sales-prediction-model-jn.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.model_selection import train_test_split\n",
    "import tensorflow as tf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Importing the csv-file\n",
    "df = pd.read_csv('/Users/julianuss/Documents/GitHub/sales-prediction-model/sales.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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>Unnamed: 0</th>\n",
       "      <th>store_ID</th>\n",
       "      <th>day_of_week</th>\n",
       "      <th>date</th>\n",
       "      <th>nb_customers_on_day</th>\n",
       "      <th>open</th>\n",
       "      <th>promotion</th>\n",
       "      <th>state_holiday</th>\n",
       "      <th>school_holiday</th>\n",
       "      <th>sales</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>425390</td>\n",
       "      <td>366</td>\n",
       "      <td>4</td>\n",
       "      <td>2013-04-18</td>\n",
       "      <td>517</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4422</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>291687</td>\n",
       "      <td>394</td>\n",
       "      <td>6</td>\n",
       "      <td>2015-04-11</td>\n",
       "      <td>694</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8297</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>411278</td>\n",
       "      <td>807</td>\n",
       "      <td>4</td>\n",
       "      <td>2013-08-29</td>\n",
       "      <td>970</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>9729</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>664714</td>\n",
       "      <td>802</td>\n",
       "      <td>2</td>\n",
       "      <td>2013-05-28</td>\n",
       "      <td>473</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6513</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>540835</td>\n",
       "      <td>726</td>\n",
       "      <td>4</td>\n",
       "      <td>2013-10-10</td>\n",
       "      <td>1068</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>10882</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0  store_ID  day_of_week        date  nb_customers_on_day  open  \\\n",
       "0      425390       366            4  2013-04-18                  517     1   \n",
       "1      291687       394            6  2015-04-11                  694     1   \n",
       "2      411278       807            4  2013-08-29                  970     1   \n",
       "3      664714       802            2  2013-05-28                  473     1   \n",
       "4      540835       726            4  2013-10-10                 1068     1   \n",
       "\n",
       "   promotion state_holiday  school_holiday  sales  \n",
       "0          0             0               0   4422  \n",
       "1          0             0               0   8297  \n",
       "2          1             0               0   9729  \n",
       "3          1             0               0   6513  \n",
       "4          1             0               0  10882  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 640840 entries, 0 to 640839\n",
      "Data columns (total 10 columns):\n",
      " #   Column               Non-Null Count   Dtype \n",
      "---  ------               --------------   ----- \n",
      " 0   Unnamed: 0           640840 non-null  int64 \n",
      " 1   store_ID             640840 non-null  int64 \n",
      " 2   day_of_week          640840 non-null  int64 \n",
      " 3   date                 640840 non-null  object\n",
      " 4   nb_customers_on_day  640840 non-null  int64 \n",
      " 5   open                 640840 non-null  int64 \n",
      " 6   promotion            640840 non-null  int64 \n",
      " 7   state_holiday        640840 non-null  object\n",
      " 8   school_holiday       640840 non-null  int64 \n",
      " 9   sales                640840 non-null  int64 \n",
      "dtypes: int64(8), object(2)\n",
      "memory usage: 48.9+ MB\n",
      "None\n",
      "(640840, 10)\n",
      "          Unnamed: 0       store_ID    day_of_week  nb_customers_on_day  \\\n",
      "count  640840.000000  640840.000000  640840.000000        640840.000000   \n",
      "mean   355990.675084     558.211348       4.000189           633.398577   \n",
      "std    205536.290268     321.878521       1.996478           464.094416   \n",
      "min         0.000000       1.000000       1.000000             0.000000   \n",
      "25%    178075.750000     280.000000       2.000000           405.000000   \n",
      "50%    355948.500000     558.000000       4.000000           609.000000   \n",
      "75%    533959.250000     837.000000       6.000000           838.000000   \n",
      "max    712044.000000    1115.000000       7.000000          5458.000000   \n",
      "\n",
      "                open      promotion  school_holiday          sales  \n",
      "count  640840.000000  640840.000000   640840.000000  640840.000000  \n",
      "mean        0.830185       0.381718        0.178472    5777.469011  \n",
      "std         0.375470       0.485808        0.382910    3851.338083  \n",
      "min         0.000000       0.000000        0.000000       0.000000  \n",
      "25%         1.000000       0.000000        0.000000    3731.000000  \n",
      "50%         1.000000       0.000000        0.000000    5746.000000  \n",
      "75%         1.000000       1.000000        0.000000    7860.000000  \n",
      "max         1.000000       1.000000        1.000000   41551.000000  \n",
      "Index(['Unnamed: 0', 'store_ID', 'day_of_week', 'date', 'nb_customers_on_day',\n",
      "       'open', 'promotion', 'state_holiday', 'school_holiday', 'sales'],\n",
      "      dtype='object')\n"
     ]
    }
   ],
   "source": [
    "# Looking into the basic details of the DataFrame\n",
    "print(df.info())\n",
    "print(df.shape)\n",
    "print(df.describe())\n",
    "print(df.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['0' 'a' 'c' 'b']\n",
      "4\n"
     ]
    }
   ],
   "source": [
    "print(df['state_holiday'].unique())\n",
    "print(df['state_holiday'].nunique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "state_holiday\n",
       "0    3697272529\n",
       "a       3626172\n",
       "b       1065876\n",
       "c        468664\n",
       "Name: sales, dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby('state_holiday')['sales'].sum()  # Summing sales for each state_holiday group"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0 3 1 2]\n"
     ]
    }
   ],
   "source": [
    "# Defining the custom mapping\n",
    "mapping = {'0': 0, 'c': 1, 'b': 2, 'a': 3}\n",
    "\n",
    "# Applying the mapping to the 'state_holiday' column\n",
    "df['state_holiday_encoded'] = df['state_holiday'].map(mapping)\n",
    "\n",
    "# Verifying the encoding\n",
    "print(df['state_holiday_encoded'].unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "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>Unnamed: 0</th>\n",
       "      <th>store_ID</th>\n",
       "      <th>day_of_week</th>\n",
       "      <th>date</th>\n",
       "      <th>nb_customers_on_day</th>\n",
       "      <th>open</th>\n",
       "      <th>promotion</th>\n",
       "      <th>state_holiday</th>\n",
       "      <th>school_holiday</th>\n",
       "      <th>sales</th>\n",
       "      <th>state_holiday_encoded</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>425390</td>\n",
       "      <td>366</td>\n",
       "      <td>4</td>\n",
       "      <td>2013-04-18</td>\n",
       "      <td>517</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4422</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>291687</td>\n",
       "      <td>394</td>\n",
       "      <td>6</td>\n",
       "      <td>2015-04-11</td>\n",
       "      <td>694</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8297</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>411278</td>\n",
       "      <td>807</td>\n",
       "      <td>4</td>\n",
       "      <td>2013-08-29</td>\n",
       "      <td>970</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>9729</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>664714</td>\n",
       "      <td>802</td>\n",
       "      <td>2</td>\n",
       "      <td>2013-05-28</td>\n",
       "      <td>473</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6513</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>540835</td>\n",
       "      <td>726</td>\n",
       "      <td>4</td>\n",
       "      <td>2013-10-10</td>\n",
       "      <td>1068</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>10882</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0  store_ID  day_of_week        date  nb_customers_on_day  open  \\\n",
       "0      425390       366            4  2013-04-18                  517     1   \n",
       "1      291687       394            6  2015-04-11                  694     1   \n",
       "2      411278       807            4  2013-08-29                  970     1   \n",
       "3      664714       802            2  2013-05-28                  473     1   \n",
       "4      540835       726            4  2013-10-10                 1068     1   \n",
       "\n",
       "   promotion state_holiday  school_holiday  sales  state_holiday_encoded  \n",
       "0          0             0               0   4422                      0  \n",
       "1          0             0               0   8297                      0  \n",
       "2          1             0               0   9729                      0  \n",
       "3          1             0               0   6513                      0  \n",
       "4          1             0               0  10882                      0  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "        date  quarter\n",
      "0 2013-04-18        2\n",
      "1 2015-04-11        2\n",
      "2 2013-08-29        3\n",
      "3 2013-05-28        2\n",
      "4 2013-10-10        4\n"
     ]
    }
   ],
   "source": [
    "# Assuming your dataframe is named 'df'\n",
    "df['date'] = pd.to_datetime(df['date'])\n",
    "# Extract the quarter from the date and create a new column\n",
    "df['quarter'] = df['date'].dt.quarter\n",
    "# Display the first few rows to check\n",
    "print(df[['date', 'quarter']].head())\n",
    "\n",
    "df = df.drop(\"date\", axis =1)\n",
    "df = df.drop(\"state_holiday\", axis =1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1200x1000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "corr_matrix = df.corr()\n",
    "\n",
    "# Set the figure size for the heatmap\n",
    "plt.figure(figsize=(12, 10))\n",
    "\n",
    "# Create the heatmap using seaborn\n",
    "sns.heatmap(corr_matrix, annot=True, cmap='inferno', fmt='.2f', linewidths=0.5)\n",
    "\n",
    "# Set title and display the heatmap\n",
    "plt.title('Correlation Matrix Heatmap')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# One-hot encoding 'day_of_week'\n",
    "df = pd.get_dummies(df, columns=['day_of_week'], drop_first=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "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>Unnamed: 0</th>\n",
       "      <th>store_ID</th>\n",
       "      <th>nb_customers_on_day</th>\n",
       "      <th>open</th>\n",
       "      <th>promotion</th>\n",
       "      <th>school_holiday</th>\n",
       "      <th>sales</th>\n",
       "      <th>state_holiday_encoded</th>\n",
       "      <th>quarter</th>\n",
       "      <th>day_of_week_2</th>\n",
       "      <th>day_of_week_3</th>\n",
       "      <th>day_of_week_4</th>\n",
       "      <th>day_of_week_5</th>\n",
       "      <th>day_of_week_6</th>\n",
       "      <th>day_of_week_7</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>425390</td>\n",
       "      <td>366</td>\n",
       "      <td>517</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4422</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>291687</td>\n",
       "      <td>394</td>\n",
       "      <td>694</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8297</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>411278</td>\n",
       "      <td>807</td>\n",
       "      <td>970</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>9729</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>664714</td>\n",
       "      <td>802</td>\n",
       "      <td>473</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>6513</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>540835</td>\n",
       "      <td>726</td>\n",
       "      <td>1068</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>10882</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0  store_ID  nb_customers_on_day  open  promotion  school_holiday  \\\n",
       "0      425390       366                  517     1          0               0   \n",
       "1      291687       394                  694     1          0               0   \n",
       "2      411278       807                  970     1          1               0   \n",
       "3      664714       802                  473     1          1               0   \n",
       "4      540835       726                 1068     1          1               0   \n",
       "\n",
       "   sales  state_holiday_encoded  quarter  day_of_week_2  day_of_week_3  \\\n",
       "0   4422                      0        2          False          False   \n",
       "1   8297                      0        2          False          False   \n",
       "2   9729                      0        3          False          False   \n",
       "3   6513                      0        2           True          False   \n",
       "4  10882                      0        4          False          False   \n",
       "\n",
       "   day_of_week_4  day_of_week_5  day_of_week_6  day_of_week_7  \n",
       "0           True          False          False          False  \n",
       "1          False          False           True          False  \n",
       "2           True          False          False          False  \n",
       "3          False          False          False          False  \n",
       "4           True          False          False          False  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "      store_ID  sales_per_customer_ratio\n",
      "0            1                  8.448965\n",
      "1            2                  8.471213\n",
      "2            3                  9.223982\n",
      "3            4                  7.317723\n",
      "4            5                  8.655336\n",
      "...        ...                       ...\n",
      "1110      1111                 11.662776\n",
      "1111      1112                 12.197177\n",
      "1112      1113                  9.225763\n",
      "1113      1114                  6.434579\n",
      "1114      1115                 14.451357\n",
      "\n",
      "[1115 rows x 2 columns]\n"
     ]
    }
   ],
   "source": [
    "df['sales_per_customer'] = df['sales'] / df['nb_customers_on_day']\n",
    "\n",
    "# If you want to compute the total sales and total customers for each store and find the ratio:\n",
    "store_sales_customers = df.groupby('store_ID').agg({'sales': 'sum', 'nb_customers_on_day': 'sum'}).reset_index()\n",
    "\n",
    "# Now compute the ratio of sales per customer for each store\n",
    "store_sales_customers['sales_per_customer_ratio'] = store_sales_customers['sales'] / store_sales_customers['nb_customers_on_day']\n",
    "\n",
    "# Display the result\n",
    "print(store_sales_customers[['store_ID', 'sales_per_customer_ratio']])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['Unnamed: 0', 'store_ID', 'nb_customers_on_day', 'open', 'promotion',\n",
      "       'school_holiday', 'sales', 'state_holiday_encoded', 'quarter',\n",
      "       'day_of_week_2', 'day_of_week_3', 'day_of_week_4', 'day_of_week_5',\n",
      "       'day_of_week_6', 'day_of_week_7', 'sales_per_customer'],\n",
      "      dtype='object')\n"
     ]
    }
   ],
   "source": [
    "print(df.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Skewness sales_per_customer: 0.5751\n"
     ]
    }
   ],
   "source": [
    "# Identifying the skewness of the 'sales per customer per store' column\n",
    "skewness = df['sales_per_customer'].skew()\n",
    "print(f'Skewness sales_per_customer: {skewness:.4f}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.figure(figsize=(8, 6))\n",
    "plt.hist(df['sales_per_customer'], bins=30, edgecolor='black')\n",
    "plt.title('Histogram of Sales Per Customer')\n",
    "plt.xlabel('Sales Per Customer')\n",
    "plt.ylabel('Frequency')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAg0AAAGxCAYAAADh+IUHAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAlGklEQVR4nO3de3TU9Z3/8dckIZOYkAkBzUWSQCpXIVykxGy24hFstnb94V7UXULFI8dYwIPVuqdltQariKeutOritV3pAq7XYrWrVUpLsBhALikgGMDEgEICXpIghgQzn98fbKaMufDOZJIJ8nyckyPM9zuf7ycf5pt5OvlO4nHOOQEAAJxGVKQnAAAAzgxEAwAAMCEaAACACdEAAABMiAYAAGBCNAAAABOiAQAAmBANAADAJCbUO/r9fh08eFD9+/eXx+MJ55wAAEAPcc7p6NGjysjIUFRU1147CDkaDh48qMzMzFDvDgAAIujAgQMaPHhwl+4TcjT0798/cNCkpKRQhwEAAL2ooaFBmZmZgefxrgg5Glq/JZGUlEQ0AABwhgnl0gIuhAQAACZEAwAAMCEaAACACdEAAABMiAYAAGBCNAAAABOiAQAAmBANAADAhGgAAAAmRAMAADAhGgAAgAnRAAAATIgGAABgQjQAAAATogEAAJgQDQAAwIRoAAAAJkQDAAAwIRoAAIAJ0QAAAEyIBgAAYEI0AAAAE6IBAACYEA0AAMCEaAAAACZEAwAAMCEaAACACdEAAABMiAYAAGBCNAAAABOiAQAAmBANAADAhGgAAAAmMZGeAP6qtrZW9fX1PTa+z+dTampqj40PAPh6Ixr6iNraWs383nU60dzUY8foF+vViuX/TTgAAEJCNPQR9fX1OtHcpMacKfLH+TrdN6qxTvFV69Q49BL545NN40cdr5cqS1VfX080AABCQjT0Mf44n/wJg2z7xieb9wUAoLu4EBIAAJgQDQAAwIRoAAAAJkQDAAAwIRoAAIAJ0QAAAEyIBgAAYEI0AAAAE6IBAACYEA0AAMCEaAAAACZEAwAAMCEaAACACdEAAABMiAYAAGBCNAAAABOiAQAAmBANAADAhGgAAAAmRAMAADAhGgAAgAnRAAAATIgGAABgQjQAAAATogEAAJgQDQAAwIRoAAAAJkQDAAAwIRoAAIAJ0QAAAEyIBgAAYEI0AAAAE6IBAACYEA0AAMCEaAAAACZEAwAAMCEaAACACdEAAABMiAYAAGBCNAAAABOiAQAAmBANAADAhGgAAAAmRAMAADAhGgAAgAnRAAAATIgGAABgQjQAAAATogEAAJgQDQAAwIRoAAAAJkQDAAAwIRoAAIAJ0QAAAEyIBgAAYEI0AAAAE6IBAACYEA0AAMCEaAAAACZEAwAAMCEaAACACdEAAABMiAYAAGBCNAAAABOiAQAAmBANAADAhGgAAAAmRAMAADAhGgAAgAnRAAAATM7qaDh+/Lj27Nmj48ePR3oqZxXWHQDOTGd1NOzfv1/FxcXav39/pKdyVmHdAeDMdFZHAwAAsCMaAACACdEAAABMiAYAAGBCNAAAABOiAQAAmBANAADAhGgAAAAmRAMAADAhGgAAgAnRAAAATIgGAABgQjQAAAATogEAAJgQDQAAwIRoAAAAJkQDAAAwIRoAAIAJ0QAAAEyIBgAAYEI0AAAAE6IBAACYEA0AAMCEaAAAACZEAwAAMCEaAACACdEAAABMiAYAAGBCNAAAABOiAQAAmBANAADAhGgAAAAmRAMAADAhGgAAgAnRAAAATIgGAABgQjQAAAATogEAAJgQDQAAwIRoAAAAJkQDAAAwIRoAAIAJ0QAAAEyIBgAAYEI0AAAAE6IBAACYEA0AAMCEaAAAACZEAwAAMCEaAACACdEAAABMiAYAAGBCNAAAABOiAQAAmBANAADAhGgAAAAmRAMAADAhGgAAgAnRAAAATIgGAABgQjQAAAATogEAAJgQDQAAwIRoAAAAJkQDAAAwIRoAAIAJ0QAAAEyIBgAAYBIT6QmcqqWlRdu3b9enn36qlJQU5ebmKjo6utvj1tfX69Zbb1VlZWW724uLi5WTk6P/+q//6vax0LlLL7008Ofi4uLITURSbGysvF6v+vfvr+HDhysqKkp1dXWKi4tTSkqKGhsbdfz4cQ0cOFAjRozQ7t27tWPHDrW0tCg3N1eDBw/WkSNHlJGRoenTp0uSVq1apR07dig+Pl7f/va3NW7cOO3YsUPbtm1TTU2NJCk1NVUTJ07U+PHjJUnl5eXavHmzKioq1NzcrLS0NBUWFgbuu3XrVh06dEgHDhyQx+PRyJEjVVxcrL1795rOlXCdV63jfPzxx6qrq1NycrIGDRoUtvO0J+dsHaenvgZZjtGdY7e0tKi8vFzl5eWSpPHjx2v8+PFhmXtPrElvrHM4jhOpx09vrU8oPM45F8odGxoa5PP5VF9fr6SkpG5PZN26dXr00UcDX1glKS0tTXPnztUll1wS8rhFRUX66KOPzPuvXbs25GN1x549e1RcXKxjo/+f/AmDOt036tjHStj1imnfr97nySef1PDhw8Mx5S47NRi+bjwej7p6KiUkJMg5py+++KLbx+/oXAnXedXeON0Zr6vHCtecOxunp74GWY5x6aWXau3atSEde926dVqyZInq6uqCbk9OTtZtt93Wrbn3xJr0xjqH4ziRevz0xvp05/m7T3x7Yt26dSopKVFOTo6WLl2q1157TUuXLlVOTo5KSkq0bt26kMbtajBIX+8ntkj6uqxrTEzbF+d8Pl8gGHw+nxYvXqwrrriizX5Dhw7VkCFDAn8/duxYUDCkp6crOzu73eN6PB4NGtQ2EC+++OIOz5VwnVet4/h8PklSXl6ebr/9duXl5cnj8cjn83XrPG3vWOGas3WcnvoaZDmGz+fTs88+K5/P1+Vjr1u3TnfddZfq6uo0duxYLVmyRA8++KDGjh2rurq6bs29J9akN9Y5HMeJ1OOnt9anOyL+SkNLS4uKioqUk5Oje++9V1FRf+0Yv9+vO++8U1VVVVqxYkWXXp6pr68PvGTcVZH4VsXX+ZWGMzUYOnr1oF+/fho4cKAaGxtVX18f2Dc6OlrOOf3ud7/T9ddfr08//VQnTpyQdPJbIf/7v/+r6Oho/fu//7s2bNgQNGZeXp4WL16slpYW/f3f/72ampqCtr/++uuKiYnRd7/7XX355ZeKiYlRc3NzYJvX6w06VySF5bxqPT+HDh2qyspKfeMb3wiMd+o4Q4YM0QcffNDl87S9Y4VrztZxeuprkGVOrbc3NTXJ6/Vq5cqVgWOc7tgtLS2aMWOG6urqNHHiRC1atCgwrt/v1x133KGtW7cqJSWly3PviTXpjXUOx3Ei9fjprfWReumVhqamJjU0NAR9hMP27dtVU1OjoqKioEWSpKioKBUVFenQoUPavn17l8a94447Ot3+zW9+s8NtlZWV2rNnT69+VFdXd+nzC1V1dXWvf25nqlODYcSIEYE/jxkzRjU1NSosLAza95prrlFLS4ueeOIJ1dbWBoJBkpqbm7Vz505FRUUpLy+vzbEuvvhiRUVFaefOnW2CQZLee+897dy5U83NzfL7/YFgkKQnnniizbkSrvOqdZzJkyertrY2aLxTx5k8eXJI52l7xwrXnK3j9NTXIMucWm+fPXu2ampqgo5xumNv375dtbW1ampq0syZM4PGjYqK0syZM9XU1BTS3HtiTXpjncNxnEg9fnprfbrLfCHk4sWLdffdd4d9Ap9++qmkky/dtqf19tb9rGprazvd/r3vfU/vvPNOh9sjfZFeT1m0aFGkp3BGysjIUEVFhSRp4MCBgdtOdcUVV+iZZ57Rhx9+2O4YrY9hr9fbZlvrbR09zjt7/Lcer71zpbvnVev2uLi4dsdr/fvp5m8Rrq8FXR2np74GWebUent+fn67x+js2Kf7dz71tq7OvSfWpDfWORzHidTjp7fWp7vM0bBgwQLddtttgb83NDQoMzOz2xNISUmRJFVVVenCCy9ss72qqipoP6vU1FQdOXKkw+3Lly/v9P5PPvlkl47XXdXV1b3yhH7HHXd0+H3znvJ1CLCDBw8G/vzJJ5+0uU2SXnvtNUnS4MGDtXnz5jZjtD6G23slofW2jh7nnT3+Bw8eLKn9c6W751Xr9uPHj7c7Xus4p5u/Rbi+FnR1nJ76GmSZU+vtZWVl7R6js2Of7t+59b6hzL0n1qQ31jkcx4nU46e31qe7zNHg9Xrb/T+k7srNzVVaWppWrlzZ7vdxVq5cqfT0dOXm5nZp3EWLFnV6TUNnrzLk5ORE7B0GPS07O/tr+7mF26nXNLS+yiBJO3fuVFpamt54442gfZ9//nlFR0frpptuUllZWZtrGsaMGSO/36+NGze2OdaGDRs0ffp0jRkzRl6vt01YjBw5UjExMYqNjW1zTcNNN93U7rkSjvOq9fzctGmTUlNTg8Y7dZxNmzaFdJ62d6xwzdk6Tk99DbLMqfX2X/3qV0pLSws6xumOnZubq9TUVNXV1WnFihVtrmlYsWKFvF5v4C174ZivZV69OWZPHCdSj5/eWp/uivi7J6KjozV37lyVlZXpzjvv1LvvvqsvvvhC7777ru68806VlZVpzpw5Xb7ww+fz6fzzzw9pTvy8hvCK1NtYu6u9iyBjYmJ04sQJ1dTUBC6CbH33xJdffqnExERt3bpVEydObHNNQ3FxsW644YY2F0FK0saNGzVjxgzNnj273VcirrjiCv3Lv/xLm2sa8vLyVFlZ2eZcCdd51TrOhg0blJycrLffflsLFizQq6++qgULFqisrExJSUnasGFDSOdpe8cK15yt4/TU1yDLnN577z35fD599tln8vl8eu+998zHjo6O1rx589TU1KSysjLdcsst2rJli7Zs2aJbbrlFZWVlam5uDmnuPbEmvbHO4ThOpB4/vbU+3RXxd0+0au+9qenp6ZozZw4/p+ErzrR3T7Q6U99FYRHpn9PQ0bkSrvOqs5/TEI7ztLfm3Nk4PfU1yHKMKVOmtPk5DdZjd/RzGgYMGKBbb7017D+nobtr0hvrHI7jROrx0xvr053n7z4TDVLkfiKkFJm3WZ7qbIgGqW+FAz8Rsmv4iZDhwU+E5CdC9vS8T+drEw29rfWJOtJPpKfO5eseDVLfWncAONuc8T8REgAA9H1EAwAAMCEaAACACdEAAABMiAYAAGBCNAAAABOiAQAAmBANAADAhGgAAAAmRAMAADAhGgAAgAnRAAAATIgGAABgQjQAAAATogEAAJgQDQAAwIRoAAAAJkQDAAAwIRoAAIAJ0QAAAEyIBgAAYEI0AAAAE6IBAACYEA0AAMCEaAAAACZEAwAAMCEaAACACdEAAABMiAYAAGBCNAAAABOiAQAAmBANAADAhGgAAAAmRAMAADAhGgAAgAnRAAAATIgGAABgQjQAAAATogEAAJgQDQAAwIRoAAAAJkQDAAAwIRoAAIAJ0QAAAEyIBgAAYEI0AAAAE6IBAACYEA0AAMCEaAAAACZEAwAAMCEaAACACdEAAABMiAYAAGBCNAAAABOiAQAAmBANAADAhGgAAAAmRAMAADAhGgAAgAnRAAAATIgGAABgQjQAAAATogEAAJgQDQAAwIRoAAAAJkQDAAAwIRoAAIAJ0QAAAEzO6mjIysrSk08+qaysrEhP5azCugPAmSkm0hOIpLi4OA0fPjzS0zjrsO4AcGY6q19pAAAAdkQDAAAwIRoAAIAJ0QAAAEyIBgAAYEI0AAAAE6IBAACYEA0AAMCEaAAAACZEAwAAMCEaAACACdEAAABMiAYAAGBCNAAAABOiAQAAmBANAADAhGgAAAAmRAMAADAhGgAAgAnRAAAATIgGAABgQjQAAAATogEAAJgQDQAAwIRoAAAAJkQDAAAwIRoAAIAJ0QAAAEyIBgAAYEI0AAAAE6IBAACYEA0AAMCEaAAAACZEAwAAMCEaAACACdEAAABMiAYAAGBCNAAAABOiAQAAmBANAADAhGgAAAAmRAMAADAhGgAAgAnRAAAATIgGAABgQjQAAAATogEAAJgQDQAAwIRoAAAAJkQDAAAwIRoAAIAJ0QAAAEyIBgAAYEI0AAAAE6IBAACYEA0AAMCEaAAAACZEAwAAMCEaAACACdEAAABMiAYAAGBCNAAAABOiAQAAmBANAADAhGgAAAAmRAMAADAhGgAAgAnRAAAATIgGAABgQjQAAACTmEhPAMGijteffp/GuqD/hmtcAAA6QzT0ET6fT/1ivVJlqfk+8VXrunSMfrFe+Xy+rk4NAABJREOfkZqaqhXL/1v19T33ioDP51NqamqPjQ8A+HojGvqQ1NRUntQBAH0WF0ICAAATogEAAJgQDQAAwIRoAAAAJkQDAAAwIRoAAIAJ0QAAAEyIBgAAYEI0AAAAE6IBAACYEA0AAMCEaAAAACZEAwAAMCEaAACACdEAAABMiAYAAGBCNAAAABOiAQAAmBANAADAhGgAAAAmRAMAADAhGgAAgAnRAAAATIgGAABgQjQAAAATogEAAJgQDQAAwIRoAAAAJkQDAAAwIRoAAIAJ0QAAAEyIBgAAYEI0AAAAk5hQ7+ickyQ1NDSEbTIAAKBntT5vtz6Pd0XI0XD06FFJUmZmZqhDAACACDl69Kh8Pl+X7uNxoaSGJL/fr4MHD6p///7yeDyhDNGuhoYGZWZm6sCBA0pKSgrbuGcD1i40rFtoWLfQsG6hY+1C89V1c87p6NGjysjIUFRU165SCPmVhqioKA0ePDjUu59WUlISD4oQsXahYd1Cw7qFhnULHWsXmlPXrauvMLTiQkgAAGBCNAAAAJM+Fw1er1clJSXyer2RnsoZh7ULDesWGtYtNKxb6Fi70IRz3UK+EBIAAJxd+twrDQAAoG8iGgAAgAnRAAAATPpcNCxdulRDhgxRXFyc8vLytGnTpkhPqU9Zt26drrzySmVkZMjj8ejll18O2u6c01133aX09HTFx8dr2rRp2rt3b2Qm24csXrxY3/zmN9W/f3+dd955uuqqq1RRURG0z/HjxzVv3jwNHDhQiYmJ+qd/+ifV1tZGaMZ9x2OPPabc3NzAe7zz8/P1+uuvB7azbqd3//33y+Px6Ac/+EHgNtatfQsXLpTH4wn6GDlyZGA769axjz76SDNnztTAgQMVHx+vsWPHavPmzYHt4Xh+6FPR8Nxzz+m2225TSUmJtm7dqnHjxqmwsFCHDx+O9NT6jGPHjmncuHFaunRpu9t/9rOf6eGHH9bjjz+ujRs3KiEhQYWFhTp+/Hgvz7RvKS0t1bx587RhwwatXr1aJ06c0Le//W0dO3YssM+tt96qV199VS+88IJKS0t18OBB/eM//mMEZ903DB48WPfff7+2bNmizZs367LLLtP06dP17rvvSmLdTuedd97RE088odzc3KDbWbeOXXjhhTp06FDg489//nNgG+vWvs8++0wFBQXq16+fXn/9de3atUsPPvigBgwYENgnLM8Prg+ZPHmymzdvXuDvLS0tLiMjwy1evDiCs+q7JLlVq1YF/u73+11aWpp74IEHArfV1dU5r9fr/ud//icCM+y7Dh8+7CS50tJS59zJderXr5974YUXAvvs3r3bSXJlZWWRmmafNWDAAPfLX/6SdTuNo0ePumHDhrnVq1e7KVOmuFtuucU5x+OtMyUlJW7cuHHtbmPdOvajH/3I/e3f/m2H28P1/NBnXmlobm7Wli1bNG3atMBtUVFRmjZtmsrKyiI4szNHVVWVampqgtbQ5/MpLy+PNfyK+vp6SVJKSookacuWLTpx4kTQ2o0cOVJZWVms3SlaWlr07LPP6tixY8rPz2fdTmPevHn67ne/G7Q+Eo+309m7d68yMjKUk5OjoqIi7d+/XxLr1plXXnlFkyZN0tVXX63zzjtPEyZM0FNPPRXYHq7nhz4TDR9//LFaWlqUmpoadHtqaqpqamoiNKszS+s6sYad8/v9+sEPfqCCggKNGTNG0sm1i42NVXJyctC+rN1JO3bsUGJiorxer77//e9r1apVGj16NOvWiWeffVZbt27V4sWL22xj3TqWl5enZcuW6fe//70ee+wxVVVV6Vvf+paOHj3KunWisrJSjz32mIYNG6Y33nhDc+bM0fz58/XrX/9aUvieH0L+hVXAmWrevHnauXNn0PdJ0bkRI0aovLxc9fX1evHFFzVr1iyVlpZGelp91oEDB3TLLbdo9erViouLi/R0zijf+c53An/Ozc1VXl6esrOz9fzzzys+Pj6CM+vb/H6/Jk2apPvuu0+SNGHCBO3cuVOPP/64Zs2aFbbj9JlXGgYNGqTo6Og2V8HW1tYqLS0tQrM6s7SuE2vYsZtvvlm/+93v9Kc//Snot7SmpaWpublZdXV1QfuzdifFxsbqggsu0EUXXaTFixdr3Lhxeuihh1i3DmzZskWHDx/WxIkTFRMTo5iYGJWWlurhhx9WTEyMUlNTWTej5ORkDR8+XPv27ePx1on09HSNHj066LZRo0YFvrUTrueHPhMNsbGxuuiii7RmzZrAbX6/X2vWrFF+fn4EZ3bmGDp0qNLS0oLWsKGhQRs3bjzr19A5p5tvvlmrVq3SH//4Rw0dOjRo+0UXXaR+/foFrV1FRYX2799/1q9de/x+v5qamli3DkydOlU7duxQeXl54GPSpEkqKioK/Jl1s/n888/1/vvvKz09ncdbJwoKCtq8jXzPnj3Kzs6WFMbnh+5crRluzz77rPN6vW7ZsmVu165drri42CUnJ7uamppIT63POHr0qNu2bZvbtm2bk+SWLFnitm3b5qqrq51zzt1///0uOTnZ/fa3v3Xbt29306dPd0OHDnWNjY0RnnlkzZkzx/l8Prd27Vp36NChwMcXX3wR2Of73/++y8rKcn/84x/d5s2bXX5+vsvPz4/grPuGH//4x660tNRVVVW57du3ux//+MfO4/G4N9980znHulmd+u4J51i3jvzwhz90a9eudVVVVW79+vVu2rRpbtCgQe7w4cPOOdatI5s2bXIxMTFu0aJFbu/evW7lypXunHPOcStWrAjsE47nhz4VDc4598gjj7isrCwXGxvrJk+e7DZs2BDpKfUpf/rTn5ykNh+zZs1yzp18W81PfvITl5qa6rxer5s6daqrqKiI7KT7gPbWTJJ7+umnA/s0Nja6uXPnugEDBrhzzjnH/cM//IM7dOhQ5CbdR9xwww0uOzvbxcbGunPPPddNnTo1EAzOsW5WX40G1q191157rUtPT3exsbHu/PPPd9dee63bt29fYDvr1rFXX33VjRkzxnm9Xjdy5Ej35JNPBm0Px/MDv+USAACY9JlrGgAAQN9GNAAAABOiAQAAmBANAADAhGgAAAAmRAMAADAhGgAAgAnRAAAATIgGIEw8Ho9efvnlSE8DAHoM0QCgTxgyZIh+8YtfRHoaADpBNACQJJ04cSLSU+jTmpubIz0FIOKIBuAUL774osaOHav4+HgNHDhQ06ZN07Fjx/TOO+/o8ssv16BBg+Tz+TRlyhRt3bq107EOHDiga665RsnJyUpJSdH06dP1wQcfBLavXbtWkydPVkJCgpKTk1VQUKDq6urTznHhwoUaP368nnjiCWVmZuqcc87RNddco/r6+qD9fvnLX2rUqFGKi4vTyJEj9eijjwa2ffDBB/J4PHruuec0ZcoUxcXFaeXKlac99vr163XppZfqnHPO0YABA1RYWKjPPvtMUvuvFIwfP14LFy6UdPLXky9cuFBZWVnyer3KyMjQ/PnzJUmXXnqpqqurdeutt8rj8cjj8QTGeOmll3ThhRfK6/VqyJAhevDBB4OOMWTIEN1777267rrrlJiYqOzsbL3yyis6cuSIpk+frsTEROXm5mrz5s1B9/vzn/+sb33rW4qPj1dmZqbmz5+vY8eOBY17zz336LrrrlNSUpKKi4tPuz7A117Yfr0WcIY7ePCgi4mJcUuWLAn8GuilS5e6o0ePujVr1rjly5e73bt3u127drnZs2e71NRU19DQELi/JLdq1SrnnHPNzc1u1KhR7oYbbnDbt293u3btcjNmzHAjRoxwTU1N7sSJE87n87nbb7/d7du3z+3atcstW7Ys8CvOO1NSUuISEhLcZZdd5rZt2+ZKS0vdBRdc4GbMmBHYZ8WKFS49Pd299NJLrrKy0r300ksuJSXFLVu2zDnnXFVVlZPkhgwZEtjn4MGDnR5327Ztzuv1ujlz5rjy8nK3c+dO98gjj7gjR44455zLzs52P//5z4PuM27cOFdSUuKcc+6FF15wSUlJ7rXXXnPV1dVu48aNgd/C98knn7jBgwe7n/70p4FfW+6cc5s3b3ZRUVHupz/9qauoqHBPP/20i4+PD/rtpNnZ2S4lJcU9/vjjbs+ePW7OnDkuKSnJ/d3f/Z17/vnnXUVFhbvqqqvcqFGjnN/vd845t2/fPpeQkOB+/vOfuz179rj169e7CRMmuOuvvz5o3KSkJPcf//Efbt++fUG/aRE4WxENwP/ZsmWLk+Q++OCD0+7b0tLi+vfv71599dXAbadGw/Lly92IESMCT1LOOdfU1OTi4+PdG2+84T755BMnya1du7bL8ywpKXHR0dHuww8/DNz2+uuvu6ioqMCT7Te+8Q33zDPPBN3vnnvucfn5+c65v0bDL37xC/Nx//Vf/9UVFBR0uP100fDggw+64cOHu+bmZvP9Z8yY4S6//PKg2/7t3/7NjR49Ouh+M2fODPz90KFDTpL7yU9+EritrKzMSQqsz+zZs11xcXHQuG+99ZaLiopyjY2NgXGvuuqqDj9f4GzEtyeA/zNu3DhNnTpVY8eO1dVXX62nnnoq8NJ7bW2tbrzxRg0bNkw+n09JSUn6/PPPtX///nbH+stf/qJ9+/apf//+SkxMVGJiolJSUnT8+HG9//77SklJ0fXXX6/CwkJdeeWVeuihh3To0CHzXLOysnT++ecH/p6fny+/36+KigodO3ZM77//vmbPnh04dmJiou699169//77QeNMmjTJfMzy8nJNnTrVvP9XXX311WpsbFROTo5uvPFGrVq1Sl9++WWn99m9e7cKCgqCbisoKNDevXvV0tISuC03Nzfw59TUVEnS2LFj29x2+PBhSSf/fZYtWxa0PoWFhfL7/aqqqgrcryvrA5wNYiI9AaCviI6O1urVq/X222/rzTff1COPPKI77rhDGzdu1Jw5c/TJJ5/ooYceUnZ2trxer/Lz8zu8OO7zzz/XRRdd1O51Aueee64k6emnn9b8+fP1+9//Xs8995zuvPNOrV69WhdffHG3Po/PP/9ckvTUU08pLy+vzed4qoSEBPO48fHxnW6PioqScy7otlMvrszMzFRFRYX+8Ic/aPXq1Zo7d64eeOABlZaWql+/fuZ5tOfU+7deD9HebX6/X9LJNbrpppsC11ScKisrK/DnrqwPcDYgGoBTeDweFRQUqKCgQHfddZeys7O1atUqrV+/Xo8++qiuuOIKSScvcvz44487HGfixIl67rnndN555ykpKanD/SZMmKAJEyZowYIFys/P1zPPPGOKhv379+vgwYPKyMiQJG3YsEFRUVEaMWKEUlNTlZGRocrKShUVFXVxBTqWm5urNWvW6O677253+7nnnhv0aklDQ0PQ/7VLJ8Pjyiuv1JVXXql58+Zp5MiR2rFjhyZOnKjY2NigVw8kadSoUVq/fn3QbevXr9fw4cPbBFBXTJw4Ubt27dIFF1wQ8hjA2YhvTwD/Z+PGjbrvvvu0efNm7d+/X7/5zW905MgRjRo1SsOGDdPy5cu1e/dubdy4UUVFRZ3+n3dRUZEGDRqk6dOn66233lJVVZXWrl2r+fPn68MPP1RVVZUWLFigsrIyVVdX680339TevXs1atQo01zj4uI0a9Ys/eUvf9Fbb72l+fPn65prrlFaWpok6e6779bixYv18MMPa8+ePdqxY4eefvppLVmyJOT1WbBggd555x3NnTtX27dv13vvvafHHnssEE+XXXaZli9frrfeeks7duzQrFmzgp7Yly1bpl/96lfauXOnKisrtWLFCsXHxys7O1vSyXcrrFu3Th999FFgzB/+8Idas2aN7rnnHu3Zs0e//vWv9Z//+Z+6/fbbQ/48JOlHP/qR3n77bd18880qLy/X3r179dvf/lY333xzt8YFvvYifVEF0Ffs2rXLFRYWunPPPdd5vV43fPhw98gjjzjnnNu6daubNGmSi4uLc8OGDXMvvPBCmwv3dMqFkM6dvCDvuuuuc4MGDXJer9fl5OS4G2+80dXX17uamhp31VVXufT0dBcbG+uys7PdXXfd5VpaWk47z5KSEjdu3Dj36KOPuoyMDBcXF+f++Z//2X366adB+61cudKNHz/excbGugEDBrhLLrnE/eY3v3HO/fVCyG3btnVpjdauXev+5m/+xnm9XpecnOwKCwvdZ5995pxzrr6+3l177bUuKSnJZWZmumXLlgVdCLlq1SqXl5fnkpKSXEJCgrv44ovdH/7wh8DYZWVlLjc313m9Xnfql6YXX3zRjR492vXr189lZWW5Bx54IGhO7V1A+dV/i/Y+302bNrnLL7/cJSYmuoSEBJebm+sWLVrU6bjA2c7j3Fe+CQmgT1u4cKFefvlllZeXR3oqAM4yfHsCAACYEA1AH3PhhRcGvRXw1A/LT20M1Xe+850Oj3vffff12HEBnDn49gTQx1RXV3f4eyBSU1PVv3//HjnuRx99pMbGxna3paSkKCUlpUeOC+DMQTQAAAATvj0BAABMiAYAAGBCNAAAABOiAQAAmBANAADAhGgAAAAmRAMAADAhGgAAgMn/ByDKzdToA3vdAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(x=df['sales_per_customer'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "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>Unnamed: 0</th>\n",
       "      <th>store_ID</th>\n",
       "      <th>nb_customers_on_day</th>\n",
       "      <th>open</th>\n",
       "      <th>promotion</th>\n",
       "      <th>school_holiday</th>\n",
       "      <th>sales</th>\n",
       "      <th>state_holiday_encoded</th>\n",
       "      <th>quarter</th>\n",
       "      <th>day_of_week_2</th>\n",
       "      <th>day_of_week_3</th>\n",
       "      <th>day_of_week_4</th>\n",
       "      <th>day_of_week_5</th>\n",
       "      <th>day_of_week_6</th>\n",
       "      <th>day_of_week_7</th>\n",
       "      <th>sales_per_customer</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>425390</td>\n",
       "      <td>366</td>\n",
       "      <td>517</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4422</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>8.553191</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>291687</td>\n",
       "      <td>394</td>\n",
       "      <td>694</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8297</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>11.955331</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>411278</td>\n",
       "      <td>807</td>\n",
       "      <td>970</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>9729</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>10.029897</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>664714</td>\n",
       "      <td>802</td>\n",
       "      <td>473</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>6513</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>13.769556</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>540835</td>\n",
       "      <td>726</td>\n",
       "      <td>1068</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>10882</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>10.189139</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0  store_ID  nb_customers_on_day  open  promotion  school_holiday  \\\n",
       "0      425390       366                  517     1          0               0   \n",
       "1      291687       394                  694     1          0               0   \n",
       "2      411278       807                  970     1          1               0   \n",
       "3      664714       802                  473     1          1               0   \n",
       "4      540835       726                 1068     1          1               0   \n",
       "\n",
       "   sales  state_holiday_encoded  quarter  day_of_week_2  day_of_week_3  \\\n",
       "0   4422                      0        2          False          False   \n",
       "1   8297                      0        2          False          False   \n",
       "2   9729                      0        3          False          False   \n",
       "3   6513                      0        2           True          False   \n",
       "4  10882                      0        4          False          False   \n",
       "\n",
       "   day_of_week_4  day_of_week_5  day_of_week_6  day_of_week_7  \\\n",
       "0           True          False          False          False   \n",
       "1          False          False           True          False   \n",
       "2           True          False          False          False   \n",
       "3          False          False          False          False   \n",
       "4           True          False          False          False   \n",
       "\n",
       "   sales_per_customer  \n",
       "0            8.553191  \n",
       "1           11.955331  \n",
       "2           10.029897  \n",
       "3           13.769556  \n",
       "4           10.189139  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "441778"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['sales_per_customer'].nunique()"
   ]
  }
 ],
 "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": "3.12.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}