black_friday_Sales_Analysis.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Import Libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(550068, 12)"
      ]
     },
     "execution_count": 122,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(r\"/Users/krishnaapurva/Downloads/train.csv\")\n",
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>User_ID</th>\n",
       "      <th>Product_ID</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Age</th>\n",
       "      <th>Occupation</th>\n",
       "      <th>City_Category</th>\n",
       "      <th>Stay_In_Current_City_Years</th>\n",
       "      <th>Marital_Status</th>\n",
       "      <th>Product_Category_1</th>\n",
       "      <th>Product_Category_2</th>\n",
       "      <th>Product_Category_3</th>\n",
       "      <th>Purchase</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1000001</td>\n",
       "      <td>P00069042</td>\n",
       "      <td>F</td>\n",
       "      <td>0-17</td>\n",
       "      <td>10</td>\n",
       "      <td>A</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8370</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1000001</td>\n",
       "      <td>P00248942</td>\n",
       "      <td>F</td>\n",
       "      <td>0-17</td>\n",
       "      <td>10</td>\n",
       "      <td>A</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>6.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>15200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1000001</td>\n",
       "      <td>P00087842</td>\n",
       "      <td>F</td>\n",
       "      <td>0-17</td>\n",
       "      <td>10</td>\n",
       "      <td>A</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1422</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1000001</td>\n",
       "      <td>P00085442</td>\n",
       "      <td>F</td>\n",
       "      <td>0-17</td>\n",
       "      <td>10</td>\n",
       "      <td>A</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "      <td>14.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1057</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1000002</td>\n",
       "      <td>P00285442</td>\n",
       "      <td>M</td>\n",
       "      <td>55+</td>\n",
       "      <td>16</td>\n",
       "      <td>C</td>\n",
       "      <td>4+</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7969</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1000003</td>\n",
       "      <td>P00193542</td>\n",
       "      <td>M</td>\n",
       "      <td>26-35</td>\n",
       "      <td>15</td>\n",
       "      <td>A</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15227</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1000004</td>\n",
       "      <td>P00184942</td>\n",
       "      <td>M</td>\n",
       "      <td>46-50</td>\n",
       "      <td>7</td>\n",
       "      <td>B</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>8.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>19215</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1000004</td>\n",
       "      <td>P00346142</td>\n",
       "      <td>M</td>\n",
       "      <td>46-50</td>\n",
       "      <td>7</td>\n",
       "      <td>B</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>15.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15854</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1000004</td>\n",
       "      <td>P0097242</td>\n",
       "      <td>M</td>\n",
       "      <td>46-50</td>\n",
       "      <td>7</td>\n",
       "      <td>B</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>16.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15686</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1000005</td>\n",
       "      <td>P00274942</td>\n",
       "      <td>M</td>\n",
       "      <td>26-35</td>\n",
       "      <td>20</td>\n",
       "      <td>A</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7871</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   User_ID Product_ID Gender    Age  Occupation City_Category  \\\n",
       "0  1000001  P00069042      F   0-17          10             A   \n",
       "1  1000001  P00248942      F   0-17          10             A   \n",
       "2  1000001  P00087842      F   0-17          10             A   \n",
       "3  1000001  P00085442      F   0-17          10             A   \n",
       "4  1000002  P00285442      M    55+          16             C   \n",
       "5  1000003  P00193542      M  26-35          15             A   \n",
       "6  1000004  P00184942      M  46-50           7             B   \n",
       "7  1000004  P00346142      M  46-50           7             B   \n",
       "8  1000004   P0097242      M  46-50           7             B   \n",
       "9  1000005  P00274942      M  26-35          20             A   \n",
       "\n",
       "  Stay_In_Current_City_Years  Marital_Status  Product_Category_1  \\\n",
       "0                          2               0                   3   \n",
       "1                          2               0                   1   \n",
       "2                          2               0                  12   \n",
       "3                          2               0                  12   \n",
       "4                         4+               0                   8   \n",
       "5                          3               0                   1   \n",
       "6                          2               1                   1   \n",
       "7                          2               1                   1   \n",
       "8                          2               1                   1   \n",
       "9                          1               1                   8   \n",
       "\n",
       "   Product_Category_2  Product_Category_3  Purchase  \n",
       "0                 NaN                 NaN      8370  \n",
       "1                 6.0                14.0     15200  \n",
       "2                 NaN                 NaN      1422  \n",
       "3                14.0                 NaN      1057  \n",
       "4                 NaN                 NaN      7969  \n",
       "5                 2.0                 NaN     15227  \n",
       "6                 8.0                17.0     19215  \n",
       "7                15.0                 NaN     15854  \n",
       "8                16.0                 NaN     15686  \n",
       "9                 NaN                 NaN      7871  "
      ]
     },
     "execution_count": 123,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<bound method DataFrame.info of         User_ID Product_ID Gender    Age  Occupation City_Category  \\\n",
       "0       1000001  P00069042      F   0-17          10             A   \n",
       "1       1000001  P00248942      F   0-17          10             A   \n",
       "2       1000001  P00087842      F   0-17          10             A   \n",
       "3       1000001  P00085442      F   0-17          10             A   \n",
       "4       1000002  P00285442      M    55+          16             C   \n",
       "...         ...        ...    ...    ...         ...           ...   \n",
       "550063  1006033  P00372445      M  51-55          13             B   \n",
       "550064  1006035  P00375436      F  26-35           1             C   \n",
       "550065  1006036  P00375436      F  26-35          15             B   \n",
       "550066  1006038  P00375436      F    55+           1             C   \n",
       "550067  1006039  P00371644      F  46-50           0             B   \n",
       "\n",
       "       Stay_In_Current_City_Years  Marital_Status  Product_Category_1  \\\n",
       "0                               2               0                   3   \n",
       "1                               2               0                   1   \n",
       "2                               2               0                  12   \n",
       "3                               2               0                  12   \n",
       "4                              4+               0                   8   \n",
       "...                           ...             ...                 ...   \n",
       "550063                          1               1                  20   \n",
       "550064                          3               0                  20   \n",
       "550065                         4+               1                  20   \n",
       "550066                          2               0                  20   \n",
       "550067                         4+               1                  20   \n",
       "\n",
       "        Product_Category_2  Product_Category_3  Purchase  \n",
       "0                      NaN                 NaN      8370  \n",
       "1                      6.0                14.0     15200  \n",
       "2                      NaN                 NaN      1422  \n",
       "3                     14.0                 NaN      1057  \n",
       "4                      NaN                 NaN      7969  \n",
       "...                    ...                 ...       ...  \n",
       "550063                 NaN                 NaN       368  \n",
       "550064                 NaN                 NaN       371  \n",
       "550065                 NaN                 NaN       137  \n",
       "550066                 NaN                 NaN       365  \n",
       "550067                 NaN                 NaN       490  \n",
       "\n",
       "[550068 rows x 12 columns]>"
      ]
     },
     "execution_count": 124,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.info"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Check the basic statistics of the dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>User_ID</th>\n",
       "      <th>Occupation</th>\n",
       "      <th>Marital_Status</th>\n",
       "      <th>Product_Category_1</th>\n",
       "      <th>Product_Category_2</th>\n",
       "      <th>Product_Category_3</th>\n",
       "      <th>Purchase</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>5.500680e+05</td>\n",
       "      <td>550068.000000</td>\n",
       "      <td>550068.000000</td>\n",
       "      <td>550068.000000</td>\n",
       "      <td>376430.000000</td>\n",
       "      <td>166821.000000</td>\n",
       "      <td>550068.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1.003029e+06</td>\n",
       "      <td>8.076707</td>\n",
       "      <td>0.409653</td>\n",
       "      <td>5.404270</td>\n",
       "      <td>9.842329</td>\n",
       "      <td>12.668243</td>\n",
       "      <td>9263.968713</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.727592e+03</td>\n",
       "      <td>6.522660</td>\n",
       "      <td>0.491770</td>\n",
       "      <td>3.936211</td>\n",
       "      <td>5.086590</td>\n",
       "      <td>4.125338</td>\n",
       "      <td>5023.065394</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000001e+06</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>12.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.001516e+06</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>5823.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1.003077e+06</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>8047.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1.004478e+06</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>12054.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.006040e+06</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>23961.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            User_ID     Occupation  Marital_Status  Product_Category_1  \\\n",
       "count  5.500680e+05  550068.000000   550068.000000       550068.000000   \n",
       "mean   1.003029e+06       8.076707        0.409653            5.404270   \n",
       "std    1.727592e+03       6.522660        0.491770            3.936211   \n",
       "min    1.000001e+06       0.000000        0.000000            1.000000   \n",
       "25%    1.001516e+06       2.000000        0.000000            1.000000   \n",
       "50%    1.003077e+06       7.000000        0.000000            5.000000   \n",
       "75%    1.004478e+06      14.000000        1.000000            8.000000   \n",
       "max    1.006040e+06      20.000000        1.000000           20.000000   \n",
       "\n",
       "       Product_Category_2  Product_Category_3       Purchase  \n",
       "count       376430.000000       166821.000000  550068.000000  \n",
       "mean             9.842329           12.668243    9263.968713  \n",
       "std              5.086590            4.125338    5023.065394  \n",
       "min              2.000000            3.000000      12.000000  \n",
       "25%              5.000000            9.000000    5823.000000  \n",
       "50%              9.000000           14.000000    8047.000000  \n",
       "75%             15.000000           16.000000   12054.000000  \n",
       "max             18.000000           18.000000   23961.000000  "
      ]
     },
     "execution_count": 126,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Rename Column Name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.columns = df.columns.str.lower()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_id</th>\n",
       "      <th>product_id</th>\n",
       "      <th>gender</th>\n",
       "      <th>age</th>\n",
       "      <th>occupation</th>\n",
       "      <th>city_category</th>\n",
       "      <th>stay_in_current_city_years</th>\n",
       "      <th>marital_status</th>\n",
       "      <th>product_category_1</th>\n",
       "      <th>product_category_2</th>\n",
       "      <th>product_category_3</th>\n",
       "      <th>purchase</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1000001</td>\n",
       "      <td>P00069042</td>\n",
       "      <td>F</td>\n",
       "      <td>0-17</td>\n",
       "      <td>10</td>\n",
       "      <td>A</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8370</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1000001</td>\n",
       "      <td>P00248942</td>\n",
       "      <td>F</td>\n",
       "      <td>0-17</td>\n",
       "      <td>10</td>\n",
       "      <td>A</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>6.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>15200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1000001</td>\n",
       "      <td>P00087842</td>\n",
       "      <td>F</td>\n",
       "      <td>0-17</td>\n",
       "      <td>10</td>\n",
       "      <td>A</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1422</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1000001</td>\n",
       "      <td>P00085442</td>\n",
       "      <td>F</td>\n",
       "      <td>0-17</td>\n",
       "      <td>10</td>\n",
       "      <td>A</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "      <td>14.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1057</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1000002</td>\n",
       "      <td>P00285442</td>\n",
       "      <td>M</td>\n",
       "      <td>55+</td>\n",
       "      <td>16</td>\n",
       "      <td>C</td>\n",
       "      <td>4+</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7969</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>550063</th>\n",
       "      <td>1006033</td>\n",
       "      <td>P00372445</td>\n",
       "      <td>M</td>\n",
       "      <td>51-55</td>\n",
       "      <td>13</td>\n",
       "      <td>B</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>20</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>368</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>550064</th>\n",
       "      <td>1006035</td>\n",
       "      <td>P00375436</td>\n",
       "      <td>F</td>\n",
       "      <td>26-35</td>\n",
       "      <td>1</td>\n",
       "      <td>C</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>20</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>371</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>550065</th>\n",
       "      <td>1006036</td>\n",
       "      <td>P00375436</td>\n",
       "      <td>F</td>\n",
       "      <td>26-35</td>\n",
       "      <td>15</td>\n",
       "      <td>B</td>\n",
       "      <td>4+</td>\n",
       "      <td>1</td>\n",
       "      <td>20</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>550066</th>\n",
       "      <td>1006038</td>\n",
       "      <td>P00375436</td>\n",
       "      <td>F</td>\n",
       "      <td>55+</td>\n",
       "      <td>1</td>\n",
       "      <td>C</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>20</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>365</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>550067</th>\n",
       "      <td>1006039</td>\n",
       "      <td>P00371644</td>\n",
       "      <td>F</td>\n",
       "      <td>46-50</td>\n",
       "      <td>0</td>\n",
       "      <td>B</td>\n",
       "      <td>4+</td>\n",
       "      <td>1</td>\n",
       "      <td>20</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>490</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>550068 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        user_id product_id gender    age  occupation city_category  \\\n",
       "0       1000001  P00069042      F   0-17          10             A   \n",
       "1       1000001  P00248942      F   0-17          10             A   \n",
       "2       1000001  P00087842      F   0-17          10             A   \n",
       "3       1000001  P00085442      F   0-17          10             A   \n",
       "4       1000002  P00285442      M    55+          16             C   \n",
       "...         ...        ...    ...    ...         ...           ...   \n",
       "550063  1006033  P00372445      M  51-55          13             B   \n",
       "550064  1006035  P00375436      F  26-35           1             C   \n",
       "550065  1006036  P00375436      F  26-35          15             B   \n",
       "550066  1006038  P00375436      F    55+           1             C   \n",
       "550067  1006039  P00371644      F  46-50           0             B   \n",
       "\n",
       "       stay_in_current_city_years  marital_status  product_category_1  \\\n",
       "0                               2               0                   3   \n",
       "1                               2               0                   1   \n",
       "2                               2               0                  12   \n",
       "3                               2               0                  12   \n",
       "4                              4+               0                   8   \n",
       "...                           ...             ...                 ...   \n",
       "550063                          1               1                  20   \n",
       "550064                          3               0                  20   \n",
       "550065                         4+               1                  20   \n",
       "550066                          2               0                  20   \n",
       "550067                         4+               1                  20   \n",
       "\n",
       "        product_category_2  product_category_3  purchase  \n",
       "0                      NaN                 NaN      8370  \n",
       "1                      6.0                14.0     15200  \n",
       "2                      NaN                 NaN      1422  \n",
       "3                     14.0                 NaN      1057  \n",
       "4                      NaN                 NaN      7969  \n",
       "...                    ...                 ...       ...  \n",
       "550063                 NaN                 NaN       368  \n",
       "550064                 NaN                 NaN       371  \n",
       "550065                 NaN                 NaN       137  \n",
       "550066                 NaN                 NaN       365  \n",
       "550067                 NaN                 NaN       490  \n",
       "\n",
       "[550068 rows x 12 columns]"
      ]
     },
     "execution_count": 128,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Check for missing values in the data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Missing values in each column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "user_id                            0\n",
       "product_id                         0\n",
       "gender                             0\n",
       "age                                0\n",
       "occupation                         0\n",
       "city_category                      0\n",
       "stay_in_current_city_years         0\n",
       "marital_status                     0\n",
       "product_category_1                 0\n",
       "product_category_2            173638\n",
       "product_category_3            383247\n",
       "purchase                           0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 129,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "missing_value = df.isna().sum()\n",
    "missing_value"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Check for Duplicate rows"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0         False\n",
       "1         False\n",
       "2         False\n",
       "3         False\n",
       "4         False\n",
       "          ...  \n",
       "550063    False\n",
       "550064    False\n",
       "550065    False\n",
       "550066    False\n",
       "550067    False\n",
       "Length: 550068, dtype: bool"
      ]
     },
     "execution_count": 130,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.duplicated()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "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>user_id</th>\n",
       "      <th>product_id</th>\n",
       "      <th>gender</th>\n",
       "      <th>age</th>\n",
       "      <th>occupation</th>\n",
       "      <th>city_category</th>\n",
       "      <th>stay_in_current_city_years</th>\n",
       "      <th>marital_status</th>\n",
       "      <th>product_category_1</th>\n",
       "      <th>product_category_2</th>\n",
       "      <th>product_category_3</th>\n",
       "      <th>purchase</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [user_id, product_id, gender, age, occupation, city_category, stay_in_current_city_years, marital_status, product_category_1, product_category_2, product_category_3, purchase]\n",
       "Index: []"
      ]
     },
     "execution_count": 131,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "duplicate = df[df.duplicated()]\n",
    "duplicate"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### **Check for unique values in data & perform EDA**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['P00069042', 'P00248942', 'P00087842', ..., 'P00370293',\n",
       "       'P00371644', 'P00370853'], dtype=object)"
      ]
     },
     "execution_count": 132,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.product_id.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['0-17', '55+', '26-35', '46-50', '51-55', '36-45', '18-25'],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 133,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.age.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([10, 16, 15,  7, 20,  9,  1, 12, 17,  0,  3,  4, 11,  8, 19,  2, 18,\n",
       "        5, 14, 13,  6])"
      ]
     },
     "execution_count": 134,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.occupation.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['A', 'C', 'B'], dtype=object)"
      ]
     },
     "execution_count": 135,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.city_category.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['2', '4+', '3', '1', '0'], dtype=object)"
      ]
     },
     "execution_count": 136,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.stay_in_current_city_years.unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### In Stay_In_Current_City_Years we have '4+' value which making this column of type Object. Apart from that all the values are integer. So, to deal with this scenario we will replace '4+' with 4."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['stay_in_current_city_years'] = df['stay_in_current_city_years'].replace('4+',4).astype(int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 1])"
      ]
     },
     "execution_count": 138,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.marital_status.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 3,  1, 12,  8,  5,  4,  2,  6, 14, 11, 13, 15,  7, 16, 18, 10, 17,\n",
       "        9, 20, 19])"
      ]
     },
     "execution_count": 139,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.product_category_1.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([nan,  6., 14.,  2.,  8., 15., 16., 11.,  5.,  3.,  4., 12.,  9.,\n",
       "       10., 17., 13.,  7., 18.])"
      ]
     },
     "execution_count": 140,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.product_category_2.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([nan, 14., 17.,  5.,  4., 16., 15.,  8.,  9., 13.,  6., 12.,  3.,\n",
       "       18., 11., 10.])"
      ]
     },
     "execution_count": 141,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.product_category_3.unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Fill nan values\n",
    "### **As we can see that we have 2 observation which we need to work on**\n",
    "##### 1. Need to deal with Null values in Product_Category_2 and Product_Category_3\n",
    "#####   *We are approaching it by replacing null values with the median of the column*\n",
    "##### 2. We need to convert the float values into integer values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {},
   "outputs": [],
   "source": [
    "pc2_median = df.product_category_2.median()\n",
    "df['product_category_2'] = df['product_category_2'].fillna(pc2_median).astype(int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "metadata": {},
   "outputs": [],
   "source": [
    "pc3_median = df.product_category_3.median()\n",
    "df['product_category_3'] = df['product_category_3'].fillna(pc3_median).astype(int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "user_id                       0\n",
       "product_id                    0\n",
       "gender                        0\n",
       "age                           0\n",
       "occupation                    0\n",
       "city_category                 0\n",
       "stay_in_current_city_years    0\n",
       "marital_status                0\n",
       "product_category_1            0\n",
       "product_category_2            0\n",
       "product_category_3            0\n",
       "purchase                      0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 145,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "missing_value = df.isna().sum()\n",
    "missing_value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<bound method DataFrame.corr of         user_id product_id gender    age  occupation city_category  \\\n",
       "0       1000001  P00069042      F   0-17          10             A   \n",
       "1       1000001  P00248942      F   0-17          10             A   \n",
       "2       1000001  P00087842      F   0-17          10             A   \n",
       "3       1000001  P00085442      F   0-17          10             A   \n",
       "4       1000002  P00285442      M    55+          16             C   \n",
       "...         ...        ...    ...    ...         ...           ...   \n",
       "550063  1006033  P00372445      M  51-55          13             B   \n",
       "550064  1006035  P00375436      F  26-35           1             C   \n",
       "550065  1006036  P00375436      F  26-35          15             B   \n",
       "550066  1006038  P00375436      F    55+           1             C   \n",
       "550067  1006039  P00371644      F  46-50           0             B   \n",
       "\n",
       "        stay_in_current_city_years  marital_status  product_category_1  \\\n",
       "0                                2               0                   3   \n",
       "1                                2               0                   1   \n",
       "2                                2               0                  12   \n",
       "3                                2               0                  12   \n",
       "4                                4               0                   8   \n",
       "...                            ...             ...                 ...   \n",
       "550063                           1               1                  20   \n",
       "550064                           3               0                  20   \n",
       "550065                           4               1                  20   \n",
       "550066                           2               0                  20   \n",
       "550067                           4               1                  20   \n",
       "\n",
       "        product_category_2  product_category_3  purchase  \n",
       "0                        9                  14      8370  \n",
       "1                        6                  14     15200  \n",
       "2                        9                  14      1422  \n",
       "3                       14                  14      1057  \n",
       "4                        9                  14      7969  \n",
       "...                    ...                 ...       ...  \n",
       "550063                   9                  14       368  \n",
       "550064                   9                  14       371  \n",
       "550065                   9                  14       137  \n",
       "550066                   9                  14       365  \n",
       "550067                   9                  14       490  \n",
       "\n",
       "[550068 rows x 12 columns]>"
      ]
     },
     "execution_count": 146,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.corr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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MTFRISIgiIyM1btw4nT3r/IVjy5YtU5cuXRQYGKgWLVpozpw5JfqZPn26mjZtqqCgIHXv3l3r1q1z+2MGAABVU6WGpuXLlyspKUlr165VcnKyCgoK1KdPH+Xm5jrGjBkzRl988YU+/PBDLV++XAcPHtRtt93mqBcWFioxMVH5+flavXq13nnnHc2ZM0eTJ092jElLS1NiYqKuvfZabd68WaNHj9af//xnff31144xH3zwgcaOHatHH31UGzduVMeOHZWQkKDDhw97ZjIAAICt+VfmnS9evNjp5zlz5igyMlIbNmxQr169lJWVpbfeekvz58/XddddJ0maPXu2WrdurbVr1+rKK6/UN998o+3bt+vbb79VVFSUOnXqpCeeeELjx4/XY489poCAAM2YMUPNmjXT888/L0lq3bq1Vq1apRdffFEJCQmSpBdeeEH33nuvhg4dKkmaMWOGFi1apLffflsTJkzw4KwAAAA7stU5TVlZWZKkiIgISdKGDRtUUFCg+Ph4x5hWrVqpcePGWrNmjSRpzZo1at++vaKiohxjEhISlJ2drZ9++skx5tx1FI8pXkd+fr42bNjgNMbX11fx8fGOMefLy8tTdna20w0AAFRftglNRUVFGj16tK666iq1a9dOkpSRkaGAgACFh4c7jY2KilJGRoZjzLmBqbheXDMbk52drdOnT+vIkSMqLCwsdUzxOs43depUhYWFOW6NGjUq3wMHAABVgm1CU1JSkrZt26b333+/sluxZOLEicrKynLc9u3bV9ktAQCAi6hSz2kqNmrUKC1cuFArVqxQw4YNHcujo6OVn5+vEydOOO1tyszMVHR0tGPM+Z9yK/503bljzv/EXWZmpkJDQxUcHCw/Pz/5+fmVOqZ4HecLDAxUYGBg+R4wAACocip1T5NhGBo1apQ++eQTLVmyRM2aNXOqd+3aVTVq1FBKSopjWWpqqtLT0xUXFydJiouL09atW50+5ZacnKzQ0FC1adPGMebcdRSPKV5HQECAunbt6jSmqKhIKSkpjjGedlVshGn96hZ1PdSJ/XVpGGZav7xxuGcaQbXi46Jum930NlCzhvls1HJRB6qKSt3TlJSUpPnz5+uzzz5T7dq1HecPhYWFKTg4WGFhYRo+fLjGjh2riIgIhYaG6v7771dcXJyuvPJKSVKfPn3Upk0bDR48WM8884wyMjI0adIkJSUlOfYEjRw5Uq+++qoeeughDRs2TEuWLNGCBQu0aNEiRy9jx47VkCFDdPnll6tbt2566aWXlJub6/g0nad9t+eYaX3lrqMe6sT+Nu7PMq2vTz/hmUZQrRgu6kUe6aJqyC0wn40cF3WgqqjU0PT6669Lknr37u20fPbs2brnnnskSS+++KJ8fX11++23Ky8vTwkJCXrttdccY/38/LRw4ULdd999iouLU82aNTVkyBBNmTLFMaZZs2ZatGiRxowZo2nTpqlhw4aaNWuW43IDkjRgwAD99ttvmjx5sjIyMtSpUyctXry4xMnhAADAO1VqaDIMV3/LSUFBQZo+fbqmT59e5pgmTZroyy+/NF1P7969tWnTJtMxo0aN0qhRo1z2BAAAvA8HmgEAACwgNAEAAFhAaAIAALCA0AQAAGABoQkAAMACQhMAAIAFhCYAAAALCE0AAAAWEJoAAAAsIDQBAABYQGiyKT8X/2dc1QEAgHvx1mtTvi6+ls9VHQAAuBehyaaiwoJM69Hh5nUAAOBehKYqykc+ld0CAABehdBkUydO5ZvWj+XmeagTAAAgEZpsK7CGn2k9yEUdAAC4F6HJpqJqm5+zFBnKOU3F6tWsYVqv76IOAIAVhCabCvA3/18T6KLuTe7p0cy0PrRnrIc6QXVSM8B8G6vlou5NwoP9Tet1XNSBsvi7OH3XVd3d2OptKrZ+LdN6cxd1b3Ik1/z8r8MnOf8LF65xnRDTepOImh7qxP4C/c1PF3B1ugFQlsYutrPGdT27HRKabOqKZhGm9a5NzeveJMLF4bd6tQI81Amqk1Yxoab1yxqY172Jq22wTgiHyIvF1jMP4y3qE8bP1blxuGm9a5M6nmnkvwhNNtXdRWi6Mrauhzqxvz90iDGtJ7qoe5Oo2uYBMjo00EOd2F+zeuZ7c5vx5ubg6hD5MA6RO/Tv3NC0fkvnSzzUSdXQ2EXIbBgR7KFOfkdosqnY+rUUV0Ywioutq2b1eMEuFlu/lro1Lf2vjW5N6zBX5xh7w2Wm9Qf7mNe9yR86NHBRJ4wXG9CtcZlvJr6S7ri8kSfbsTWeVxemU8Nw03qXxuxpwn/N+FNX9WpZ32lZr5b1NeNPXSupI/t68+4rSp2rN+++opI6sqcB3Rqb1nlz+5/Y+rV0RRm7/q9oQhg/38L7e8rf1/msXH9fHy28v2cldWRPPK8uzDWXRZZ5eLdOSA1dfd7r/sXmYxgG32LmBtnZ2QoLC1NWVpZCQ917rkPakVztPZqrpnVrskG5wFy5tv1Alm6e/p3OFv1v0/f39dHnSVepzSVhldiZ/WSdKtD9723Sip2/OZb1allfrwzsrDDO0ynVh+v36bvdR3RV83qE8DLwvLow+46e0s3TV+n4qQLHsjohNfR5Uk81qmt++M6KC3n/JjS5ycUMTcDFwJubdYRxXAw8ry7Myp2/aWP6cXVpXMete5gITZWA0AQAQNVzIe/fXHGsCvhgXbrWpB1lj4AFI975QRv2HdcVTSI0Y/Dlld2OrTWdsMjx771PJVZiJ/Z39VMpOpB1Ro3Cg7V8/HWV3Y6t3fjicu06kqtLI2tp4QO9KrsdW2MbvDB2eG6xp8lNLsaepq37T+jW11Zz7okF765J06TPtpdY/tSt7XRn9yaV0JF9xU5YpKJSlteQtJMXbicPf7RZ89cfKLH87isbaUr/DpXQkX09/eV2vb4ircTy+69trgcTWlVCR/Z1xROL9VtuYYnlDWrX0Jp/9KmEjuztYj+3LuT9m0/P2dhNrzqfrCtJZ4sM3fjKqkrqyL5KC0ySNOGTbR7uxP5KC0ySVFDGcm9WWmCSpLlr93m4E/sr7U1Nkl5ZutvDndhfaYFJkg6dZCssjZ2eW4Qmm/pgXbpp/cP1vGgXG/HOD6b1kf9e76FO7O/cwwHlqXuTq59KMa1f8/QSD3Vifze+uNy0/odpKzzUif2xDV4Yuz23CE029cZy8wQ9Y9kuD3Vif9/tPmJaX3nOx3oBq/adOGNa//X4aQ91Yn/bM3NM69sOnfRQJ6hu7PbcIjTZ1KEs8xfkgyd4wS4W7OLLQF3VAQCwgtBkU2Wdd1KMs/f/p1GEi2+j9/C3YAMAqidCk125+FAjH3r8H1d73Q6cOOWhTgAA1RmhyabyS/9wheW6N8k8mW9az8g2rwMAYAWhyaZc7UdiPxMAAJ5FaAIAALCA0AQAAGABoQkAAMACQhMAAIAFhCYAAAALCE0AAAAWEJoAAAAsIDQBAABYQGgCAACwgNAEAABgAaEJAADAAkITAACABYQmAAAACwhNAAAAFhCaAAAALCA0AQAAWEBoAgAAsIDQBAAAYAGhCQAAwAJCEwAAgAWEJgAAAAsITQAAABYQmgAAACyo1NC0YsUK3XTTTYqJiZGPj48+/fRTp/o999wjHx8fp1vfvn2dxhw7dkyDBg1SaGiowsPDNXz4cOXk5DiN2bJli66++moFBQWpUaNGeuaZZ0r08uGHH6pVq1YKCgpS+/bt9eWXX7r98QIAgKqrUkNTbm6uOnbsqOnTp5c5pm/fvjp06JDj9t577znVBw0apJ9++knJyclauHChVqxYoREjRjjq2dnZ6tOnj5o0aaINGzbo2Wef1WOPPaaZM2c6xqxevVoDBw7U8OHDtWnTJvXv31/9+/fXtm3b3P+gAQBAleRfmXfer18/9evXz3RMYGCgoqOjS63t2LFDixcv1g8//KDLL79ckvTKK6/oxhtv1HPPPaeYmBjNmzdP+fn5evvttxUQEKC2bdtq8+bNeuGFFxzhatq0aerbt6/GjRsnSXriiSeUnJysV199VTNmzHDjIwYAAFWV7c9pWrZsmSIjI3XZZZfpvvvu09GjRx21NWvWKDw83BGYJCk+Pl6+vr76/vvvHWN69eqlgIAAx5iEhASlpqbq+PHjjjHx8fFO95uQkKA1a9ZczIcGAACqEFuHpr59+2ru3LlKSUnR008/reXLl6tfv34qLCyUJGVkZCgyMtLpd/z9/RUREaGMjAzHmKioKKcxxT+7GlNcL01eXp6ys7Odbu4U3zqyQnVvclVsXdN6zxbmdaA0rl4cbf3i6WHMFS4WnwrW3a1SD8+5cueddzr+3b59e3Xo0EHNmzfXsmXLdP3111diZ9LUqVP1+OOPX7T1N6oTbFpvEhFy0e67qjFkuBoAXLCiCta9CXOFi8XVy7enX96r1B8AsbGxqlevnnbt2iVJio6O1uHDh53GnD17VseOHXOcBxUdHa3MzEynMcU/uxpT1rlUkjRx4kRlZWU5bvv27avYgzvP4LimpvU/uah7kz1Hck3ru37LMa0DpfF38SesqzqA6qdKhab9+/fr6NGjatCggSQpLi5OJ06c0IYNGxxjlixZoqKiInXv3t0xZsWKFSooKHCMSU5O1mWXXaY6deo4xqSkpDjdV3JysuLi4srsJTAwUKGhoU43d/pyyyHT+ldbzeveJCTAz7ReM8DWO1RhU/7mTyuXdQDVT6WGppycHG3evFmbN2+WJKWlpWnz5s1KT09XTk6Oxo0bp7Vr12rv3r1KSUnRLbfcohYtWighIUGS1Lp1a/Xt21f33nuv1q1bp++++06jRo3SnXfeqZiYGEnSXXfdpYCAAA0fPlw//fSTPvjgA02bNk1jx4519PHAAw9o8eLFev755/Xzzz/rscce0/r16zVq1CiPz0mxb3/ONK1/s73s8628TWbWGdN6RtZpD3WC6iT/bMXqAKqfSg1N69evV+fOndW5c2dJ0tixY9W5c2dNnjxZfn5+2rJli26++WZdeumlGj58uLp27aqVK1cqMDDQsY558+apVatWuv7663XjjTeqZ8+eTtdgCgsL0zfffKO0tDR17dpVDz74oCZPnux0LacePXpo/vz5mjlzpjp27KiPPvpIn376qdq1a+e5yThPSA3zP2NrsffEIbfA/IwJV3WgNJynA+B8lfrO27t3bxlG2adxff311y7XERERofnz55uO6dChg1auXGk65o477tAdd9zh8v485dLoUK3ec6zMeouo2h7sBgAAVKlzmrxJvZoBpvXI2oGmdW8S7G/+NA6uwdMcAFBxvJvYVKGLD1IWFHFwoFhosPkO07DgGh7qBPBOgX7mHyV0VQeqCkKTTUXXDjKtx4SZX8fJmwS4+BhTDT+e5sDFVMNFKHJVB6oK3k1s6vu0ss9nkqTv9xw1rXuTgkLzvW6u6gAqJiffxYcxXNSBqoLQZFPbD2WZ1n86aF73JrH1aprWm9ev5aFOUJ3w1SDuw0X5UV2w3dtURIj5ieARNTkRvJiPi28f8uHIAMqhTi3zc+Eiaplvo97Ebt8PBlwshCabOp1f6KLOlfWKrf/V/FDlD2kcysSFO3XGfBvLPVNgWvcmLj7A6rIOlMVue3wrfH9nzphfjRnlk+XiBfnEaV6wi+WZ50uXdaA0p8+aH1RyVfcmrq4fy/VlUV6ujhR4+khCuUJTUVGRnnjiCV1yySWqVauW9uzZI0l65JFH9NZbb7m1QW8V6OITX8F88ZWDqw/m8MEd4OJyuTeAbRDlVOjibxNXdXcrV2j65z//qTlz5uiZZ55RQMD/juu3a9dOs2bNcltz3uxwTp5pPfMke/iK1Qx08YW9gXzlDHAxRdQ0P/+rbgjXSkP1UK7QNHfuXM2cOVODBg2Sn9//3rA6duyon3/+2W3NeTeb7ZO0MVfXrLok3PyaV0BpXJ+nwzZYrFPjOqb1zo0jPNQJqhu7HUkoV2g6cOCAWrRoUWJ5UVGRCgo418Ydjubmm9aP5JjXvcmvR3PN60fM60Bpzro4D+dsEec0Fft2x2HT+jc7Mj3UCaqbanF4rk2bNqV+Ae5HH32kzp07V7gp4EK4OiH3FCfsAgDcoFwne0yePFlDhgzRgQMHVFRUpI8//lipqamaO3euFi5c6O4eAQAAKl259jTdcsst+uKLL/Ttt9+qZs2amjx5snbs2KEvvvhCN9xwg7t7BAAAqHTl/ljR1VdfreTkZHf2AgAAYFvl2tO0b98+7d+/3/HzunXrNHr0aM2cOdNtjQEAANhJuULTXXfdpaVLl0qSMjIyFB8fr3Xr1ukf//iHpkyZ4tYGAQAA7KBcoWnbtm3q1q2bJGnBggVq3769Vq9erXnz5mnOnDnu7A8AAMAWyhWaCgoKFBgYKEn69ttvdfPNN0uSWrVqpUOHDrmvOwAAAJsoV2hq27atZsyYoZUrVyo5OVl9+/aVJB08eFB169Z1a4MAAAB2UK7Q9PTTT+uNN95Q7969NXDgQHXs2FGS9PnnnzsO2wEAAFQn5brkQO/evXXkyBFlZ2erTp3/fefQiBEjFBIS4rbmAAAA7KLc12ny8/NzCkyS1LRp04r2AwAAYEvlDk0fffSRFixYoPT0dOXnO3957MaNGyvcGAAAgJ2U65yml19+WUOHDlVUVJQ2bdqkbt26qW7dutqzZ4/69evn7h4BAAAqXblC02uvvaaZM2fqlVdeUUBAgB566CElJyfrb3/7m7KystzdIwAAQKUrV2hKT09Xjx49JEnBwcE6efKkJGnw4MF677333NcdAACATZQrNEVHR+vYsWOSpMaNG2vt2rWSpLS0NBmG4b7uAAAAbKJcoem6667T559/LkkaOnSoxowZoxtuuEEDBgzQrbfe6tYGAQAA7KBcn56bOXOmioqKJElJSUmqW7euVq9erZtvvll/+ctf3NogAACAHZQrNPn6+srX9387qe68807deeedbmsKAADAbsp9naYTJ05o3bp1Onz4sGOvU7G77767wo0BAADYSblC0xdffKFBgwYpJydHoaGh8vHxcdR8fHwITQAAoNop14ngDz74oIYNG6acnBydOHFCx48fd9yKP1UHAABQnZQrNB04cEB/+9vf+HJeAADgNcoVmhISErR+/Xp39wIAAGBbls9pKr4ukyQlJiZq3Lhx2r59u9q3b68aNWo4jb355pvd1yEAAIANWA5N/fv3L7FsypQpJZb5+PiosLCwQk0BAADYjeXQdP5lBQAAALxJuc5pAgAA8DblCk1/+9vf9PLLL5dY/uqrr2r06NEV7QkAAMB2yhWa/vOf/+iqq64qsbxHjx766KOPKtwUAACA3ZQrNB09elRhYWElloeGhurIkSMVbgoAAMBuyhWaWrRoocWLF5dY/tVXXyk2NrbCTQEAANhNub57buzYsRo1apR+++03XXfddZKklJQUPf/883rppZfc2R8AAIAtlCs0DRs2THl5eXryySf1xBNPSJKaNm2q119/nS/rdZMesRFavafs7/Hr2byuB7uxt9qBfjqZV/a1wUID/TzYDQCgurrgw3Nnz57V3Llzddttt2n//v3KzMxUdna29uzZQ2Byo5s6XWJaT+wY46FO7O+GNtGm9T5tzetAaWoFmL88uqp7kx6x5n/EXcUfeSgnfxebmau6u13w3fn7+2vkyJE6c+aMJKl+/fqqVauW2xvzdhM/3lqhujf5eNMB0/pHG83rQGly8s0v6Ouq7k1W7zlqWv9ut3kdKMtZF5uZq7q7lSujdevWTZs2bXJ3LwAAALZVrnOa/vrXv+rBBx/U/v371bVrV9WsWdOp3qFDB7c0BwAAYBflCk133nmnpN+vDF7Mx8dHhmHwhb0AAKBaKldoSktLc3cfAAAAtlau0NSkSRN39wEAAGBr5QpNc+fONa1z6QEAAFDdlCs0PfDAA04/FxQU6NSpUwoICFBISAihCQAAVDvluuTA8ePHnW45OTlKTU1Vz5499d5777m7RwAAgErntmtptmzZUk899VSJvVAAAADVgVsvQO7v76+DBw+6c5Vea+9TiRWqexMfF3W+7OJ/AnzNZ8tV3Zs0DA8yrTeuE+yhTgDvFVsvxLTe3EXd3cr1fvL555873T777DPNmDFDf/rTn3TVVVdZXs+KFSt00003KSYmRj4+Pvr000+d6oZhaPLkyWrQoIGCg4MVHx+vnTt3Oo05duyYBg0apNDQUIWHh2v48OHKyclxGrNlyxZdffXVCgoKUqNGjfTMM8+U6OXDDz9Uq1atFBQUpPbt2+vLL7+0PiGoVEH+5m/0gTWITcX8XHx3sau6NzmUfca0fjDrtIc6AbxXWFAN03p4cICHOvlduU4E79+/v9PPPj4+ql+/vq677jo9//zzlteTm5urjh07atiwYbrttttK1J955hm9/PLLeuedd9SsWTM98sgjSkhI0Pbt2xUU9PtfgYMGDdKhQ4eUnJysgoICDR06VCNGjND8+fMlSdnZ2erTp4/i4+M1Y8YMbd26VcOGDVN4eLhGjBghSVq9erUGDhyoqVOn6g9/+IPmz5+v/v37a+PGjWrXrl15pgge1CA8WHuOnCqzHhPGHoFihlGxujcpcvGdVoV89RzKwVeS2VOHP/Gc1a0daFqvU6sKhKaic15Niv/t63vh/6v79eunfv36lVozDEMvvfSSJk2apFtuuUXS75c6iIqK0qeffqo777xTO3bs0OLFi/XDDz/o8ssvlyS98soruvHGG/Xcc88pJiZG8+bNU35+vt5++20FBASobdu22rx5s1544QVHaJo2bZr69u2rcePGSZKeeOIJJScn69VXX9WMGTMu+HG5Q7MJi0zrsRMWaQ+H6CTJNDBJ0u4juR7qxP7OnDVPRa7q3sTVTDBTKA9XWZss7uzbHYcrVHe3cofat956S+3atVNwcLCCg4PVrl07zZo1y22NpaWlKSMjQ/Hx8Y5lYWFh6t69u9asWSNJWrNmjcLDwx2BSZLi4+Pl6+ur77//3jGmV69eCgj4XxpNSEhQamqqjh8/7hhz7v0Ujym+n8rg6gWZDQsAAM8q156myZMn64UXXtD999+vuLg4Sb8HjzFjxig9PV1TpkypcGMZGRmSpKioKKflUVFRjlpGRoYiIyOd6v7+/oqIiHAa06xZsxLrKK7VqVNHGRkZpvdTmry8POXl5Tl+zs7OvpCHBwAAqphyhabXX39db775pgYOHOhYdvPNN6tDhw66//773RKa7G7q1Kl6/PHHK7sNAADgIeU6PFdQUOB0SKxY165ddfbs2Qo3JUnR0dGSpMzMTKflmZmZjlp0dLQOH3Y+nnn27FkdO3bMaUxp6zj3PsoaU1wvzcSJE5WVleW47du370IfIgAAqELKFZoGDx6s119/vcTymTNnatCgQRVuSpKaNWum6OhopaSkOJZlZ2fr+++/dxwSjIuL04kTJ7RhwwbHmCVLlqioqEjdu3d3jFmxYoUKCgocY5KTk3XZZZepTp06jjHn3k/xmOL7KU1gYKBCQ0OdbgAAoPoq1+E56fcTwb/55htdeeWVkqTvv/9e6enpuvvuuzV27FjHuBdeeKHMdeTk5GjXrl2On9PS0rR582ZFRESocePGGj16tP75z3+qZcuWjksOxMTEOC550Lp1a/Xt21f33nuvZsyYoYKCAo0aNUp33nmnYmJiJEl33XWXHn/8cQ0fPlzjx4/Xtm3bNG3aNL344ouO+33ggQd0zTXX6Pnnn1diYqLef/99rV+/XjNnzizv9AAAgGqmXKFp27Zt6tKliyRp9+7dkqR69eqpXr162rZtm2Ocj4/5RQfXr1+va6+91vFzcdgaMmSI5syZo4ceeki5ubkaMWKETpw4oZ49e2rx4sWOazRJ0rx58zRq1Chdf/318vX11e23366XX37ZUQ8LC9M333yjpKQkde3aVfXq1dPkyZMdlxuQpB49emj+/PmaNGmSHn74YbVs2VKffvop12gCAAAO5QpNS5cudcud9+7dW4bJ1fR8fHw0ZcoU0xPLIyIiHBeyLEuHDh20cuVK0zF33HGH7rjjDvOGAQCA1+LiowAAABYQmgAAACwgNNnUkgevMa0v/XtvzzRSBcTF1jWt93BRB0pzQ+tI03pCmyjTujcZc0PLCtW9SbCLLxh3Vfc2nRqGmda7NAr3TCP/RWhCldcqupZpvXWD2h7qBNXJ7sM5pvVdLurexE/mb/Q1yvHdpNVVkYvvyHJV9zZHc/NM67/lmNfdjWeyTf16zPxLaPce5Utoiw2Oa2pa/5OLujcJDfSrUN2bZJ8pMK1nnc73UCf2t3n/CfN6unndmxSafPhJkopc1L3NqfxC0/rpfPdcUNsqQpNNufof4+/LLtxisfXN9zQ1q1fTQ53YX3ae+QuQq7o3CaphHiCDA8p9mbtq58Dx06b1/cfN/wj0JmddfNt6Ad/G7qTIxa63Qg/vmiM02dSPLv5y+3Gfed2bLE89bFpfufM3D3WC6uR4rvmepGMePixgZyfzzPfKnczz7N4AVB/ZZ8yfO67q7kZosqljueYvQkdyODRQ7NPNB03rn2w84KFOUJ3kuviT31Xdm/yWbR4gD2ef8VAnqG4KXexIclV3N0KTTc1ZvbdCdW/yySbzUPSxizqAislz8c7lqg5UFYQmAAAACwhNAAAAFhCaAAAALCA0AQAAWEBoAgAAsIDQBAAAYAGhCQAAwAJCEwAAgAWEJgAAAAsITQAAABYQmgAAACwgNAEAAFhAaAIAALCA0AQAAGABoQkAAMACQhMAAIAFhCYAAAALCE0AAAAWEJoAAAAsIDQBAABYQGgCAACwgNAEAABgAaEJAADAAkITAACABYQmAAAACwhNAAAAFhCaAAAALCA0AQAAWEBoAgAAsIDQBAAAYAGhCQAAwAJCEwAAgAWEJgAAAAsITQAAABYQmgAAACwgNAEAAFhAaEKVVzvIz7QeGuTvoU4AANUZoQlV3skzhab17DNnPdQJAKA6IzQBAABYQGgCAACwgNAEAABgAaEJAADAAkITAACABYQmAAAACwhNAAAAFhCaUOXVDDB/GruqA6gYV9eP5fqyqC54N0GVl19YZFovcFEHUDGurh/L9WVRXRCaUOUVmF8QXPku6gAAWEFoAgAAsIDQBAAAYAGhCQAAwAJbh6bHHntMPj4+TrdWrVo56mfOnFFSUpLq1q2rWrVq6fbbb1dmZqbTOtLT05WYmKiQkBBFRkZq3LhxOnvW+azEZcuWqUuXLgoMDFSLFi00Z84cTzw8AABQhdg6NElS27ZtdejQIcdt1apVjtqYMWP0xRdf6MMPP9Ty5ct18OBB3XbbbY56YWGhEhMTlZ+fr9WrV+udd97RnDlzNHnyZMeYtLQ0JSYm6tprr9XmzZs1evRo/fnPf9bXX3/t0ccJAADszfZXz/D391d0dHSJ5VlZWXrrrbc0f/58XXfddZKk2bNnq3Xr1lq7dq2uvPJKffPNN9q+fbu+/fZbRUVFqVOnTnriiSc0fvx4PfbYYwoICNCMGTPUrFkzPf/885Kk1q1ba9WqVXrxxReVkJDg0ccKAADsy/Z7mnbu3KmYmBjFxsZq0KBBSk9PlyRt2LBBBQUFio+Pd4xt1aqVGjdurDVr1kiS1qxZo/bt2ysqKsoxJiEhQdnZ2frpp58cY85dR/GY4nWUJS8vT9nZ2U43AABQfdk6NHXv3l1z5szR4sWL9frrrystLU1XX321Tp48qYyMDAUEBCg8PNzpd6KiopSRkSFJysjIcApMxfXimtmY7OxsnT59uszepk6dqrCwMMetUaNGFX24TpY8eI1pfenfe7v1/qqyv99wqWn9oYTLPNQJqpNbO8eY1m9zUfcmY11sgw/2Ma97k2B/nwrVvU2wv3lMCa7h2Rhj69DUr18/3XHHHerQoYMSEhL05Zdf6sSJE1qwYEFlt6aJEycqKyvLcdu3b59b1//rsVOm9b1Hc916f1XZ++vTTevvrTOvA6XZe8R8G9t7xHwb9Safbtzvon7AQ53Y3+mzRoXq3ub0WfNvdDhd4NlvfLB1aDpfeHi4Lr30Uu3atUvR0dHKz8/XiRMnnMZkZmY6zoGKjo4u8Wm64p9djQkNDVVwcHCZvQQGBio0NNTp5k5NIkJM603r1nTr/VVlR0/mmdaP5JzxUCeoTnYfzjGt7zp80kOd2N+hLPNt7GBW2XvtgaqkSoWmnJwc7d69Ww0aNFDXrl1Vo0YNpaSkOOqpqalKT09XXFycJCkuLk5bt27V4cOHHWOSk5MVGhqqNm3aOMacu47iMcXrqCzXPb/ctH7tc8s800gV4PIvtwL+csOFy84z//4dV3VvYre9AcDFYuvQ9Pe//13Lly/X3r17tXr1at16663y8/PTwIEDFRYWpuHDh2vs2LFaunSpNmzYoKFDhyouLk5XXnmlJKlPnz5q06aNBg8erB9//FFff/21Jk2apKSkJAUGBkqSRo4cqT179uihhx7Szz//rNdee00LFizQmDFjKvOhAwAAm7H1JQf279+vgQMH6ujRo6pfv7569uyptWvXqn79+pKkF198Ub6+vrr99tuVl5enhIQEvfbaa47f9/Pz08KFC3XfffcpLi5ONWvW1JAhQzRlyhTHmGbNmmnRokUaM2aMpk2bpoYNG2rWrFlcbgAAADixdWh6//33TetBQUGaPn26pk+fXuaYJk2a6MsvvzRdT+/evbVp06Zy9QgAALyDrQ/PAQAA2AWhCQAAwAJCEwAAgAWEJgAAAAsITQAAABYQmgAAACwgNAEAAFhAaAIAALCA0AQAAGABoQkAAMACQhMAAIAFhCYAAAALCE0AAAAWEJoAAAAsIDQBAABYQGgCAACwgNAEAABgAaEJAADAAkITAACABYQmAAAACwhNAAAAFhCaAAAALCA0AQAAWEBoAgAAsIDQBAAAYAGhCQAAwAJCE6q8qNAA03p0aKCHOgEAVGeEJptqXjfEtN6yfk0PdWJ/z9ze0bT+7B3mdaA07wy9wrT+7+HdPNSJ/S158BrT+tK/9/ZMI1XAVbERpvWrW9T1UCdVg7+Peb2Gi7q7EZpsKmXctab15Ad7e6aRKmDr/qwK1b1Jl4ZhpvXLG4d7ppEqICPrTIXq3mT6kl2m9deWmte9yWXRoRWqe5tdUxNN6ztd1N2N0GRTr6bsNK3zIvQ/zyX/Ylp/5utUD3VifxtdBMj16Sc800gVMP7jrab1cR9t8VAn9vefTQdM6x9u2O+hTuzv7dV7TeuzVqV5ppEqoumERRWquxuhyaYIAgAA2AuhCQAAwAJCEwAAgAWEJgAAAAsITQAAABYQmgAAACwgNAEAAFhAaAIAALCA0AQAAGABoQkAAMACQhMAAIAFhCYAAAALCE0AAAAWEJoAAAAsIDQBAABYQGgCAACwgNBkU3ufSqxQ3ZswV9YxV9YxV9YxV9YxVxfGbvNFaLKpto98ZVpv56LuTZpOWFShujdhrqxjrqxjrqxjri6M3eaL0GRTuQVFpvUcF3UAAOBehCYAAAALCE0AAAAWEJoAAAAsIDQBAABYQGgCAACwgNAEAABgAaEJAADAAkITAACABYQmAAAACwhNAAAAFhCazjN9+nQ1bdpUQUFB6t69u9atW1fZLQEAABsgNJ3jgw8+0NixY/Xoo49q48aN6tixoxISEnT48OHKbg0AAFQyQtM5XnjhBd17770aOnSo2rRpoxkzZigkJERvv/12ZbcGAAAqGaHpv/Lz87VhwwbFx8c7lvn6+io+Pl5r1qwpMT4vL0/Z2dlONwAAUH0Rmv7ryJEjKiwsVFRUlNPyqKgoZWRklBg/depUhYWFOW6NGjXyVKsAAKASEJrKaeLEicrKynLc9u3bV9ktAQCAi4jQ9F/16tWTn5+fMjMznZZnZmYqOjq6xPjAwECFhoY63dxp71OJFap7E+bKOubKOubKOubKOubqwthtvghN/xUQEKCuXbsqJSXFsayoqEgpKSmKi4urlJ5CAy9sOQAAuHh8DMMwKrsJu/jggw80ZMgQvfHGG+rWrZteeuklLViwQD///HOJc53Ol52drbCwMGVlZbl9r1PTCYsc/+avEHPMlXXMlXXMlXXMlXXM1YW5WPN1Ie/fhKbzvPrqq3r22WeVkZGhTp066eWXX1b37t1d/t7FDE0AAODiIDRVAkITAABVz4W8f3NOEwAAgAWEJgAAAAsITQAAABYQmgAAACwgNAEAAFhAaAIAALCA0AQAAGABoQkAAMACQhMAAIAF/pXdQHVRfGH17OzsSu4EAABYVfy+beULUghNbnLy5ElJUqNGjSq5EwAAcKFOnjypsLAw0zF895ybFBUV6eDBg6pdu7Z8fHzcuu7s7Gw1atRI+/bt43vtXGCurGOurGOurGOurGOuLszFmi/DMHTy5EnFxMTI19f8rCX2NLmJr6+vGjZseFHvIzQ0lA3LIubKOubKOubKOubKOubqwlyM+XK1h6kYJ4IDAABYQGgCAACwgNBUBQQGBurRRx9VYGBgZbdie8yVdcyVdcyVdcyVdczVhbHDfHEiOAAAgAXsaQIAALCA0AQAAGABoQkAAMACQhMAAIAFhKZKMH36dDVt2lRBQUHq3r271q1bZzr+ySefVI8ePRQSEqLw8PAS9Tlz5sjHx6fU2+HDhy/So7j4HnvssRKPp1WrVo567969S9RHjhxZiR17xtSpU3XFFVeodu3aioyMVP/+/ZWamlpi3Jo1a3TdddepZs2aCg0NVa9evXT69Oky13v06FH17dtXMTExCgwMVKNGjTRq1Cin71NctmxZqc+zjIyMi/JY3e2pp56Sj4+PRo8e7bT8QudKUqnz8P777zuNWbZsmbp06aLAwEC1aNFCc+bMcfMjch9X29vMmTPVu3dvhYaGysfHRydOnLC0XlfzVFWfU6+//ro6dOjguNBiXFycvvrqK6cx5XleFTt69KgaNmxYYq6r4nytWLFCN910k2JiYuTj46NPP/3UqZ6Tk6NRo0apYcOGCg4OVps2bTRjxgzTde7du1fDhw9Xs2bNFBwcrObNm+vRRx9Vfn6+05jS5mrt2rXlfixcEdzDPvjgA40dO1YzZsxQ9+7d9dJLLykhIUGpqamKjIws9Xfy8/N1xx13KC4uTm+99VaJ+oABA9S3b1+nZffcc4/OnDlT5jqrirZt2+rbb791/Ozv7/yUvffeezVlyhTHzyEhIWWua9myZbrnnnu0d+9et/fpScuXL1dSUpKuuOIKnT17Vg8//LD69Omj7du3q2bNmpJ+f7Hu27evJk6cqFdeeUX+/v768ccfTb8iwNfXV7fccov++c9/qn79+tq1a5eSkpJ07NgxzZ8/32lsamqq0xV5q8Lz7IcfftAbb7yhDh06OC0vz1wVmz17ttO2d+4fNWlpaUpMTNTIkSM1b948paSk6M9//rMaNGighIQEtz0udzLb3k6dOqW+ffs65upCmM1Tsar2nGrYsKGeeuoptWzZUoZh6J133tEtt9yiTZs2qW3bthV6XknS8OHD1aFDBx04cKDUelWar9zcXHXs2FHDhg3TbbfdVqI+duxYLVmyRO+++66aNm2qb775Rn/9618VExOjm2++udR1/vzzzyoqKtIbb7yhFi1aaNu2bbr33nuVm5ur5557zmnst99+q7Zt2zp+rlu3bvkfjAGP6tatm5GUlOT4ubCw0IiJiTGmTp3q8ndnz55thIWFuRx3+PBho0aNGsbcuXMr0mqle/TRR42OHTuWWb/mmmuMBx54wPL6li5dajRp0qTCfdnN4cOHDUnG8uXLHcu6d+9uTJo0qcLrnjZtmtGwYUPHz0uXLjUkGcePH6/wuj3p5MmTRsuWLY3k5OQSz5vyzpUk45NPPimz/tBDDxlt27Z1WjZgwAAjISHhgu/LE1xtb8Uu9Dngap6q6nOqNHXq1DFmzZplGEbFtsHXXnvNuOaaa4yUlJQSc1PV56u050Pbtm2NKVOmOC3r0qWL8Y9//OOC1v3MM88YzZo1c/yclpZmSDI2bdpU3nZL4PCcB+Xn52vDhg2Kj493LPP19VV8fLzWrFnjtvuZO3euQkJC9H//939uW2dl2blzp2JiYhQbG6tBgwYpPT3dqT5v3jzVq1dP7dq108SJE3Xq1KlK6rTyZGVlSZIiIiIkSYcPH9b333+vyMhI9ejRQ1FRUbrmmmu0atWqC1rvwYMH9fHHH+uaa64pUevUqZMaNGigG264Qd99913FH8RFlpSUpMTERKdtT6r4XCUlJalevXrq1q2b3n77bRnnXPZuzZo1Je4vISHBrdu6u7na3srLbJ6KVbXn1LkKCwv1/vvvKzc3V3FxcRV6Xm3fvl1TpkzR3LlzTfdKVeX5Ol+PHj30+eef68CBAzIMQ0uXLtUvv/yiPn36XNB6srKyHK+D57r55psVGRmpnj176vPPP69Ys26LX3DpwIEDhiRj9erVTsvHjRtndOvWzeXvW93T1Lp1a+O+++4rb5u28eWXXxoLFiwwfvzxR2Px4sVGXFyc0bhxYyM7O9swDMN44403jMWLFxtbtmwx3n33XeOSSy4xbr311jLXVx33NBUWFhqJiYnGVVdd5Vi2Zs0aQ5IRERFhvP3228bGjRuN0aNHGwEBAcYvv/zicp133nmnERwcbEgybrrpJuP06dOO2s8//2zMmDHDWL9+vfHdd98ZQ4cONfz9/Y0NGzZclMfnDu+9957Rrl07x+M4d09TReZqypQpxqpVq4yNGzcaTz31lBEYGGhMmzbNUW/ZsqXxr3/9y+l3Fi1aZEgyTp065d4H6QautrdiF7qnw9U8VcXnVLEtW7YYNWvWNPz8/IywsDBj0aJFhmGU/3l15swZo0OHDsa///1vwzBKn+uqPF+GUfqepjNnzhh33323Icnw9/c3AgICjHfeeeeC1rtz504jNDTUmDlzpmPZb7/9Zjz//PPG2rVrjXXr1hnjx483fHx8jM8++6z8/Zf7N3HBXIWmv/zlL0bNmjUdt/NZCU2rV682JBnr1693Z+u2cPz4cSM0NNSx+/t8xbuyd+3a5Vh27nwGBQUZPj4+Tsv+8pe/eKr9i2LkyJFGkyZNjH379jmWfffdd4YkY+LEiU5j27dvb0yYMMEwDMPo27evYw7atGnjNO7QoUPGjh07jM8++8xo06aNywDeq1cv409/+pObHpF7paenG5GRkcaPP/7oWHZuaKroXJ3rkUcecTqUWdVC0/nK2t7KCk3lnafS2Pk5da68vDxj586dxvr1640JEyYY9erVM3766adyP6/GjBljDBgwwDHeakCtKvNlGKWHpmeffda49NJLjc8//9z48ccfjVdeecWoVauWkZycbBiG4fK9cf/+/Ubz5s2N4cOHu7z/wYMHGz179ix3/5wI7kH16tWTn5+fMjMznZZnZmYqOjpaU6ZM0d///vcK3cesWbPUqVMnde3atULrsaPw8HBdeuml2rVrV6n17t27S5J27dql5s2bS5I2b97sqH///fcaP368li1b5lh27omUVc2oUaO0cOFCrVixQg0bNnQsb9CggSSpTZs2TuNbt27tONwya9Ysx6d4atSo4TQuOjpa0dHRatWqlSIiInT11VfrkUcecaz3fN26dbvgQ3+esmHDBh0+fFhdunRxLCssLNSKFSv06quvOj51WN65Olf37t31xBNPKC8vT4GBgYqOji51Ww8NDVVwcLBbHt/F5Gp7O19556k0dn5OnSsgIEAtWrSQJHXt2lU//PCDpk2bpgkTJki68OfVkiVLtHXrVn300UeS5DiMWa9ePf3jH//Q448/XmofVWW+SnP69Gk9/PDD+uSTT5SYmChJ6tChgzZv3qznnntO8fHxpu+NBw8e1LXXXqsePXpo5syZLu+ve/fuSk5OLne/hCYPCggIUNeuXZWSkqL+/ftLkoqKipSSkqJRo0YpMjKyQp+AyMnJ0YIFCzR16lQ3dWwvOTk52r17twYPHlxqvTggnfvmXvyCJkn79++Xv7+/07KqyDAM3X///frkk0+0bNkyNWvWzKnetGlTxcTElLgMwS+//KJ+/fpJki655BJL91VUVCRJysvLK3PM5s2bywxUle3666/X1q1bnZYNHTpUrVq10vjx4xUbG+u2udq8ebPq1KnjCAJxcXH68ssvncYkJycrLi6uvA/Ho1xtb+cr7zyVNcauzykzRUVFysvLK/c2+J///MfpkgQ//PCDhg0bppUrVzr+ECxNVZ0vSSooKFBBQUGJ87f8/Pwcrz9lvTceOHBA1157rbp27arZs2db+mRiheeq3PuoUC7vv/++ERgYaMyZM8fYvn27MWLECCM8PNzIyMgo83d+/fVXY9OmTcbjjz9u1KpVy9i0aZOxadMm4+TJk07jZs2aZQQFBVXZT1Wc78EHHzSWLVtmpKWlGd99950RHx9v1KtXzzh8+LCxa9cuY8qUKcb69euNtLQ047PPPjNiY2ONXr16lbm+6nJO03333WeEhYUZy5YtMw4dOuS4nXvI58UXXzRCQ0ONDz/80Ni5c6cxadIkIygoyOnQ5fkWLVpkvP3228bWrVuNtLQ0Y+HChUbr1q2dzpd68cUXjU8//dTYuXOnsXXrVuOBBx4wfH19jW+//faiPmZ3Ov/Tc+WZq88//9x48803ja1btxo7d+40XnvtNSMkJMSYPHmyY8yePXuMkJAQY9y4ccaOHTuM6dOnG35+fsbixYsv5sMrN7PtzTB+P2y7adMm48033zQkGStWrDA2bdpkHD16tMx1WpmnqvqcmjBhgrF8+XIjLS3N2LJlizFhwgTDx8fH+OabbwzDKN/z6nylHZ6rivN18uRJx/uWJOOFF14wNm3aZPz666+GYfy+TbZt29ZYunSpsWfPHmP27NlGUFCQ8dprr5W5zv379xstWrQwrr/+emP//v1Or4XF5syZY8yfP9/YsWOHsWPHDuPJJ580fH19jbfffrvcj4XQVAleeeUVo3HjxkZAQIDRrVs3Y+3atabjhwwZYkgqcVu6dKnTuLi4OOOuu+66iJ171oABA4wGDRoYAQEBxiWXXGIMGDDA8YKTnp5u9OrVy4iIiDACAwONFi1aGOPGjTOysrLKXF91CU2lPRckGbNnz3YaN3XqVKNhw4ZGSEiIERcXZ6xcudJ0vUuWLDHi4uKMsLAwIygoyGjZsqUxfvx4pxfsp59+2mjevLkRFBRkREREGL179zaWLFlyER7lxVPapSoudK6++uoro1OnTkatWrWMmjVrGh07djRmzJhhFBYWOo1bunSp0alTJyMgIMCIjY0t8f/ITsy2N8P4/ZIEVp5357IyT1X1OTVs2DCjSZMmRkBAgFG/fn3j+uuvdwSmYhf6vDpfaaGpKs5X8eM4/zZkyBDDMH4P5Pfcc48RExNjBAUFGZdddpnx/PPPG0VFRWWuc/bs2WW+FhabM2eO0bp1ayMkJMQIDQ01unXrZnz44YcVeiw+hlHKZz8BAADghOs0AQAAWEBoAgAAsIDQBAAAYAGhCQAAwAJCEwAAgAWEJgAAAAsITQAAABYQmgAAACwgNAEAAFhAaAIAALCA0ATAay1evFg9e/ZUeHi46tatqz/84Q/avXu3o7569Wp16tRJQUFBuvzyy/Xpp5/Kx8dHmzdvdozZtm2b+vXrp1q1aikqKkqDBw/WkSNHKuHRALjYCE0AvFZubq7Gjh2r9evXKyUlRb6+vrr11ltVVFSk7Oxs3XTTTWrfvr02btyoJ554QuPHj3f6/RMnTui6665T586dtX79ei1evFiZmZn64x//WEmPCMDFxBf2AsB/HTlyRPXr19fWrVu1atUqTZo0Sfv371dQUJAkadasWbr33nu1adMmderUSf/85z+1cuVKff3114517N+/X40aNVJqaqouvfTSynooAC4C9jQB8Fo7d+7UwIEDFRsbq9DQUDVt2lSSlJ6ertTUVHXo0MERmCSpW7duTr//448/aunSpapVq5bj1qpVK0lyOswHoHrwr+wGAKCy3HTTTWrSpInefPNNxcTEqKioSO3atVN+fr6l38/JydFNN92kp59+ukStQYMG7m4XQCUjNAHwSkePHlVqaqrefPNNXX311ZKkVatWOeqXXXaZ3n33XeXl5SkwMFCS9MMPPzito0uXLvrPf/6jpk2byt+fl1OguuPwHACvVKdOHdWtW1czZ87Url27tGTJEo0dO9ZRv+uuu1RUVKQRI0Zox44d+vrrr/Xcc89Jknx8fCRJSUlJOnbsmAYOHKgffvhBu3fv1tdff62hQ4eqsLCwUh4XgIuH0ATAK/n6+ur999/Xhg0b1K5dO40ZM0bPPvusox4aGqovvvhCmzdvVqdOnfSPf/xDkydPliTHeU4xMTH67rvvVFhYqD59+qh9+/YaPXq0wsPD5evLyytQ3fDpOQCwaN68eRo6dKiysrIUHBxc2e0A8DAOwgNAGebOnavY2Fhdcskl+vHHHzV+/Hj98Y9/JDABXorQBABlyMjI0OTJk5WRkaEGDRrojjvu0JNPPlnZbQGoJByeAwAAsIAzFQEAACwgNAEAAFhAaAIAALCA0AQAAGABoQkAAMACQhMAAIAFhCYAAAALCE0AAAAWEJoAAAAs+H/wPqm8GM5xwAAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot(kind='scatter',x='age', y='purchase')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Puchase Distribution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.histplot(df['purchase'], bins=50)\n",
    "plt.title('Purchase Distribution')\n",
    "plt.xlabel('Purchase Amount')\n",
    "plt.ylabel('Frequency')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "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>user_id</th>\n",
       "      <th>product_id</th>\n",
       "      <th>gender</th>\n",
       "      <th>age</th>\n",
       "      <th>occupation</th>\n",
       "      <th>city_category</th>\n",
       "      <th>stay_in_current_city_years</th>\n",
       "      <th>marital_status</th>\n",
       "      <th>product_category_1</th>\n",
       "      <th>product_category_2</th>\n",
       "      <th>product_category_3</th>\n",
       "      <th>purchase</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1000001</td>\n",
       "      <td>P00069042</td>\n",
       "      <td>F</td>\n",
       "      <td>0-17</td>\n",
       "      <td>10</td>\n",
       "      <td>A</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>9</td>\n",
       "      <td>14</td>\n",
       "      <td>8370</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1000001</td>\n",
       "      <td>P00248942</td>\n",
       "      <td>F</td>\n",
       "      <td>0-17</td>\n",
       "      <td>10</td>\n",
       "      <td>A</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>14</td>\n",
       "      <td>15200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1000001</td>\n",
       "      <td>P00087842</td>\n",
       "      <td>F</td>\n",
       "      <td>0-17</td>\n",
       "      <td>10</td>\n",
       "      <td>A</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "      <td>9</td>\n",
       "      <td>14</td>\n",
       "      <td>1422</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1000001</td>\n",
       "      <td>P00085442</td>\n",
       "      <td>F</td>\n",
       "      <td>0-17</td>\n",
       "      <td>10</td>\n",
       "      <td>A</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>1057</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1000002</td>\n",
       "      <td>P00285442</td>\n",
       "      <td>M</td>\n",
       "      <td>55+</td>\n",
       "      <td>16</td>\n",
       "      <td>C</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>9</td>\n",
       "      <td>14</td>\n",
       "      <td>7969</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   user_id product_id gender   age  occupation city_category  \\\n",
       "0  1000001  P00069042      F  0-17          10             A   \n",
       "1  1000001  P00248942      F  0-17          10             A   \n",
       "2  1000001  P00087842      F  0-17          10             A   \n",
       "3  1000001  P00085442      F  0-17          10             A   \n",
       "4  1000002  P00285442      M   55+          16             C   \n",
       "\n",
       "   stay_in_current_city_years  marital_status  product_category_1  \\\n",
       "0                           2               0                   3   \n",
       "1                           2               0                   1   \n",
       "2                           2               0                  12   \n",
       "3                           2               0                  12   \n",
       "4                           4               0                   8   \n",
       "\n",
       "   product_category_2  product_category_3  purchase  \n",
       "0                   9                  14      8370  \n",
       "1                   6                  14     15200  \n",
       "2                   9                  14      1422  \n",
       "3                  14                  14      1057  \n",
       "4                   9                  14      7969  "
      ]
     },
     "execution_count": 154,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sum_gender = df.groupby('gender')['purchase'].sum()\n",
    "ax = sns.barplot(df, x='gender', y='purchase', hue='gender', errorbar= None, estimator=\"sum\")\n",
    "for container in ax.containers:\n",
    "    ax.bar_label(container, fmt='%d', fontsize=12)\n",
    "# ax.set_yscale('log')\n",
    "max_sum = sum_gender.max()\n",
    "ax.set_ylim(0, max_sum + max_sum * 0.1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(df, x='age', y='purchase', hue= 'age', errorbar= None)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The above graph is showing the average purchase by each group of age people\n",
    "\n",
    "By default the estimator in sns.barplot is 'mean'."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(df, x='age', y='purchase', hue= 'age', errorbar= None, estimator='sum')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The above graph shows the total amout spend by each group of people"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Check for outliers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.displot(df, x='purchase', kind='kde')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 590.125x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.displot(df, x='purchase', kind='kde', hue = 'age')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(df, y='purchase')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### **Analysis by Gender, Marital Status, occupation, occupation vs purchase, purchase by city, purchase by age group, etc**\n",
    "\n",
    "#### Analysis by Gender"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(df, x='gender', y='purchase', hue='gender')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "key = ['Female', 'Male']\n",
    "explode = [0,0.1]\n",
    "gp_data = df.groupby('gender')['purchase'].count()\n",
    "\n",
    "plt.pie(gp_data.values, labels=key, explode=explode, autopct='%.0f%%')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.displot(df[df['gender']=='M'].value_counts('purchase').to_frame(), x='purchase', kind='kde')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.displot(df[df['gender']=='F'].value_counts('purchase').to_frame(), x='purchase', kind='kde')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 562x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.displot(df, x='purchase', kind='kde', hue='gender')\n",
    "plt.title('Purchase Distribution by Gender')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Bar chart for product selling for each product category and puchase by male and female."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "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>gender</th>\n",
       "      <th>product_category_1</th>\n",
       "      <th>product_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>F</td>\n",
       "      <td>5</td>\n",
       "      <td>41961</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>F</td>\n",
       "      <td>8</td>\n",
       "      <td>33558</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>F</td>\n",
       "      <td>1</td>\n",
       "      <td>24831</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>F</td>\n",
       "      <td>3</td>\n",
       "      <td>6006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>F</td>\n",
       "      <td>2</td>\n",
       "      <td>5658</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>F</td>\n",
       "      <td>11</td>\n",
       "      <td>4739</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>F</td>\n",
       "      <td>6</td>\n",
       "      <td>4559</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>F</td>\n",
       "      <td>4</td>\n",
       "      <td>3639</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>F</td>\n",
       "      <td>16</td>\n",
       "      <td>2402</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>F</td>\n",
       "      <td>12</td>\n",
       "      <td>1532</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>F</td>\n",
       "      <td>13</td>\n",
       "      <td>1462</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>F</td>\n",
       "      <td>10</td>\n",
       "      <td>1162</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>F</td>\n",
       "      <td>15</td>\n",
       "      <td>1046</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>943</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>F</td>\n",
       "      <td>20</td>\n",
       "      <td>723</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>F</td>\n",
       "      <td>14</td>\n",
       "      <td>623</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>F</td>\n",
       "      <td>19</td>\n",
       "      <td>451</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>F</td>\n",
       "      <td>18</td>\n",
       "      <td>382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>F</td>\n",
       "      <td>9</td>\n",
       "      <td>70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>F</td>\n",
       "      <td>17</td>\n",
       "      <td>62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>M</td>\n",
       "      <td>1</td>\n",
       "      <td>115547</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>108972</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>M</td>\n",
       "      <td>8</td>\n",
       "      <td>80367</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>M</td>\n",
       "      <td>11</td>\n",
       "      <td>19548</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>M</td>\n",
       "      <td>2</td>\n",
       "      <td>18206</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>M</td>\n",
       "      <td>6</td>\n",
       "      <td>15907</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>M</td>\n",
       "      <td>3</td>\n",
       "      <td>14207</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>M</td>\n",
       "      <td>4</td>\n",
       "      <td>8114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>M</td>\n",
       "      <td>16</td>\n",
       "      <td>7426</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>M</td>\n",
       "      <td>15</td>\n",
       "      <td>5244</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>M</td>\n",
       "      <td>13</td>\n",
       "      <td>4087</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>M</td>\n",
       "      <td>10</td>\n",
       "      <td>3963</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>M</td>\n",
       "      <td>7</td>\n",
       "      <td>2778</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>M</td>\n",
       "      <td>18</td>\n",
       "      <td>2743</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>M</td>\n",
       "      <td>12</td>\n",
       "      <td>2415</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>M</td>\n",
       "      <td>20</td>\n",
       "      <td>1827</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>M</td>\n",
       "      <td>19</td>\n",
       "      <td>1152</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>M</td>\n",
       "      <td>14</td>\n",
       "      <td>900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>M</td>\n",
       "      <td>17</td>\n",
       "      <td>516</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>M</td>\n",
       "      <td>9</td>\n",
       "      <td>340</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   gender  product_category_1  product_count\n",
       "0       F                   5          41961\n",
       "1       F                   8          33558\n",
       "2       F                   1          24831\n",
       "3       F                   3           6006\n",
       "4       F                   2           5658\n",
       "5       F                  11           4739\n",
       "6       F                   6           4559\n",
       "7       F                   4           3639\n",
       "8       F                  16           2402\n",
       "9       F                  12           1532\n",
       "10      F                  13           1462\n",
       "11      F                  10           1162\n",
       "12      F                  15           1046\n",
       "13      F                   7            943\n",
       "14      F                  20            723\n",
       "15      F                  14            623\n",
       "16      F                  19            451\n",
       "17      F                  18            382\n",
       "18      F                   9             70\n",
       "19      F                  17             62\n",
       "20      M                   1         115547\n",
       "21      M                   5         108972\n",
       "22      M                   8          80367\n",
       "23      M                  11          19548\n",
       "24      M                   2          18206\n",
       "25      M                   6          15907\n",
       "26      M                   3          14207\n",
       "27      M                   4           8114\n",
       "28      M                  16           7426\n",
       "29      M                  15           5244\n",
       "30      M                  13           4087\n",
       "31      M                  10           3963\n",
       "32      M                   7           2778\n",
       "33      M                  18           2743\n",
       "34      M                  12           2415\n",
       "35      M                  20           1827\n",
       "36      M                  19           1152\n",
       "37      M                  14            900\n",
       "38      M                  17            516\n",
       "39      M                   9            340"
      ]
     },
     "execution_count": 171,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_gp_gen = df.groupby('gender')['product_category_1'].value_counts().to_frame(name='product_count').reset_index()\n",
    "df_gp_gen"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(df_gp_gen, x='product_category_1', y='product_count', hue='gender')\n",
    "plt.title('Product Category 1 sells among male and Female')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "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>gender</th>\n",
       "      <th>product_category_2</th>\n",
       "      <th>product_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>F</td>\n",
       "      <td>9</td>\n",
       "      <td>45776</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>F</td>\n",
       "      <td>14</td>\n",
       "      <td>19693</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>F</td>\n",
       "      <td>8</td>\n",
       "      <td>16529</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>F</td>\n",
       "      <td>16</td>\n",
       "      <td>9496</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>F</td>\n",
       "      <td>2</td>\n",
       "      <td>9199</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>F</td>\n",
       "      <td>4</td>\n",
       "      <td>7619</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>F</td>\n",
       "      <td>15</td>\n",
       "      <td>6432</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>F</td>\n",
       "      <td>5</td>\n",
       "      <td>6155</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>F</td>\n",
       "      <td>6</td>\n",
       "      <td>3291</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>F</td>\n",
       "      <td>11</td>\n",
       "      <td>2754</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>F</td>\n",
       "      <td>13</td>\n",
       "      <td>2669</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>F</td>\n",
       "      <td>17</td>\n",
       "      <td>2484</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>F</td>\n",
       "      <td>12</td>\n",
       "      <td>1744</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>F</td>\n",
       "      <td>10</td>\n",
       "      <td>736</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>F</td>\n",
       "      <td>3</td>\n",
       "      <td>617</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>F</td>\n",
       "      <td>18</td>\n",
       "      <td>478</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>M</td>\n",
       "      <td>9</td>\n",
       "      <td>133555</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>M</td>\n",
       "      <td>8</td>\n",
       "      <td>47559</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>M</td>\n",
       "      <td>2</td>\n",
       "      <td>40018</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>M</td>\n",
       "      <td>14</td>\n",
       "      <td>35415</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>M</td>\n",
       "      <td>16</td>\n",
       "      <td>33759</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>M</td>\n",
       "      <td>15</td>\n",
       "      <td>31423</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>20080</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>M</td>\n",
       "      <td>4</td>\n",
       "      <td>18058</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>M</td>\n",
       "      <td>6</td>\n",
       "      <td>13175</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>M</td>\n",
       "      <td>11</td>\n",
       "      <td>11380</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>M</td>\n",
       "      <td>17</td>\n",
       "      <td>10836</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>M</td>\n",
       "      <td>13</td>\n",
       "      <td>7862</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>M</td>\n",
       "      <td>12</td>\n",
       "      <td>3784</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>M</td>\n",
       "      <td>10</td>\n",
       "      <td>2307</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>M</td>\n",
       "      <td>18</td>\n",
       "      <td>2292</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>M</td>\n",
       "      <td>3</td>\n",
       "      <td>2267</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>M</td>\n",
       "      <td>7</td>\n",
       "      <td>489</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   gender  product_category_2  product_count\n",
       "0       F                   9          45776\n",
       "1       F                  14          19693\n",
       "2       F                   8          16529\n",
       "3       F                  16           9496\n",
       "4       F                   2           9199\n",
       "5       F                   4           7619\n",
       "6       F                  15           6432\n",
       "7       F                   5           6155\n",
       "8       F                   6           3291\n",
       "9       F                  11           2754\n",
       "10      F                  13           2669\n",
       "11      F                  17           2484\n",
       "12      F                  12           1744\n",
       "13      F                  10            736\n",
       "14      F                   3            617\n",
       "15      F                  18            478\n",
       "16      F                   7            137\n",
       "17      M                   9         133555\n",
       "18      M                   8          47559\n",
       "19      M                   2          40018\n",
       "20      M                  14          35415\n",
       "21      M                  16          33759\n",
       "22      M                  15          31423\n",
       "23      M                   5          20080\n",
       "24      M                   4          18058\n",
       "25      M                   6          13175\n",
       "26      M                  11          11380\n",
       "27      M                  17          10836\n",
       "28      M                  13           7862\n",
       "29      M                  12           3784\n",
       "30      M                  10           2307\n",
       "31      M                  18           2292\n",
       "32      M                   3           2267\n",
       "33      M                   7            489"
      ]
     },
     "execution_count": 178,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_gp_gen_2 = df.groupby('gender')['product_category_2'].value_counts().to_frame(name='product_count').reset_index()\n",
    "df_gp_gen_2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(df_gp_gen_2, x='product_category_2', y='product_count', hue='gender')\n",
    "plt.title('Product Category 2 sells among male and Female')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 180,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_gp_gen_3 = df.groupby('gender')['product_category_3'].value_counts().to_frame(name='product_count').reset_index()\n",
    "sns.barplot(df_gp_gen_3, x='product_category_3', y='product_count', hue='gender')\n",
    "plt.title('Product Category 3 sells among male and Female')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Analysis on Marital_Status"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 181,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.displot(df[df['marital_status']==0].value_counts('purchase').to_frame(),x='purchase', kind='kde')\n",
    "plt.title('UnMarried')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 182,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.displot(df[df['marital_status']==1].value_counts('purchase').to_frame(), x='purchase', kind='kde')\n",
    "plt.title('Married')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 183,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "key = ['UnMarried', 'Married']\n",
    "explode = [0,0.1]\n",
    "gp_data1 = df.groupby('marital_status')['purchase'].count()\n",
    "\n",
    "plt.pie(gp_data1.values, labels=key, explode=explode, autopct='%.0f%%')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Check the puchase made by gender and their marital status"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 184,
   "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>gender</th>\n",
       "      <th>marital_status</th>\n",
       "      <th>purchase</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>F</td>\n",
       "      <td>0</td>\n",
       "      <td>684154127</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>F</td>\n",
       "      <td>1</td>\n",
       "      <td>502078515</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>M</td>\n",
       "      <td>0</td>\n",
       "      <td>2324773320</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>M</td>\n",
       "      <td>1</td>\n",
       "      <td>1584806780</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  gender  marital_status    purchase\n",
       "0      F               0   684154127\n",
       "1      F               1   502078515\n",
       "2      M               0  2324773320\n",
       "3      M               1  1584806780"
      ]
     },
     "execution_count": 184,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "puch_gender_marital_status =  df.groupby(['gender', 'marital_status']).agg({'purchase':'sum'}).reset_index()\n",
    "puch_gender_marital_status"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Drop unnecessary fields"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "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>user_id</th>\n",
       "      <th>product_id</th>\n",
       "      <th>gender</th>\n",
       "      <th>age</th>\n",
       "      <th>occupation</th>\n",
       "      <th>city_category</th>\n",
       "      <th>stay_in_current_city_years</th>\n",
       "      <th>marital_status</th>\n",
       "      <th>product_category_1</th>\n",
       "      <th>product_category_2</th>\n",
       "      <th>product_category_3</th>\n",
       "      <th>purchase</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1000001</td>\n",
       "      <td>P00069042</td>\n",
       "      <td>F</td>\n",
       "      <td>0-17</td>\n",
       "      <td>10</td>\n",
       "      <td>A</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>9</td>\n",
       "      <td>14</td>\n",
       "      <td>8370</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1000001</td>\n",
       "      <td>P00248942</td>\n",
       "      <td>F</td>\n",
       "      <td>0-17</td>\n",
       "      <td>10</td>\n",
       "      <td>A</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>14</td>\n",
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       "      <td>4</td>\n",
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       "      <td>14</td>\n",
       "      <td>7969</td>\n",
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       "  </tbody>\n",
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      ],
      "text/plain": [
       "   user_id product_id gender   age  occupation city_category  \\\n",
       "0  1000001  P00069042      F  0-17          10             A   \n",
       "1  1000001  P00248942      F  0-17          10             A   \n",
       "2  1000001  P00087842      F  0-17          10             A   \n",
       "3  1000001  P00085442      F  0-17          10             A   \n",
       "4  1000002  P00285442      M   55+          16             C   \n",
       "\n",
       "   stay_in_current_city_years  marital_status  product_category_1  \\\n",
       "0                           2               0                   3   \n",
       "1                           2               0                   1   \n",
       "2                           2               0                  12   \n",
       "3                           2               0                  12   \n",
       "4                           4               0                   8   \n",
       "\n",
       "   product_category_2  product_category_3  purchase  \n",
       "0                   9                  14      8370  \n",
       "1                   6                  14     15200  \n",
       "2                   9                  14      1422  \n",
       "3                  14                  14      1057  \n",
       "4                   9                  14      7969  "
      ]
     },
     "execution_count": 185,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can drop User_ID and Product_ID as we are not analyzing data on inividual user level. It would be veru fruitful if we are analyzing data to create recommendation for individual User."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 186,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.drop(['user_id', 'product_id'], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 187,
   "metadata": {},
   "outputs": [
    {
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       "       gender    age  occupation city_category  stay_in_current_city_years  \\\n",
       "0           F   0-17          10             A                           2   \n",
       "1           F   0-17          10             A                           2   \n",
       "2           F   0-17          10             A                           2   \n",
       "3           F   0-17          10             A                           2   \n",
       "4           M    55+          16             C                           4   \n",
       "...       ...    ...         ...           ...                         ...   \n",
       "550063      M  51-55          13             B                           1   \n",
       "550064      F  26-35           1             C                           3   \n",
       "550065      F  26-35          15             B                           4   \n",
       "550066      F    55+           1             C                           2   \n",
       "550067      F  46-50           0             B                           4   \n",
       "\n",
       "        marital_status  product_category_1  product_category_2  \\\n",
       "0                    0                   3                   9   \n",
       "1                    0                   1                   6   \n",
       "2                    0                  12                   9   \n",
       "3                    0                  12                  14   \n",
       "4                    0                   8                   9   \n",
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       "550066               0                  20                   9   \n",
       "550067               1                  20                   9   \n",
       "\n",
       "        product_category_3  purchase  \n",
       "0                       14      8370  \n",
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       "4                       14      7969  \n",
       "...                    ...       ...  \n",
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       "550064                  14       371  \n",
       "550065                  14       137  \n",
       "550066                  14       365  \n",
       "550067                  14       490  \n",
       "\n",
       "[550068 rows x 10 columns]"
      ]
     },
     "execution_count": 187,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Convert categorical data into integer using map function (e.g 'Gender' column)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 188,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['gender'] = df['gender'].map({'F':0, 'M':1})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 189,
   "metadata": {},
   "outputs": [
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       "        gender    age  occupation city_category  stay_in_current_city_years  \\\n",
       "0            0   0-17          10             A                           2   \n",
       "1            0   0-17          10             A                           2   \n",
       "2            0   0-17          10             A                           2   \n",
       "3            0   0-17          10             A                           2   \n",
       "4            1    55+          16             C                           4   \n",
       "...        ...    ...         ...           ...                         ...   \n",
       "550063       1  51-55          13             B                           1   \n",
       "550064       0  26-35           1             C                           3   \n",
       "550065       0  26-35          15             B                           4   \n",
       "550066       0    55+           1             C                           2   \n",
       "550067       0  46-50           0             B                           4   \n",
       "\n",
       "        marital_status  product_category_1  product_category_2  \\\n",
       "0                    0                   3                   9   \n",
       "1                    0                   1                   6   \n",
       "2                    0                  12                   9   \n",
       "3                    0                  12                  14   \n",
       "4                    0                   8                   9   \n",
       "...                ...                 ...                 ...   \n",
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       "550066               0                  20                   9   \n",
       "550067               1                  20                   9   \n",
       "\n",
       "        product_category_3  purchase  \n",
       "0                       14      8370  \n",
       "1                       14     15200  \n",
       "2                       14      1422  \n",
       "3                       14      1057  \n",
       "4                       14      7969  \n",
       "...                    ...       ...  \n",
       "550063                  14       368  \n",
       "550064                  14       371  \n",
       "550065                  14       137  \n",
       "550066                  14       365  \n",
       "550067                  14       490  \n",
       "\n",
       "[550068 rows x 10 columns]"
      ]
     },
     "execution_count": 189,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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