task_event_2_I Putu Andika Bagas Jiwanta.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Tugas Event 2 : Solving Real Problems with Data Science\n",
    "\n",
    "    nama : I Putu Andika Bagas Jiwanta\n",
    "    NIM : 16520313\n",
    "    Universitas : ITB\n",
    "    Tanggal mulai : 10 November 2020\n",
    "    Dataset : country_wise_latest\n",
    "    Sumber data : https://www.kaggle.com/imdevskp/corona-virus-report"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Country_wise_latest\n",
    "\n",
    "    Data ini berisi tentang informasi mengenai covid di hampir setiap negara\n",
    "    Data diupload per hari oleh pemiliknya dan data yang saya gunakan disini terakhir pada tanggal 14 November 2020"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data observation and preparation\n",
    "\n",
    "    Pada analisis ini, saya akan menganalisis hubungan-hubungan naik dan turunnya covid khusus di asia tenggara\n",
    "    dan membuat model yang menganalisis berapa tambahan kasus minggu ini dengan rasio 80 persen untuk training\n",
    "    dan 20 persen untuk testing\n",
    "   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Importing libraries\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Inserting data\n",
    "df = pd.read_csv('country_wise_latest.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Dataset Info"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 187 entries, 0 to 186\n",
      "Data columns (total 15 columns):\n",
      " #   Column                  Non-Null Count  Dtype  \n",
      "---  ------                  --------------  -----  \n",
      " 0   Country/Region          187 non-null    object \n",
      " 1   Confirmed               187 non-null    int64  \n",
      " 2   Deaths                  187 non-null    int64  \n",
      " 3   Recovered               187 non-null    int64  \n",
      " 4   Active                  187 non-null    int64  \n",
      " 5   New cases               187 non-null    int64  \n",
      " 6   New deaths              187 non-null    int64  \n",
      " 7   New recovered           187 non-null    int64  \n",
      " 8   Deaths / 100 Cases      187 non-null    float64\n",
      " 9   Recovered / 100 Cases   187 non-null    float64\n",
      " 10  Deaths / 100 Recovered  187 non-null    float64\n",
      " 11  Confirmed last week     187 non-null    int64  \n",
      " 12  1 week change           187 non-null    int64  \n",
      " 13  1 week % increase       187 non-null    float64\n",
      " 14  WHO Region              187 non-null    object \n",
      "dtypes: float64(4), int64(9), object(2)\n",
      "memory usage: 22.0+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Data kita tidak memiliki nilai null, sehingga tidak perlu cleaning alias data sudah bersih "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\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>Country/Region</th>\n",
       "      <th>Confirmed</th>\n",
       "      <th>Deaths</th>\n",
       "      <th>Recovered</th>\n",
       "      <th>Active</th>\n",
       "      <th>New cases</th>\n",
       "      <th>New deaths</th>\n",
       "      <th>New recovered</th>\n",
       "      <th>Deaths / 100 Cases</th>\n",
       "      <th>Recovered / 100 Cases</th>\n",
       "      <th>Deaths / 100 Recovered</th>\n",
       "      <th>Confirmed last week</th>\n",
       "      <th>1 week change</th>\n",
       "      <th>1 week % increase</th>\n",
       "      <th>WHO Region</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>36263</td>\n",
       "      <td>1269</td>\n",
       "      <td>25198</td>\n",
       "      <td>9796</td>\n",
       "      <td>106</td>\n",
       "      <td>10</td>\n",
       "      <td>18</td>\n",
       "      <td>3.50</td>\n",
       "      <td>69.49</td>\n",
       "      <td>5.04</td>\n",
       "      <td>35526</td>\n",
       "      <td>737</td>\n",
       "      <td>2.07</td>\n",
       "      <td>Eastern Mediterranean</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Albania</td>\n",
       "      <td>4880</td>\n",
       "      <td>144</td>\n",
       "      <td>2745</td>\n",
       "      <td>1991</td>\n",
       "      <td>117</td>\n",
       "      <td>6</td>\n",
       "      <td>63</td>\n",
       "      <td>2.95</td>\n",
       "      <td>56.25</td>\n",
       "      <td>5.25</td>\n",
       "      <td>4171</td>\n",
       "      <td>709</td>\n",
       "      <td>17.00</td>\n",
       "      <td>Europe</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Algeria</td>\n",
       "      <td>27973</td>\n",
       "      <td>1163</td>\n",
       "      <td>18837</td>\n",
       "      <td>7973</td>\n",
       "      <td>616</td>\n",
       "      <td>8</td>\n",
       "      <td>749</td>\n",
       "      <td>4.16</td>\n",
       "      <td>67.34</td>\n",
       "      <td>6.17</td>\n",
       "      <td>23691</td>\n",
       "      <td>4282</td>\n",
       "      <td>18.07</td>\n",
       "      <td>Africa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Andorra</td>\n",
       "      <td>907</td>\n",
       "      <td>52</td>\n",
       "      <td>803</td>\n",
       "      <td>52</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5.73</td>\n",
       "      <td>88.53</td>\n",
       "      <td>6.48</td>\n",
       "      <td>884</td>\n",
       "      <td>23</td>\n",
       "      <td>2.60</td>\n",
       "      <td>Europe</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Angola</td>\n",
       "      <td>950</td>\n",
       "      <td>41</td>\n",
       "      <td>242</td>\n",
       "      <td>667</td>\n",
       "      <td>18</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4.32</td>\n",
       "      <td>25.47</td>\n",
       "      <td>16.94</td>\n",
       "      <td>749</td>\n",
       "      <td>201</td>\n",
       "      <td>26.84</td>\n",
       "      <td>Africa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Antigua and Barbuda</td>\n",
       "      <td>86</td>\n",
       "      <td>3</td>\n",
       "      <td>65</td>\n",
       "      <td>18</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>3.49</td>\n",
       "      <td>75.58</td>\n",
       "      <td>4.62</td>\n",
       "      <td>76</td>\n",
       "      <td>10</td>\n",
       "      <td>13.16</td>\n",
       "      <td>Americas</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Country/Region  Confirmed  Deaths  Recovered  Active  New cases  \\\n",
       "0          Afghanistan      36263    1269      25198    9796        106   \n",
       "1              Albania       4880     144       2745    1991        117   \n",
       "2              Algeria      27973    1163      18837    7973        616   \n",
       "3              Andorra        907      52        803      52         10   \n",
       "4               Angola        950      41        242     667         18   \n",
       "5  Antigua and Barbuda         86       3         65      18          4   \n",
       "\n",
       "   New deaths  New recovered  Deaths / 100 Cases  Recovered / 100 Cases  \\\n",
       "0          10             18                3.50                  69.49   \n",
       "1           6             63                2.95                  56.25   \n",
       "2           8            749                4.16                  67.34   \n",
       "3           0              0                5.73                  88.53   \n",
       "4           1              0                4.32                  25.47   \n",
       "5           0              5                3.49                  75.58   \n",
       "\n",
       "   Deaths / 100 Recovered  Confirmed last week  1 week change  \\\n",
       "0                    5.04                35526            737   \n",
       "1                    5.25                 4171            709   \n",
       "2                    6.17                23691           4282   \n",
       "3                    6.48                  884             23   \n",
       "4                   16.94                  749            201   \n",
       "5                    4.62                   76             10   \n",
       "\n",
       "   1 week % increase             WHO Region  \n",
       "0               2.07  Eastern Mediterranean  \n",
       "1              17.00                 Europe  \n",
       "2              18.07                 Africa  \n",
       "3               2.60                 Europe  \n",
       "4              26.84                 Africa  \n",
       "5              13.16               Americas  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#melihat data\n",
    "df.head(6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Confirmed</th>\n",
       "      <th>Deaths</th>\n",
       "      <th>Recovered</th>\n",
       "      <th>Active</th>\n",
       "      <th>New cases</th>\n",
       "      <th>New deaths</th>\n",
       "      <th>New recovered</th>\n",
       "      <th>Deaths / 100 Cases</th>\n",
       "      <th>Recovered / 100 Cases</th>\n",
       "      <th>Deaths / 100 Recovered</th>\n",
       "      <th>Confirmed last week</th>\n",
       "      <th>1 week change</th>\n",
       "      <th>1 week % increase</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1.870000e+02</td>\n",
       "      <td>187.000000</td>\n",
       "      <td>1.870000e+02</td>\n",
       "      <td>1.870000e+02</td>\n",
       "      <td>187.000000</td>\n",
       "      <td>187.000000</td>\n",
       "      <td>187.000000</td>\n",
       "      <td>187.000000</td>\n",
       "      <td>187.000000</td>\n",
       "      <td>187.00</td>\n",
       "      <td>1.870000e+02</td>\n",
       "      <td>187.000000</td>\n",
       "      <td>187.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>8.813094e+04</td>\n",
       "      <td>3497.518717</td>\n",
       "      <td>5.063148e+04</td>\n",
       "      <td>3.400194e+04</td>\n",
       "      <td>1222.957219</td>\n",
       "      <td>28.957219</td>\n",
       "      <td>933.812834</td>\n",
       "      <td>3.019519</td>\n",
       "      <td>64.820535</td>\n",
       "      <td>inf</td>\n",
       "      <td>7.868248e+04</td>\n",
       "      <td>9448.459893</td>\n",
       "      <td>13.606203</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>3.833187e+05</td>\n",
       "      <td>14100.002482</td>\n",
       "      <td>1.901882e+05</td>\n",
       "      <td>2.133262e+05</td>\n",
       "      <td>5710.374790</td>\n",
       "      <td>120.037173</td>\n",
       "      <td>4197.719635</td>\n",
       "      <td>3.454302</td>\n",
       "      <td>26.287694</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.382737e+05</td>\n",
       "      <td>47491.127684</td>\n",
       "      <td>24.509838</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000e+01</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.000000e+01</td>\n",
       "      <td>-47.000000</td>\n",
       "      <td>-3.840000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.114000e+03</td>\n",
       "      <td>18.500000</td>\n",
       "      <td>6.265000e+02</td>\n",
       "      <td>1.415000e+02</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.945000</td>\n",
       "      <td>48.770000</td>\n",
       "      <td>1.45</td>\n",
       "      <td>1.051500e+03</td>\n",
       "      <td>49.000000</td>\n",
       "      <td>2.775000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>5.059000e+03</td>\n",
       "      <td>108.000000</td>\n",
       "      <td>2.815000e+03</td>\n",
       "      <td>1.600000e+03</td>\n",
       "      <td>49.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>22.000000</td>\n",
       "      <td>2.150000</td>\n",
       "      <td>71.320000</td>\n",
       "      <td>3.62</td>\n",
       "      <td>5.020000e+03</td>\n",
       "      <td>432.000000</td>\n",
       "      <td>6.890000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>4.046050e+04</td>\n",
       "      <td>734.000000</td>\n",
       "      <td>2.260600e+04</td>\n",
       "      <td>9.149000e+03</td>\n",
       "      <td>419.500000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>221.000000</td>\n",
       "      <td>3.875000</td>\n",
       "      <td>86.885000</td>\n",
       "      <td>6.44</td>\n",
       "      <td>3.708050e+04</td>\n",
       "      <td>3172.000000</td>\n",
       "      <td>16.855000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>4.290259e+06</td>\n",
       "      <td>148011.000000</td>\n",
       "      <td>1.846641e+06</td>\n",
       "      <td>2.816444e+06</td>\n",
       "      <td>56336.000000</td>\n",
       "      <td>1076.000000</td>\n",
       "      <td>33728.000000</td>\n",
       "      <td>28.560000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>inf</td>\n",
       "      <td>3.834677e+06</td>\n",
       "      <td>455582.000000</td>\n",
       "      <td>226.320000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Confirmed         Deaths     Recovered        Active     New cases  \\\n",
       "count  1.870000e+02     187.000000  1.870000e+02  1.870000e+02    187.000000   \n",
       "mean   8.813094e+04    3497.518717  5.063148e+04  3.400194e+04   1222.957219   \n",
       "std    3.833187e+05   14100.002482  1.901882e+05  2.133262e+05   5710.374790   \n",
       "min    1.000000e+01       0.000000  0.000000e+00  0.000000e+00      0.000000   \n",
       "25%    1.114000e+03      18.500000  6.265000e+02  1.415000e+02      4.000000   \n",
       "50%    5.059000e+03     108.000000  2.815000e+03  1.600000e+03     49.000000   \n",
       "75%    4.046050e+04     734.000000  2.260600e+04  9.149000e+03    419.500000   \n",
       "max    4.290259e+06  148011.000000  1.846641e+06  2.816444e+06  56336.000000   \n",
       "\n",
       "        New deaths  New recovered  Deaths / 100 Cases  Recovered / 100 Cases  \\\n",
       "count   187.000000     187.000000          187.000000             187.000000   \n",
       "mean     28.957219     933.812834            3.019519              64.820535   \n",
       "std     120.037173    4197.719635            3.454302              26.287694   \n",
       "min       0.000000       0.000000            0.000000               0.000000   \n",
       "25%       0.000000       0.000000            0.945000              48.770000   \n",
       "50%       1.000000      22.000000            2.150000              71.320000   \n",
       "75%       6.000000     221.000000            3.875000              86.885000   \n",
       "max    1076.000000   33728.000000           28.560000             100.000000   \n",
       "\n",
       "       Deaths / 100 Recovered  Confirmed last week  1 week change  \\\n",
       "count                  187.00         1.870000e+02     187.000000   \n",
       "mean                      inf         7.868248e+04    9448.459893   \n",
       "std                       NaN         3.382737e+05   47491.127684   \n",
       "min                      0.00         1.000000e+01     -47.000000   \n",
       "25%                      1.45         1.051500e+03      49.000000   \n",
       "50%                      3.62         5.020000e+03     432.000000   \n",
       "75%                      6.44         3.708050e+04    3172.000000   \n",
       "max                       inf         3.834677e+06  455582.000000   \n",
       "\n",
       "       1 week % increase  \n",
       "count         187.000000  \n",
       "mean           13.606203  \n",
       "std            24.509838  \n",
       "min            -3.840000  \n",
       "25%             2.775000  \n",
       "50%             6.890000  \n",
       "75%            16.855000  \n",
       "max           226.320000  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Melihat statistik dasar dari data\n",
    "df.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Visualization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Grafik 1 sembuh terhadap jumlah kasus\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.regplot( x = \"Recovered\" , y = \"Confirmed\" , data = df)\n",
    "print('Grafik 1 sembuh terhadap jumlah kasus')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Grafik 2 kematian terhadap jumlah kasus\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.regplot( x = \"Deaths\" , y = \"Confirmed\" , data = df)\n",
    "print('Grafik 2 kematian terhadap jumlah kasus')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Grafik 3, persentase kematian tiap region\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.catplot(x = 'WHO Region', y = 'Deaths / 100 Cases', data = df)\n",
    "print(\"Grafik 3, persentase kematian tiap region\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Grafik 4, Persentase sembuh per region\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.catplot(x = 'WHO Region', y = 'Recovered / 100 Cases', data = df)\n",
    "print(\"Grafik 4, Persentase sembuh per region\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Presentation "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "    Dari grafik 1 dan 2 diatas, diambil beberapa kesimpulan :\n",
    "    Kemiringan grafik kematian masih lebih besar daripada kemiringan dari grafik sembuh \n",
    "    hal ini berarti pandemi Covid 19 masih belum dalam kendali manusia \n",
    "    \n",
    "    Dari grafik 3 dan 4 diatas, dapat diambil beberapa kesimpulan :\n",
    "    1. Wilayah eropa, afrika, dan amerika masih memiliki jumlah kematian yang cukup tinggi dibandingkan\n",
    "    dengan daerah lainnya\n",
    "    2. Wilayah timur tengah, eropa, afrika, dan amerika masih kurang dalam hal penyembuhan kasus\n",
    "    3. Wilayah Pasifik dan Asia tenggara terbilang cukup baik dalam menangani kasus covid "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}