Customer_Churn_Rate_Analysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "a532b4d9",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import numpy as np\n",
    "from matplotlib import pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "3a194fe9",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import csv file and read the dataframe. This dataset took from online\n",
    "data = pd.read_csv(r'customerchurn.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "2e39a393",
   "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>Customer ID</th>\n",
       "      <th>Churn Label</th>\n",
       "      <th>Account Length (in months)</th>\n",
       "      <th>Local Calls</th>\n",
       "      <th>Local Mins</th>\n",
       "      <th>...</th>\n",
       "      <th>Payment Method</th>\n",
       "      <th>Monthly Charge</th>\n",
       "      <th>Total Charges</th>\n",
       "      <th>Churn Category</th>\n",
       "      <th>Churn Reason</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4444-BZPU</td>\n",
       "      <td>No</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>8.0</td>\n",
       "      <td>...</td>\n",
       "      <td>Direct Debit</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5676-PTZX</td>\n",
       "      <td>No</td>\n",
       "      <td>33</td>\n",
       "      <td>179</td>\n",
       "      <td>431.3</td>\n",
       "      <td>...</td>\n",
       "      <td>Paper Check</td>\n",
       "      <td>21</td>\n",
       "      <td>703</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8532-ZEKQ</td>\n",
       "      <td>No</td>\n",
       "      <td>44</td>\n",
       "      <td>82</td>\n",
       "      <td>217.6</td>\n",
       "      <td>...</td>\n",
       "      <td>Direct Debit</td>\n",
       "      <td>23</td>\n",
       "      <td>1014</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1314-SMPJ</td>\n",
       "      <td>No</td>\n",
       "      <td>10</td>\n",
       "      <td>47</td>\n",
       "      <td>111.6</td>\n",
       "      <td>...</td>\n",
       "      <td>Paper Check</td>\n",
       "      <td>17</td>\n",
       "      <td>177</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2956-TXCJ</td>\n",
       "      <td>No</td>\n",
       "      <td>62</td>\n",
       "      <td>184</td>\n",
       "      <td>621.2</td>\n",
       "      <td>...</td>\n",
       "      <td>Direct Debit</td>\n",
       "      <td>28</td>\n",
       "      <td>1720</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <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>6682</th>\n",
       "      <td>2940-QHVU</td>\n",
       "      <td>Yes</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>16.8</td>\n",
       "      <td>...</td>\n",
       "      <td>Paper Check</td>\n",
       "      <td>19</td>\n",
       "      <td>52</td>\n",
       "      <td>Competitor</td>\n",
       "      <td>Competitor offered higher download speeds</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6683</th>\n",
       "      <td>3033-TMYG</td>\n",
       "      <td>Yes</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>15.0</td>\n",
       "      <td>...</td>\n",
       "      <td>Direct Debit</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "      <td>Competitor</td>\n",
       "      <td>Competitor offered higher download speeds</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6684</th>\n",
       "      <td>7029-XDVM</td>\n",
       "      <td>Yes</td>\n",
       "      <td>6</td>\n",
       "      <td>20</td>\n",
       "      <td>46.9</td>\n",
       "      <td>...</td>\n",
       "      <td>Paper Check</td>\n",
       "      <td>18</td>\n",
       "      <td>108</td>\n",
       "      <td>Competitor</td>\n",
       "      <td>Competitor made better offer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6685</th>\n",
       "      <td>6614-NAJG</td>\n",
       "      <td>Yes</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>15.4</td>\n",
       "      <td>...</td>\n",
       "      <td>Credit Card</td>\n",
       "      <td>15</td>\n",
       "      <td>46</td>\n",
       "      <td>Attitude</td>\n",
       "      <td>Attitude of support person</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6686</th>\n",
       "      <td>5104-AGDX</td>\n",
       "      <td>Yes</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>15.0</td>\n",
       "      <td>...</td>\n",
       "      <td>Direct Debit</td>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "      <td>Competitor</td>\n",
       "      <td>Competitor made better offer</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6687 rows × 29 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Customer ID Churn Label  Account Length (in months)  Local Calls  \\\n",
       "0      4444-BZPU          No                           1            3   \n",
       "1      5676-PTZX          No                          33          179   \n",
       "2      8532-ZEKQ          No                          44           82   \n",
       "3      1314-SMPJ          No                          10           47   \n",
       "4      2956-TXCJ          No                          62          184   \n",
       "...          ...         ...                         ...          ...   \n",
       "6682   2940-QHVU         Yes                           3            6   \n",
       "6683   3033-TMYG         Yes                           1            7   \n",
       "6684   7029-XDVM         Yes                           6           20   \n",
       "6685   6614-NAJG         Yes                           3            6   \n",
       "6686   5104-AGDX         Yes                           1            7   \n",
       "\n",
       "      Local Mins  ...  Payment Method  Monthly Charge Total Charges  \\\n",
       "0            8.0  ...    Direct Debit              10            10   \n",
       "1          431.3  ...     Paper Check              21           703   \n",
       "2          217.6  ...    Direct Debit              23          1014   \n",
       "3          111.6  ...     Paper Check              17           177   \n",
       "4          621.2  ...    Direct Debit              28          1720   \n",
       "...          ...  ...             ...             ...           ...   \n",
       "6682        16.8  ...     Paper Check              19            52   \n",
       "6683        15.0  ...    Direct Debit              20            20   \n",
       "6684        46.9  ...     Paper Check              18           108   \n",
       "6685        15.4  ...     Credit Card              15            46   \n",
       "6686        15.0  ...    Direct Debit               9             9   \n",
       "\n",
       "     Churn Category                               Churn Reason  \n",
       "0               NaN                                        NaN  \n",
       "1               NaN                                        NaN  \n",
       "2               NaN                                        NaN  \n",
       "3               NaN                                        NaN  \n",
       "4               NaN                                        NaN  \n",
       "...             ...                                        ...  \n",
       "6682     Competitor  Competitor offered higher download speeds  \n",
       "6683     Competitor  Competitor offered higher download speeds  \n",
       "6684     Competitor               Competitor made better offer  \n",
       "6685       Attitude                 Attitude of support person  \n",
       "6686     Competitor               Competitor made better offer  \n",
       "\n",
       "[6687 rows x 29 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "31865de7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(6687, 29)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "a48d01b6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6687"
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     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "len(data)"
   ]
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  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "955b3d68",
   "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>Customer ID</th>\n",
       "      <th>Churn Label</th>\n",
       "      <th>Account Length (in months)</th>\n",
       "      <th>Local Calls</th>\n",
       "      <th>Local Mins</th>\n",
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       "      <th>Intl Active</th>\n",
       "      <th>Intl Plan</th>\n",
       "      <th>Extra International Charges</th>\n",
       "      <th>Customer Service Calls</th>\n",
       "      <th>Avg Monthly GB Download</th>\n",
       "      <th>Unlimited Data Plan</th>\n",
       "      <th>Extra Data Charges</th>\n",
       "      <th>State</th>\n",
       "      <th>Phone Number</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Age</th>\n",
       "      <th>Under 30</th>\n",
       "      <th>Senior</th>\n",
       "      <th>Group</th>\n",
       "      <th>Number of Customers in Group</th>\n",
       "      <th>Device Protection &amp; Online Backup</th>\n",
       "      <th>Contract Type</th>\n",
       "      <th>Payment Method</th>\n",
       "      <th>Monthly Charge</th>\n",
       "      <th>Total Charges</th>\n",
       "      <th>Churn Category</th>\n",
       "      <th>Churn Reason</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4444-BZPU</td>\n",
       "      <td>No</td>\n",
       "      <td>1</td>\n",
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       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>3</td>\n",
       "      <td>Yes</td>\n",
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       "      <td>KS</td>\n",
       "      <td>382-4657</td>\n",
       "      <td>Female</td>\n",
       "      <td>35</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-Month</td>\n",
       "      <td>Direct Debit</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5676-PTZX</td>\n",
       "      <td>No</td>\n",
       "      <td>33</td>\n",
       "      <td>179</td>\n",
       "      <td>431.3</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>371-7191</td>\n",
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       "      <td>49</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>One Year</td>\n",
       "      <td>Paper Check</td>\n",
       "      <td>21</td>\n",
       "      <td>703</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8532-ZEKQ</td>\n",
       "      <td>No</td>\n",
       "      <td>44</td>\n",
       "      <td>82</td>\n",
       "      <td>217.6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>No</td>\n",
       "      <td>yes</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Yes</td>\n",
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       "      <td>375-9999</td>\n",
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       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>One Year</td>\n",
       "      <td>Direct Debit</td>\n",
       "      <td>23</td>\n",
       "      <td>1014</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1314-SMPJ</td>\n",
       "      <td>No</td>\n",
       "      <td>10</td>\n",
       "      <td>47</td>\n",
       "      <td>111.6</td>\n",
       "      <td>60.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>yes</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>0</td>\n",
       "      <td>MO</td>\n",
       "      <td>329-9001</td>\n",
       "      <td>Female</td>\n",
       "      <td>41</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
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       "      <td>No</td>\n",
       "      <td>Month-to-Month</td>\n",
       "      <td>Paper Check</td>\n",
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       "      <td>177</td>\n",
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       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
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       "      <td>184</td>\n",
       "      <td>621.2</td>\n",
       "      <td>310.0</td>\n",
       "      <td>694.4</td>\n",
       "      <td>Yes</td>\n",
       "      <td>yes</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Yes</td>\n",
       "      <td>0</td>\n",
       "      <td>WV</td>\n",
       "      <td>330-8173</td>\n",
       "      <td>Male</td>\n",
       "      <td>51</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>One Year</td>\n",
       "      <td>Direct Debit</td>\n",
       "      <td>28</td>\n",
       "      <td>1720</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "  Customer ID Churn Label  Account Length (in months)  Local Calls  \\\n",
       "0   4444-BZPU          No                           1            3   \n",
       "1   5676-PTZX          No                          33          179   \n",
       "2   8532-ZEKQ          No                          44           82   \n",
       "3   1314-SMPJ          No                          10           47   \n",
       "4   2956-TXCJ          No                          62          184   \n",
       "\n",
       "   Local Mins  Intl Calls  Intl Mins Intl Active Intl Plan  \\\n",
       "0         8.0         0.0        0.0          No        no   \n",
       "1       431.3         0.0        0.0          No        no   \n",
       "2       217.6         0.0        0.0          No       yes   \n",
       "3       111.6        60.0       71.0         Yes       yes   \n",
       "4       621.2       310.0      694.4         Yes       yes   \n",
       "\n",
       "   Extra International Charges  Customer Service Calls  \\\n",
       "0                          0.0                       0   \n",
       "1                          0.0                       0   \n",
       "2                          0.0                       0   \n",
       "3                          0.0                       0   \n",
       "4                          0.0                       0   \n",
       "\n",
       "   Avg Monthly GB Download Unlimited Data Plan  Extra Data Charges State  \\\n",
       "0                        3                 Yes                   0    KS   \n",
       "1                        3                 Yes                   0    OH   \n",
       "2                        3                 Yes                   0    OH   \n",
       "3                        2                 Yes                   0    MO   \n",
       "4                        3                 Yes                   0    WV   \n",
       "\n",
       "  Phone Number  Gender  Age Under 30 Senior Group  \\\n",
       "0     382-4657  Female   35       No     No    No   \n",
       "1     371-7191    Male   49       No     No    No   \n",
       "2     375-9999    Male   51       No     No    No   \n",
       "3     329-9001  Female   41       No     No    No   \n",
       "4     330-8173    Male   51       No     No    No   \n",
       "\n",
       "   Number of Customers in Group Device Protection & Online Backup  \\\n",
       "0                             0                                No   \n",
       "1                             0                               Yes   \n",
       "2                             0                               Yes   \n",
       "3                             0                                No   \n",
       "4                             0                                No   \n",
       "\n",
       "    Contract Type Payment Method  Monthly Charge  Total Charges  \\\n",
       "0  Month-to-Month   Direct Debit              10             10   \n",
       "1        One Year    Paper Check              21            703   \n",
       "2        One Year   Direct Debit              23           1014   \n",
       "3  Month-to-Month    Paper Check              17            177   \n",
       "4        One Year   Direct Debit              28           1720   \n",
       "\n",
       "  Churn Category Churn Reason  \n",
       "0            NaN          NaN  \n",
       "1            NaN          NaN  \n",
       "2            NaN          NaN  \n",
       "3            NaN          NaN  \n",
       "4            NaN          NaN  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.set_option('display.max_columns', 29)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "7ec9ac7d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# summary stats details and then transpose T or transpose() to make it easier to read (swappig rows and colmns)\n",
    "details = data.describe().T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "818dce87",
   "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>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Account Length (in months)</th>\n",
       "      <td>6687.0</td>\n",
       "      <td>32.337820</td>\n",
       "      <td>24.595689</td>\n",
       "      <td>1.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>55.00</td>\n",
       "      <td>77.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Local Calls</th>\n",
       "      <td>6687.0</td>\n",
       "      <td>130.974129</td>\n",
       "      <td>121.893966</td>\n",
       "      <td>1.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>98.0</td>\n",
       "      <td>199.00</td>\n",
       "      <td>918.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Local Mins</th>\n",
       "      <td>6687.0</td>\n",
       "      <td>322.752864</td>\n",
       "      <td>288.619931</td>\n",
       "      <td>4.0</td>\n",
       "      <td>76.9</td>\n",
       "      <td>250.5</td>\n",
       "      <td>498.05</td>\n",
       "      <td>1234.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Intl Calls</th>\n",
       "      <td>6687.0</td>\n",
       "      <td>51.097524</td>\n",
       "      <td>103.592369</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>52.00</td>\n",
       "      <td>1120.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Intl Mins</th>\n",
       "      <td>6687.0</td>\n",
       "      <td>130.070624</td>\n",
       "      <td>243.527828</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>140.40</td>\n",
       "      <td>1372.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Extra International Charges</th>\n",
       "      <td>6687.0</td>\n",
       "      <td>33.641783</td>\n",
       "      <td>76.346828</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16.40</td>\n",
       "      <td>585.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Customer Service Calls</th>\n",
       "      <td>6687.0</td>\n",
       "      <td>0.915657</td>\n",
       "      <td>1.411484</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.00</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Avg Monthly GB Download</th>\n",
       "      <td>6687.0</td>\n",
       "      <td>6.696276</td>\n",
       "      <td>7.454339</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>9.00</td>\n",
       "      <td>43.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Extra Data Charges</th>\n",
       "      <td>6687.0</td>\n",
       "      <td>3.374458</td>\n",
       "      <td>12.565309</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Age</th>\n",
       "      <td>6687.0</td>\n",
       "      <td>47.448632</td>\n",
       "      <td>16.969893</td>\n",
       "      <td>19.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>60.00</td>\n",
       "      <td>85.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Number of Customers in Group</th>\n",
       "      <td>6687.0</td>\n",
       "      <td>0.837894</td>\n",
       "      <td>1.700780</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Monthly Charge</th>\n",
       "      <td>6687.0</td>\n",
       "      <td>31.030357</td>\n",
       "      <td>16.288147</td>\n",
       "      <td>5.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>43.00</td>\n",
       "      <td>78.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total Charges</th>\n",
       "      <td>6687.0</td>\n",
       "      <td>1083.755645</td>\n",
       "      <td>1127.074863</td>\n",
       "      <td>6.0</td>\n",
       "      <td>181.0</td>\n",
       "      <td>647.0</td>\n",
       "      <td>1732.50</td>\n",
       "      <td>5574.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                               count         mean          std   min    25%  \\\n",
       "Account Length (in months)    6687.0    32.337820    24.595689   1.0    9.0   \n",
       "Local Calls                   6687.0   130.974129   121.893966   1.0   31.0   \n",
       "Local Mins                    6687.0   322.752864   288.619931   4.0   76.9   \n",
       "Intl Calls                    6687.0    51.097524   103.592369   0.0    0.0   \n",
       "Intl Mins                     6687.0   130.070624   243.527828   0.0    0.0   \n",
       "Extra International Charges   6687.0    33.641783    76.346828   0.0    0.0   \n",
       "Customer Service Calls        6687.0     0.915657     1.411484   0.0    0.0   \n",
       "Avg Monthly GB Download       6687.0     6.696276     7.454339   0.0    1.0   \n",
       "Extra Data Charges            6687.0     3.374458    12.565309   0.0    0.0   \n",
       "Age                           6687.0    47.448632    16.969893  19.0   33.0   \n",
       "Number of Customers in Group  6687.0     0.837894     1.700780   0.0    0.0   \n",
       "Monthly Charge                6687.0    31.030357    16.288147   5.0   16.0   \n",
       "Total Charges                 6687.0  1083.755645  1127.074863   6.0  181.0   \n",
       "\n",
       "                                50%      75%     max  \n",
       "Account Length (in months)     29.0    55.00    77.0  \n",
       "Local Calls                    98.0   199.00   918.0  \n",
       "Local Mins                    250.5   498.05  1234.2  \n",
       "Intl Calls                      0.0    52.00  1120.0  \n",
       "Intl Mins                       0.0   140.40  1372.5  \n",
       "Extra International Charges     0.0    16.40   585.8  \n",
       "Customer Service Calls          0.0     2.00     5.0  \n",
       "Avg Monthly GB Download         5.0     9.00    43.0  \n",
       "Extra Data Charges              0.0     0.00    99.0  \n",
       "Age                            47.0    60.00    85.0  \n",
       "Number of Customers in Group    0.0     0.00     6.0  \n",
       "Monthly Charge                 31.0    43.00    78.0  \n",
       "Total Charges                 647.0  1732.50  5574.0  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "details"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "e2ab6678",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 6687 entries, 0 to 6686\n",
      "Data columns (total 29 columns):\n",
      " #   Column                             Non-Null Count  Dtype  \n",
      "---  ------                             --------------  -----  \n",
      " 0   Customer ID                        6687 non-null   object \n",
      " 1   Churn Label                        6687 non-null   object \n",
      " 2   Account Length (in months)         6687 non-null   int64  \n",
      " 3   Local Calls                        6687 non-null   int64  \n",
      " 4   Local Mins                         6687 non-null   float64\n",
      " 5   Intl Calls                         6687 non-null   float64\n",
      " 6   Intl Mins                          6687 non-null   float64\n",
      " 7   Intl Active                        6687 non-null   object \n",
      " 8   Intl Plan                          6687 non-null   object \n",
      " 9   Extra International Charges        6687 non-null   float64\n",
      " 10  Customer Service Calls             6687 non-null   int64  \n",
      " 11  Avg Monthly GB Download            6687 non-null   int64  \n",
      " 12  Unlimited Data Plan                6687 non-null   object \n",
      " 13  Extra Data Charges                 6687 non-null   int64  \n",
      " 14  State                              6687 non-null   object \n",
      " 15  Phone Number                       6687 non-null   object \n",
      " 16  Gender                             6687 non-null   object \n",
      " 17  Age                                6687 non-null   int64  \n",
      " 18  Under 30                           6687 non-null   object \n",
      " 19  Senior                             6687 non-null   object \n",
      " 20  Group                              6687 non-null   object \n",
      " 21  Number of Customers in Group       6687 non-null   int64  \n",
      " 22  Device Protection & Online Backup  6687 non-null   object \n",
      " 23  Contract Type                      6687 non-null   object \n",
      " 24  Payment Method                     6687 non-null   object \n",
      " 25  Monthly Charge                     6687 non-null   int64  \n",
      " 26  Total Charges                      6687 non-null   int64  \n",
      " 27  Churn Category                     1769 non-null   object \n",
      " 28  Churn Reason                       1769 non-null   object \n",
      "dtypes: float64(4), int64(9), object(16)\n",
      "memory usage: 1.5+ MB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "d5f4cefd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 13 entries, Account Length (in months) to Total Charges\n",
      "Data columns (total 8 columns):\n",
      " #   Column  Non-Null Count  Dtype  \n",
      "---  ------  --------------  -----  \n",
      " 0   count   13 non-null     float64\n",
      " 1   mean    13 non-null     float64\n",
      " 2   std     13 non-null     float64\n",
      " 3   min     13 non-null     float64\n",
      " 4   25%     13 non-null     float64\n",
      " 5   50%     13 non-null     float64\n",
      " 6   75%     13 non-null     float64\n",
      " 7   max     13 non-null     float64\n",
      "dtypes: float64(8)\n",
      "memory usage: 1.5+ KB\n"
     ]
    }
   ],
   "source": [
    "details.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "0524b8ec",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Categorical (say, Intl Plan) column that contain Yes or No\n",
    "data['Intl Plan'] = data['Intl Plan'].map(str.capitalize)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "965a1bfa",
   "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>Churn Category</th>\n",
       "      <th>Churn Reason</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Churn Label</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>No</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Yes</th>\n",
       "      <td>1769</td>\n",
       "      <td>1769</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Churn Category  Churn Reason\n",
       "Churn Label                              \n",
       "No                        0             0\n",
       "Yes                    1769          1769"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Churn Category and Churn Reason shows NaN\n",
    "data.groupby('Churn Label')[['Churn Category', 'Churn Reason']].count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "1fa5d531",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Churn Categories for No customers: [nan]\n",
      "Churn Reasons for No customers:    [nan]\n",
      "\n",
      "Churn Categories for Yes customers: [nan 'Competitor' 'Other' 'Attitude' 'Dissatisfaction' 'Price']\n",
      "Churn Reasons for Yes customers:    [nan 'Competitor made better offer' 'Moved'\n",
      " 'Competitor had better devices'\n",
      " 'Competitor offered higher download speeds' 'Attitude of support person'\n",
      " 'Network reliability' \"Don't know\" 'Service dissatisfaction'\n",
      " 'Product dissatisfaction' 'Poor expertise of online support'\n",
      " 'Price too high' 'Limited range of services'\n",
      " 'Lack of affordable download/upload speed' 'Long distance charges'\n",
      " 'Competitor offered more data' 'Attitude of service provider'\n",
      " 'Poor expertise of phone support' 'Extra data charges' 'Deceased'\n",
      " 'Lack of self-service on Website']\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Find the reason and category for churn rate\n",
    "grouped = data.groupby('Churn Label')\n",
    "for label, group in grouped:\n",
    "    churn_c = group['Churn Category'].unique()\n",
    "    churn_r = group['Churn Reason'].unique()\n",
    "    print(f\"Churn Categories for {label} customers: {churn_c}\")\n",
    "    print(f\"Churn Reasons for {label} customers:    {churn_r}\\n\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "888857e2",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Find why NULL on Churn category and churn reason\n",
    "Fill_Null = {'Churn Category': 'Other', 'Churn Reason': \"Don't know\"}\n",
    "data[\n",
    "    (data['Churn Label'] == 'Yes') & (data['Churn Category'].isna())\n",
    "] = data[\n",
    "    (data['Churn Label'] == 'Yes') & (data['Churn Category'].isna())\n",
    "].fillna(value=Fill_Null)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "9968cbf4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Combine senior and under 30 colmn into one\n",
    "def categorize_age(row):\n",
    "    if row['Under 30'] == 'Yes' and row['Senior'] == 'No':\n",
    "        return 'Under 30'\n",
    "    elif row['Under 30'] == 'No' and row['Senior'] == 'Yes':\n",
    "        return 'Senior'\n",
    "    else:\n",
    "        return 'In between'\n",
    "\n",
    "data['Age Category'] = data.apply(categorize_age, axis=1)\n",
    "data.drop(columns=['Under 30', 'Senior'], inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "a2cdc283",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Intl calls shows float or having decimal number, we will truncate it to whole number and change dtype to int\n",
    "data['Intl Calls'] = np.trunc(data['Intl Calls']).astype('int64')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "a59c84d6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 6687 entries, 0 to 6686\n",
      "Data columns (total 28 columns):\n",
      " #   Column                             Non-Null Count  Dtype  \n",
      "---  ------                             --------------  -----  \n",
      " 0   Customer ID                        6687 non-null   object \n",
      " 1   Churn Label                        6687 non-null   object \n",
      " 2   Account Length (in months)         6687 non-null   int64  \n",
      " 3   Local Calls                        6687 non-null   int64  \n",
      " 4   Local Mins                         6687 non-null   float64\n",
      " 5   Intl Calls                         6687 non-null   int64  \n",
      " 6   Intl Mins                          6687 non-null   float64\n",
      " 7   Intl Active                        6687 non-null   object \n",
      " 8   Intl Plan                          6687 non-null   object \n",
      " 9   Extra International Charges        6687 non-null   float64\n",
      " 10  Customer Service Calls             6687 non-null   int64  \n",
      " 11  Avg Monthly GB Download            6687 non-null   int64  \n",
      " 12  Unlimited Data Plan                6687 non-null   object \n",
      " 13  Extra Data Charges                 6687 non-null   int64  \n",
      " 14  State                              6687 non-null   object \n",
      " 15  Phone Number                       6687 non-null   object \n",
      " 16  Gender                             6687 non-null   object \n",
      " 17  Age                                6687 non-null   int64  \n",
      " 18  Group                              6687 non-null   object \n",
      " 19  Number of Customers in Group       6687 non-null   int64  \n",
      " 20  Device Protection & Online Backup  6687 non-null   object \n",
      " 21  Contract Type                      6687 non-null   object \n",
      " 22  Payment Method                     6687 non-null   object \n",
      " 23  Monthly Charge                     6687 non-null   int64  \n",
      " 24  Total Charges                      6687 non-null   int64  \n",
      " 25  Churn Category                     1796 non-null   object \n",
      " 26  Churn Reason                       1796 non-null   object \n",
      " 27  Age Category                       6687 non-null   object \n",
      "dtypes: float64(3), int64(10), object(15)\n",
      "memory usage: 1.4+ MB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "8a0dc310",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Exploratory Data Analysis EDA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "6acc362a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Churn Rate: 26.86%\n"
     ]
    }
   ],
   "source": [
    "# Overall Churn rate Calculation\n",
    "# Count the number of churned and non-churned customers\n",
    "churn_counts = data['Churn Label'].value_counts()\n",
    "\n",
    "# Extract the count of churned customers\n",
    "churned_count = churn_counts['Yes']\n",
    "\n",
    "# Extract the count of non-churned customers\n",
    "non_churned_count = churn_counts.get('No', 0)\n",
    "\n",
    "# Calculate the churn rate\n",
    "total_customers = churned_count + non_churned_count\n",
    "churn_rate = (churned_count / total_customers) * 100\n",
    "\n",
    "# Round the churn rate to two decimal places\n",
    "churn_rate_rounded = round(churn_rate, 2)\n",
    "\n",
    "# Print the churn rate\n",
    "print(f'Churn Rate: {churn_rate_rounded}%')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "0eb04b5b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Churned customers dataframe\n",
    "churned_df = data[data['Churn Label'] == 'Yes']\n",
    "\n",
    "# Current customers dataframe\n",
    "current_df = data[data['Churn Label'] == 'No']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "99935086",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the histogram\n",
    "sns.histplot(data['Age'], binwidth=5, color='blue', kde=True)\n",
    "\n",
    "plt.title('All Current Customers Ages')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "ce21e6c6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the histogram\n",
    "sns.histplot(churned_df['Age'], binwidth=5, color='blue', kde=True)\n",
    "\n",
    "plt.title('All Churned Customers Ages')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "0d3e7954",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the histogram\n",
    "sns.histplot(current_df['Age'], binwidth=5, color='blue', kde=True)\n",
    "\n",
    "plt.title('All Current Customers Ages')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "5fc8807f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "In between    1017\n",
       "Senior         483\n",
       "Under 30       296\n",
       "Name: Age Category, dtype: int64"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "churned_df['Age Category'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "e024dae5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "In between    3127\n",
       "Under 30       991\n",
       "Senior         773\n",
       "Name: Age Category, dtype: int64"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "current_df['Age Category'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "c4723861",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Age_Cate = {'Under 30': 'blue', 'In between': 'green', 'Senior': 'red'}\n",
    "\n",
    "# Plot the countplot\n",
    "sns.countplot(data=data,\n",
    "              x='Churn Label',\n",
    "              hue='Age Category',\n",
    "              palette=Age_Cate)\n",
    "\n",
    "plt.title('Current and Churned Customers Age Categories Count')\n",
    "\n",
    "plt.legend(title='Age Category')\n",
    "\n",
    "plt.xlabel('Churned')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "792d3d64",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Male                 897\n",
       "Female               897\n",
       "Prefer not to say      2\n",
       "Name: Gender, dtype: int64"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "churned_df['Gender'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "15774213",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Male                 2482\n",
       "Female               2404\n",
       "Prefer not to say       5\n",
       "Name: Gender, dtype: int64"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "current_df['Gender'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "9132e533",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(data=churned_df,\n",
    "              x='Gender', hue='Gender')\n",
    "\n",
    "plt.title('Churned Customer Count By Gender')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "ba304acb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(data=current_df,\n",
    "              x='Gender', hue='Gender')\n",
    "\n",
    "plt.title('Churned Customer Count By Gender')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "536187c2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WV    57\n",
      "OH    55\n",
      "OR    48\n",
      "MD    46\n",
      "AL    46\n",
      "MT    43\n",
      "CA    43\n",
      "IN    42\n",
      "TX    42\n",
      "VA    42\n",
      "ID    41\n",
      "MI    40\n",
      "NE    40\n",
      "VT    39\n",
      "WI    39\n",
      "NY    39\n",
      "MN    38\n",
      "WY    38\n",
      "CT    38\n",
      "NJ    37\n",
      "MS    37\n",
      "DE    37\n",
      "UT    36\n",
      "KS    36\n",
      "MO    36\n",
      "NH    36\n",
      "SC    36\n",
      "KY    36\n",
      "NV    36\n",
      "IL    33\n",
      "RI    33\n",
      "MA    33\n",
      "ND    31\n",
      "PA    30\n",
      "AK    30\n",
      "AZ    30\n",
      "NM    30\n",
      "WA    29\n",
      "ME    29\n",
      "CO    29\n",
      "HI    28\n",
      "NC    28\n",
      "SD    27\n",
      "AR    27\n",
      "FL    27\n",
      "LA    25\n",
      "GA    25\n",
      "OK    24\n",
      "IA    24\n",
      "TN    24\n",
      "DC    21\n",
      "Name: State, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "# State or customer location wise churn rate count\n",
    "state_churned_counts = churned_df['State'].value_counts().sort_values(ascending=False)\n",
    "print(state_churned_counts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "10dc84f8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AK    28.85\n",
      "AL    28.57\n",
      "AR    24.55\n",
      "AZ    23.44\n",
      "CA    63.24\n",
      "CO    21.97\n",
      "CT    25.68\n",
      "DC    19.44\n",
      "DE    30.33\n",
      "FL    21.26\n",
      "GA    23.15\n",
      "HI    26.42\n",
      "IA    26.67\n",
      "ID    27.89\n",
      "IL    28.45\n",
      "IN    29.37\n",
      "KS    25.53\n",
      "KY    30.51\n",
      "LA    24.27\n",
      "MA    25.19\n",
      "MD    32.86\n",
      "ME    23.39\n",
      "MI    27.40\n",
      "MN    22.62\n",
      "MO    28.35\n",
      "MS    28.46\n",
      "MT    31.39\n",
      "NC    20.59\n",
      "ND    25.00\n",
      "NE    32.79\n",
      "NH    32.14\n",
      "NJ    27.01\n",
      "NM    24.19\n",
      "NV    27.27\n",
      "NY    23.35\n",
      "OH    34.81\n",
      "OK    19.51\n",
      "OR    30.77\n",
      "PA    33.33\n",
      "RI    25.19\n",
      "SC    30.00\n",
      "SD    22.50\n",
      "TN    22.64\n",
      "TX    28.97\n",
      "UT    25.00\n",
      "VA    27.10\n",
      "VT    26.53\n",
      "WA    21.97\n",
      "WI    25.00\n",
      "WV    26.76\n",
      "WY    24.68\n",
      "Name: State, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "# Churn rate for each state calculation\n",
    "states = data['State'].value_counts().sort_index(ascending=True)\n",
    "sChurnRate = round((state_churned_counts / states) * 100, 2)\n",
    "print(sChurnRate)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "5a67e20d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Average of state churn rate: 27.18\n",
      "Median of state churn rate:  26.53\n",
      "Maximum value of state churn rate: 63.24\n",
      "Minimum value of state churn rate: 19.44\n"
     ]
    }
   ],
   "source": [
    "print(f\"Average of state churn rate: {round(np.mean(sChurnRate), 2)}\")\n",
    "print(f\"Median of state churn rate:  {round(np.median(sChurnRate), 2)}\")\n",
    "print(f\"Maximum value of state churn rate: {sChurnRate.max()}\")\n",
    "print(f\"Minimum value of state churn rate: {sChurnRate.min()}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "35e19d18",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Convert the churn rates to a list or array-like object\n",
    "state_churn_rate_list = sChurnRate.tolist()  # Convert to list if not already a list\n",
    "\n",
    "sns.histplot(data=state_churn_rate_list, color='red')\n",
    "\n",
    "plt.xlabel('Churn Rate')\n",
    "\n",
    "plt.title('All States Churn Rate Distribution Chart')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "d06119d1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "State with highest churn rate: CA\n",
      "Churn rate: 63.24\n"
     ]
    }
   ],
   "source": [
    "# Find the state with the highest churn rate\n",
    "max_state = sChurnRate.idxmax()\n",
    "max_val = sChurnRate[max_state]\n",
    "\n",
    "print(f\"State with highest churn rate: {max_state}\\nChurn rate: {max_val}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "e7ac72cc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "CA     68\n",
       "PA     90\n",
       "IA     90\n",
       "LA    103\n",
       "AK    104\n",
       "HI    106\n",
       "TN    106\n",
       "DC    108\n",
       "GA    108\n",
       "AR    110\n",
       "NH    112\n",
       "IL    116\n",
       "KY    118\n",
       "SD    120\n",
       "SC    120\n",
       "DE    122\n",
       "NE    122\n",
       "OK    123\n",
       "NM    124\n",
       "ND    124\n",
       "ME    124\n",
       "FL    127\n",
       "MO    127\n",
       "AZ    128\n",
       "MS    130\n",
       "RI    131\n",
       "MA    131\n",
       "NV    132\n",
       "WA    132\n",
       "CO    132\n",
       "NC    136\n",
       "NJ    137\n",
       "MT    137\n",
       "MD    140\n",
       "KS    141\n",
       "IN    143\n",
       "UT    144\n",
       "TX    145\n",
       "MI    146\n",
       "VT    147\n",
       "ID    147\n",
       "CT    148\n",
       "WY    154\n",
       "VA    155\n",
       "WI    156\n",
       "OR    156\n",
       "OH    158\n",
       "AL    161\n",
       "NY    167\n",
       "MN    168\n",
       "WV    213\n",
       "Name: State, dtype: int64"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "states.sort_values(ascending=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "84ffa3ee",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Account length mean: 18.071269487750556\n",
      "Account length median: 10.0\n",
      "Account length max: 74\n",
      "Account length min: 1\n"
     ]
    }
   ],
   "source": [
    "# Check how long usually customer use the service and get churn out\n",
    "print(f\"Account length mean: {churned_df['Account Length (in months)'].mean()}\")\n",
    "print(f\"Account length median: {churned_df['Account Length (in months)'].median()}\")\n",
    "print(f\"Account length max: {churned_df['Account Length (in months)'].max()}\")\n",
    "print(f\"Account length min: {churned_df['Account Length (in months)'].min()}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "38814b0e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Calculate counts of churns over account lengths in months\n",
    "account_len = churned_df['Account Length (in months)'].value_counts()\n",
    "\n",
    "sns.lineplot(x=account_len.index,\n",
    "            y=account_len.values)\n",
    "\n",
    "plt.title('Accounts Length in Months when Customer Churn')\n",
    "plt.xlabel('Account Length (in months)')\n",
    "plt.ylabel('Count of churns')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "c2e0b308",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Percentage of churns that occur in the first month: 20.43%\n"
     ]
    }
   ],
   "source": [
    "# Calculate the count of churns in the first month\n",
    "churns_first_month = account_len.get(1, 0)\n",
    "\n",
    "# Calculate the total count of churns\n",
    "total_churns = account_len.sum()\n",
    "\n",
    "# Calculate the percentage of churns that occur in the first month\n",
    "percentage_first_month_churns = (churns_first_month / total_churns) * 100\n",
    "\n",
    "# Round the percentage to two decimal places\n",
    "percentage_first_month_churns_rounded = round(percentage_first_month_churns, 2)\n",
    "\n",
    "print(f\"Percentage of churns that occur in the first month: {percentage_first_month_churns_rounded}%\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "24fbc429",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}