3e16cd6"
+  },
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/lessons/pydata/pandas_joins/info.yml b/lessons/pydata/pandas_joins/info.yml
new file mode 100644
index 0000000..1e45f47
--- /dev/null
+++ b/lessons/pydata/pandas_joins/info.yml
@@ -0,0 +1,4 @@
+title: Pandas - spojování tabulek a vztahy mezi více proměnnými
+style: ipynb
+attribution: Pro PyDataCZ napsal Jan Pipek, 2020.
+license: cc-by-sa-40
\ No newline at end of file
diff --git a/lessons/pydata/pandas_correlations/rotten_tomatoes_top_movies_2019-01-15.csv b/lessons/pydata/pandas_joins/rotten_tomatoes_top_movies_2019-01-15.csv
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rename to lessons/pydata/pandas_joins/rotten_tomatoes_top_movies_2019-01-15.csv
diff --git a/lessons/pydata/pandas_correlations/static/joins.svg b/lessons/pydata/pandas_joins/static/joins.svg
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rename from lessons/pydata/pandas_correlations/static/joins.svg
rename to lessons/pydata/pandas_joins/static/joins.svg
diff --git a/lessons/pydata/pandas_correlations/title.basics.tsv.gz b/lessons/pydata/pandas_joins/title.basics.tsv.gz
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rename from lessons/pydata/pandas_correlations/title.basics.tsv.gz
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diff --git a/lessons/pydata/pandas_correlations/title.ratings.tsv.gz b/lessons/pydata/pandas_joins/title.ratings.tsv.gz
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