CustomerAnalytics_CustomerBehavior.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('C:/Users/Admin/Desktop/Customer Behaviour.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(9134, 24)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "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>Customer</th>\n",
       "      <th>State</th>\n",
       "      <th>Customer Lifetime Value</th>\n",
       "      <th>Response</th>\n",
       "      <th>Coverage</th>\n",
       "      <th>Education</th>\n",
       "      <th>Effective To Date</th>\n",
       "      <th>EmploymentStatus</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Income</th>\n",
       "      <th>...</th>\n",
       "      <th>Months Since Policy Inception</th>\n",
       "      <th>Number of Open Complaints</th>\n",
       "      <th>Number of Policies</th>\n",
       "      <th>Policy Type</th>\n",
       "      <th>Policy</th>\n",
       "      <th>Renew Offer Type</th>\n",
       "      <th>Sales Channel</th>\n",
       "      <th>Total Claim Amount</th>\n",
       "      <th>Vehicle Class</th>\n",
       "      <th>Vehicle Size</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>BU79786</td>\n",
       "      <td>Washington</td>\n",
       "      <td>2763.519279</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>2/24/11</td>\n",
       "      <td>Employed</td>\n",
       "      <td>F</td>\n",
       "      <td>56274</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Corporate L3</td>\n",
       "      <td>Offer1</td>\n",
       "      <td>Agent</td>\n",
       "      <td>384.811147</td>\n",
       "      <td>Two-Door Car</td>\n",
       "      <td>Medsize</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>QZ44356</td>\n",
       "      <td>Arizona</td>\n",
       "      <td>6979.535903</td>\n",
       "      <td>No</td>\n",
       "      <td>Extended</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>1/31/11</td>\n",
       "      <td>Unemployed</td>\n",
       "      <td>F</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>42</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Personal L3</td>\n",
       "      <td>Offer3</td>\n",
       "      <td>Agent</td>\n",
       "      <td>1131.464935</td>\n",
       "      <td>Four-Door Car</td>\n",
       "      <td>Medsize</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AI49188</td>\n",
       "      <td>Nevada</td>\n",
       "      <td>12887.431650</td>\n",
       "      <td>No</td>\n",
       "      <td>Premium</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>2/19/11</td>\n",
       "      <td>Employed</td>\n",
       "      <td>F</td>\n",
       "      <td>48767</td>\n",
       "      <td>...</td>\n",
       "      <td>38</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Personal L3</td>\n",
       "      <td>Offer1</td>\n",
       "      <td>Agent</td>\n",
       "      <td>566.472247</td>\n",
       "      <td>Two-Door Car</td>\n",
       "      <td>Medsize</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>WW63253</td>\n",
       "      <td>California</td>\n",
       "      <td>7645.861827</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>1/20/11</td>\n",
       "      <td>Unemployed</td>\n",
       "      <td>M</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>65</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Corporate L2</td>\n",
       "      <td>Offer1</td>\n",
       "      <td>Call Center</td>\n",
       "      <td>529.881344</td>\n",
       "      <td>SUV</td>\n",
       "      <td>Medsize</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>HB64268</td>\n",
       "      <td>Washington</td>\n",
       "      <td>2813.692575</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>2/3/11</td>\n",
       "      <td>Employed</td>\n",
       "      <td>M</td>\n",
       "      <td>43836</td>\n",
       "      <td>...</td>\n",
       "      <td>44</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Personal L1</td>\n",
       "      <td>Offer1</td>\n",
       "      <td>Agent</td>\n",
       "      <td>138.130879</td>\n",
       "      <td>Four-Door Car</td>\n",
       "      <td>Medsize</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>OC83172</td>\n",
       "      <td>Oregon</td>\n",
       "      <td>8256.297800</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>1/25/11</td>\n",
       "      <td>Employed</td>\n",
       "      <td>F</td>\n",
       "      <td>62902</td>\n",
       "      <td>...</td>\n",
       "      <td>94</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Personal L3</td>\n",
       "      <td>Offer2</td>\n",
       "      <td>Web</td>\n",
       "      <td>159.383042</td>\n",
       "      <td>Two-Door Car</td>\n",
       "      <td>Medsize</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>XZ87318</td>\n",
       "      <td>Oregon</td>\n",
       "      <td>5380.898636</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Basic</td>\n",
       "      <td>College</td>\n",
       "      <td>2/24/11</td>\n",
       "      <td>Employed</td>\n",
       "      <td>F</td>\n",
       "      <td>55350</td>\n",
       "      <td>...</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Corporate L3</td>\n",
       "      <td>Offer1</td>\n",
       "      <td>Agent</td>\n",
       "      <td>321.600000</td>\n",
       "      <td>Four-Door Car</td>\n",
       "      <td>Medsize</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>CF85061</td>\n",
       "      <td>Arizona</td>\n",
       "      <td>7216.100311</td>\n",
       "      <td>No</td>\n",
       "      <td>Premium</td>\n",
       "      <td>Master</td>\n",
       "      <td>1/18/11</td>\n",
       "      <td>Unemployed</td>\n",
       "      <td>M</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>68</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Corporate L3</td>\n",
       "      <td>Offer1</td>\n",
       "      <td>Agent</td>\n",
       "      <td>363.029680</td>\n",
       "      <td>Four-Door Car</td>\n",
       "      <td>Medsize</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>DY87989</td>\n",
       "      <td>Oregon</td>\n",
       "      <td>24127.504020</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>1/26/11</td>\n",
       "      <td>Medical Leave</td>\n",
       "      <td>M</td>\n",
       "      <td>14072</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Corporate L3</td>\n",
       "      <td>Offer1</td>\n",
       "      <td>Agent</td>\n",
       "      <td>511.200000</td>\n",
       "      <td>Four-Door Car</td>\n",
       "      <td>Medsize</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>BQ94931</td>\n",
       "      <td>Oregon</td>\n",
       "      <td>7388.178085</td>\n",
       "      <td>No</td>\n",
       "      <td>Extended</td>\n",
       "      <td>College</td>\n",
       "      <td>2/17/11</td>\n",
       "      <td>Employed</td>\n",
       "      <td>F</td>\n",
       "      <td>28812</td>\n",
       "      <td>...</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>Special Auto</td>\n",
       "      <td>Special L2</td>\n",
       "      <td>Offer2</td>\n",
       "      <td>Branch</td>\n",
       "      <td>425.527834</td>\n",
       "      <td>Four-Door Car</td>\n",
       "      <td>Medsize</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>SX51350</td>\n",
       "      <td>California</td>\n",
       "      <td>4738.992022</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>College</td>\n",
       "      <td>2/21/11</td>\n",
       "      <td>Unemployed</td>\n",
       "      <td>M</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Personal L3</td>\n",
       "      <td>Offer1</td>\n",
       "      <td>Agent</td>\n",
       "      <td>482.400000</td>\n",
       "      <td>Four-Door Car</td>\n",
       "      <td>Small</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>VQ65197</td>\n",
       "      <td>California</td>\n",
       "      <td>8197.197078</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>College</td>\n",
       "      <td>1/6/11</td>\n",
       "      <td>Unemployed</td>\n",
       "      <td>F</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>87</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Personal L3</td>\n",
       "      <td>Offer2</td>\n",
       "      <td>Agent</td>\n",
       "      <td>528.000000</td>\n",
       "      <td>SUV</td>\n",
       "      <td>Medsize</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>DP39365</td>\n",
       "      <td>California</td>\n",
       "      <td>8798.797003</td>\n",
       "      <td>No</td>\n",
       "      <td>Premium</td>\n",
       "      <td>Master</td>\n",
       "      <td>2/6/11</td>\n",
       "      <td>Employed</td>\n",
       "      <td>M</td>\n",
       "      <td>77026</td>\n",
       "      <td>...</td>\n",
       "      <td>82</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Corporate L1</td>\n",
       "      <td>Offer2</td>\n",
       "      <td>Agent</td>\n",
       "      <td>472.029737</td>\n",
       "      <td>Four-Door Car</td>\n",
       "      <td>Medsize</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>SJ95423</td>\n",
       "      <td>Arizona</td>\n",
       "      <td>8819.018934</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Basic</td>\n",
       "      <td>High School or Below</td>\n",
       "      <td>1/10/11</td>\n",
       "      <td>Employed</td>\n",
       "      <td>M</td>\n",
       "      <td>99845</td>\n",
       "      <td>...</td>\n",
       "      <td>25</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Corporate L3</td>\n",
       "      <td>Offer2</td>\n",
       "      <td>Branch</td>\n",
       "      <td>528.000000</td>\n",
       "      <td>SUV</td>\n",
       "      <td>Medsize</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>IL66569</td>\n",
       "      <td>California</td>\n",
       "      <td>5384.431665</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>College</td>\n",
       "      <td>1/18/11</td>\n",
       "      <td>Employed</td>\n",
       "      <td>M</td>\n",
       "      <td>83689</td>\n",
       "      <td>...</td>\n",
       "      <td>10</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Corporate L3</td>\n",
       "      <td>Offer4</td>\n",
       "      <td>Call Center</td>\n",
       "      <td>307.139132</td>\n",
       "      <td>Four-Door Car</td>\n",
       "      <td>Medsize</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>BW63560</td>\n",
       "      <td>Oregon</td>\n",
       "      <td>7463.139377</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>1/17/11</td>\n",
       "      <td>Employed</td>\n",
       "      <td>F</td>\n",
       "      <td>24599</td>\n",
       "      <td>...</td>\n",
       "      <td>50</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Corporate L2</td>\n",
       "      <td>Offer2</td>\n",
       "      <td>Branch</td>\n",
       "      <td>42.920271</td>\n",
       "      <td>Four-Door Car</td>\n",
       "      <td>Medsize</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>FV94802</td>\n",
       "      <td>Nevada</td>\n",
       "      <td>2566.867823</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>High School or Below</td>\n",
       "      <td>2/6/11</td>\n",
       "      <td>Medical Leave</td>\n",
       "      <td>M</td>\n",
       "      <td>25049</td>\n",
       "      <td>...</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Personal L3</td>\n",
       "      <td>Offer2</td>\n",
       "      <td>Call Center</td>\n",
       "      <td>454.245098</td>\n",
       "      <td>Two-Door Car</td>\n",
       "      <td>Medsize</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>OE15005</td>\n",
       "      <td>California</td>\n",
       "      <td>3945.241604</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>College</td>\n",
       "      <td>1/5/11</td>\n",
       "      <td>Medical Leave</td>\n",
       "      <td>M</td>\n",
       "      <td>28855</td>\n",
       "      <td>...</td>\n",
       "      <td>59</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Personal L2</td>\n",
       "      <td>Offer3</td>\n",
       "      <td>Call Center</td>\n",
       "      <td>647.442031</td>\n",
       "      <td>SUV</td>\n",
       "      <td>Medsize</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>WC83389</td>\n",
       "      <td>Oregon</td>\n",
       "      <td>5710.333115</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>College</td>\n",
       "      <td>2/27/11</td>\n",
       "      <td>Employed</td>\n",
       "      <td>M</td>\n",
       "      <td>51148</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Personal L2</td>\n",
       "      <td>Offer2</td>\n",
       "      <td>Branch</td>\n",
       "      <td>308.981664</td>\n",
       "      <td>Four-Door Car</td>\n",
       "      <td>Medsize</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>FL50705</td>\n",
       "      <td>California</td>\n",
       "      <td>8162.617053</td>\n",
       "      <td>No</td>\n",
       "      <td>Premium</td>\n",
       "      <td>High School or Below</td>\n",
       "      <td>1/14/11</td>\n",
       "      <td>Employed</td>\n",
       "      <td>F</td>\n",
       "      <td>66140</td>\n",
       "      <td>...</td>\n",
       "      <td>21</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Corporate L2</td>\n",
       "      <td>Offer1</td>\n",
       "      <td>Call Center</td>\n",
       "      <td>484.800000</td>\n",
       "      <td>Four-Door Car</td>\n",
       "      <td>Small</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>ZK25313</td>\n",
       "      <td>Oregon</td>\n",
       "      <td>2872.051273</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>High School or Below</td>\n",
       "      <td>2/19/11</td>\n",
       "      <td>Employed</td>\n",
       "      <td>M</td>\n",
       "      <td>57749</td>\n",
       "      <td>...</td>\n",
       "      <td>21</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Personal L2</td>\n",
       "      <td>Offer1</td>\n",
       "      <td>Branch</td>\n",
       "      <td>355.200000</td>\n",
       "      <td>Two-Door Car</td>\n",
       "      <td>Medsize</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>SV62436</td>\n",
       "      <td>Washington</td>\n",
       "      <td>3041.791561</td>\n",
       "      <td>No</td>\n",
       "      <td>Extended</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>1/21/11</td>\n",
       "      <td>Disabled</td>\n",
       "      <td>F</td>\n",
       "      <td>13789</td>\n",
       "      <td>...</td>\n",
       "      <td>49</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Personal L3</td>\n",
       "      <td>Offer4</td>\n",
       "      <td>Call Center</td>\n",
       "      <td>379.200000</td>\n",
       "      <td>Four-Door Car</td>\n",
       "      <td>Medsize</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>YH23384</td>\n",
       "      <td>Arizona</td>\n",
       "      <td>24127.504020</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>1/26/11</td>\n",
       "      <td>Medical Leave</td>\n",
       "      <td>M</td>\n",
       "      <td>14072</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Personal L3</td>\n",
       "      <td>Offer1</td>\n",
       "      <td>Agent</td>\n",
       "      <td>511.200000</td>\n",
       "      <td>Four-Door Car</td>\n",
       "      <td>Medsize</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>TZ98966</td>\n",
       "      <td>Nevada</td>\n",
       "      <td>2450.190996</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>2/24/11</td>\n",
       "      <td>Unemployed</td>\n",
       "      <td>F</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>44</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Corporate L3</td>\n",
       "      <td>Offer1</td>\n",
       "      <td>Branch</td>\n",
       "      <td>554.376763</td>\n",
       "      <td>Four-Door Car</td>\n",
       "      <td>Medsize</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>HM55802</td>\n",
       "      <td>California</td>\n",
       "      <td>2392.107890</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>2/5/11</td>\n",
       "      <td>Disabled</td>\n",
       "      <td>F</td>\n",
       "      <td>17870</td>\n",
       "      <td>...</td>\n",
       "      <td>91</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Corporate L2</td>\n",
       "      <td>Offer2</td>\n",
       "      <td>Branch</td>\n",
       "      <td>439.200000</td>\n",
       "      <td>Four-Door Car</td>\n",
       "      <td>Medsize</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>FS42516</td>\n",
       "      <td>Oregon</td>\n",
       "      <td>5802.065978</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>College</td>\n",
       "      <td>1/29/11</td>\n",
       "      <td>Employed</td>\n",
       "      <td>M</td>\n",
       "      <td>97541</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Personal L3</td>\n",
       "      <td>Offer2</td>\n",
       "      <td>Call Center</td>\n",
       "      <td>389.185006</td>\n",
       "      <td>Four-Door Car</td>\n",
       "      <td>Large</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>US89481</td>\n",
       "      <td>California</td>\n",
       "      <td>3946.372085</td>\n",
       "      <td>No</td>\n",
       "      <td>Premium</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>2/28/11</td>\n",
       "      <td>Unemployed</td>\n",
       "      <td>F</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>47</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Personal L3</td>\n",
       "      <td>Offer1</td>\n",
       "      <td>Agent</td>\n",
       "      <td>799.200000</td>\n",
       "      <td>Four-Door Car</td>\n",
       "      <td>Small</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>HO30839</td>\n",
       "      <td>Washington</td>\n",
       "      <td>5346.916576</td>\n",
       "      <td>No</td>\n",
       "      <td>Extended</td>\n",
       "      <td>Master</td>\n",
       "      <td>2/12/11</td>\n",
       "      <td>Disabled</td>\n",
       "      <td>F</td>\n",
       "      <td>10511</td>\n",
       "      <td>...</td>\n",
       "      <td>64</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Corporate L1</td>\n",
       "      <td>Offer1</td>\n",
       "      <td>Branch</td>\n",
       "      <td>516.237951</td>\n",
       "      <td>SUV</td>\n",
       "      <td>Medsize</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>GE62437</td>\n",
       "      <td>Arizona</td>\n",
       "      <td>12902.560140</td>\n",
       "      <td>No</td>\n",
       "      <td>Premium</td>\n",
       "      <td>College</td>\n",
       "      <td>2/2/11</td>\n",
       "      <td>Employed</td>\n",
       "      <td>F</td>\n",
       "      <td>86584</td>\n",
       "      <td>...</td>\n",
       "      <td>54</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Personal L3</td>\n",
       "      <td>Offer1</td>\n",
       "      <td>Call Center</td>\n",
       "      <td>532.800000</td>\n",
       "      <td>Four-Door Car</td>\n",
       "      <td>Large</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>EJ77678</td>\n",
       "      <td>Oregon</td>\n",
       "      <td>3235.360468</td>\n",
       "      <td>No</td>\n",
       "      <td>Extended</td>\n",
       "      <td>Master</td>\n",
       "      <td>2/7/11</td>\n",
       "      <td>Employed</td>\n",
       "      <td>F</td>\n",
       "      <td>75690</td>\n",
       "      <td>...</td>\n",
       "      <td>44</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Personal L3</td>\n",
       "      <td>Offer2</td>\n",
       "      <td>Branch</td>\n",
       "      <td>384.000000</td>\n",
       "      <td>Four-Door Car</td>\n",
       "      <td>Small</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>30 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Customer       State  Customer Lifetime Value Response  Coverage  \\\n",
       "0   BU79786  Washington              2763.519279       No     Basic   \n",
       "1   QZ44356     Arizona              6979.535903       No  Extended   \n",
       "2   AI49188      Nevada             12887.431650       No   Premium   \n",
       "3   WW63253  California              7645.861827       No     Basic   \n",
       "4   HB64268  Washington              2813.692575       No     Basic   \n",
       "5   OC83172      Oregon              8256.297800      Yes     Basic   \n",
       "6   XZ87318      Oregon              5380.898636      Yes     Basic   \n",
       "7   CF85061     Arizona              7216.100311       No   Premium   \n",
       "8   DY87989      Oregon             24127.504020      Yes     Basic   \n",
       "9   BQ94931      Oregon              7388.178085       No  Extended   \n",
       "10  SX51350  California              4738.992022       No     Basic   \n",
       "11  VQ65197  California              8197.197078       No     Basic   \n",
       "12  DP39365  California              8798.797003       No   Premium   \n",
       "13  SJ95423     Arizona              8819.018934      Yes     Basic   \n",
       "14  IL66569  California              5384.431665       No     Basic   \n",
       "15  BW63560      Oregon              7463.139377       No     Basic   \n",
       "16  FV94802      Nevada              2566.867823       No     Basic   \n",
       "17  OE15005  California              3945.241604       No     Basic   \n",
       "18  WC83389      Oregon              5710.333115       No     Basic   \n",
       "19  FL50705  California              8162.617053       No   Premium   \n",
       "20  ZK25313      Oregon              2872.051273       No     Basic   \n",
       "21  SV62436  Washington              3041.791561       No  Extended   \n",
       "22  YH23384     Arizona             24127.504020      Yes     Basic   \n",
       "23  TZ98966      Nevada              2450.190996       No     Basic   \n",
       "24  HM55802  California              2392.107890       No     Basic   \n",
       "25  FS42516      Oregon              5802.065978       No     Basic   \n",
       "26  US89481  California              3946.372085       No   Premium   \n",
       "27  HO30839  Washington              5346.916576       No  Extended   \n",
       "28  GE62437     Arizona             12902.560140       No   Premium   \n",
       "29  EJ77678      Oregon              3235.360468       No  Extended   \n",
       "\n",
       "               Education Effective To Date EmploymentStatus Gender  Income  \\\n",
       "0               Bachelor           2/24/11         Employed      F   56274   \n",
       "1               Bachelor           1/31/11       Unemployed      F       0   \n",
       "2               Bachelor           2/19/11         Employed      F   48767   \n",
       "3               Bachelor           1/20/11       Unemployed      M       0   \n",
       "4               Bachelor            2/3/11         Employed      M   43836   \n",
       "5               Bachelor           1/25/11         Employed      F   62902   \n",
       "6                College           2/24/11         Employed      F   55350   \n",
       "7                 Master           1/18/11       Unemployed      M       0   \n",
       "8               Bachelor           1/26/11    Medical Leave      M   14072   \n",
       "9                College           2/17/11         Employed      F   28812   \n",
       "10               College           2/21/11       Unemployed      M       0   \n",
       "11               College            1/6/11       Unemployed      F       0   \n",
       "12                Master            2/6/11         Employed      M   77026   \n",
       "13  High School or Below           1/10/11         Employed      M   99845   \n",
       "14               College           1/18/11         Employed      M   83689   \n",
       "15              Bachelor           1/17/11         Employed      F   24599   \n",
       "16  High School or Below            2/6/11    Medical Leave      M   25049   \n",
       "17               College            1/5/11    Medical Leave      M   28855   \n",
       "18               College           2/27/11         Employed      M   51148   \n",
       "19  High School or Below           1/14/11         Employed      F   66140   \n",
       "20  High School or Below           2/19/11         Employed      M   57749   \n",
       "21              Bachelor           1/21/11         Disabled      F   13789   \n",
       "22              Bachelor           1/26/11    Medical Leave      M   14072   \n",
       "23              Bachelor           2/24/11       Unemployed      F       0   \n",
       "24              Bachelor            2/5/11         Disabled      F   17870   \n",
       "25               College           1/29/11         Employed      M   97541   \n",
       "26              Bachelor           2/28/11       Unemployed      F       0   \n",
       "27                Master           2/12/11         Disabled      F   10511   \n",
       "28               College            2/2/11         Employed      F   86584   \n",
       "29                Master            2/7/11         Employed      F   75690   \n",
       "\n",
       "    ... Months Since Policy Inception Number of Open Complaints  \\\n",
       "0   ...                             5                         0   \n",
       "1   ...                            42                         0   \n",
       "2   ...                            38                         0   \n",
       "3   ...                            65                         0   \n",
       "4   ...                            44                         0   \n",
       "5   ...                            94                         0   \n",
       "6   ...                            13                         0   \n",
       "7   ...                            68                         0   \n",
       "8   ...                             3                         0   \n",
       "9   ...                             7                         0   \n",
       "10  ...                             5                         0   \n",
       "11  ...                            87                         0   \n",
       "12  ...                            82                         2   \n",
       "13  ...                            25                         1   \n",
       "14  ...                            10                         2   \n",
       "15  ...                            50                         1   \n",
       "16  ...                             7                         0   \n",
       "17  ...                            59                         0   \n",
       "18  ...                             1                         0   \n",
       "19  ...                            21                         0   \n",
       "20  ...                            21                         0   \n",
       "21  ...                            49                         0   \n",
       "22  ...                             3                         0   \n",
       "23  ...                            44                         3   \n",
       "24  ...                            91                         0   \n",
       "25  ...                             1                         0   \n",
       "26  ...                            47                         0   \n",
       "27  ...                            64                         0   \n",
       "28  ...                            54                         2   \n",
       "29  ...                            44                         1   \n",
       "\n",
       "    Number of Policies     Policy Type        Policy  Renew Offer Type  \\\n",
       "0                    1  Corporate Auto  Corporate L3            Offer1   \n",
       "1                    8   Personal Auto   Personal L3            Offer3   \n",
       "2                    2   Personal Auto   Personal L3            Offer1   \n",
       "3                    7  Corporate Auto  Corporate L2            Offer1   \n",
       "4                    1   Personal Auto   Personal L1            Offer1   \n",
       "5                    2   Personal Auto   Personal L3            Offer2   \n",
       "6                    9  Corporate Auto  Corporate L3            Offer1   \n",
       "7                    4  Corporate Auto  Corporate L3            Offer1   \n",
       "8                    2  Corporate Auto  Corporate L3            Offer1   \n",
       "9                    8    Special Auto    Special L2            Offer2   \n",
       "10                   3   Personal Auto   Personal L3            Offer1   \n",
       "11                   3   Personal Auto   Personal L3            Offer2   \n",
       "12                   3  Corporate Auto  Corporate L1            Offer2   \n",
       "13                   8  Corporate Auto  Corporate L3            Offer2   \n",
       "14                   8  Corporate Auto  Corporate L3            Offer4   \n",
       "15                   2  Corporate Auto  Corporate L2            Offer2   \n",
       "16                   1   Personal Auto   Personal L3            Offer2   \n",
       "17                   1   Personal Auto   Personal L2            Offer3   \n",
       "18                   7   Personal Auto   Personal L2            Offer2   \n",
       "19                   3  Corporate Auto  Corporate L2            Offer1   \n",
       "20                   1   Personal Auto   Personal L2            Offer1   \n",
       "21                   1   Personal Auto   Personal L3            Offer4   \n",
       "22                   2   Personal Auto   Personal L3            Offer1   \n",
       "23                   1  Corporate Auto  Corporate L3            Offer1   \n",
       "24                   1  Corporate Auto  Corporate L2            Offer2   \n",
       "25                   3   Personal Auto   Personal L3            Offer2   \n",
       "26                   1   Personal Auto   Personal L3            Offer1   \n",
       "27                   1  Corporate Auto  Corporate L1            Offer1   \n",
       "28                   2   Personal Auto   Personal L3            Offer1   \n",
       "29                   1   Personal Auto   Personal L3            Offer2   \n",
       "\n",
       "    Sales Channel Total Claim Amount  Vehicle Class Vehicle Size  \n",
       "0           Agent         384.811147   Two-Door Car      Medsize  \n",
       "1           Agent        1131.464935  Four-Door Car      Medsize  \n",
       "2           Agent         566.472247   Two-Door Car      Medsize  \n",
       "3     Call Center         529.881344            SUV      Medsize  \n",
       "4           Agent         138.130879  Four-Door Car      Medsize  \n",
       "5             Web         159.383042   Two-Door Car      Medsize  \n",
       "6           Agent         321.600000  Four-Door Car      Medsize  \n",
       "7           Agent         363.029680  Four-Door Car      Medsize  \n",
       "8           Agent         511.200000  Four-Door Car      Medsize  \n",
       "9          Branch         425.527834  Four-Door Car      Medsize  \n",
       "10          Agent         482.400000  Four-Door Car        Small  \n",
       "11          Agent         528.000000            SUV      Medsize  \n",
       "12          Agent         472.029737  Four-Door Car      Medsize  \n",
       "13         Branch         528.000000            SUV      Medsize  \n",
       "14    Call Center         307.139132  Four-Door Car      Medsize  \n",
       "15         Branch          42.920271  Four-Door Car      Medsize  \n",
       "16    Call Center         454.245098   Two-Door Car      Medsize  \n",
       "17    Call Center         647.442031            SUV      Medsize  \n",
       "18         Branch         308.981664  Four-Door Car      Medsize  \n",
       "19    Call Center         484.800000  Four-Door Car        Small  \n",
       "20         Branch         355.200000   Two-Door Car      Medsize  \n",
       "21    Call Center         379.200000  Four-Door Car      Medsize  \n",
       "22          Agent         511.200000  Four-Door Car      Medsize  \n",
       "23         Branch         554.376763  Four-Door Car      Medsize  \n",
       "24         Branch         439.200000  Four-Door Car      Medsize  \n",
       "25    Call Center         389.185006  Four-Door Car        Large  \n",
       "26          Agent         799.200000  Four-Door Car        Small  \n",
       "27         Branch         516.237951            SUV      Medsize  \n",
       "28    Call Center         532.800000  Four-Door Car        Large  \n",
       "29         Branch         384.000000  Four-Door Car        Small  \n",
       "\n",
       "[30 rows x 24 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(30)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Customer', 'State', 'Customer Lifetime Value', 'Response', 'Coverage',\n",
       "       'Education', 'Effective To Date', 'EmploymentStatus', 'Gender',\n",
       "       'Income', 'Location Code', 'Marital Status', 'Monthly Premium Auto',\n",
       "       'Months Since Last Claim', 'Months Since Policy Inception',\n",
       "       'Number of Open Complaints', 'Number of Policies', 'Policy Type',\n",
       "       'Policy', 'Renew Offer Type', 'Sales Channel', 'Total Claim Amount',\n",
       "       'Vehicle Class', 'Vehicle Size'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Response\n",
       "No     7826\n",
       "Yes    1308\n",
       "Name: Customer, dtype: int64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby('Response').count()['Customer']\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualize this in a bar plot\n",
    "ax = df.groupby('Response').count()['Customer'].plot(\n",
    "kind='bar',\n",
    "color='orchid',\n",
    "grid=True,\n",
    "figsize=(10, 7),\n",
    "title='Marketing Engagement'\n",
    ")\n",
    "ax.set_xlabel('Engaged')\n",
    "ax.set_ylabel('Count')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Response\n",
       "No     0.856799\n",
       "Yes    0.143201\n",
       "Name: Customer, dtype: float64"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby('Response').count()['Customer']/df.shape[0]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9134"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Renew Offer Type\n",
       "Offer1    3752\n",
       "Offer2    2926\n",
       "Offer3    1432\n",
       "Offer4    1024\n",
       "Name: Customer, dtype: int64"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    " df.groupby('Renew Offer Type').count()['Customer']\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Renew Offer Type\n",
       "Offer1    0.158316\n",
       "Offer2    0.233766\n",
       "Offer3    0.020950\n",
       "Offer4         NaN\n",
       "Name: Customer, dtype: float64"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "by_offer_type_df = df.loc[\n",
    "df['Response'] == 'Yes', # count only engaged customers\n",
    "].groupby([\n",
    "'Renew Offer Type'# engaged customers grouped by renewal offer type\n",
    "]).count()['Customer'] / df.groupby('Renew Offer Type').count()['Customer']\n",
    "\n",
    "by_offer_type_df\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualize it in a bar plot\n",
    "ax = (by_offer_type_df*100.0).plot(\n",
    "kind='bar',\n",
    "figsize=(7, 7),\n",
    "color='dodgerblue',\n",
    "grid=True\n",
    ")\n",
    "ax.set_ylabel('Engagement Rate (%)')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Renew Offer Type  Vehicle Class\n",
       "Offer1            Four-Door Car    0.070362\n",
       "                  Luxury Car       0.001599\n",
       "                  Luxury SUV       0.004797\n",
       "                  SUV              0.044776\n",
       "                  Sports Car       0.011194\n",
       "                  Two-Door Car     0.025586\n",
       "Offer2            Four-Door Car    0.114833\n",
       "                  Luxury Car       0.002051\n",
       "                  Luxury SUV       0.004101\n",
       "                  SUV              0.041012\n",
       "                  Sports Car       0.016405\n",
       "                  Two-Door Car     0.055366\n",
       "Offer3            Four-Door Car    0.016760\n",
       "                  Two-Door Car     0.004190\n",
       "Name: Customer, dtype: float64"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "by_offer_type_df = df.loc[\n",
    "df['Response'] == 'Yes' # engaged customers\n",
    "].groupby([\n",
    "'Renew Offer Type', 'Vehicle Class' # grouping the data by these two columns\n",
    "]).count()['Customer'] / df.groupby('Renew Offer Type').count()['Customer']\n",
    "\n",
    "by_offer_type_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "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>Vehicle Class</th>\n",
       "      <th>Four-Door Car</th>\n",
       "      <th>Luxury Car</th>\n",
       "      <th>Luxury SUV</th>\n",
       "      <th>SUV</th>\n",
       "      <th>Sports Car</th>\n",
       "      <th>Two-Door Car</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Renew Offer Type</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Offer1</th>\n",
       "      <td>0.070362</td>\n",
       "      <td>0.001599</td>\n",
       "      <td>0.004797</td>\n",
       "      <td>0.044776</td>\n",
       "      <td>0.011194</td>\n",
       "      <td>0.025586</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Offer2</th>\n",
       "      <td>0.114833</td>\n",
       "      <td>0.002051</td>\n",
       "      <td>0.004101</td>\n",
       "      <td>0.041012</td>\n",
       "      <td>0.016405</td>\n",
       "      <td>0.055366</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Offer3</th>\n",
       "      <td>0.016760</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.004190</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Vehicle Class     Four-Door Car  Luxury Car  Luxury SUV       SUV  Sports Car  \\\n",
       "Renew Offer Type                                                                \n",
       "Offer1                 0.070362    0.001599    0.004797  0.044776    0.011194   \n",
       "Offer2                 0.114833    0.002051    0.004101  0.041012    0.016405   \n",
       "Offer3                 0.016760    0.000000    0.000000  0.000000    0.000000   \n",
       "\n",
       "Vehicle Class     Two-Door Car  \n",
       "Renew Offer Type                \n",
       "Offer1                0.025586  \n",
       "Offer2                0.055366  \n",
       "Offer3                0.004190  "
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "by_offer_type_df = by_offer_type_df.unstack().fillna(0)\n",
    "by_offer_type_df\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualize this data in bar plot\n",
    "ax = (by_offer_type_df*100.0).plot(\n",
    "kind='bar',\n",
    "figsize=(10, 7),\n",
    "grid=True\n",
    ")\n",
    "ax.set_ylabel('Engagement Rate (%)')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Sales Channel\n",
       "Agent          0.191544\n",
       "Branch         0.114531\n",
       "Call Center    0.108782\n",
       "Web            0.117736\n",
       "Name: Customer, dtype: float64"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "by_sales_channel_df = df.loc[\n",
    "df['Response'] == 'Yes'\n",
    "].groupby([\n",
    "'Sales Channel'\n",
    "]).count()['Customer']/df.groupby('Sales Channel').count()['Customer']\n",
    "by_sales_channel_df\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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jgH2SvHParvsDm8ddmCRJ0lI016M0rgU2AM8CNk5rvwV49TiLkiRJWqrmepTGBcAFST5SVT+fx5okSZKWrFGuOTskyRlJLk9yVZLvJLlqlC9PclKS65NcPK1tj+77ruh+7j7LZ4/tjrkiybEj/nkkSZIWtFHC2YnAXwOHA08AJrqfo/gAcOSMttcBX6yq/YAvdtu/IMkewJuAJwKHAG+aLcRJkiQtJqOEs5ur6vNVdX1V3Tj1GuXLq+os4KYZzc8GPti9/yDw74d89OnAGVV1U7fo+hlsHfIkSZIWnbluCJhyZpK/Aj4B3D7VWFXn3c1zrqyq67rvuC7JXkOO2Qf43rTta7o2SZKkRW2UcPbE7ufEtLYCnrLzy9kiQ9pq6IHJOmAdwMqVK5mcnBxjWaNZwYq+S9hi2aZlrDi7jXommey7hCbZX4azv2zNvjKcfWU4+8twC6G/bDOcVdWanXzOHyTZuxs12xu4fsgx1wCrp23vC8P/aVbVCcAJABMTE7V69ephh82r9ZvX913CFivOXsGNh480Cz12a5ev7buEJtlfhrO/bM2+Mpx9ZTj7y3ALob+MsnzTyiQnJvl8t31AkhftwDlPBabuvjwW+PSQY74AHJFk9+5GgCO6NkmSpEVtlBsCPsAgGD24274ceNUoX57kZOAcYP8k13Sh7m3A05JcATyt2ybJRJL3A1TVTcBbga93r7d0bZIkSYvaKNec7VlVH0vyeoCq2pzkjlG+vKqOmWXXU4ccuwF48bTtk4CTRjmPJEnSYjHKyNlPkqyguyA/yaHAzWOtSpIkaYkaZeTsNQyuE3tEkq8ADwLav5pOkiRpARrlbs3zkvwGsD+DR1xc5lqbkiRJ47HNcJZkGXAUsKo7/ogkVNVfj7k2SZKkJWeUac1/BG4DLgLuHG85kiRJS9so4Wzfqnrs2CuRJEnSSHdrfj7JEWOvRJIkSSONnJ0LfDLJPYCfM7gpoKrq/mOtTJIkaQkaJZy9HTgMuKiqhi4+LkmSpJ1jlGnNK4CLDWaSJEnjN8rI2XXAZLfw+e1TjT5KQ5IkaecbJZx9p3vdq3tJkiRpTEZZIeAvAJLsWlU/GX9JkiRJS9c2rzlLcliSbwKXdtuPS/LusVcmSZK0BI1yQ8A7gKcDNwJU1QXAr4+zKEmSpKVqlHBGVX1vRtMdY6hFkiRpyRvlhoDvJXkSUEnuBbyCbopTkiRJO9coI2cvAV4G7ANcAxzUbUuSJGknG+VuzRuA/zAPtUiSJC152wxnSd45pPlmYENVfXrnlyRJkrR0jTKtuQuDqcwrutdjgT2AFyV5xxhrkyRJWnJGuSHgkcBTqmozQJL3AKcDTwMuGmNtkiRJS84oI2f7ALtO294VeHBV3cG0tTYlSZK040YZOfsfwPlJJoEweADtf02yK/BPY6xNkiRpyRnlbs0Tk3wOOIRBOHtDVV3b7f6TcRYnSZK01Iy0QgBwG3AdcBPwyCQu3yRJkjQGozxK48XAK4F9gfOBQ4FzgKeMtzRJkqSlZ5SRs1cCTwC+W1VrgMcDPxxrVZIkSUvUKOHstqq6DSDJvavqW8D+4y1LkiRpaRrlbs1rkjwQ+BRwRpIfAddu4zOSJEm6G0a5W/M53ds3JzkTeABw2lirkiRJWqJGuSFgj2mbUysC1HjKkSRJWtpGuebsPAY3AFzOYG3NHwLfSXJekoPHWZwkSdJSM0o4Ow04qqr2rKoVwDOAjwEvBd49zuIkSZKWmlHC2URVfWFqo6pOB369qs4F7j22yiRJkpagUe7WvCnJa4FTuu3nAz9Ksgy4c2yVSZIkLUGjjJz9DoPVAT4FfBp4aNe2DPjt8ZUmSZK09IzyKI0bgD+aZfeVO7ccSZKkpW2UR2k8CvhjYNX046vKtTUlSZJ2slGuOfs48F7g/cAdO3rCJPsDH53W9HDgz6vqHdOOWc1gCvU7XdMnquotO3puSZKk1o0SzjZX1Xt21gmr6jLgIIDupoLvA58ccuiXq+qZO+u8kiRJC8EoNwT8Y5KXJtk7yR5Tr510/qcC366q7+6k75MkSVrQRhk5O7b7+SfT2orBdOSOOho4eZZ9hyW5gMEi639cVZfshPNJkiQ1LVX9LJOZ5F4MgtdjquoHM/bdH7izqjYlOQr426rab5bvWQesA1i5cuXBp5xyyrDD5tUN3NB3CVss27SMO3bb4UsFd4o92bPvEppkfxnO/rI1+8pw9pXh7C/DtdRf1qxZs7GqJma2zxrOkvxpVf2P7v3zqurj0/b916p6w44UlOTZwMuq6ogRjr2awUoFc/a0iYmJ2rBhw46UtVOs37y+7xK2WHH2Cm48/Ma+ywDguOXH9V1Ck+wvw9lftmZfGc6+Mpz9ZbiW+kuSoeFsrmvOjp72/vUz9h25E2o6hlmmNJP8UpJ07w9hUGcb/1YlSZLGaK5rzjLL+2Hb2yXJfYGnAcdNa3sJQFW9F1gL/GGSzcCtwNHV1/yrJEnSPJornNUs74dtb5eq+imwYkbbe6e9Px44fkfOIUmStBDNFc4el+RfGYyS3ad7T7e9y9grkyRJWoJmDWdVtWw+C5EkSdJoD6GVJEnSPDGcSZIkNcRwJkmS1BDDmSRJUkMMZ5IkSQ0xnEmSJDXEcCZJktQQw5kkSVJDDGeSJEkNMZxJkiQ1xHAmSZLUEMOZJElSQwxnkiRJDTGcSZIkNcRwJkmS1BDDmSRJUkMMZ5IkSQ0xnEmSJDXEcCZJktQQw5kkSVJDDGeSJEkNMZxJkiQ1xHAmSZLUEMOZJElSQwxnkiRJDTGcSZIkNcRwJkmS1BDDmSRJUkMMZ5IkSQ0xnEmSJDXEcCZJktQQw5kkSVJDDGeSJEkNMZxJkiQ1xHAmSZLUEMOZJElSQ3oLZ0muTnJRkvOTbBiyP0nemeTKJBcm+dU+6pQkSZpPy3s+/5qqumGWfc8A9uteTwTe0/2UJElatFqe1nw28KEaOBd4YJK9+y5KkiRpnPoMZwWcnmRjknVD9u8DfG/a9jVdmyRJ0qLV57Tmk6vq2iR7AWck+VZVnTVtf4Z8pmY2dMFuHcDKlSuZnJwcS7HbYwUr+i5hi2WblrHi7DbqmWSy7xKaZH8Zzv6yNfvKcPaV4ewvwy2E/tJbOKuqa7uf1yf5JHAIMD2cXQM8ZNr2vsC1Q77nBOAEgImJiVq9evW4Sh7Z+s3r+y5hixVnr+DGw2/suwwA1i5f23cJTbK/DGd/2Zp9ZTj7ynD2l+EWQn/pZVozya5J7jf1HjgCuHjGYacC/7G7a/NQ4Oaqum6eS5UkSZpXfY2crQQ+mWSqho9U1WlJXgJQVe8FPgccBVwJ/BT4/Z5qlSRJmje9hLOqugp43JD29057X8DL5rMuSZKkvrX8KA1JkqQlx3AmSZLUEMOZJElSQwxnkiRJDTGcSZIkNcRwJkmS1BDDmSRJUkMMZ5IkSQ0xnEmSJDXEcCZJktQQw5kkSVJDDGeSJEkNMZxJkiQ1xHAmSZLUEMOZJElSQwxnkiRJDTGcSZIkNcRwJkmS1BDDmSRJUkMMZ5IkSQ0xnEmSJDXEcCZJktQQw5kkSVJDDGeSJEkNMZxJkiQ1xHAmSZLUEMOZJElSQwxnkiRJDTGcSZIkNcRwJkmS1BDDmSRJUkMMZ5IkSQ0xnEmSJDXEcCZJktQQw5kkSVJDDGeSJEkNMZxJkiQ1xHAmSZLUkHkPZ0kekuTMJJcmuSTJK4ccszrJzUnO715/Pt91SpIk9WF5D+fcDPynqjovyf2AjUnOqKpvzjjuy1X1zB7qkyRJ6s28j5xV1XVVdV73/hbgUmCf+a5DkiSpRb1ec5ZkFfB44GtDdh+W5IIkn0/ymHktTJIkqSepqn5OnOwGfAn4y6r6xIx99wfurKpNSY4C/raq9pvle9YB6wBWrlx58CmnnDLmyrftBm7ou4Qtlm1axh273dF3GQDsyZ59l9Ak+8tw9pet2VeGs68MZ38ZrqX+smbNmo1VNTGzvZdwluSewGeAL1TVX49w/NXARFXN2dMmJiZqw4YNO6fIHbB+8/q+S9hixdkruPHwG/suA4Djlh/XdwlNsr8MZ3/Zmn1lOPvKcPaX4VrqL0mGhrM+7tYMcCJw6WzBLMkvdceR5BAGdbbxb1WSJGmM+rhb88nAC4CLkpzftb0BeChAVb0XWAv8YZLNwK3A0dXX/KskSdI8mvdwVlVnA9nGMccDx89PRZIkSe1whQBJkqSGGM4kSZIaYjiTJElqiOFMkiSpIYYzSZKkhhjOJEmSGmI4kyRJaojhTJIkqSGGM0mSpIYYziRJkhpiOJMkSWqI4UySJKkhhjNJkqSGGM4kSZIaYjiTJElqiOFMkiSpIYYzSZKkhhjOJEmSGmI4kyRJaojhTJIkqSGGM0mSpIYYziRJkhpiOJMkSWqI4UySJKkhhjNJkqSGGM4kSZIaYjiTJElqiOFMkiSpIYYzSZKkhhjOJEmSGmI4kyRJaojhTJIkqSGGM0mSpIYYziRJkhpiOJMkSWqI4UySJKkhhjNJkqSGGM4kSZIaYjiTJElqSC/hLMmRSS5LcmWS1w3Zf+8kH+32fy3JqvmvUpIkaf7NezhLsgz4X8AzgAOAY5IcMOOwFwE/qqpHAn8D/Pf5rVKSJKkffYycHQJcWVVXVdXPgFOAZ8845tnAB7v3/wA8NUnmsUZJkqRepKrm94TJWuDIqnpxt/0C4IlV9fJpx1zcHXNNt/3t7pgbhnzfOmBdt7k/cNmY/wgLzZ7AVv/cpFnYXzQq+4q2h/1luIdV1YNmNi7voZBhI2AzE+Ioxwwaq04ATtjRoharJBuqaqLvOrQw2F80KvuKtof9Zfv0Ma15DfCQadv7AtfOdkyS5cADgJvmpTpJkqQe9RHOvg7sl+SXk9wLOBo4dcYxpwLHdu/XAv+35nv+VZIkqQfzPq1ZVZuTvBz4ArAMOKmqLknyFmBDVZ0KnAh8OMmVDEbMjp7vOhcRp3y1PewvGpV9RdvD/rId5v2GAEmSJM3OFQIkSZIaYjiTJElqiOFMkjSnJPdI8tt91yEtFYazRSbJ80Zpk6RRVdWdwMu3eaCkncIbAhaZJOdV1a9uq02akuTewHOBVUy7g7uq3tJXTWpPkj8DbgU+Cvxkqr2qfAaltpJkF+ClwOEMHiJ/NvCeqrqt18IWCMPZIpHkGcBRwG8z+OU55f7AAVV1SC+FqXlJTgNuBjYCd0y1V9XbeytKzUnynSHNVVUPn/di1LwkHwNuAf5313QMsHtVOZMzgj6Wb9J4XAtsAJ7F4D+yU24BXt1LRVoo9q2qI/suQm2rql/uuwYtKPtX1eOmbZ+Z5ILeqllgDGeLRFVdAFyQ5CNV9fO+69GC8tUk/6aqLuq7ELUryX2B1wAPrap1SfZj8B/gz/Rcmtr0jSSHVtW5AEmeCHyl55oWDKc1F5kkTwbeDDyMQfgOTj1oiCQXMbgWZDmwH3AVcDt39ZnH9lieGpPkowxG5f9jVR2Y5D7AOVV1UM+lqSHTfq/cE9gf+H/d9sOAb1bVgT2Wt2A4crb4nMhgGvMXrh+Shnhm3wVoQXlEVT0/yTEAVXVrkvRdlJrj75WdwHC2+NxcVZ/vuwi1r6q+C5DkUOCSqrql274fcADw3R7LU3t+1o2WFUCSRzAYaZW2mPq9ApDkcGC/qvq7JHsC9+uvsoXFac1FJsnbGCwo/wmm/eKsqvN6K0pNS/IN4Fer+2WQ5B7ABh+/oumSHAG8kUFwPx14MvD7VXVmr4WpSUneBEwwuC7xUUkeDHy8qp7cc2kLgiNni88Tu58T09oKeEoPtWhhSE37v7SqujOJvxv0C6rq9CQbgUMZXJf4yqq6oeey1K7nAI8HzgOoqmu7UXmNwF/Ai0xVrem7Bi04VyV5BfCebvulDG4OkLZI8sWqeirw2SFt0kw/q6pKMjUiv2vfBS0kLt+0yCRZmeTEJJ/vtg9I8qK+61LTXgI8Cfg+cA2D0dd1vVakZiTZJckewJ5Jdk+yR/daBTy43+rUsI8lWQ88MMkfAP8EvK/nmhYMrzlbZLpQ9nfAG6vqcd301Deq6t/0XJqkBSjJK4FXMQhi32cwpQnwr8D7qur4vmpTe5K8isHzzL4BrAGOYNBnvlBVZ/RZ20JiOFtkklTFqqkAAAlySURBVHy9qp6Q5BtV9fiu7XyfRaTZJHkQ8AdsvbbmC/uqSe1J8kdV9a6+61DbkvxPBiPxjwYuBL7KIKyd4zqso/Oas8XnJ0lWcNft7ocyWDdRms2ngS8zmHbw2XgaqqreleRJbB3iP9RbUWpOVf0xQJJ7Mbgx7UnAC4H3JflxVR3QZ30LheFs8XkNcCrwiCRfAR4ErO23JDXuvlX12r6LUNuSfBh4BHA+d4X4AgxnGuY+wP2BB3SvawGXiBuR05qLUHed2f4M5vkvc61NzSXJfwG+WlWf67sWtSvJpcAB5X80NIckJwCPAW4BvgacC5xbVT/qtbAFxpGzRSbJb81oelSSm4GLqur6PmpS814JvCHJ7cDPuWttzfv3W5YaczHwS8B1fReipj0UuDdwBXfdAf7jXitagBw5W2SSfBY4DJh6avdqBv/n8ijgLVX14Z5Kk7SAJTkTOAj4Z35x9ZFn9VaUmtStufoYBtebPQk4ELiJwU0Bb+qztoXCkbPF507gV6rqBzB47hmDh4s+ETgLMJxpK0l2B/YDdplqq6qz+qtIDXpz3wVoYeimvi9O8mMGN6TdzGBB9EMAw9kIDGeLz6qpYNa5HnhUVd2UxGvPtJUkL2Ywtbkvg4u9DwXOwSW/NE1VfSnJwxgsZP1PSe7LYB1faYtutZEnMVh79ed0j9EATsIbAkZmOFt8vpzkM8DHu+3nAmd1S2c4769hXgk8gcFFu2uSPBr4i55rUmO6p7yvA/ZgcNfmPsB7AZdv0nSrgH8AXl1VXp94NxnOFp+XAb8FHN5t/zOwd1X9hMHTmqWZbquq25KQ5N5V9a0k+/ddlJrzMgbTUl8DqKorkuzVb0lqTVW9pu8aFgPX1lxkurn+bzMYTn4Og/+rvbTXotS6a5I8EPgUcEaSTzN4JpE03e1V9bOpje6RPd5RJo2BI2eLRJJHAUcDxwA3Ah9lcDeuo2WaU1U9p3v75u6OvAcAp/VYktr0pSRvAO6T5GnAS4F/7LkmaVHyURqLRJI7GSzB86KqurJru6qqHt5vZWpZknsAF1bVgX3XorZ1feVFTFvIGni/D6WVdj6nNReP5wL/ApyZ5H1JnsrgF6g0q6q6E7ggyUP7rkVtSvKgJAdU1Z1V9b6qel5VrWVwB96efdcnLUaGs0Wiqj5ZVc8HHg1MAq8GViZ5T5Ijei1OrdsbuCTJF5OcOvXquyg1410M1uidaR/gb+e5FmlJcFpzEUuyB/A84PlV5TOrNFSS3xjWXlVfmu9a1J4kl1TVY2bZd7FT4tLOZziTtEWSPYEbvY5IU5JcXlWPmmXfZVXlY1ekncxpTWmJSnJokskkn0jy+CQXM1jc+gdJjuy7PjXjiiRHzWxM8gzgqh7qkRY9R86kJSrJBuANDB6dcQLwjKo6t1sh4OSqenyvBaoJ3WN6PgN8FdjYNU8AhwHPrKrL+6pNWqwMZ9ISleT8qjqoe39pVf3KtH3fMJxpSpJ7A78DTF1fdgnwkaq6rb+qpMXLh9BKS9ed097fOmOf/9emLarqduDv+q5DWiocOZOWqCR3AD9h8Dy8+wA/ndoF7FJV9+yrNklaygxnkiRJDfFuTUmSpIZ4zZkkaVZJLmL4NYgBqqoeO88lSYue05qSpFkledhc+6vqu/NVi7RUGM4kSZIa4rSmJGlWSW5h7mnN+89zSdKi58iZJElSQxw5kySNLMlewC5T21X1/3osR1qUfJSGJGmbkjwryRXAd4AvAVcDn++1KGmRMpxJkkbxVuBQ4PKq+mXgqcBX+i1JWpwMZ5KkUfy8qm4E7pHkHlV1JnBQ30VJi5HXnEmSRvHjJLsBZwF/n+R6YHPPNUmLkndrSpK2KcmuwK0MZlz+A/AA4O+70TRJO5HhTJI0qySPBFZW1VdmtP868P2q+nY/lUmLl9ecSZLm8g7gliHtP+32SdrJDGeSpLmsqqoLZzZW1QZg1fyXIy1+hjNJ0lx2mWPffeatCmkJMZxJkuby9SR/MLMxyYuAjT3UIy163hAgSZpVkpXAJ4GfcVcYmwDuBTynqv6lr9qkxcpwJknapiRrgAO7zUuq6v/2WY+0mBnOJEmSGuI1Z5IkSQ0xnEmSJDXEcCapSUnemOSSJBcmOT/JE7dx/AeSrN0J5z0kyVlJLkvyrSTvT3LfJG9O8sc7+v07UNemvs4taX658Lmk5iQ5DHgm8KtVdXuSPRncHTju864EPg4cXVXnJAnwXOB+4z63JE1x5ExSi/YGbqiq2wGq6oaquhYgyZ8n+XqSi5Oc0AWoX5Dk4CRfSrIxyReS7N21vyLJN7vRuFOGnPdlwAer6pzuvFVV/1BVP+j2H5BkMslVSV4x7Xyf6s51SZJ109o3JfnLJBckObcLf1OjfO9M8tXuu9ZO+8yfdH++C5P8xY7+g5S08BjOJLXodOAhSS5P8u4kvzFt3/FV9YSqOpDBE+qfOf2DSe4JvAtYW1UHAycBf9ntfh3w+Kp6LPCSIec9kLkfrPpo4OnAIcCbunMBvLA71wTwiiQruvZdgXOr6nHAWcD0h7nuDRze1f+2rvYjgP267z8IOLhbYFzSEmI4k9ScqtoEHAysA34IfDTJ73W71yT5WpKLgKcAj5nx8f0ZhKwzkpwP/Gdg327fhcDfJ/ldYPPdKO2zVXV7Vd0AXA+s7NpfkeQC4FzgIQwCFgwe3PqZ7v1GfnEtyk9V1Z1V9c1p33NE9/oGcB6DMLgfkpYUrzmT1KSqugOYBCa7IHZsNxX5bmCiqr6X5M1svfZjGDwk9bAhX/ubwK8DzwL+LMljqmp6SLuEQSj89Cxl3T7t/R3A8iSrgX8LHFZVP00yOa2mn9ddD5O8g1/8nTv9uzLt53+rqvWznF/SEuDImaTmJNk/yfQRo4OA73JX6LkhyW7AsLszLwMe1N1UQJJ7JnlMknsAD6mqM4E/BR4I7Dbjs8czCIFb7gxN8rtJfmmOch8A/KgLZo8GDh39T7qVLwAv7P5sJNknyV478H2SFiBHziS1aDfgXUkeyGD68UpgXVX9OMn7gIuAq4Gvz/xgVf2su8D+nUkewOD33DuAy4H/3bUF+Juq+vGMz/4gydHA/+xC0Z0MrhX7xBy1nga8JMmFDILhuXf3D11Vpyf5FeCc7j6HTcDvMphClbREuHyTJElSQ5zWlCRJaojhTJIkqSGGM0mSpIYYziRJkhpiOJMkSWqI4UySJKkhhjNJkqSGGM4kSZIa8v8BVktB3HNlaDkAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 720x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = (by_sales_channel_df*100.0).plot(\n",
    "kind='bar',\n",
    "figsize=(10, 7),\n",
    "color='palegreen',\n",
    "grid=True\n",
    ")\n",
    "ax.set_ylabel('Engagement Rate (%)')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Sales Channel  Vehicle Size\n",
       "Agent          Large           0.020708\n",
       "               Medsize         0.144953\n",
       "               Small           0.025884\n",
       "Branch         Large           0.021036\n",
       "               Medsize         0.074795\n",
       "               Small           0.018699\n",
       "Call Center    Large           0.013598\n",
       "               Medsize         0.067989\n",
       "               Small           0.027195\n",
       "Web            Large           0.013585\n",
       "               Medsize         0.095094\n",
       "               Small           0.009057\n",
       "Name: Customer, dtype: float64"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "by_sales_channel_df = df.loc[\n",
    "df['Response'] == 'Yes'\n",
    "].groupby([\n",
    "'Sales Channel', 'Vehicle Size'\n",
    "]).count()['Customer'] / df.groupby('Sales Channel').count()['Customer']\n",
    "by_sales_channel_df\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "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>Vehicle Size</th>\n",
       "      <th>Large</th>\n",
       "      <th>Medsize</th>\n",
       "      <th>Small</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sales Channel</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Agent</th>\n",
       "      <td>0.020708</td>\n",
       "      <td>0.144953</td>\n",
       "      <td>0.025884</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Branch</th>\n",
       "      <td>0.021036</td>\n",
       "      <td>0.074795</td>\n",
       "      <td>0.018699</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Call Center</th>\n",
       "      <td>0.013598</td>\n",
       "      <td>0.067989</td>\n",
       "      <td>0.027195</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Web</th>\n",
       "      <td>0.013585</td>\n",
       "      <td>0.095094</td>\n",
       "      <td>0.009057</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Vehicle Size      Large   Medsize     Small\n",
       "Sales Channel                              \n",
       "Agent          0.020708  0.144953  0.025884\n",
       "Branch         0.021036  0.074795  0.018699\n",
       "Call Center    0.013598  0.067989  0.027195\n",
       "Web            0.013585  0.095094  0.009057"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Unstack the data into a more visible format\n",
    "by_sales_channel_df = by_sales_channel_df.unstack().fillna(0)\n",
    "by_sales_channel_df\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = (by_sales_channel_df*100.0).plot(\n",
    "kind='bar',\n",
    "figsize=(10, 7),grid=True)\n",
    "ax.set_ylabel('Engagement Rate (%)')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Months Since Policy Inception\n",
       "0     14.457831\n",
       "1     14.117647\n",
       "2     20.224719\n",
       "3     26.315789\n",
       "4     19.780220\n",
       "5      6.896552\n",
       "6      0.000000\n",
       "7      7.594937\n",
       "8      7.407407\n",
       "9     18.750000\n",
       "10    15.789474\n",
       "11    17.307692\n",
       "12     6.000000\n",
       "13    14.814815\n",
       "14     0.000000\n",
       "15    22.018349\n",
       "16     0.000000\n",
       "17    11.881188\n",
       "18    13.333333\n",
       "19    16.981132\n",
       "20    11.650485\n",
       "21    11.428571\n",
       "22    12.903226\n",
       "23    20.454545\n",
       "24    21.951220\n",
       "25    13.483146\n",
       "26    15.000000\n",
       "27    12.371134\n",
       "28    17.475728\n",
       "29    12.244898\n",
       "        ...    \n",
       "70    23.529412\n",
       "71    12.000000\n",
       "72    23.762376\n",
       "73     6.818182\n",
       "74    19.780220\n",
       "75     6.122449\n",
       "76     6.976744\n",
       "77    18.947368\n",
       "78     7.317073\n",
       "79    11.881188\n",
       "80    16.438356\n",
       "81    15.789474\n",
       "82     0.000000\n",
       "83    24.000000\n",
       "84     6.000000\n",
       "85    14.117647\n",
       "86     0.000000\n",
       "87     7.894737\n",
       "88     7.894737\n",
       "89    18.556701\n",
       "90    14.285714\n",
       "91     8.000000\n",
       "92    16.216216\n",
       "93    26.666667\n",
       "94    25.000000\n",
       "95    15.584416\n",
       "96    17.910448\n",
       "97     0.000000\n",
       "98     0.000000\n",
       "99     7.692308\n",
       "Name: Response, Length: 100, dtype: float64"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "by_months_since_inception_df = df.loc[\n",
    "df['Response'] == 'Yes'\n",
    "].groupby(\n",
    "by='Months Since Policy Inception'\n",
    ")['Response'].count() / df.groupby(\n",
    "by='Months Since Policy Inception'\n",
    ")['Response'].count() * 100.0\n",
    "by_months_since_inception_df.fillna(0)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    " ax = by_months_since_inception_df.fillna(0).plot(\n",
    "figsize=(10, 7),\n",
    "title='Engagement Rates by Months Since Inception',\n",
    "grid=True,\n",
    "color='skyblue'\n",
    ")\n",
    "ax.set_xlabel('Months Since Policy Inception')\n",
    "ax.set_ylabel('Engagement Rate (%)')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count     9134.000000\n",
       "mean      8004.940475\n",
       "std       6870.967608\n",
       "min       1898.007675\n",
       "25%       3994.251794\n",
       "50%       5780.182197\n",
       "75%       8962.167041\n",
       "max      83325.381190\n",
       "Name: Customer Lifetime Value, dtype: float64"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Customer Lifetime Value'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['CLV Segment'] = df['Customer Lifetime Value'].apply(\n",
    "lambda x: 'High' if x > df['Customer Lifetime Value'].median() else 'Low')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    9134.000000\n",
       "mean       48.064594\n",
       "std        27.905991\n",
       "min         0.000000\n",
       "25%        24.000000\n",
       "50%        48.000000\n",
       "75%        71.000000\n",
       "max        99.000000\n",
       "Name: Months Since Policy Inception, dtype: float64"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Months Since Policy Inception'].describe()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Policy Age Segment'] = df['Months Since Policy Inception'].apply(\n",
    "lambda x: 'High' if x > df['Months Since Policy Inception'].median() else 'Low'\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "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>Customer</th>\n",
       "      <th>State</th>\n",
       "      <th>Customer Lifetime Value</th>\n",
       "      <th>Response</th>\n",
       "      <th>Coverage</th>\n",
       "      <th>Education</th>\n",
       "      <th>Effective To Date</th>\n",
       "      <th>EmploymentStatus</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Income</th>\n",
       "      <th>...</th>\n",
       "      <th>Number of Policies</th>\n",
       "      <th>Policy Type</th>\n",
       "      <th>Policy</th>\n",
       "      <th>Renew Offer Type</th>\n",
       "      <th>Sales Channel</th>\n",
       "      <th>Total Claim Amount</th>\n",
       "      <th>Vehicle Class</th>\n",
       "      <th>Vehicle Size</th>\n",
       "      <th>CLV Segment</th>\n",
       "      <th>Policy Age Segment</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>BU79786</td>\n",
       "      <td>Washington</td>\n",
       "      <td>2763.519279</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>2/24/11</td>\n",
       "      <td>Employed</td>\n",
       "      <td>F</td>\n",
       "      <td>56274</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Corporate L3</td>\n",
       "      <td>Offer1</td>\n",
       "      <td>Agent</td>\n",
       "      <td>384.811147</td>\n",
       "      <td>Two-Door Car</td>\n",
       "      <td>Medsize</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>QZ44356</td>\n",
       "      <td>Arizona</td>\n",
       "      <td>6979.535903</td>\n",
       "      <td>No</td>\n",
       "      <td>Extended</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>1/31/11</td>\n",
       "      <td>Unemployed</td>\n",
       "      <td>F</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>8</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Personal L3</td>\n",
       "      <td>Offer3</td>\n",
       "      <td>Agent</td>\n",
       "      <td>1131.464935</td>\n",
       "      <td>Four-Door Car</td>\n",
       "      <td>Medsize</td>\n",
       "      <td>High</td>\n",
       "      <td>Low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AI49188</td>\n",
       "      <td>Nevada</td>\n",
       "      <td>12887.431650</td>\n",
       "      <td>No</td>\n",
       "      <td>Premium</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>2/19/11</td>\n",
       "      <td>Employed</td>\n",
       "      <td>F</td>\n",
       "      <td>48767</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Personal L3</td>\n",
       "      <td>Offer1</td>\n",
       "      <td>Agent</td>\n",
       "      <td>566.472247</td>\n",
       "      <td>Two-Door Car</td>\n",
       "      <td>Medsize</td>\n",
       "      <td>High</td>\n",
       "      <td>Low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>WW63253</td>\n",
       "      <td>California</td>\n",
       "      <td>7645.861827</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>1/20/11</td>\n",
       "      <td>Unemployed</td>\n",
       "      <td>M</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>7</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Corporate L2</td>\n",
       "      <td>Offer1</td>\n",
       "      <td>Call Center</td>\n",
       "      <td>529.881344</td>\n",
       "      <td>SUV</td>\n",
       "      <td>Medsize</td>\n",
       "      <td>High</td>\n",
       "      <td>High</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>HB64268</td>\n",
       "      <td>Washington</td>\n",
       "      <td>2813.692575</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>2/3/11</td>\n",
       "      <td>Employed</td>\n",
       "      <td>M</td>\n",
       "      <td>43836</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Personal L1</td>\n",
       "      <td>Offer1</td>\n",
       "      <td>Agent</td>\n",
       "      <td>138.130879</td>\n",
       "      <td>Four-Door Car</td>\n",
       "      <td>Medsize</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  Customer       State  Customer Lifetime Value Response  Coverage Education  \\\n",
       "0  BU79786  Washington              2763.519279       No     Basic  Bachelor   \n",
       "1  QZ44356     Arizona              6979.535903       No  Extended  Bachelor   \n",
       "2  AI49188      Nevada             12887.431650       No   Premium  Bachelor   \n",
       "3  WW63253  California              7645.861827       No     Basic  Bachelor   \n",
       "4  HB64268  Washington              2813.692575       No     Basic  Bachelor   \n",
       "\n",
       "  Effective To Date EmploymentStatus Gender  Income  ... Number of Policies  \\\n",
       "0           2/24/11         Employed      F   56274  ...                  1   \n",
       "1           1/31/11       Unemployed      F       0  ...                  8   \n",
       "2           2/19/11         Employed      F   48767  ...                  2   \n",
       "3           1/20/11       Unemployed      M       0  ...                  7   \n",
       "4            2/3/11         Employed      M   43836  ...                  1   \n",
       "\n",
       "      Policy Type        Policy  Renew Offer Type  Sales Channel  \\\n",
       "0  Corporate Auto  Corporate L3            Offer1          Agent   \n",
       "1   Personal Auto   Personal L3            Offer3          Agent   \n",
       "2   Personal Auto   Personal L3            Offer1          Agent   \n",
       "3  Corporate Auto  Corporate L2            Offer1    Call Center   \n",
       "4   Personal Auto   Personal L1            Offer1          Agent   \n",
       "\n",
       "   Total Claim Amount  Vehicle Class Vehicle Size CLV Segment  \\\n",
       "0          384.811147   Two-Door Car      Medsize         Low   \n",
       "1         1131.464935  Four-Door Car      Medsize        High   \n",
       "2          566.472247   Two-Door Car      Medsize        High   \n",
       "3          529.881344            SUV      Medsize        High   \n",
       "4          138.130879  Four-Door Car      Medsize         Low   \n",
       "\n",
       "  Policy Age Segment  \n",
       "0                Low  \n",
       "1                Low  \n",
       "2                Low  \n",
       "3               High  \n",
       "4                Low  \n",
       "\n",
       "[5 rows x 26 columns]"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualize these segments\n",
    "ax = df.loc[\n",
    "(df['CLV Segment'] == 'High') & (df['Policy Age Segment'] == 'High')\n",
    "].plot.scatter(\n",
    "x='Months Since Policy Inception',\n",
    "y='Customer Lifetime Value',\n",
    "logy=True,\n",
    "color='red'\n",
    ")\n",
    "df.loc[\n",
    "(df['CLV Segment'] == 'Low') & (df['Policy Age Segment'] == 'High')\n",
    "].plot.scatter(\n",
    "ax=ax,\n",
    "x='Months Since Policy Inception',\n",
    "y='Customer Lifetime Value',\n",
    "logy=True,\n",
    "color='blue'\n",
    ")\n",
    "df.loc[\n",
    "(df['CLV Segment'] == 'High') & (df['Policy Age Segment'] == 'Low')\n",
    "].plot.scatter(\n",
    "ax=ax,\n",
    "x='Months Since Policy Inception',\n",
    "y='Customer Lifetime Value',\n",
    "logy=True,\n",
    "color='orange'\n",
    ")\n",
    "df.loc[\n",
    "(df['CLV Segment'] == 'Low') & (df['Policy Age Segment'] == 'Low')\n",
    "].plot.scatter(\n",
    "ax=ax,\n",
    "x='Months Since Policy Inception',\n",
    "y='Customer Lifetime Value',\n",
    "logy=True,\n",
    "color='green',\n",
    "grid=True,\n",
    "figsize=(10, 7)\n",
    ")\n",
    "ax.set_ylabel('CLV (in log scale)')\n",
    "ax.set_xlabel('Months Since Policy Inception')\n",
    "ax.set_title('Segments by CLV and Policy Age')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "CLV Segment  Policy Age Segment\n",
       "High         High                  0.138728\n",
       "             Low                   0.132067\n",
       "Low          High                  0.162450\n",
       "             Low                   0.139957\n",
       "Name: Customer, dtype: float64"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "engagement_rates_by_segment_df = df.loc[\n",
    "df['Response'] == 'Yes'\n",
    "].groupby([\n",
    "'CLV Segment', 'Policy Age Segment'\n",
    "]). count()['Customer'] / df.groupby([\n",
    "'CLV Segment', 'Policy Age Segment'\n",
    "]).count()['Customer']\n",
    "engagement_rates_by_segment_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Look at these differences in a chart\n",
    "ax = (engagement_rates_by_segment_df.unstack()*100.0).plot(\n",
    "kind='bar',\n",
    "figsize=(10, 7),\n",
    "grid=True\n",
    ")\n",
    "ax.set_ylabel('Engagement Rate (%)')\n",
    "ax.set_title('Engagement Rates by Customer Segments')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Gender\n",
       "F    4658\n",
       "M    4476\n",
       "Name: Customer, dtype: int64"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "df.groupby('Gender').count()['Customer']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Renew Offer Type\n",
       "Offer1   NaN\n",
       "Offer2   NaN\n",
       "Offer3   NaN\n",
       "Offer4   NaN\n",
       "Name: Customer, dtype: float64"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "by_offer_type_df = df.loc[\n",
    "df['Gender'] == 'No', # count only engaged customers\n",
    "].groupby([\n",
    "'Renew Offer Type'# engaged customers grouped by renewal offer type\n",
    "]).count()['Customer'] / df.groupby('Renew Offer Type').count()['Customer']\n",
    "\n",
    "by_offer_type_df\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}