EDA.ipynb

{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Importing the required libraries for exploratory data analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd \n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "\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>order_id</th>\n",
       "      <th>user_id</th>\n",
       "      <th>eval_set</th>\n",
       "      <th>order_number</th>\n",
       "      <th>order_dow</th>\n",
       "      <th>order_hour_of_day</th>\n",
       "      <th>days_since_prior_order</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2539329</td>\n",
       "      <td>1</td>\n",
       "      <td>prior</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2398795</td>\n",
       "      <td>1</td>\n",
       "      <td>prior</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>7</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>473747</td>\n",
       "      <td>1</td>\n",
       "      <td>prior</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>12</td>\n",
       "      <td>21.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2254736</td>\n",
       "      <td>1</td>\n",
       "      <td>prior</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>7</td>\n",
       "      <td>29.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>431534</td>\n",
       "      <td>1</td>\n",
       "      <td>prior</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>15</td>\n",
       "      <td>28.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   order_id  user_id eval_set  order_number  order_dow  order_hour_of_day  \\\n",
       "0   2539329        1    prior             1          2                  8   \n",
       "1   2398795        1    prior             2          3                  7   \n",
       "2    473747        1    prior             3          3                 12   \n",
       "3   2254736        1    prior             4          4                  7   \n",
       "4    431534        1    prior             5          4                 15   \n",
       "\n",
       "   days_since_prior_order  \n",
       "0                     NaN  \n",
       "1                    15.0  \n",
       "2                    21.0  \n",
       "3                    29.0  \n",
       "4                    28.0  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "orders = pd.read_csv(\"Data/orders.csv\")\n",
    "orders.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "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>order_id</th>\n",
       "      <th>user_id</th>\n",
       "      <th>order_number</th>\n",
       "      <th>order_dow</th>\n",
       "      <th>order_hour_of_day</th>\n",
       "      <th>days_since_prior_order</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>3.421083e+06</td>\n",
       "      <td>3.421083e+06</td>\n",
       "      <td>3.421083e+06</td>\n",
       "      <td>3.421083e+06</td>\n",
       "      <td>3.421083e+06</td>\n",
       "      <td>3.214874e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1.710542e+06</td>\n",
       "      <td>1.029782e+05</td>\n",
       "      <td>1.715486e+01</td>\n",
       "      <td>2.776219e+00</td>\n",
       "      <td>1.345202e+01</td>\n",
       "      <td>1.111484e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>9.875817e+05</td>\n",
       "      <td>5.953372e+04</td>\n",
       "      <td>1.773316e+01</td>\n",
       "      <td>2.046829e+00</td>\n",
       "      <td>4.226088e+00</td>\n",
       "      <td>9.206737e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>8.552715e+05</td>\n",
       "      <td>5.139400e+04</td>\n",
       "      <td>5.000000e+00</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>1.000000e+01</td>\n",
       "      <td>4.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1.710542e+06</td>\n",
       "      <td>1.026890e+05</td>\n",
       "      <td>1.100000e+01</td>\n",
       "      <td>3.000000e+00</td>\n",
       "      <td>1.300000e+01</td>\n",
       "      <td>7.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>2.565812e+06</td>\n",
       "      <td>1.543850e+05</td>\n",
       "      <td>2.300000e+01</td>\n",
       "      <td>5.000000e+00</td>\n",
       "      <td>1.600000e+01</td>\n",
       "      <td>1.500000e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>3.421083e+06</td>\n",
       "      <td>2.062090e+05</td>\n",
       "      <td>1.000000e+02</td>\n",
       "      <td>6.000000e+00</td>\n",
       "      <td>2.300000e+01</td>\n",
       "      <td>3.000000e+01</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           order_id       user_id  order_number     order_dow  \\\n",
       "count  3.421083e+06  3.421083e+06  3.421083e+06  3.421083e+06   \n",
       "mean   1.710542e+06  1.029782e+05  1.715486e+01  2.776219e+00   \n",
       "std    9.875817e+05  5.953372e+04  1.773316e+01  2.046829e+00   \n",
       "min    1.000000e+00  1.000000e+00  1.000000e+00  0.000000e+00   \n",
       "25%    8.552715e+05  5.139400e+04  5.000000e+00  1.000000e+00   \n",
       "50%    1.710542e+06  1.026890e+05  1.100000e+01  3.000000e+00   \n",
       "75%    2.565812e+06  1.543850e+05  2.300000e+01  5.000000e+00   \n",
       "max    3.421083e+06  2.062090e+05  1.000000e+02  6.000000e+00   \n",
       "\n",
       "       order_hour_of_day  days_since_prior_order  \n",
       "count       3.421083e+06            3.214874e+06  \n",
       "mean        1.345202e+01            1.111484e+01  \n",
       "std         4.226088e+00            9.206737e+00  \n",
       "min         0.000000e+00            0.000000e+00  \n",
       "25%         1.000000e+01            4.000000e+00  \n",
       "50%         1.300000e+01            7.000000e+00  \n",
       "75%         1.600000e+01            1.500000e+01  \n",
       "max         2.300000e+01            3.000000e+01  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "orders.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Users')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(10,6))\n",
    "ax = plt.axes()\n",
    "ax.hist(orders.user_id.value_counts(),bins=100)\n",
    "ax.set_title(\"Orders per user\")\n",
    "ax.set_xlabel(\"Orders\")\n",
    "ax.set_ylabel(\"Users\")"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As we can tell that most users placing orders <20."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean orders per customer: 16.590367054784224\n",
      "Median orders per customer: 10.0\n"
     ]
    }
   ],
   "source": [
    "print(f\"Mean orders per customer: {orders.user_id.value_counts().mean()}\")\n",
    "print(f\"Median orders per customer: {orders.user_id.value_counts().median()}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,6))\n",
    "plt.hist(orders.user_id.value_counts(),bins=100,color=\"red\")\n",
    "plt.axvline(orders.user_id.value_counts().mean(),color=\"black\",label=\"Mean\")\n",
    "plt.axvline(orders.user_id.value_counts().median(),color=\"blue\",label=\"Median\")\n",
    "plt.title(\"Orders per user\")\n",
    "plt.xlabel(\"Orders\")\n",
    "plt.ylabel(\"Users\")\n",
    "plt.legend();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,8))\n",
    "plt.hist(orders.order_dow,bins=7,color=\"orange\",histtype=\"bar\")\n",
    "plt.title(\"Orders per day\")\n",
    "plt.xlabel(\"Day of week\")\n",
    "plt.ylabel(\"Orders\")\n",
    "sns.despine()\n",
    "plt.show();"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "day0 starts with Sunday and ends with Saturday, Most people have placed their orders on Sunday (pretty predictable)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "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>product_id</th>\n",
       "      <th>product_name</th>\n",
       "      <th>aisle_id</th>\n",
       "      <th>department_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Chocolate Sandwich Cookies</td>\n",
       "      <td>61</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>All-Seasons Salt</td>\n",
       "      <td>104</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Robust Golden Unsweetened Oolong Tea</td>\n",
       "      <td>94</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Smart Ones Classic Favorites Mini Rigatoni Wit...</td>\n",
       "      <td>38</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Green Chile Anytime Sauce</td>\n",
       "      <td>5</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   product_id                                       product_name  aisle_id  \\\n",
       "0           1                         Chocolate Sandwich Cookies        61   \n",
       "1           2                                   All-Seasons Salt       104   \n",
       "2           3               Robust Golden Unsweetened Oolong Tea        94   \n",
       "3           4  Smart Ones Classic Favorites Mini Rigatoni Wit...        38   \n",
       "4           5                          Green Chile Anytime Sauce         5   \n",
       "\n",
       "   department_id  \n",
       "0             19  \n",
       "1             13  \n",
       "2              7  \n",
       "3              1  \n",
       "4             13  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "products = pd.read_csv(\"Data/products.csv\")\n",
    "products.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x144 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(6,2))\n",
    "plt.hist(products.aisle_id)\n",
    "plt.title(\"Products in Aisles\")\n",
    "plt.tight_layout();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x144 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(6,2))\n",
    "plt.hist(products.department_id)\n",
    "plt.title(\"Products in Departments\")\n",
    "plt.tight_layout();"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Most of the products are from Department id 20, which are deli products or ready-to-eat items such as meat cuts,cheese,sandwiches,breads and so on."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "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>aisle_id</th>\n",
       "      <th>aisle</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>prepared soups salads</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>specialty cheeses</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>energy granola bars</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>instant foods</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>marinades meat preparation</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   aisle_id                       aisle\n",
       "0         1       prepared soups salads\n",
       "1         2           specialty cheeses\n",
       "2         3         energy granola bars\n",
       "3         4               instant foods\n",
       "4         5  marinades meat preparation"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aisles = pd.read_csv(\"Data/aisles.csv\")\n",
    "aisles.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total products on aisles: 134\n",
      "No.of unique products on aisles: 134\n"
     ]
    }
   ],
   "source": [
    "print(f\"Total products on aisles: {len(aisles['aisle'])}\")\n",
    "print(f\"No.of unique products on aisles: {len(aisles['aisle'].unique())}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "days = {0:'Sun', 1:'Mon', 2:'Tue', 3:'Wed', 4:'Thu', 5:'Fri', 6:'Sat'}\n",
    "values = [orders.order_dow.value_counts()[day] for day in days.keys()]\n",
    "plt.bar(days.values(),values)\n",
    "plt.title(\"Orders by week\")\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "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>department_id</th>\n",
       "      <th>department</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>frozen</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>other</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>bakery</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>produce</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>alcohol</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   department_id department\n",
       "0              1     frozen\n",
       "1              2      other\n",
       "2              3     bakery\n",
       "3              4    produce\n",
       "4              5    alcohol"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "departments = pd.read_csv(\"Data/departments.csv\")\n",
    "departments.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "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>order_id</th>\n",
       "      <th>product_id</th>\n",
       "      <th>add_to_cart_order</th>\n",
       "      <th>reordered</th>\n",
       "      <th>product_name</th>\n",
       "      <th>aisle_id</th>\n",
       "      <th>department_id</th>\n",
       "      <th>user_id</th>\n",
       "      <th>eval_set</th>\n",
       "      <th>order_number</th>\n",
       "      <th>order_dow</th>\n",
       "      <th>order_hour_of_day</th>\n",
       "      <th>days_since_prior_order</th>\n",
       "      <th>department</th>\n",
       "      <th>aisle</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>49302</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulgarian Yogurt</td>\n",
       "      <td>120</td>\n",
       "      <td>16</td>\n",
       "      <td>112108</td>\n",
       "      <td>train</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>10</td>\n",
       "      <td>9.0</td>\n",
       "      <td>dairy eggs</td>\n",
       "      <td>yogurt</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>98</td>\n",
       "      <td>43654</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>Whole Milk Greek Blended Vanilla Bean Yogurt</td>\n",
       "      <td>120</td>\n",
       "      <td>16</td>\n",
       "      <td>56463</td>\n",
       "      <td>train</td>\n",
       "      <td>41</td>\n",
       "      <td>3</td>\n",
       "      <td>8</td>\n",
       "      <td>14.0</td>\n",
       "      <td>dairy eggs</td>\n",
       "      <td>yogurt</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>170</td>\n",
       "      <td>8153</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>Plain Non-Fat Greek Yogurt</td>\n",
       "      <td>120</td>\n",
       "      <td>16</td>\n",
       "      <td>182389</td>\n",
       "      <td>train</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td>14.0</td>\n",
       "      <td>dairy eggs</td>\n",
       "      <td>yogurt</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>631</td>\n",
       "      <td>9203</td>\n",
       "      <td>13</td>\n",
       "      <td>1</td>\n",
       "      <td>Dairy Free Coconut Milk Raspberry Yogurt Alter...</td>\n",
       "      <td>120</td>\n",
       "      <td>16</td>\n",
       "      <td>184099</td>\n",
       "      <td>train</td>\n",
       "      <td>7</td>\n",
       "      <td>3</td>\n",
       "      <td>9</td>\n",
       "      <td>30.0</td>\n",
       "      <td>dairy eggs</td>\n",
       "      <td>yogurt</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>631</td>\n",
       "      <td>15842</td>\n",
       "      <td>14</td>\n",
       "      <td>1</td>\n",
       "      <td>Dairy Free Coconut Milk Yogurt Alternative</td>\n",
       "      <td>120</td>\n",
       "      <td>16</td>\n",
       "      <td>184099</td>\n",
       "      <td>train</td>\n",
       "      <td>7</td>\n",
       "      <td>3</td>\n",
       "      <td>9</td>\n",
       "      <td>30.0</td>\n",
       "      <td>dairy eggs</td>\n",
       "      <td>yogurt</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   order_id  product_id  add_to_cart_order  reordered  \\\n",
       "0         1       49302                  1          1   \n",
       "1        98       43654                  3          1   \n",
       "2       170        8153                  6          0   \n",
       "3       631        9203                 13          1   \n",
       "4       631       15842                 14          1   \n",
       "\n",
       "                                        product_name  aisle_id  department_id  \\\n",
       "0                                   Bulgarian Yogurt       120             16   \n",
       "1       Whole Milk Greek Blended Vanilla Bean Yogurt       120             16   \n",
       "2                         Plain Non-Fat Greek Yogurt       120             16   \n",
       "3  Dairy Free Coconut Milk Raspberry Yogurt Alter...       120             16   \n",
       "4         Dairy Free Coconut Milk Yogurt Alternative       120             16   \n",
       "\n",
       "   user_id eval_set  order_number  order_dow  order_hour_of_day  \\\n",
       "0   112108    train             4          4                 10   \n",
       "1    56463    train            41          3                  8   \n",
       "2   182389    train             7          0                 13   \n",
       "3   184099    train             7          3                  9   \n",
       "4   184099    train             7          3                  9   \n",
       "\n",
       "   days_since_prior_order  department   aisle  \n",
       "0                     9.0  dairy eggs  yogurt  \n",
       "1                    14.0  dairy eggs  yogurt  \n",
       "2                    14.0  dairy eggs  yogurt  \n",
       "3                    30.0  dairy eggs  yogurt  \n",
       "4                    30.0  dairy eggs  yogurt  "
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "order_prod_train = pd.read_csv(\"Data/order_products__train.csv\")\n",
    "order_prod_prior = pd.read_csv(\"Data/order_products__prior.csv\")\n",
    "order_prod = pd.concat([order_prod_train,order_prod_prior])\n",
    "order_products = order_prod.merge(products, on='product_id', how='left').merge(orders, on='order_id', how='left').merge(departments, on='department_id').merge(aisles, on='aisle_id')\n",
    "order_products.head()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "*Ratio of reordered products:*\n",
    "* 58.96% of products in prior orders were re-ordered\n",
    "* 59.85% of products in train orders were re-order"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "total_orders = order_products['order_id'].nunique()\n",
    "products_frequency_desc = order_products.groupby('product_name')['order_id'].aggregate('count').reset_index()\n",
    "products_frequency_desc['count_of_ordering'] =  products_frequency_desc['order_id']\n",
    "products_frequency_desc = products_frequency_desc.sort_values(by=['count_of_ordering'], ascending=False)\n",
    "\n",
    "products_frequency_desc['percentage_of_ordering'] = (products_frequency_desc['count_of_ordering']/total_orders) * 100 \n",
    "products_frequency_desc.iloc[:30].plot.bar(x='product_name', y='percentage_of_ordering')\n",
    "plt.xlabel('30 most frequently ordered products')\n",
    "plt.ylabel('percentage of being ordered')\n",
    "plt.xticks(rotation=90)\n",
    "plt.title('Percentage of ordering a product')\n",
    "plt.show()\n",
    "\n",
    "products_frequency_desc.iloc[:30].plot.bar(x='product_name', y='count_of_ordering')\n",
    "plt.xlabel('30 most frequently ordered products')\n",
    "plt.ylabel('count of orders')\n",
    "plt.xticks(rotation=90)\n",
    "plt.title('Count of orders having a product')\n",
    "plt.show()\n",
    "\n",
    "del products_frequency_desc"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "*How often a product is the first item purchased:*\n",
    "> 5 most products added to the cart:\n",
    "\n",
    "    * Banana\n",
    "    * Bag of Organic Bananas\n",
    "    * Organic Strawberries\n",
    "    * Organic Baby spinach\n",
    "    * Organic Hass Avocado\n",
    "* 15>% of the orders are Bananas\n",
    "* People always go for the \"Organic\" items the most"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Purchasing behaviour on Departments:\n",
    "*Count of products in each department*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "colors = sns.color_palette(\"crest\",8)\n",
    "prod_dept = products.merge(departments, on='department_id', how='left')\n",
    "data = prod_dept.groupby(['department']).agg({'product_id':'count'}).reset_index().rename(columns={'product_id':'products_count'})\n",
    "plt.pie(data['products_count'], labels = data['department'], colors = colors, autopct='%.0f%%', radius=1.7)\n",
    "plt.title('count of products in each department')\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "base",
   "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": "3.8.8"
  },
  "orig_nbformat": 4,
  "vscode": {
   "interpreter": {
    "hash": "e0ce1521a7301c1560a645ddd855208a2d7b05c9f8dc5e19ed903ef2b2623e0e"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}