04-05-pandas_rows_Logic_in_Python_(and_pandas).ipynb

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   "source": [
    "## Logic in Python (and pandas)\n",
    "* https://pandas.pydata.org/Pandas_Cheat_Sheet.pdf"
   ]
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       "       a    b     c\n",
       "n v                \n",
       "d 1  4.0  7.0  10.0\n",
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     "execution_count": 1,
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   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "df = pd.DataFrame(\n",
    "        {\"a\" : [4 ,5, 6, 6, np.nan],\n",
    "        \"b\" : [7, 8, np.nan, 9, 9],\n",
    "        \"c\" : [10, 11, 12, np.nan, 12]},\n",
    "        index = pd.MultiIndex.from_tuples(\n",
    "        [('d',1),('d',2),('e',2),('e',3),('e',4)],\n",
    "        names=['n','v']))\n",
    "df"
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       "       a    b     c\n",
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    "df.head()"
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       "       a    b     c\n",
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    "df[df[\"b\"] != 7]"
   ]
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       "n  v\n",
       "d  1    False\n",
       "   2     True\n",
       "e  2    False\n",
       "   3    False\n",
       "   4    False\n",
       "Name: a, dtype: bool"
      ]
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     "execution_count": 4,
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   "source": [
    "df['a'].isin([5])"
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       "         a      b      c\n",
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    "pd.notnull(df)"
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   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "a    4\n",
       "b    4\n",
       "c    4\n",
       "dtype: int64"
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     "execution_count": 8,
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    {
     "data": {
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       "n  v\n",
       "d  1     True\n",
       "   2     True\n",
       "e  2     True\n",
       "   3     True\n",
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       "Name: a, dtype: bool"
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     "execution_count": 9,
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   "source": [
    "df.a.notnull()"
   ]
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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* &,|,~,^,df.any(),df.all() \n",
    "* and, or, not, xor, any, all"
   ]
  },
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    "df = pd.DataFrame({'a': [1, 10, 8, 11, -1],\n",
    "                'b': list('abdce'),\n",
    "                'c': [1.0, 2.0, np.nan, 3.0, 4.0]})\n",
    "df"
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       "4  -1  e  4.0  True  False   True"
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     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Return whether all elements are True, potentially over an axis.\n",
    "# all, any 기능을 알아보기 위해 d, e 컬럼을 만들고 \n",
    "# d에는 모두 True를 e에는 False 를 f에는 하나만 False를 생성\n",
    "df[\"d\"] = True\n",
    "df[\"e\"] = False\n",
    "df[\"f\"] = True\n",
    "df.loc[1, \"f\"] = False\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "a     True\n",
       "b     True\n",
       "c     True\n",
       "d     True\n",
       "e    False\n",
       "f    False\n",
       "dtype: bool"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Return whether all elements are True, potentially over an axis.\n",
    "# True, False 형태로 되어있는 컬럼에서 True, False 여부를 확인\n",
    "# df.all()은 모두 True 일때만 True로 출력\n",
    "df.all()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "a     True\n",
       "b     True\n",
       "c     True\n",
       "d     True\n",
       "e    False\n",
       "f     True\n",
       "dtype: bool"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Return whether any element is True, potentially over an axis.\n",
    "# df.any()는 하나라도 True 라면 True로 출력\n",
    "df.any()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "a     True\n",
       "b     True\n",
       "c     True\n",
       "d     True\n",
       "e    False\n",
       "f     True\n",
       "dtype: bool"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# df.any()는 하나라도 False 라면 True로 출력\n",
    "df.any()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
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       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "<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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
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       "      <th>2</th>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      a     b      c     d     e     f\n",
       "0  True  True   True  True  True  True\n",
       "1  True  True   True  True  True  True\n",
       "2  True  True  False  True  True  True\n",
       "3  True  True   True  True  True  True\n",
       "4  True  True   True  True  True  True"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 응용 : 결측치 여부를 True(결측치아님) False(결측치)로 구함\n",
    "df.notnull()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "a     True\n",
       "b     True\n",
       "c    False\n",
       "d     True\n",
       "e     True\n",
       "f     True\n",
       "dtype: bool"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# notnull 로 결측치 여부를 확인하고 결측치가 하나라도 있는 컬럼을 찾음\n",
    "df.notnull().all()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "a    True\n",
       "b    True\n",
       "c    True\n",
       "d    True\n",
       "e    True\n",
       "f    True\n",
       "dtype: bool"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.notnull().any()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "a    False\n",
       "b    False\n",
       "c     True\n",
       "d    False\n",
       "e    False\n",
       "f    False\n",
       "dtype: bool"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# isnull로 결측치 여부를 확인하고 결측치가 하나라도 있는 컬럼을 찾음\n",
    "df.isnull().any()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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