DataWrangling.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "f191929a",
   "metadata": {},
   "source": [
    "# Notebook used to used to load csv files into Pandas DataFrames, reformat and store."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "e63088be",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib\n",
    "import datetime as dt\n",
    "import pickle\n",
    "import seaborn as sns\n",
    "sns.set(rc={'figure.figsize':(11.7,8.27)})\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fcbeb0c7",
   "metadata": {},
   "source": [
    "# Load the three data files, inspect, merge and split by 2010-11/2012"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "c1bfe798",
   "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>Store</th>\n",
       "      <th>Type</th>\n",
       "      <th>Size</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>A</td>\n",
       "      <td>151315</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>A</td>\n",
       "      <td>202307</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Store Type    Size\n",
       "0      1    A  151315\n",
       "1      2    A  202307"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_stores = pd.read_csv('../data/original_data/stores data-set.csv')\n",
    "df_stores.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "82374884",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 45 entries, 0 to 44\n",
      "Data columns (total 3 columns):\n",
      " #   Column  Non-Null Count  Dtype \n",
      "---  ------  --------------  ----- \n",
      " 0   Store   45 non-null     int64 \n",
      " 1   Type    45 non-null     object\n",
      " 2   Size    45 non-null     int64 \n",
      "dtypes: int64(2), object(1)\n",
      "memory usage: 1.2+ KB\n"
     ]
    }
   ],
   "source": [
    "df_stores.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "d67bfa64",
   "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>Store</th>\n",
       "      <th>Date</th>\n",
       "      <th>Temperature</th>\n",
       "      <th>Fuel_Price</th>\n",
       "      <th>MarkDown1</th>\n",
       "      <th>MarkDown2</th>\n",
       "      <th>MarkDown3</th>\n",
       "      <th>MarkDown4</th>\n",
       "      <th>MarkDown5</th>\n",
       "      <th>CPI</th>\n",
       "      <th>Unemployment</th>\n",
       "      <th>IsHoliday</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>05/02/2010</td>\n",
       "      <td>42.31</td>\n",
       "      <td>2.572</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>211.096358</td>\n",
       "      <td>8.106</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>12/02/2010</td>\n",
       "      <td>38.51</td>\n",
       "      <td>2.548</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>211.242170</td>\n",
       "      <td>8.106</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Store        Date  Temperature  Fuel_Price  MarkDown1  MarkDown2  \\\n",
       "0      1  05/02/2010        42.31       2.572        NaN        NaN   \n",
       "1      1  12/02/2010        38.51       2.548        NaN        NaN   \n",
       "\n",
       "   MarkDown3  MarkDown4  MarkDown5         CPI  Unemployment  IsHoliday  \n",
       "0        NaN        NaN        NaN  211.096358         8.106      False  \n",
       "1        NaN        NaN        NaN  211.242170         8.106       True  "
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_features = pd.read_csv('../data/original_data/Features data set.csv')\n",
    "df_features.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "dd4622c7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 8190 entries, 0 to 8189\n",
      "Data columns (total 12 columns):\n",
      " #   Column        Non-Null Count  Dtype  \n",
      "---  ------        --------------  -----  \n",
      " 0   Store         8190 non-null   int64  \n",
      " 1   Date          8190 non-null   object \n",
      " 2   Temperature   8190 non-null   float64\n",
      " 3   Fuel_Price    8190 non-null   float64\n",
      " 4   MarkDown1     4032 non-null   float64\n",
      " 5   MarkDown2     2921 non-null   float64\n",
      " 6   MarkDown3     3613 non-null   float64\n",
      " 7   MarkDown4     3464 non-null   float64\n",
      " 8   MarkDown5     4050 non-null   float64\n",
      " 9   CPI           7605 non-null   float64\n",
      " 10  Unemployment  7605 non-null   float64\n",
      " 11  IsHoliday     8190 non-null   bool   \n",
      "dtypes: bool(1), float64(9), int64(1), object(1)\n",
      "memory usage: 712.0+ KB\n"
     ]
    }
   ],
   "source": [
    "df_features.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "994360d8",
   "metadata": {},
   "source": [
    "## Several columns appear to have null values - fillna with zeros"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "e2ac0298",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_features.fillna(0, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7661dccf",
   "metadata": {},
   "source": [
    "## Convert dates to datetime with format \"%d/%m/%Y\" "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "87d2fef8",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_features['Date']= pd.to_datetime(df_features['Date'], format='%d/%m/%Y')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "fc82c7b7",
   "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>Store</th>\n",
       "      <th>Dept</th>\n",
       "      <th>Date</th>\n",
       "      <th>Weekly_Sales</th>\n",
       "      <th>IsHoliday</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>05/02/2010</td>\n",
       "      <td>24924.50</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>12/02/2010</td>\n",
       "      <td>46039.49</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Store  Dept        Date  Weekly_Sales  IsHoliday\n",
       "0      1     1  05/02/2010      24924.50      False\n",
       "1      1     1  12/02/2010      46039.49       True"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sales = pd.read_csv('../data/original_data/sales data-set.csv')\n",
    "df_sales.drop([\"Unnamed: 5\", \"Unnamed: 6\"], axis=1, inplace=True)\n",
    "df_sales.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "ff035266",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 421570 entries, 0 to 421569\n",
      "Data columns (total 5 columns):\n",
      " #   Column        Non-Null Count   Dtype  \n",
      "---  ------        --------------   -----  \n",
      " 0   Store         421570 non-null  int64  \n",
      " 1   Dept          421570 non-null  int64  \n",
      " 2   Date          421570 non-null  object \n",
      " 3   Weekly_Sales  421570 non-null  float64\n",
      " 4   IsHoliday     421570 non-null  bool   \n",
      "dtypes: bool(1), float64(1), int64(2), object(1)\n",
      "memory usage: 13.3+ MB\n"
     ]
    }
   ],
   "source": [
    "df_sales.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "1ad462a0",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_sales['Date'] = pd.to_datetime(df_sales[\"Date\"], format=\"%d/%m/%Y\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "5ca1dbd4",
   "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>Store</th>\n",
       "      <th>Dept</th>\n",
       "      <th>Weekly_Sales</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>421570.000000</td>\n",
       "      <td>421570.000000</td>\n",
       "      <td>421570.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>22.200546</td>\n",
       "      <td>44.260317</td>\n",
       "      <td>15981.258123</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>12.785297</td>\n",
       "      <td>30.492054</td>\n",
       "      <td>22711.183519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-4988.940000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>11.000000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>2079.650000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>22.000000</td>\n",
       "      <td>37.000000</td>\n",
       "      <td>7612.030000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>33.000000</td>\n",
       "      <td>74.000000</td>\n",
       "      <td>20205.852500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>45.000000</td>\n",
       "      <td>99.000000</td>\n",
       "      <td>693099.360000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               Store           Dept   Weekly_Sales\n",
       "count  421570.000000  421570.000000  421570.000000\n",
       "mean       22.200546      44.260317   15981.258123\n",
       "std        12.785297      30.492054   22711.183519\n",
       "min         1.000000       1.000000   -4988.940000\n",
       "25%        11.000000      18.000000    2079.650000\n",
       "50%        22.000000      37.000000    7612.030000\n",
       "75%        33.000000      74.000000   20205.852500\n",
       "max        45.000000      99.000000  693099.360000"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sales.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1f5f866c",
   "metadata": {},
   "source": [
    "## Quick fix to remove negative values from Weekly_Sales data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "75ace367",
   "metadata": {},
   "outputs": [],
   "source": [
    "# num = df_sales._get_numeric_data()\n",
    "# num[num < 0] = 0"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "74f5b28f",
   "metadata": {},
   "source": [
    "# Merge the 3 DataFrames"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "c19d74f7",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_features_sales = pd.merge(df_features, df_sales, left_on =['Store','Date','IsHoliday'],\n",
    "                             right_on=['Store','Date','IsHoliday'])\n",
    "\n",
    "df_final = pd.merge(df_features_sales,df_stores, left_on =['Store'],right_on=['Store'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "e4cee6f2",
   "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>Store</th>\n",
       "      <th>Date</th>\n",
       "      <th>Temperature</th>\n",
       "      <th>Fuel_Price</th>\n",
       "      <th>MarkDown1</th>\n",
       "      <th>MarkDown2</th>\n",
       "      <th>MarkDown3</th>\n",
       "      <th>MarkDown4</th>\n",
       "      <th>MarkDown5</th>\n",
       "      <th>CPI</th>\n",
       "      <th>Unemployment</th>\n",
       "      <th>IsHoliday</th>\n",
       "      <th>Dept</th>\n",
       "      <th>Weekly_Sales</th>\n",
       "      <th>Type</th>\n",
       "      <th>Size</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>421565</th>\n",
       "      <td>45</td>\n",
       "      <td>2012-10-26</td>\n",
       "      <td>58.85</td>\n",
       "      <td>3.882</td>\n",
       "      <td>4018.91</td>\n",
       "      <td>58.08</td>\n",
       "      <td>100.0</td>\n",
       "      <td>211.94</td>\n",
       "      <td>858.33</td>\n",
       "      <td>192.308899</td>\n",
       "      <td>8.667</td>\n",
       "      <td>False</td>\n",
       "      <td>93</td>\n",
       "      <td>2487.80</td>\n",
       "      <td>B</td>\n",
       "      <td>118221</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>421566</th>\n",
       "      <td>45</td>\n",
       "      <td>2012-10-26</td>\n",
       "      <td>58.85</td>\n",
       "      <td>3.882</td>\n",
       "      <td>4018.91</td>\n",
       "      <td>58.08</td>\n",
       "      <td>100.0</td>\n",
       "      <td>211.94</td>\n",
       "      <td>858.33</td>\n",
       "      <td>192.308899</td>\n",
       "      <td>8.667</td>\n",
       "      <td>False</td>\n",
       "      <td>94</td>\n",
       "      <td>5203.31</td>\n",
       "      <td>B</td>\n",
       "      <td>118221</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>421567</th>\n",
       "      <td>45</td>\n",
       "      <td>2012-10-26</td>\n",
       "      <td>58.85</td>\n",
       "      <td>3.882</td>\n",
       "      <td>4018.91</td>\n",
       "      <td>58.08</td>\n",
       "      <td>100.0</td>\n",
       "      <td>211.94</td>\n",
       "      <td>858.33</td>\n",
       "      <td>192.308899</td>\n",
       "      <td>8.667</td>\n",
       "      <td>False</td>\n",
       "      <td>95</td>\n",
       "      <td>56017.47</td>\n",
       "      <td>B</td>\n",
       "      <td>118221</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>421568</th>\n",
       "      <td>45</td>\n",
       "      <td>2012-10-26</td>\n",
       "      <td>58.85</td>\n",
       "      <td>3.882</td>\n",
       "      <td>4018.91</td>\n",
       "      <td>58.08</td>\n",
       "      <td>100.0</td>\n",
       "      <td>211.94</td>\n",
       "      <td>858.33</td>\n",
       "      <td>192.308899</td>\n",
       "      <td>8.667</td>\n",
       "      <td>False</td>\n",
       "      <td>97</td>\n",
       "      <td>6817.48</td>\n",
       "      <td>B</td>\n",
       "      <td>118221</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>421569</th>\n",
       "      <td>45</td>\n",
       "      <td>2012-10-26</td>\n",
       "      <td>58.85</td>\n",
       "      <td>3.882</td>\n",
       "      <td>4018.91</td>\n",
       "      <td>58.08</td>\n",
       "      <td>100.0</td>\n",
       "      <td>211.94</td>\n",
       "      <td>858.33</td>\n",
       "      <td>192.308899</td>\n",
       "      <td>8.667</td>\n",
       "      <td>False</td>\n",
       "      <td>98</td>\n",
       "      <td>1076.80</td>\n",
       "      <td>B</td>\n",
       "      <td>118221</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Store       Date  Temperature  Fuel_Price  MarkDown1  MarkDown2  \\\n",
       "421565     45 2012-10-26        58.85       3.882    4018.91      58.08   \n",
       "421566     45 2012-10-26        58.85       3.882    4018.91      58.08   \n",
       "421567     45 2012-10-26        58.85       3.882    4018.91      58.08   \n",
       "421568     45 2012-10-26        58.85       3.882    4018.91      58.08   \n",
       "421569     45 2012-10-26        58.85       3.882    4018.91      58.08   \n",
       "\n",
       "        MarkDown3  MarkDown4  MarkDown5         CPI  Unemployment  IsHoliday  \\\n",
       "421565      100.0     211.94     858.33  192.308899         8.667      False   \n",
       "421566      100.0     211.94     858.33  192.308899         8.667      False   \n",
       "421567      100.0     211.94     858.33  192.308899         8.667      False   \n",
       "421568      100.0     211.94     858.33  192.308899         8.667      False   \n",
       "421569      100.0     211.94     858.33  192.308899         8.667      False   \n",
       "\n",
       "        Dept  Weekly_Sales Type    Size  \n",
       "421565    93       2487.80    B  118221  \n",
       "421566    94       5203.31    B  118221  \n",
       "421567    95      56017.47    B  118221  \n",
       "421568    97       6817.48    B  118221  \n",
       "421569    98       1076.80    B  118221  "
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_final.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "07440147",
   "metadata": {},
   "source": [
    "# Split into 2010/11 and 2012  - Most EDA performed on 2010/11"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "0b5354ac",
   "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>Store</th>\n",
       "      <th>Date</th>\n",
       "      <th>Temperature</th>\n",
       "      <th>Fuel_Price</th>\n",
       "      <th>MarkDown1</th>\n",
       "      <th>MarkDown2</th>\n",
       "      <th>MarkDown3</th>\n",
       "      <th>MarkDown4</th>\n",
       "      <th>MarkDown5</th>\n",
       "      <th>CPI</th>\n",
       "      <th>Unemployment</th>\n",
       "      <th>IsHoliday</th>\n",
       "      <th>Dept</th>\n",
       "      <th>Weekly_Sales</th>\n",
       "      <th>Type</th>\n",
       "      <th>Size</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>294129</th>\n",
       "      <td>45</td>\n",
       "      <td>2011-12-30</td>\n",
       "      <td>37.79</td>\n",
       "      <td>3.389</td>\n",
       "      <td>3604.35</td>\n",
       "      <td>43941.56</td>\n",
       "      <td>287.45</td>\n",
       "      <td>357.43</td>\n",
       "      <td>750.01</td>\n",
       "      <td>189.062016</td>\n",
       "      <td>8.523</td>\n",
       "      <td>True</td>\n",
       "      <td>95</td>\n",
       "      <td>42084.36</td>\n",
       "      <td>B</td>\n",
       "      <td>118221</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>294130</th>\n",
       "      <td>45</td>\n",
       "      <td>2011-12-30</td>\n",
       "      <td>37.79</td>\n",
       "      <td>3.389</td>\n",
       "      <td>3604.35</td>\n",
       "      <td>43941.56</td>\n",
       "      <td>287.45</td>\n",
       "      <td>357.43</td>\n",
       "      <td>750.01</td>\n",
       "      <td>189.062016</td>\n",
       "      <td>8.523</td>\n",
       "      <td>True</td>\n",
       "      <td>97</td>\n",
       "      <td>5569.82</td>\n",
       "      <td>B</td>\n",
       "      <td>118221</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>294131</th>\n",
       "      <td>45</td>\n",
       "      <td>2011-12-30</td>\n",
       "      <td>37.79</td>\n",
       "      <td>3.389</td>\n",
       "      <td>3604.35</td>\n",
       "      <td>43941.56</td>\n",
       "      <td>287.45</td>\n",
       "      <td>357.43</td>\n",
       "      <td>750.01</td>\n",
       "      <td>189.062016</td>\n",
       "      <td>8.523</td>\n",
       "      <td>True</td>\n",
       "      <td>98</td>\n",
       "      <td>553.21</td>\n",
       "      <td>B</td>\n",
       "      <td>118221</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Store       Date  Temperature  Fuel_Price  MarkDown1  MarkDown2  \\\n",
       "294129     45 2011-12-30        37.79       3.389    3604.35   43941.56   \n",
       "294130     45 2011-12-30        37.79       3.389    3604.35   43941.56   \n",
       "294131     45 2011-12-30        37.79       3.389    3604.35   43941.56   \n",
       "\n",
       "        MarkDown3  MarkDown4  MarkDown5         CPI  Unemployment  IsHoliday  \\\n",
       "294129     287.45     357.43     750.01  189.062016         8.523       True   \n",
       "294130     287.45     357.43     750.01  189.062016         8.523       True   \n",
       "294131     287.45     357.43     750.01  189.062016         8.523       True   \n",
       "\n",
       "        Dept  Weekly_Sales Type    Size  \n",
       "294129    95      42084.36    B  118221  \n",
       "294130    97       5569.82    B  118221  \n",
       "294131    98        553.21    B  118221  "
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2010_11 = df_final[df_final['Date'].dt.year != 2012]\n",
    "df_2010_11.reset_index(inplace=True)\n",
    "df_2010_11.drop(['index'], axis=1, inplace=True)\n",
    "df_2010_11.tail(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "f0a007f7",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_2010_11.to_csv(\"../data/wrangled_data/df_2010_11.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "4760f590",
   "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>Store</th>\n",
       "      <th>Date</th>\n",
       "      <th>Temperature</th>\n",
       "      <th>Fuel_Price</th>\n",
       "      <th>MarkDown1</th>\n",
       "      <th>MarkDown2</th>\n",
       "      <th>MarkDown3</th>\n",
       "      <th>MarkDown4</th>\n",
       "      <th>MarkDown5</th>\n",
       "      <th>CPI</th>\n",
       "      <th>Unemployment</th>\n",
       "      <th>IsHoliday</th>\n",
       "      <th>Dept</th>\n",
       "      <th>Weekly_Sales</th>\n",
       "      <th>Type</th>\n",
       "      <th>Size</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2012-01-06</td>\n",
       "      <td>49.01</td>\n",
       "      <td>3.157</td>\n",
       "      <td>6277.39</td>\n",
       "      <td>21813.16</td>\n",
       "      <td>143.1</td>\n",
       "      <td>1450.13</td>\n",
       "      <td>8483.0</td>\n",
       "      <td>219.714258</td>\n",
       "      <td>7.348</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>16567.69</td>\n",
       "      <td>A</td>\n",
       "      <td>151315</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>2012-01-06</td>\n",
       "      <td>49.01</td>\n",
       "      <td>3.157</td>\n",
       "      <td>6277.39</td>\n",
       "      <td>21813.16</td>\n",
       "      <td>143.1</td>\n",
       "      <td>1450.13</td>\n",
       "      <td>8483.0</td>\n",
       "      <td>219.714258</td>\n",
       "      <td>7.348</td>\n",
       "      <td>False</td>\n",
       "      <td>2</td>\n",
       "      <td>44481.38</td>\n",
       "      <td>A</td>\n",
       "      <td>151315</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>2012-01-06</td>\n",
       "      <td>49.01</td>\n",
       "      <td>3.157</td>\n",
       "      <td>6277.39</td>\n",
       "      <td>21813.16</td>\n",
       "      <td>143.1</td>\n",
       "      <td>1450.13</td>\n",
       "      <td>8483.0</td>\n",
       "      <td>219.714258</td>\n",
       "      <td>7.348</td>\n",
       "      <td>False</td>\n",
       "      <td>3</td>\n",
       "      <td>13926.04</td>\n",
       "      <td>A</td>\n",
       "      <td>151315</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Store       Date  Temperature  Fuel_Price  MarkDown1  MarkDown2  MarkDown3  \\\n",
       "0      1 2012-01-06        49.01       3.157    6277.39   21813.16      143.1   \n",
       "1      1 2012-01-06        49.01       3.157    6277.39   21813.16      143.1   \n",
       "2      1 2012-01-06        49.01       3.157    6277.39   21813.16      143.1   \n",
       "\n",
       "   MarkDown4  MarkDown5         CPI  Unemployment  IsHoliday  Dept  \\\n",
       "0    1450.13     8483.0  219.714258         7.348      False     1   \n",
       "1    1450.13     8483.0  219.714258         7.348      False     2   \n",
       "2    1450.13     8483.0  219.714258         7.348      False     3   \n",
       "\n",
       "   Weekly_Sales Type    Size  \n",
       "0      16567.69    A  151315  \n",
       "1      44481.38    A  151315  \n",
       "2      13926.04    A  151315  "
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2012 = df_final[df_final['Date'].dt.year == 2012]\n",
    "df_2012.reset_index(inplace=True)\n",
    "df_2012.drop(['index'], axis=1, inplace=True)\n",
    "df_2012.head(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "46349b6f",
   "metadata": {},
   "source": [
    "## Create DF for each Store/Department - Fill in missing dates in DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "cf723be2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 15.2 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "df_dict = {}\n",
    "for st in df_2010_11['Store'].unique():\n",
    "    dp_dict = {}\n",
    "    for dp in df_2010_11['Dept'].unique():\n",
    "        df_sales_by_store_dept = df_2010_11[(df_2010_11['Store'] == st) & (df_2010_11['Dept'] == dp)]\n",
    "        df_sales_by_store_dept.index = df_sales_by_store_dept[\"Date\"]\n",
    "        if len(df_sales_by_store_dept) == 0:\n",
    "            continue\n",
    "        if len(df_sales_by_store_dept) < 100:\n",
    "            df_sales_by_store_dept = df_sales_by_store_dept.groupby('Store').resample('W-FRI').pad()\n",
    "            df_sales_by_store_dept = df_sales_by_store_dept.droplevel('Store')\n",
    "        dp_dict[dp] = df_sales_by_store_dept\n",
    "    df_dict[st] =  dp_dict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "91c4d408",
   "metadata": {},
   "outputs": [],
   "source": [
    "with open('../data/wrangled_data/dict_of_dfs_padded.pickle', 'wb') as handle:\n",
    "    pickle.dump(df_dict, handle, protocol=pickle.HIGHEST_PROTOCOL)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ff0fc3af",
   "metadata": {},
   "source": [
    "## Concat in to one big DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "2695825d",
   "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>Store</th>\n",
       "      <th>Date</th>\n",
       "      <th>Temperature</th>\n",
       "      <th>Fuel_Price</th>\n",
       "      <th>MarkDown1</th>\n",
       "      <th>MarkDown2</th>\n",
       "      <th>MarkDown3</th>\n",
       "      <th>MarkDown4</th>\n",
       "      <th>MarkDown5</th>\n",
       "      <th>CPI</th>\n",
       "      <th>Unemployment</th>\n",
       "      <th>IsHoliday</th>\n",
       "      <th>Dept</th>\n",
       "      <th>Weekly_Sales</th>\n",
       "      <th>Type</th>\n",
       "      <th>Size</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</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",
       "      <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>2010-02-05</th>\n",
       "      <td>1</td>\n",
       "      <td>2010-02-05</td>\n",
       "      <td>42.31</td>\n",
       "      <td>2.572</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>211.096358</td>\n",
       "      <td>8.106</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>24924.50</td>\n",
       "      <td>A</td>\n",
       "      <td>151315</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-02-12</th>\n",
       "      <td>1</td>\n",
       "      <td>2010-02-12</td>\n",
       "      <td>38.51</td>\n",
       "      <td>2.548</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>211.242170</td>\n",
       "      <td>8.106</td>\n",
       "      <td>True</td>\n",
       "      <td>1</td>\n",
       "      <td>46039.49</td>\n",
       "      <td>A</td>\n",
       "      <td>151315</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-02-19</th>\n",
       "      <td>1</td>\n",
       "      <td>2010-02-19</td>\n",
       "      <td>39.93</td>\n",
       "      <td>2.514</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>211.289143</td>\n",
       "      <td>8.106</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>41595.55</td>\n",
       "      <td>A</td>\n",
       "      <td>151315</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Store       Date  Temperature  Fuel_Price  MarkDown1  MarkDown2  \\\n",
       "Date                                                                          \n",
       "2010-02-05      1 2010-02-05        42.31       2.572        0.0        0.0   \n",
       "2010-02-12      1 2010-02-12        38.51       2.548        0.0        0.0   \n",
       "2010-02-19      1 2010-02-19        39.93       2.514        0.0        0.0   \n",
       "\n",
       "            MarkDown3  MarkDown4  MarkDown5         CPI  Unemployment  \\\n",
       "Date                                                                    \n",
       "2010-02-05        0.0        0.0        0.0  211.096358         8.106   \n",
       "2010-02-12        0.0        0.0        0.0  211.242170         8.106   \n",
       "2010-02-19        0.0        0.0        0.0  211.289143         8.106   \n",
       "\n",
       "            IsHoliday  Dept  Weekly_Sales Type    Size  \n",
       "Date                                                    \n",
       "2010-02-05      False     1      24924.50    A  151315  \n",
       "2010-02-12       True     1      46039.49    A  151315  \n",
       "2010-02-19      False     1      41595.55    A  151315  "
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "value_list = []\n",
    "for k, v in df_dict.items():\n",
    "    for k1, v1 in v.items():\n",
    "        value_list.append(v1) \n",
    "\n",
    "df = pd.concat(value_list)\n",
    "df.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "1966bac6",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_csv(\"../data/wrangled_data/df_with_padding.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "33dab1fb",
   "metadata": {},
   "source": [
    "# Total Sales for store (Departments summed)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "19f26ea1",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_total_sales = df_2010_11.groupby(['Store', 'Date'])\\\n",
    "                [\"Weekly_Sales\"].sum().reset_index().join(df_2010_11.drop(\\\n",
    "                [\"Date\", \"Dept\", \"Weekly_Sales\"], axis=1).drop_duplicates().reset_index(),\n",
    "                 lsuffix='_caller')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "2a10019d",
   "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>Store_caller</th>\n",
       "      <th>Date</th>\n",
       "      <th>Weekly_Sales</th>\n",
       "      <th>index</th>\n",
       "      <th>Store</th>\n",
       "      <th>Temperature</th>\n",
       "      <th>Fuel_Price</th>\n",
       "      <th>MarkDown1</th>\n",
       "      <th>MarkDown2</th>\n",
       "      <th>MarkDown3</th>\n",
       "      <th>MarkDown4</th>\n",
       "      <th>MarkDown5</th>\n",
       "      <th>CPI</th>\n",
       "      <th>Unemployment</th>\n",
       "      <th>IsHoliday</th>\n",
       "      <th>Type</th>\n",
       "      <th>Size</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2010-02-05</td>\n",
       "      <td>1643690.90</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>42.31</td>\n",
       "      <td>2.572</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>211.096358</td>\n",
       "      <td>8.106</td>\n",
       "      <td>False</td>\n",
       "      <td>A</td>\n",
       "      <td>151315</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>2010-02-12</td>\n",
       "      <td>1641957.44</td>\n",
       "      <td>73</td>\n",
       "      <td>1</td>\n",
       "      <td>38.51</td>\n",
       "      <td>2.548</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>211.242170</td>\n",
       "      <td>8.106</td>\n",
       "      <td>True</td>\n",
       "      <td>A</td>\n",
       "      <td>151315</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>2010-02-19</td>\n",
       "      <td>1611968.17</td>\n",
       "      <td>145</td>\n",
       "      <td>1</td>\n",
       "      <td>39.93</td>\n",
       "      <td>2.514</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>211.289143</td>\n",
       "      <td>8.106</td>\n",
       "      <td>False</td>\n",
       "      <td>A</td>\n",
       "      <td>151315</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>2010-02-26</td>\n",
       "      <td>1409727.59</td>\n",
       "      <td>218</td>\n",
       "      <td>1</td>\n",
       "      <td>46.63</td>\n",
       "      <td>2.561</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>211.319643</td>\n",
       "      <td>8.106</td>\n",
       "      <td>False</td>\n",
       "      <td>A</td>\n",
       "      <td>151315</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Store_caller       Date  Weekly_Sales  index  Store  Temperature  \\\n",
       "0             1 2010-02-05    1643690.90      0      1        42.31   \n",
       "1             1 2010-02-12    1641957.44     73      1        38.51   \n",
       "2             1 2010-02-19    1611968.17    145      1        39.93   \n",
       "3             1 2010-02-26    1409727.59    218      1        46.63   \n",
       "\n",
       "   Fuel_Price  MarkDown1  MarkDown2  MarkDown3  MarkDown4  MarkDown5  \\\n",
       "0       2.572        0.0        0.0        0.0        0.0        0.0   \n",
       "1       2.548        0.0        0.0        0.0        0.0        0.0   \n",
       "2       2.514        0.0        0.0        0.0        0.0        0.0   \n",
       "3       2.561        0.0        0.0        0.0        0.0        0.0   \n",
       "\n",
       "          CPI  Unemployment  IsHoliday Type    Size  \n",
       "0  211.096358         8.106      False    A  151315  \n",
       "1  211.242170         8.106       True    A  151315  \n",
       "2  211.289143         8.106      False    A  151315  \n",
       "3  211.319643         8.106      False    A  151315  "
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_total_sales.head(4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "d9b67754",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_total_sales.to_csv(\"../data/wrangled_data/df_total_sales.csv\")"
   ]
  }
 ],
 "metadata": {
  "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": "3.7.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}