Churn Project_Me.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# PROJECT CHURN\n",
    "\n",
    "This project is regarding Customer Churn Prediction. If we can know what all customers are going to churn out we can give thme offers or hear them inorder to retain them. In current business scenerio, It is very difficult and expensive to develop new customers as comapred to retaining our old customers\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Lets Load Important Libraries\n",
    "\n",
    "import os\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib as mlt\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from scipy.stats import chi2_contingency\n",
    "import seaborn as sns\n",
    "from random import randrange, uniform\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "import statsmodels.api as sm\n",
    "from sklearn.metrics import roc_auc_score\n",
    "from sklearn.metrics import roc_curve\n",
    "import random\n",
    "from sklearn.metrics import accuracy_score\n",
    "from sklearn.metrics import confusion_matrix\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Lets Read the Data and do Basic Pre-processing.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'F:\\\\Data Scientist\\\\Project_Churn'"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Lets Set working directory\n",
    "\n",
    "os.chdir(\"F:/Data Scientist/Project_Churn\")\n",
    "os.getcwd()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Lets import data\n",
    "\n",
    "#Train Data\n",
    "Train=pd.read_csv(\"Train_data.csv\")\n",
    "\n",
    "#Test Data\n",
    "Test=pd.read_csv(\"Test_data.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1667"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Lets check the data\n",
    "\n",
    "Train.head(10)\n",
    "Test.head(10)\n",
    "len(Train)\n",
    "len(Test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "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>account length</th>\n",
       "      <th>area code</th>\n",
       "      <th>number vmail messages</th>\n",
       "      <th>total day minutes</th>\n",
       "      <th>total day calls</th>\n",
       "      <th>total day charge</th>\n",
       "      <th>total eve minutes</th>\n",
       "      <th>total eve calls</th>\n",
       "      <th>total eve charge</th>\n",
       "      <th>total night minutes</th>\n",
       "      <th>total night calls</th>\n",
       "      <th>total night charge</th>\n",
       "      <th>total intl minutes</th>\n",
       "      <th>total intl calls</th>\n",
       "      <th>total intl charge</th>\n",
       "      <th>number customer service calls</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>3333.000000</td>\n",
       "      <td>3333.000000</td>\n",
       "      <td>3333.000000</td>\n",
       "      <td>3333.000000</td>\n",
       "      <td>3333.000000</td>\n",
       "      <td>3333.000000</td>\n",
       "      <td>3333.000000</td>\n",
       "      <td>3333.000000</td>\n",
       "      <td>3333.000000</td>\n",
       "      <td>3333.000000</td>\n",
       "      <td>3333.000000</td>\n",
       "      <td>3333.000000</td>\n",
       "      <td>3333.000000</td>\n",
       "      <td>3333.000000</td>\n",
       "      <td>3333.000000</td>\n",
       "      <td>3333.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>101.064806</td>\n",
       "      <td>437.182418</td>\n",
       "      <td>8.099010</td>\n",
       "      <td>179.775098</td>\n",
       "      <td>100.435644</td>\n",
       "      <td>30.562307</td>\n",
       "      <td>200.980348</td>\n",
       "      <td>100.114311</td>\n",
       "      <td>17.083540</td>\n",
       "      <td>200.872037</td>\n",
       "      <td>100.107711</td>\n",
       "      <td>9.039325</td>\n",
       "      <td>10.237294</td>\n",
       "      <td>4.479448</td>\n",
       "      <td>2.764581</td>\n",
       "      <td>1.562856</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>39.822106</td>\n",
       "      <td>42.371290</td>\n",
       "      <td>13.688365</td>\n",
       "      <td>54.467389</td>\n",
       "      <td>20.069084</td>\n",
       "      <td>9.259435</td>\n",
       "      <td>50.713844</td>\n",
       "      <td>19.922625</td>\n",
       "      <td>4.310668</td>\n",
       "      <td>50.573847</td>\n",
       "      <td>19.568609</td>\n",
       "      <td>2.275873</td>\n",
       "      <td>2.791840</td>\n",
       "      <td>2.461214</td>\n",
       "      <td>0.753773</td>\n",
       "      <td>1.315491</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>408.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>23.200000</td>\n",
       "      <td>33.000000</td>\n",
       "      <td>1.040000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>74.000000</td>\n",
       "      <td>408.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>143.700000</td>\n",
       "      <td>87.000000</td>\n",
       "      <td>24.430000</td>\n",
       "      <td>166.600000</td>\n",
       "      <td>87.000000</td>\n",
       "      <td>14.160000</td>\n",
       "      <td>167.000000</td>\n",
       "      <td>87.000000</td>\n",
       "      <td>7.520000</td>\n",
       "      <td>8.500000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>2.300000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>101.000000</td>\n",
       "      <td>415.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>179.400000</td>\n",
       "      <td>101.000000</td>\n",
       "      <td>30.500000</td>\n",
       "      <td>201.400000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>17.120000</td>\n",
       "      <td>201.200000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>9.050000</td>\n",
       "      <td>10.300000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>2.780000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>127.000000</td>\n",
       "      <td>510.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>216.400000</td>\n",
       "      <td>114.000000</td>\n",
       "      <td>36.790000</td>\n",
       "      <td>235.300000</td>\n",
       "      <td>114.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>235.300000</td>\n",
       "      <td>113.000000</td>\n",
       "      <td>10.590000</td>\n",
       "      <td>12.100000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>3.270000</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>243.000000</td>\n",
       "      <td>510.000000</td>\n",
       "      <td>51.000000</td>\n",
       "      <td>350.800000</td>\n",
       "      <td>165.000000</td>\n",
       "      <td>59.640000</td>\n",
       "      <td>363.700000</td>\n",
       "      <td>170.000000</td>\n",
       "      <td>30.910000</td>\n",
       "      <td>395.000000</td>\n",
       "      <td>175.000000</td>\n",
       "      <td>17.770000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>5.400000</td>\n",
       "      <td>9.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       account length    area code  number vmail messages  total day minutes  \\\n",
       "count     3333.000000  3333.000000            3333.000000        3333.000000   \n",
       "mean       101.064806   437.182418               8.099010         179.775098   \n",
       "std         39.822106    42.371290              13.688365          54.467389   \n",
       "min          1.000000   408.000000               0.000000           0.000000   \n",
       "25%         74.000000   408.000000               0.000000         143.700000   \n",
       "50%        101.000000   415.000000               0.000000         179.400000   \n",
       "75%        127.000000   510.000000              20.000000         216.400000   \n",
       "max        243.000000   510.000000              51.000000         350.800000   \n",
       "\n",
       "       total day calls  total day charge  total eve minutes  total eve calls  \\\n",
       "count      3333.000000       3333.000000        3333.000000      3333.000000   \n",
       "mean        100.435644         30.562307         200.980348       100.114311   \n",
       "std          20.069084          9.259435          50.713844        19.922625   \n",
       "min           0.000000          0.000000           0.000000         0.000000   \n",
       "25%          87.000000         24.430000         166.600000        87.000000   \n",
       "50%         101.000000         30.500000         201.400000       100.000000   \n",
       "75%         114.000000         36.790000         235.300000       114.000000   \n",
       "max         165.000000         59.640000         363.700000       170.000000   \n",
       "\n",
       "       total eve charge  total night minutes  total night calls  \\\n",
       "count       3333.000000          3333.000000        3333.000000   \n",
       "mean          17.083540           200.872037         100.107711   \n",
       "std            4.310668            50.573847          19.568609   \n",
       "min            0.000000            23.200000          33.000000   \n",
       "25%           14.160000           167.000000          87.000000   \n",
       "50%           17.120000           201.200000         100.000000   \n",
       "75%           20.000000           235.300000         113.000000   \n",
       "max           30.910000           395.000000         175.000000   \n",
       "\n",
       "       total night charge  total intl minutes  total intl calls  \\\n",
       "count         3333.000000         3333.000000       3333.000000   \n",
       "mean             9.039325           10.237294          4.479448   \n",
       "std              2.275873            2.791840          2.461214   \n",
       "min              1.040000            0.000000          0.000000   \n",
       "25%              7.520000            8.500000          3.000000   \n",
       "50%              9.050000           10.300000          4.000000   \n",
       "75%             10.590000           12.100000          6.000000   \n",
       "max             17.770000           20.000000         20.000000   \n",
       "\n",
       "       total intl charge  number customer service calls  \n",
       "count        3333.000000                    3333.000000  \n",
       "mean            2.764581                       1.562856  \n",
       "std             0.753773                       1.315491  \n",
       "min             0.000000                       0.000000  \n",
       "25%             2.300000                       1.000000  \n",
       "50%             2.780000                       1.000000  \n",
       "75%             3.270000                       2.000000  \n",
       "max             5.400000                       9.000000  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Lets check summary of the data\n",
    "\n",
    "Train.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 3333 entries, 0 to 3332\n",
      "Data columns (total 21 columns):\n",
      "state                            3333 non-null object\n",
      "account length                   3333 non-null int64\n",
      "area code                        3333 non-null int64\n",
      "phone number                     3333 non-null object\n",
      "international plan               3333 non-null object\n",
      "voice mail plan                  3333 non-null object\n",
      "number vmail messages            3333 non-null int64\n",
      "total day minutes                3333 non-null float64\n",
      "total day calls                  3333 non-null int64\n",
      "total day charge                 3333 non-null float64\n",
      "total eve minutes                3333 non-null float64\n",
      "total eve calls                  3333 non-null int64\n",
      "total eve charge                 3333 non-null float64\n",
      "total night minutes              3333 non-null float64\n",
      "total night calls                3333 non-null int64\n",
      "total night charge               3333 non-null float64\n",
      "total intl minutes               3333 non-null float64\n",
      "total intl calls                 3333 non-null int64\n",
      "total intl charge                3333 non-null float64\n",
      "number customer service calls    3333 non-null int64\n",
      "Churn                            3333 non-null object\n",
      "dtypes: float64(8), int64(8), object(5)\n",
      "memory usage: 546.9+ KB\n"
     ]
    }
   ],
   "source": [
    "#Now lets check DATA TYPES of variables inorder to convert them in proper format\n",
    "\n",
    "Train.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1667 entries, 0 to 1666\n",
      "Data columns (total 21 columns):\n",
      "state                            1667 non-null object\n",
      "account length                   1667 non-null int64\n",
      "area code                        1667 non-null int64\n",
      "phone number                     1667 non-null object\n",
      "international plan               1667 non-null object\n",
      "voice mail plan                  1667 non-null object\n",
      "number vmail messages            1667 non-null int64\n",
      "total day minutes                1667 non-null float64\n",
      "total day calls                  1667 non-null int64\n",
      "total day charge                 1667 non-null float64\n",
      "total eve minutes                1667 non-null float64\n",
      "total eve calls                  1667 non-null int64\n",
      "total eve charge                 1667 non-null float64\n",
      "total night minutes              1667 non-null float64\n",
      "total night calls                1667 non-null int64\n",
      "total night charge               1667 non-null float64\n",
      "total intl minutes               1667 non-null float64\n",
      "total intl calls                 1667 non-null int64\n",
      "total intl charge                1667 non-null float64\n",
      "number customer service calls    1667 non-null int64\n",
      "Churn                            1667 non-null object\n",
      "dtypes: float64(8), int64(8), object(5)\n",
      "memory usage: 273.6+ KB\n"
     ]
    }
   ],
   "source": [
    "Test.info()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Lets change the area.code type to categorical\n",
    "\n",
    "Train['area code']=Train['area code'].astype('object')\n",
    "Test['area code']=Test['area code'].astype('object')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Drop Variable Phone Number\n",
    "Train=Train.drop('phone number',axis=1)\n",
    "Test=Test.drop('phone number',axis=1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['state', 'area code', 'international plan', 'voice mail plan']"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Lets seperate Continuous Variables\n",
    "num_variable=Train.columns[(Train.dtypes=='float64')|(Train.dtypes=='int64')].tolist()\n",
    "\n",
    "#Seperate Categorical Data wihtout Target Variable\n",
    "cat_variable=Train.columns[Train.dtypes=='object'].tolist()\n",
    "cat_variable.remove('Churn')\n",
    "cat_variable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['account length',\n",
       " 'number vmail messages',\n",
       " 'total day minutes',\n",
       " 'total day calls',\n",
       " 'total day charge',\n",
       " 'total eve minutes',\n",
       " 'total eve calls',\n",
       " 'total eve charge',\n",
       " 'total night minutes',\n",
       " 'total night calls',\n",
       " 'total night charge',\n",
       " 'total intl minutes',\n",
       " 'total intl calls',\n",
       " 'total intl charge',\n",
       " 'number customer service calls']"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "num_variable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "#For Test Variable\n",
    "num_variable01=Test.columns[(Test.dtypes=='float64')|(Test.dtypes=='int64')].tolist()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['account length',\n",
       " 'number vmail messages',\n",
       " 'total day minutes',\n",
       " 'total day calls',\n",
       " 'total day charge',\n",
       " 'total eve minutes',\n",
       " 'total eve calls',\n",
       " 'total eve charge',\n",
       " 'total night minutes',\n",
       " 'total night calls',\n",
       " 'total night charge',\n",
       " 'total intl minutes',\n",
       " 'total intl calls',\n",
       " 'total intl charge',\n",
       " 'number customer service calls']"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "num_variable01"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['state', 'area code', 'international plan', 'voice mail plan']"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "#Now seperate categorical data\n",
    "cat_variable01=Test.columns[Test.dtypes=='object'].tolist()\n",
    "cat_variable01.remove('Churn')\n",
    "cat_variable01"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Now we will go for Advanced Pre-processing."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# MISSING VALUE ANALYSIS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "state                            0\n",
       "account length                   0\n",
       "area code                        0\n",
       "international plan               0\n",
       "voice mail plan                  0\n",
       "number vmail messages            0\n",
       "total day minutes                0\n",
       "total day calls                  0\n",
       "total day charge                 0\n",
       "total eve minutes                0\n",
       "total eve calls                  0\n",
       "total eve charge                 0\n",
       "total night minutes              0\n",
       "total night calls                0\n",
       "total night charge               0\n",
       "total intl minutes               0\n",
       "total intl calls                 0\n",
       "total intl charge                0\n",
       "number customer service calls    0\n",
       "Churn                            0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Lets check if there are any missing values in our Data\n",
    "(Train.isnull().sum())\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#Check missing values in Test Data\n",
    "\n",
    "Test.isnull().sum()\n",
    "\n",
    "#As observed there are no missing values present in our data."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# OUTLIERS ANALYSIS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Lets load important libraries\n",
    "#For plotting graphs\n",
    "import matplotlib.pyplot as plt\n",
    "import random\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Treating Outliers\n",
    "#For Train Data\n",
    "#for i in num_variable:\n",
    " #       print(i)\n",
    "  #      q75, q25 = np.percentile(Train.loc[:,i], [75 ,25])\n",
    "   #     iqr = q75 - q25\n",
    "    #    mini = q25 - (iqr*1.5)\n",
    "     #   maxi = q75 + (iqr*1.5)\n",
    "      #  print(mini)\n",
    "       # print(maxi)\n",
    "        #Train = Train.drop(Train[Train.loc[:,i] < mini].index)\n",
    "        #Train = Train.drop(Train[Train.loc[:,i] > maxi].index)\n",
    "      \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "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>state</th>\n",
       "      <th>account length</th>\n",
       "      <th>area code</th>\n",
       "      <th>international plan</th>\n",
       "      <th>voice mail plan</th>\n",
       "      <th>number vmail messages</th>\n",
       "      <th>total day minutes</th>\n",
       "      <th>total day calls</th>\n",
       "      <th>total day charge</th>\n",
       "      <th>total eve minutes</th>\n",
       "      <th>total eve calls</th>\n",
       "      <th>total eve charge</th>\n",
       "      <th>total night minutes</th>\n",
       "      <th>total night calls</th>\n",
       "      <th>total night charge</th>\n",
       "      <th>total intl minutes</th>\n",
       "      <th>total intl calls</th>\n",
       "      <th>total intl charge</th>\n",
       "      <th>number customer service calls</th>\n",
       "      <th>Churn</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>KS</td>\n",
       "      <td>128</td>\n",
       "      <td>415</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>25</td>\n",
       "      <td>265.1</td>\n",
       "      <td>110</td>\n",
       "      <td>45.07</td>\n",
       "      <td>197.4</td>\n",
       "      <td>99</td>\n",
       "      <td>16.78</td>\n",
       "      <td>244.7</td>\n",
       "      <td>91</td>\n",
       "      <td>11.01</td>\n",
       "      <td>10.0</td>\n",
       "      <td>3</td>\n",
       "      <td>2.70</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>OH</td>\n",
       "      <td>107</td>\n",
       "      <td>415</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>26</td>\n",
       "      <td>161.6</td>\n",
       "      <td>123</td>\n",
       "      <td>27.47</td>\n",
       "      <td>195.5</td>\n",
       "      <td>103</td>\n",
       "      <td>16.62</td>\n",
       "      <td>254.4</td>\n",
       "      <td>103</td>\n",
       "      <td>11.45</td>\n",
       "      <td>13.7</td>\n",
       "      <td>3</td>\n",
       "      <td>3.70</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>NJ</td>\n",
       "      <td>137</td>\n",
       "      <td>415</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>243.4</td>\n",
       "      <td>114</td>\n",
       "      <td>41.38</td>\n",
       "      <td>121.2</td>\n",
       "      <td>110</td>\n",
       "      <td>10.30</td>\n",
       "      <td>162.6</td>\n",
       "      <td>104</td>\n",
       "      <td>7.32</td>\n",
       "      <td>12.2</td>\n",
       "      <td>5</td>\n",
       "      <td>3.29</td>\n",
       "      <td>0</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>OH</td>\n",
       "      <td>84</td>\n",
       "      <td>408</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>299.4</td>\n",
       "      <td>71</td>\n",
       "      <td>50.90</td>\n",
       "      <td>61.9</td>\n",
       "      <td>88</td>\n",
       "      <td>5.26</td>\n",
       "      <td>196.9</td>\n",
       "      <td>89</td>\n",
       "      <td>8.86</td>\n",
       "      <td>6.6</td>\n",
       "      <td>7</td>\n",
       "      <td>1.78</td>\n",
       "      <td>2</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>OK</td>\n",
       "      <td>75</td>\n",
       "      <td>415</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>166.7</td>\n",
       "      <td>113</td>\n",
       "      <td>28.34</td>\n",
       "      <td>148.3</td>\n",
       "      <td>122</td>\n",
       "      <td>12.61</td>\n",
       "      <td>186.9</td>\n",
       "      <td>121</td>\n",
       "      <td>8.41</td>\n",
       "      <td>10.1</td>\n",
       "      <td>3</td>\n",
       "      <td>2.73</td>\n",
       "      <td>3</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  state  account length area code international plan voice mail plan  \\\n",
       "0    KS             128       415                 no             yes   \n",
       "1    OH             107       415                 no             yes   \n",
       "2    NJ             137       415                 no              no   \n",
       "3    OH              84       408                yes              no   \n",
       "4    OK              75       415                yes              no   \n",
       "\n",
       "   number vmail messages  total day minutes  total day calls  \\\n",
       "0                     25              265.1              110   \n",
       "1                     26              161.6              123   \n",
       "2                      0              243.4              114   \n",
       "3                      0              299.4               71   \n",
       "4                      0              166.7              113   \n",
       "\n",
       "   total day charge  total eve minutes  total eve calls  total eve charge  \\\n",
       "0             45.07              197.4               99             16.78   \n",
       "1             27.47              195.5              103             16.62   \n",
       "2             41.38              121.2              110             10.30   \n",
       "3             50.90               61.9               88              5.26   \n",
       "4             28.34              148.3              122             12.61   \n",
       "\n",
       "   total night minutes  total night calls  total night charge  \\\n",
       "0                244.7                 91               11.01   \n",
       "1                254.4                103               11.45   \n",
       "2                162.6                104                7.32   \n",
       "3                196.9                 89                8.86   \n",
       "4                186.9                121                8.41   \n",
       "\n",
       "   total intl minutes  total intl calls  total intl charge  \\\n",
       "0                10.0                 3               2.70   \n",
       "1                13.7                 3               3.70   \n",
       "2                12.2                 5               3.29   \n",
       "3                 6.6                 7               1.78   \n",
       "4                10.1                 3               2.73   \n",
       "\n",
       "   number customer service calls    Churn  \n",
       "0                              1   False.  \n",
       "1                              1   False.  \n",
       "2                              0   False.  \n",
       "3                              2   False.  \n",
       "4                              3   False.  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Train.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "#For Test Data\n",
    "\n",
    "#for i in num_variable01:\n",
    " #       print(i)\n",
    "  #      q75, q25 = np.percentile(Test.loc[:,i], [75 ,25])\n",
    "   #     iqr = q75 - q25\n",
    "    #    mini = q25 - (iqr*1.5)\n",
    "     #   maxi = q75 + (iqr*1.5)\n",
    "      #  print(mini)\n",
    "       # print(maxi)\n",
    "        #Test = Test.drop(Test[Test.loc[:,i] < mini].index)\n",
    "        #Test = Test.drop(Test[Test.loc[:,i] > maxi].index)\n",
    "      \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\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>state</th>\n",
       "      <th>account length</th>\n",
       "      <th>area code</th>\n",
       "      <th>phone number</th>\n",
       "      <th>international plan</th>\n",
       "      <th>voice mail plan</th>\n",
       "      <th>number vmail messages</th>\n",
       "      <th>total day minutes</th>\n",
       "      <th>total day calls</th>\n",
       "      <th>total day charge</th>\n",
       "      <th>...</th>\n",
       "      <th>total eve calls</th>\n",
       "      <th>total eve charge</th>\n",
       "      <th>total night minutes</th>\n",
       "      <th>total night calls</th>\n",
       "      <th>total night charge</th>\n",
       "      <th>total intl minutes</th>\n",
       "      <th>total intl calls</th>\n",
       "      <th>total intl charge</th>\n",
       "      <th>number customer service calls</th>\n",
       "      <th>Churn</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NM</td>\n",
       "      <td>99</td>\n",
       "      <td>415</td>\n",
       "      <td>418-9100</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>216.8</td>\n",
       "      <td>123</td>\n",
       "      <td>36.86</td>\n",
       "      <td>...</td>\n",
       "      <td>88</td>\n",
       "      <td>10.74</td>\n",
       "      <td>220.6</td>\n",
       "      <td>82</td>\n",
       "      <td>9.93</td>\n",
       "      <td>15.7</td>\n",
       "      <td>2</td>\n",
       "      <td>4.24</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>SC</td>\n",
       "      <td>108</td>\n",
       "      <td>415</td>\n",
       "      <td>413-3643</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>197.4</td>\n",
       "      <td>78</td>\n",
       "      <td>33.56</td>\n",
       "      <td>...</td>\n",
       "      <td>101</td>\n",
       "      <td>10.54</td>\n",
       "      <td>204.5</td>\n",
       "      <td>107</td>\n",
       "      <td>9.20</td>\n",
       "      <td>7.7</td>\n",
       "      <td>4</td>\n",
       "      <td>2.08</td>\n",
       "      <td>2</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>IA</td>\n",
       "      <td>117</td>\n",
       "      <td>415</td>\n",
       "      <td>375-6180</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>226.5</td>\n",
       "      <td>85</td>\n",
       "      <td>38.51</td>\n",
       "      <td>...</td>\n",
       "      <td>68</td>\n",
       "      <td>12.04</td>\n",
       "      <td>223.0</td>\n",
       "      <td>90</td>\n",
       "      <td>10.04</td>\n",
       "      <td>6.9</td>\n",
       "      <td>5</td>\n",
       "      <td>1.86</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>LA</td>\n",
       "      <td>94</td>\n",
       "      <td>408</td>\n",
       "      <td>359-9881</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>157.5</td>\n",
       "      <td>97</td>\n",
       "      <td>26.78</td>\n",
       "      <td>...</td>\n",
       "      <td>112</td>\n",
       "      <td>19.08</td>\n",
       "      <td>310.8</td>\n",
       "      <td>106</td>\n",
       "      <td>13.99</td>\n",
       "      <td>11.1</td>\n",
       "      <td>6</td>\n",
       "      <td>3.00</td>\n",
       "      <td>0</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>TX</td>\n",
       "      <td>140</td>\n",
       "      <td>415</td>\n",
       "      <td>353-1755</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>93.2</td>\n",
       "      <td>109</td>\n",
       "      <td>15.84</td>\n",
       "      <td>...</td>\n",
       "      <td>116</td>\n",
       "      <td>16.80</td>\n",
       "      <td>219.8</td>\n",
       "      <td>94</td>\n",
       "      <td>9.89</td>\n",
       "      <td>10.5</td>\n",
       "      <td>2</td>\n",
       "      <td>2.84</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>ND</td>\n",
       "      <td>108</td>\n",
       "      <td>415</td>\n",
       "      <td>371-5951</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>112.6</td>\n",
       "      <td>86</td>\n",
       "      <td>19.14</td>\n",
       "      <td>...</td>\n",
       "      <td>101</td>\n",
       "      <td>9.77</td>\n",
       "      <td>177.8</td>\n",
       "      <td>119</td>\n",
       "      <td>8.00</td>\n",
       "      <td>7.2</td>\n",
       "      <td>6</td>\n",
       "      <td>1.94</td>\n",
       "      <td>3</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>DE</td>\n",
       "      <td>60</td>\n",
       "      <td>408</td>\n",
       "      <td>381-5937</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>207.3</td>\n",
       "      <td>77</td>\n",
       "      <td>35.24</td>\n",
       "      <td>...</td>\n",
       "      <td>105</td>\n",
       "      <td>17.67</td>\n",
       "      <td>108.2</td>\n",
       "      <td>89</td>\n",
       "      <td>4.87</td>\n",
       "      <td>12.9</td>\n",
       "      <td>5</td>\n",
       "      <td>3.48</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>MN</td>\n",
       "      <td>96</td>\n",
       "      <td>408</td>\n",
       "      <td>357-1784</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>208.1</td>\n",
       "      <td>93</td>\n",
       "      <td>35.38</td>\n",
       "      <td>...</td>\n",
       "      <td>107</td>\n",
       "      <td>16.08</td>\n",
       "      <td>279.6</td>\n",
       "      <td>90</td>\n",
       "      <td>12.58</td>\n",
       "      <td>7.4</td>\n",
       "      <td>2</td>\n",
       "      <td>2.00</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>MN</td>\n",
       "      <td>75</td>\n",
       "      <td>415</td>\n",
       "      <td>400-5627</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>225.3</td>\n",
       "      <td>124</td>\n",
       "      <td>38.30</td>\n",
       "      <td>...</td>\n",
       "      <td>81</td>\n",
       "      <td>19.38</td>\n",
       "      <td>254.3</td>\n",
       "      <td>106</td>\n",
       "      <td>11.44</td>\n",
       "      <td>11.7</td>\n",
       "      <td>3</td>\n",
       "      <td>3.16</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>OH</td>\n",
       "      <td>69</td>\n",
       "      <td>415</td>\n",
       "      <td>328-6124</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>229.2</td>\n",
       "      <td>111</td>\n",
       "      <td>38.96</td>\n",
       "      <td>...</td>\n",
       "      <td>104</td>\n",
       "      <td>14.05</td>\n",
       "      <td>235.1</td>\n",
       "      <td>80</td>\n",
       "      <td>10.58</td>\n",
       "      <td>5.2</td>\n",
       "      <td>5</td>\n",
       "      <td>1.40</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>ID</td>\n",
       "      <td>72</td>\n",
       "      <td>415</td>\n",
       "      <td>413-5754</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>101.0</td>\n",
       "      <td>110</td>\n",
       "      <td>17.17</td>\n",
       "      <td>...</td>\n",
       "      <td>70</td>\n",
       "      <td>20.40</td>\n",
       "      <td>333.5</td>\n",
       "      <td>105</td>\n",
       "      <td>15.01</td>\n",
       "      <td>11.1</td>\n",
       "      <td>6</td>\n",
       "      <td>3.00</td>\n",
       "      <td>0</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>MD</td>\n",
       "      <td>68</td>\n",
       "      <td>408</td>\n",
       "      <td>359-5139</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>150.4</td>\n",
       "      <td>106</td>\n",
       "      <td>25.57</td>\n",
       "      <td>...</td>\n",
       "      <td>131</td>\n",
       "      <td>16.92</td>\n",
       "      <td>109.7</td>\n",
       "      <td>103</td>\n",
       "      <td>4.94</td>\n",
       "      <td>12.3</td>\n",
       "      <td>3</td>\n",
       "      <td>3.32</td>\n",
       "      <td>3</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>AZ</td>\n",
       "      <td>97</td>\n",
       "      <td>415</td>\n",
       "      <td>416-8332</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>100.8</td>\n",
       "      <td>74</td>\n",
       "      <td>17.14</td>\n",
       "      <td>...</td>\n",
       "      <td>88</td>\n",
       "      <td>19.87</td>\n",
       "      <td>208.7</td>\n",
       "      <td>79</td>\n",
       "      <td>9.39</td>\n",
       "      <td>12.6</td>\n",
       "      <td>3</td>\n",
       "      <td>3.40</td>\n",
       "      <td>2</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>IA</td>\n",
       "      <td>92</td>\n",
       "      <td>415</td>\n",
       "      <td>350-4349</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>138.1</td>\n",
       "      <td>131</td>\n",
       "      <td>23.48</td>\n",
       "      <td>...</td>\n",
       "      <td>128</td>\n",
       "      <td>14.93</td>\n",
       "      <td>192.7</td>\n",
       "      <td>119</td>\n",
       "      <td>8.67</td>\n",
       "      <td>10.0</td>\n",
       "      <td>3</td>\n",
       "      <td>2.70</td>\n",
       "      <td>3</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>CA</td>\n",
       "      <td>73</td>\n",
       "      <td>415</td>\n",
       "      <td>378-8356</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>137.6</td>\n",
       "      <td>113</td>\n",
       "      <td>23.39</td>\n",
       "      <td>...</td>\n",
       "      <td>75</td>\n",
       "      <td>15.27</td>\n",
       "      <td>172.8</td>\n",
       "      <td>71</td>\n",
       "      <td>7.78</td>\n",
       "      <td>10.7</td>\n",
       "      <td>2</td>\n",
       "      <td>2.89</td>\n",
       "      <td>1</td>\n",
       "      <td>True.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>NE</td>\n",
       "      <td>161</td>\n",
       "      <td>415</td>\n",
       "      <td>329-1253</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>166.2</td>\n",
       "      <td>125</td>\n",
       "      <td>28.25</td>\n",
       "      <td>...</td>\n",
       "      <td>78</td>\n",
       "      <td>23.75</td>\n",
       "      <td>181.0</td>\n",
       "      <td>85</td>\n",
       "      <td>8.15</td>\n",
       "      <td>13.4</td>\n",
       "      <td>6</td>\n",
       "      <td>3.62</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>OR</td>\n",
       "      <td>194</td>\n",
       "      <td>415</td>\n",
       "      <td>403-2167</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>258.3</td>\n",
       "      <td>76</td>\n",
       "      <td>43.91</td>\n",
       "      <td>...</td>\n",
       "      <td>88</td>\n",
       "      <td>26.01</td>\n",
       "      <td>241.8</td>\n",
       "      <td>106</td>\n",
       "      <td>10.88</td>\n",
       "      <td>13.6</td>\n",
       "      <td>4</td>\n",
       "      <td>3.67</td>\n",
       "      <td>1</td>\n",
       "      <td>True.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>ME</td>\n",
       "      <td>70</td>\n",
       "      <td>415</td>\n",
       "      <td>390-1881</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>169.1</td>\n",
       "      <td>48</td>\n",
       "      <td>28.75</td>\n",
       "      <td>...</td>\n",
       "      <td>62</td>\n",
       "      <td>18.68</td>\n",
       "      <td>193.5</td>\n",
       "      <td>105</td>\n",
       "      <td>8.71</td>\n",
       "      <td>10.7</td>\n",
       "      <td>8</td>\n",
       "      <td>2.89</td>\n",
       "      <td>3</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>NM</td>\n",
       "      <td>72</td>\n",
       "      <td>415</td>\n",
       "      <td>412-5272</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>190.7</td>\n",
       "      <td>111</td>\n",
       "      <td>32.42</td>\n",
       "      <td>...</td>\n",
       "      <td>103</td>\n",
       "      <td>20.54</td>\n",
       "      <td>278.1</td>\n",
       "      <td>95</td>\n",
       "      <td>12.51</td>\n",
       "      <td>4.4</td>\n",
       "      <td>3</td>\n",
       "      <td>1.19</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>WV</td>\n",
       "      <td>66</td>\n",
       "      <td>415</td>\n",
       "      <td>381-5680</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>239.6</td>\n",
       "      <td>120</td>\n",
       "      <td>40.73</td>\n",
       "      <td>...</td>\n",
       "      <td>110</td>\n",
       "      <td>19.58</td>\n",
       "      <td>153.0</td>\n",
       "      <td>82</td>\n",
       "      <td>6.89</td>\n",
       "      <td>8.6</td>\n",
       "      <td>3</td>\n",
       "      <td>2.32</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>HI</td>\n",
       "      <td>63</td>\n",
       "      <td>415</td>\n",
       "      <td>330-7635</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>112.5</td>\n",
       "      <td>95</td>\n",
       "      <td>19.13</td>\n",
       "      <td>...</td>\n",
       "      <td>67</td>\n",
       "      <td>17.95</td>\n",
       "      <td>227.5</td>\n",
       "      <td>96</td>\n",
       "      <td>10.24</td>\n",
       "      <td>11.1</td>\n",
       "      <td>8</td>\n",
       "      <td>3.00</td>\n",
       "      <td>0</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>OR</td>\n",
       "      <td>159</td>\n",
       "      <td>408</td>\n",
       "      <td>385-9556</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>180.1</td>\n",
       "      <td>103</td>\n",
       "      <td>30.62</td>\n",
       "      <td>...</td>\n",
       "      <td>148</td>\n",
       "      <td>16.44</td>\n",
       "      <td>251.2</td>\n",
       "      <td>109</td>\n",
       "      <td>11.30</td>\n",
       "      <td>13.4</td>\n",
       "      <td>5</td>\n",
       "      <td>3.62</td>\n",
       "      <td>0</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>UT</td>\n",
       "      <td>98</td>\n",
       "      <td>415</td>\n",
       "      <td>364-1015</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>211.9</td>\n",
       "      <td>65</td>\n",
       "      <td>36.02</td>\n",
       "      <td>...</td>\n",
       "      <td>95</td>\n",
       "      <td>19.09</td>\n",
       "      <td>233.0</td>\n",
       "      <td>81</td>\n",
       "      <td>10.49</td>\n",
       "      <td>9.9</td>\n",
       "      <td>3</td>\n",
       "      <td>2.67</td>\n",
       "      <td>2</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>NJ</td>\n",
       "      <td>163</td>\n",
       "      <td>415</td>\n",
       "      <td>419-2100</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>95</td>\n",
       "      <td>13.94</td>\n",
       "      <td>...</td>\n",
       "      <td>103</td>\n",
       "      <td>10.64</td>\n",
       "      <td>171.3</td>\n",
       "      <td>107</td>\n",
       "      <td>7.71</td>\n",
       "      <td>8.0</td>\n",
       "      <td>4</td>\n",
       "      <td>2.16</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>NV</td>\n",
       "      <td>111</td>\n",
       "      <td>415</td>\n",
       "      <td>341-8937</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>304.6</td>\n",
       "      <td>56</td>\n",
       "      <td>51.78</td>\n",
       "      <td>...</td>\n",
       "      <td>101</td>\n",
       "      <td>13.40</td>\n",
       "      <td>188.2</td>\n",
       "      <td>116</td>\n",
       "      <td>8.47</td>\n",
       "      <td>12.4</td>\n",
       "      <td>1</td>\n",
       "      <td>3.35</td>\n",
       "      <td>1</td>\n",
       "      <td>True.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>AL</td>\n",
       "      <td>117</td>\n",
       "      <td>415</td>\n",
       "      <td>410-6396</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>198.5</td>\n",
       "      <td>75</td>\n",
       "      <td>33.75</td>\n",
       "      <td>...</td>\n",
       "      <td>92</td>\n",
       "      <td>15.28</td>\n",
       "      <td>234.1</td>\n",
       "      <td>119</td>\n",
       "      <td>10.53</td>\n",
       "      <td>10.6</td>\n",
       "      <td>6</td>\n",
       "      <td>2.86</td>\n",
       "      <td>0</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>LA</td>\n",
       "      <td>85</td>\n",
       "      <td>408</td>\n",
       "      <td>409-7595</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>209.1</td>\n",
       "      <td>57</td>\n",
       "      <td>35.55</td>\n",
       "      <td>...</td>\n",
       "      <td>111</td>\n",
       "      <td>9.41</td>\n",
       "      <td>113.3</td>\n",
       "      <td>113</td>\n",
       "      <td>5.10</td>\n",
       "      <td>12.8</td>\n",
       "      <td>4</td>\n",
       "      <td>3.46</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>FL</td>\n",
       "      <td>190</td>\n",
       "      <td>415</td>\n",
       "      <td>388-9782</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>196.1</td>\n",
       "      <td>95</td>\n",
       "      <td>33.34</td>\n",
       "      <td>...</td>\n",
       "      <td>88</td>\n",
       "      <td>19.41</td>\n",
       "      <td>243.6</td>\n",
       "      <td>95</td>\n",
       "      <td>10.96</td>\n",
       "      <td>7.6</td>\n",
       "      <td>3</td>\n",
       "      <td>2.05</td>\n",
       "      <td>3</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>WY</td>\n",
       "      <td>114</td>\n",
       "      <td>415</td>\n",
       "      <td>369-7164</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>178.3</td>\n",
       "      <td>86</td>\n",
       "      <td>30.31</td>\n",
       "      <td>...</td>\n",
       "      <td>99</td>\n",
       "      <td>15.00</td>\n",
       "      <td>187.1</td>\n",
       "      <td>83</td>\n",
       "      <td>8.42</td>\n",
       "      <td>13.8</td>\n",
       "      <td>2</td>\n",
       "      <td>3.73</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>NE</td>\n",
       "      <td>135</td>\n",
       "      <td>415</td>\n",
       "      <td>332-1979</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>181.8</td>\n",
       "      <td>92</td>\n",
       "      <td>30.91</td>\n",
       "      <td>...</td>\n",
       "      <td>63</td>\n",
       "      <td>13.57</td>\n",
       "      <td>232.4</td>\n",
       "      <td>78</td>\n",
       "      <td>10.46</td>\n",
       "      <td>7.0</td>\n",
       "      <td>6</td>\n",
       "      <td>1.89</td>\n",
       "      <td>0</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>171</th>\n",
       "      <td>AL</td>\n",
       "      <td>97</td>\n",
       "      <td>415</td>\n",
       "      <td>349-6216</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>164.3</td>\n",
       "      <td>106</td>\n",
       "      <td>27.93</td>\n",
       "      <td>...</td>\n",
       "      <td>97</td>\n",
       "      <td>15.50</td>\n",
       "      <td>183.9</td>\n",
       "      <td>93</td>\n",
       "      <td>8.28</td>\n",
       "      <td>12.1</td>\n",
       "      <td>2</td>\n",
       "      <td>3.27</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>IN</td>\n",
       "      <td>185</td>\n",
       "      <td>415</td>\n",
       "      <td>399-2948</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>89.4</td>\n",
       "      <td>77</td>\n",
       "      <td>15.20</td>\n",
       "      <td>...</td>\n",
       "      <td>128</td>\n",
       "      <td>24.56</td>\n",
       "      <td>162.9</td>\n",
       "      <td>93</td>\n",
       "      <td>7.33</td>\n",
       "      <td>10.4</td>\n",
       "      <td>2</td>\n",
       "      <td>2.81</td>\n",
       "      <td>3</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>VA</td>\n",
       "      <td>130</td>\n",
       "      <td>415</td>\n",
       "      <td>358-6530</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>138.7</td>\n",
       "      <td>68</td>\n",
       "      <td>23.58</td>\n",
       "      <td>...</td>\n",
       "      <td>102</td>\n",
       "      <td>17.48</td>\n",
       "      <td>231.2</td>\n",
       "      <td>108</td>\n",
       "      <td>10.40</td>\n",
       "      <td>13.6</td>\n",
       "      <td>3</td>\n",
       "      <td>3.67</td>\n",
       "      <td>2</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>177</th>\n",
       "      <td>ID</td>\n",
       "      <td>139</td>\n",
       "      <td>408</td>\n",
       "      <td>354-7753</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>187.4</td>\n",
       "      <td>86</td>\n",
       "      <td>31.86</td>\n",
       "      <td>...</td>\n",
       "      <td>116</td>\n",
       "      <td>14.39</td>\n",
       "      <td>153.4</td>\n",
       "      <td>88</td>\n",
       "      <td>6.90</td>\n",
       "      <td>11.7</td>\n",
       "      <td>3</td>\n",
       "      <td>3.16</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>178</th>\n",
       "      <td>DE</td>\n",
       "      <td>12</td>\n",
       "      <td>415</td>\n",
       "      <td>405-8712</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>206.1</td>\n",
       "      <td>105</td>\n",
       "      <td>35.04</td>\n",
       "      <td>...</td>\n",
       "      <td>104</td>\n",
       "      <td>20.96</td>\n",
       "      <td>254.6</td>\n",
       "      <td>83</td>\n",
       "      <td>11.46</td>\n",
       "      <td>12.1</td>\n",
       "      <td>7</td>\n",
       "      <td>3.27</td>\n",
       "      <td>2</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180</th>\n",
       "      <td>WY</td>\n",
       "      <td>63</td>\n",
       "      <td>415</td>\n",
       "      <td>385-9991</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>120.1</td>\n",
       "      <td>103</td>\n",
       "      <td>20.42</td>\n",
       "      <td>...</td>\n",
       "      <td>132</td>\n",
       "      <td>15.23</td>\n",
       "      <td>127.3</td>\n",
       "      <td>82</td>\n",
       "      <td>5.73</td>\n",
       "      <td>6.3</td>\n",
       "      <td>4</td>\n",
       "      <td>1.70</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>184</th>\n",
       "      <td>TX</td>\n",
       "      <td>98</td>\n",
       "      <td>408</td>\n",
       "      <td>339-9316</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>158.5</td>\n",
       "      <td>90</td>\n",
       "      <td>26.95</td>\n",
       "      <td>...</td>\n",
       "      <td>67</td>\n",
       "      <td>21.62</td>\n",
       "      <td>178.4</td>\n",
       "      <td>104</td>\n",
       "      <td>8.03</td>\n",
       "      <td>14.8</td>\n",
       "      <td>5</td>\n",
       "      <td>4.00</td>\n",
       "      <td>2</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>186</th>\n",
       "      <td>NY</td>\n",
       "      <td>101</td>\n",
       "      <td>415</td>\n",
       "      <td>418-8226</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>229.8</td>\n",
       "      <td>97</td>\n",
       "      <td>39.07</td>\n",
       "      <td>...</td>\n",
       "      <td>133</td>\n",
       "      <td>18.51</td>\n",
       "      <td>243.5</td>\n",
       "      <td>53</td>\n",
       "      <td>10.96</td>\n",
       "      <td>8.9</td>\n",
       "      <td>2</td>\n",
       "      <td>2.40</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>187</th>\n",
       "      <td>OH</td>\n",
       "      <td>163</td>\n",
       "      <td>415</td>\n",
       "      <td>350-7491</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>241.6</td>\n",
       "      <td>102</td>\n",
       "      <td>41.07</td>\n",
       "      <td>...</td>\n",
       "      <td>100</td>\n",
       "      <td>11.81</td>\n",
       "      <td>148.8</td>\n",
       "      <td>129</td>\n",
       "      <td>6.70</td>\n",
       "      <td>9.8</td>\n",
       "      <td>6</td>\n",
       "      <td>2.65</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>192</th>\n",
       "      <td>TX</td>\n",
       "      <td>104</td>\n",
       "      <td>415</td>\n",
       "      <td>378-9221</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>261.2</td>\n",
       "      <td>81</td>\n",
       "      <td>44.40</td>\n",
       "      <td>...</td>\n",
       "      <td>130</td>\n",
       "      <td>17.77</td>\n",
       "      <td>281.1</td>\n",
       "      <td>121</td>\n",
       "      <td>12.65</td>\n",
       "      <td>11.3</td>\n",
       "      <td>1</td>\n",
       "      <td>3.05</td>\n",
       "      <td>2</td>\n",
       "      <td>True.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193</th>\n",
       "      <td>TN</td>\n",
       "      <td>96</td>\n",
       "      <td>415</td>\n",
       "      <td>350-5500</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>264.6</td>\n",
       "      <td>117</td>\n",
       "      <td>44.98</td>\n",
       "      <td>...</td>\n",
       "      <td>121</td>\n",
       "      <td>22.45</td>\n",
       "      <td>77.1</td>\n",
       "      <td>89</td>\n",
       "      <td>3.47</td>\n",
       "      <td>8.1</td>\n",
       "      <td>4</td>\n",
       "      <td>2.19</td>\n",
       "      <td>0</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>IN</td>\n",
       "      <td>66</td>\n",
       "      <td>408</td>\n",
       "      <td>400-7057</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>241.7</td>\n",
       "      <td>112</td>\n",
       "      <td>41.09</td>\n",
       "      <td>...</td>\n",
       "      <td>78</td>\n",
       "      <td>21.39</td>\n",
       "      <td>105.0</td>\n",
       "      <td>82</td>\n",
       "      <td>4.72</td>\n",
       "      <td>11.3</td>\n",
       "      <td>2</td>\n",
       "      <td>3.05</td>\n",
       "      <td>2</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>199</th>\n",
       "      <td>OK</td>\n",
       "      <td>127</td>\n",
       "      <td>408</td>\n",
       "      <td>345-3986</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>212.9</td>\n",
       "      <td>92</td>\n",
       "      <td>36.19</td>\n",
       "      <td>...</td>\n",
       "      <td>124</td>\n",
       "      <td>22.11</td>\n",
       "      <td>177.6</td>\n",
       "      <td>85</td>\n",
       "      <td>7.99</td>\n",
       "      <td>8.6</td>\n",
       "      <td>2</td>\n",
       "      <td>2.32</td>\n",
       "      <td>2</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>204</th>\n",
       "      <td>HI</td>\n",
       "      <td>17</td>\n",
       "      <td>408</td>\n",
       "      <td>413-7801</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>168.5</td>\n",
       "      <td>102</td>\n",
       "      <td>28.65</td>\n",
       "      <td>...</td>\n",
       "      <td>130</td>\n",
       "      <td>25.26</td>\n",
       "      <td>244.7</td>\n",
       "      <td>117</td>\n",
       "      <td>11.01</td>\n",
       "      <td>8.8</td>\n",
       "      <td>6</td>\n",
       "      <td>2.38</td>\n",
       "      <td>3</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>205</th>\n",
       "      <td>DC</td>\n",
       "      <td>165</td>\n",
       "      <td>415</td>\n",
       "      <td>372-7067</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>81.4</td>\n",
       "      <td>110</td>\n",
       "      <td>13.84</td>\n",
       "      <td>...</td>\n",
       "      <td>150</td>\n",
       "      <td>22.41</td>\n",
       "      <td>219.7</td>\n",
       "      <td>107</td>\n",
       "      <td>9.89</td>\n",
       "      <td>12.2</td>\n",
       "      <td>3</td>\n",
       "      <td>3.29</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>209</th>\n",
       "      <td>MN</td>\n",
       "      <td>93</td>\n",
       "      <td>415</td>\n",
       "      <td>393-4261</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>172.0</td>\n",
       "      <td>80</td>\n",
       "      <td>29.24</td>\n",
       "      <td>...</td>\n",
       "      <td>76</td>\n",
       "      <td>18.62</td>\n",
       "      <td>169.8</td>\n",
       "      <td>108</td>\n",
       "      <td>7.64</td>\n",
       "      <td>10.3</td>\n",
       "      <td>3</td>\n",
       "      <td>2.78</td>\n",
       "      <td>0</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>211</th>\n",
       "      <td>WA</td>\n",
       "      <td>106</td>\n",
       "      <td>415</td>\n",
       "      <td>342-3748</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>149.7</td>\n",
       "      <td>114</td>\n",
       "      <td>25.45</td>\n",
       "      <td>...</td>\n",
       "      <td>72</td>\n",
       "      <td>8.88</td>\n",
       "      <td>227.9</td>\n",
       "      <td>87</td>\n",
       "      <td>10.26</td>\n",
       "      <td>9.0</td>\n",
       "      <td>2</td>\n",
       "      <td>2.43</td>\n",
       "      <td>2</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>212</th>\n",
       "      <td>AL</td>\n",
       "      <td>92</td>\n",
       "      <td>408</td>\n",
       "      <td>378-2599</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>185.8</td>\n",
       "      <td>61</td>\n",
       "      <td>31.59</td>\n",
       "      <td>...</td>\n",
       "      <td>131</td>\n",
       "      <td>10.04</td>\n",
       "      <td>257.5</td>\n",
       "      <td>70</td>\n",
       "      <td>11.59</td>\n",
       "      <td>11.8</td>\n",
       "      <td>4</td>\n",
       "      <td>3.19</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>213</th>\n",
       "      <td>WA</td>\n",
       "      <td>93</td>\n",
       "      <td>415</td>\n",
       "      <td>329-4592</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>214.4</td>\n",
       "      <td>112</td>\n",
       "      <td>36.45</td>\n",
       "      <td>...</td>\n",
       "      <td>97</td>\n",
       "      <td>22.23</td>\n",
       "      <td>280.8</td>\n",
       "      <td>112</td>\n",
       "      <td>12.64</td>\n",
       "      <td>14.8</td>\n",
       "      <td>3</td>\n",
       "      <td>4.00</td>\n",
       "      <td>0</td>\n",
       "      <td>True.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>214</th>\n",
       "      <td>NM</td>\n",
       "      <td>124</td>\n",
       "      <td>408</td>\n",
       "      <td>337-2326</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>244.6</td>\n",
       "      <td>91</td>\n",
       "      <td>41.58</td>\n",
       "      <td>...</td>\n",
       "      <td>70</td>\n",
       "      <td>10.63</td>\n",
       "      <td>303.4</td>\n",
       "      <td>104</td>\n",
       "      <td>13.65</td>\n",
       "      <td>12.0</td>\n",
       "      <td>5</td>\n",
       "      <td>3.24</td>\n",
       "      <td>0</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>215</th>\n",
       "      <td>MA</td>\n",
       "      <td>117</td>\n",
       "      <td>408</td>\n",
       "      <td>363-4527</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>302.6</td>\n",
       "      <td>83</td>\n",
       "      <td>51.44</td>\n",
       "      <td>...</td>\n",
       "      <td>106</td>\n",
       "      <td>14.20</td>\n",
       "      <td>209.8</td>\n",
       "      <td>79</td>\n",
       "      <td>9.44</td>\n",
       "      <td>10.4</td>\n",
       "      <td>7</td>\n",
       "      <td>2.81</td>\n",
       "      <td>1</td>\n",
       "      <td>True.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>218</th>\n",
       "      <td>LA</td>\n",
       "      <td>59</td>\n",
       "      <td>415</td>\n",
       "      <td>383-3933</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>119.0</td>\n",
       "      <td>119</td>\n",
       "      <td>20.23</td>\n",
       "      <td>...</td>\n",
       "      <td>115</td>\n",
       "      <td>11.43</td>\n",
       "      <td>298.6</td>\n",
       "      <td>75</td>\n",
       "      <td>13.44</td>\n",
       "      <td>9.0</td>\n",
       "      <td>6</td>\n",
       "      <td>2.43</td>\n",
       "      <td>2</td>\n",
       "      <td>True.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>219</th>\n",
       "      <td>HI</td>\n",
       "      <td>103</td>\n",
       "      <td>415</td>\n",
       "      <td>403-3365</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>245.8</td>\n",
       "      <td>116</td>\n",
       "      <td>41.79</td>\n",
       "      <td>...</td>\n",
       "      <td>97</td>\n",
       "      <td>11.51</td>\n",
       "      <td>190.9</td>\n",
       "      <td>73</td>\n",
       "      <td>8.59</td>\n",
       "      <td>9.9</td>\n",
       "      <td>7</td>\n",
       "      <td>2.67</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>220</th>\n",
       "      <td>FL</td>\n",
       "      <td>101</td>\n",
       "      <td>408</td>\n",
       "      <td>383-6272</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>131.0</td>\n",
       "      <td>148</td>\n",
       "      <td>22.27</td>\n",
       "      <td>...</td>\n",
       "      <td>126</td>\n",
       "      <td>20.20</td>\n",
       "      <td>281.3</td>\n",
       "      <td>111</td>\n",
       "      <td>12.66</td>\n",
       "      <td>12.6</td>\n",
       "      <td>4</td>\n",
       "      <td>3.40</td>\n",
       "      <td>3</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>226</th>\n",
       "      <td>MN</td>\n",
       "      <td>126</td>\n",
       "      <td>415</td>\n",
       "      <td>340-9582</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>152.4</td>\n",
       "      <td>94</td>\n",
       "      <td>25.91</td>\n",
       "      <td>...</td>\n",
       "      <td>91</td>\n",
       "      <td>14.13</td>\n",
       "      <td>199.2</td>\n",
       "      <td>84</td>\n",
       "      <td>8.96</td>\n",
       "      <td>10.2</td>\n",
       "      <td>1</td>\n",
       "      <td>2.75</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>228</th>\n",
       "      <td>MA</td>\n",
       "      <td>158</td>\n",
       "      <td>415</td>\n",
       "      <td>403-1671</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>214.7</td>\n",
       "      <td>112</td>\n",
       "      <td>36.50</td>\n",
       "      <td>...</td>\n",
       "      <td>115</td>\n",
       "      <td>22.35</td>\n",
       "      <td>228.9</td>\n",
       "      <td>68</td>\n",
       "      <td>10.30</td>\n",
       "      <td>11.6</td>\n",
       "      <td>2</td>\n",
       "      <td>3.13</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>229</th>\n",
       "      <td>WV</td>\n",
       "      <td>66</td>\n",
       "      <td>415</td>\n",
       "      <td>371-1011</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>180.4</td>\n",
       "      <td>99</td>\n",
       "      <td>30.67</td>\n",
       "      <td>...</td>\n",
       "      <td>114</td>\n",
       "      <td>11.48</td>\n",
       "      <td>206.0</td>\n",
       "      <td>98</td>\n",
       "      <td>9.27</td>\n",
       "      <td>9.5</td>\n",
       "      <td>6</td>\n",
       "      <td>2.57</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>230</th>\n",
       "      <td>MI</td>\n",
       "      <td>82</td>\n",
       "      <td>415</td>\n",
       "      <td>407-1032</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>164.1</td>\n",
       "      <td>84</td>\n",
       "      <td>27.90</td>\n",
       "      <td>...</td>\n",
       "      <td>109</td>\n",
       "      <td>27.00</td>\n",
       "      <td>241.5</td>\n",
       "      <td>87</td>\n",
       "      <td>10.87</td>\n",
       "      <td>13.3</td>\n",
       "      <td>4</td>\n",
       "      <td>3.59</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>234</th>\n",
       "      <td>WA</td>\n",
       "      <td>62</td>\n",
       "      <td>415</td>\n",
       "      <td>394-9346</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>166.9</td>\n",
       "      <td>76</td>\n",
       "      <td>28.37</td>\n",
       "      <td>...</td>\n",
       "      <td>113</td>\n",
       "      <td>19.01</td>\n",
       "      <td>188.9</td>\n",
       "      <td>87</td>\n",
       "      <td>8.50</td>\n",
       "      <td>14.2</td>\n",
       "      <td>5</td>\n",
       "      <td>3.83</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>239</th>\n",
       "      <td>CO</td>\n",
       "      <td>36</td>\n",
       "      <td>415</td>\n",
       "      <td>337-5061</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>245.0</td>\n",
       "      <td>119</td>\n",
       "      <td>41.65</td>\n",
       "      <td>...</td>\n",
       "      <td>91</td>\n",
       "      <td>16.62</td>\n",
       "      <td>165.7</td>\n",
       "      <td>87</td>\n",
       "      <td>7.46</td>\n",
       "      <td>7.8</td>\n",
       "      <td>7</td>\n",
       "      <td>2.11</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    state  account length  area code phone number international plan  \\\n",
       "3      NM              99        415     418-9100                 no   \n",
       "4      SC             108        415     413-3643                 no   \n",
       "5      IA             117        415     375-6180                 no   \n",
       "7      LA              94        408     359-9881                 no   \n",
       "11     TX             140        415     353-1755                 no   \n",
       "13     ND             108        415     371-5951                 no   \n",
       "14     DE              60        408     381-5937                 no   \n",
       "15     MN              96        408     357-1784                 no   \n",
       "17     MN              75        415     400-5627                 no   \n",
       "24     OH              69        415     328-6124                 no   \n",
       "27     ID              72        415     413-5754                yes   \n",
       "29     MD              68        408     359-5139                 no   \n",
       "31     AZ              97        415     416-8332                 no   \n",
       "32     IA              92        415     350-4349                 no   \n",
       "36     CA              73        415     378-8356                 no   \n",
       "38     NE             161        415     329-1253                 no   \n",
       "40     OR             194        415     403-2167                 no   \n",
       "45     ME              70        415     390-1881                 no   \n",
       "46     NM              72        415     412-5272                 no   \n",
       "47     WV              66        415     381-5680                 no   \n",
       "51     HI              63        415     330-7635                 no   \n",
       "55     OR             159        408     385-9556                 no   \n",
       "59     UT              98        415     364-1015                 no   \n",
       "60     NJ             163        415     419-2100                 no   \n",
       "62     NV             111        415     341-8937                 no   \n",
       "65     AL             117        415     410-6396                 no   \n",
       "66     LA              85        408     409-7595                 no   \n",
       "68     FL             190        415     388-9782                 no   \n",
       "72     WY             114        415     369-7164                 no   \n",
       "73     NE             135        415     332-1979                 no   \n",
       "..    ...             ...        ...          ...                ...   \n",
       "171    AL              97        415     349-6216                 no   \n",
       "172    IN             185        415     399-2948                 no   \n",
       "175    VA             130        415     358-6530                 no   \n",
       "177    ID             139        408     354-7753                 no   \n",
       "178    DE              12        415     405-8712                 no   \n",
       "180    WY              63        415     385-9991                 no   \n",
       "184    TX              98        408     339-9316                 no   \n",
       "186    NY             101        415     418-8226                 no   \n",
       "187    OH             163        415     350-7491                 no   \n",
       "192    TX             104        415     378-9221                 no   \n",
       "193    TN              96        415     350-5500                 no   \n",
       "197    IN              66        408     400-7057                 no   \n",
       "199    OK             127        408     345-3986                 no   \n",
       "204    HI              17        408     413-7801                 no   \n",
       "205    DC             165        415     372-7067                yes   \n",
       "209    MN              93        415     393-4261                 no   \n",
       "211    WA             106        415     342-3748                 no   \n",
       "212    AL              92        408     378-2599                 no   \n",
       "213    WA              93        415     329-4592                 no   \n",
       "214    NM             124        408     337-2326                 no   \n",
       "215    MA             117        408     363-4527                 no   \n",
       "218    LA              59        415     383-3933                 no   \n",
       "219    HI             103        415     403-3365                 no   \n",
       "220    FL             101        408     383-6272                 no   \n",
       "226    MN             126        415     340-9582                 no   \n",
       "228    MA             158        415     403-1671                 no   \n",
       "229    WV              66        415     371-1011                 no   \n",
       "230    MI              82        415     407-1032                 no   \n",
       "234    WA              62        415     394-9346                 no   \n",
       "239    CO              36        415     337-5061                yes   \n",
       "\n",
       "    voice mail plan  number vmail messages  total day minutes  \\\n",
       "3                no                      0              216.8   \n",
       "4                no                      0              197.4   \n",
       "5                no                      0              226.5   \n",
       "7                no                      0              157.5   \n",
       "11               no                      0               93.2   \n",
       "13               no                      0              112.6   \n",
       "14               no                      0              207.3   \n",
       "15               no                      0              208.1   \n",
       "17               no                      0              225.3   \n",
       "24               no                      0              229.2   \n",
       "27               no                      0              101.0   \n",
       "29               no                      0              150.4   \n",
       "31               no                      0              100.8   \n",
       "32               no                      0              138.1   \n",
       "36               no                      0              137.6   \n",
       "38               no                      0              166.2   \n",
       "40               no                      0              258.3   \n",
       "45               no                      0              169.1   \n",
       "46               no                      0              190.7   \n",
       "47               no                      0              239.6   \n",
       "51               no                      0              112.5   \n",
       "55               no                      0              180.1   \n",
       "59               no                      0              211.9   \n",
       "60               no                      0               82.0   \n",
       "62               no                      0              304.6   \n",
       "65               no                      0              198.5   \n",
       "66               no                      0              209.1   \n",
       "68               no                      0              196.1   \n",
       "72               no                      0              178.3   \n",
       "73               no                      0              181.8   \n",
       "..              ...                    ...                ...   \n",
       "171              no                      0              164.3   \n",
       "172              no                      0               89.4   \n",
       "175              no                      0              138.7   \n",
       "177              no                      0              187.4   \n",
       "178              no                      0              206.1   \n",
       "180              no                      0              120.1   \n",
       "184              no                      0              158.5   \n",
       "186              no                      0              229.8   \n",
       "187              no                      0              241.6   \n",
       "192              no                      0              261.2   \n",
       "193              no                      0              264.6   \n",
       "197              no                      0              241.7   \n",
       "199              no                      0              212.9   \n",
       "204              no                      0              168.5   \n",
       "205              no                      0               81.4   \n",
       "209              no                      0              172.0   \n",
       "211              no                      0              149.7   \n",
       "212              no                      0              185.8   \n",
       "213              no                      0              214.4   \n",
       "214              no                      0              244.6   \n",
       "215              no                      0              302.6   \n",
       "218              no                      0              119.0   \n",
       "219              no                      0              245.8   \n",
       "220              no                      0              131.0   \n",
       "226              no                      0              152.4   \n",
       "228              no                      0              214.7   \n",
       "229              no                      0              180.4   \n",
       "230              no                      0              164.1   \n",
       "234              no                      0              166.9   \n",
       "239              no                      0              245.0   \n",
       "\n",
       "     total day calls  total day charge   ...     total eve calls  \\\n",
       "3                123             36.86   ...                  88   \n",
       "4                 78             33.56   ...                 101   \n",
       "5                 85             38.51   ...                  68   \n",
       "7                 97             26.78   ...                 112   \n",
       "11               109             15.84   ...                 116   \n",
       "13                86             19.14   ...                 101   \n",
       "14                77             35.24   ...                 105   \n",
       "15                93             35.38   ...                 107   \n",
       "17               124             38.30   ...                  81   \n",
       "24               111             38.96   ...                 104   \n",
       "27               110             17.17   ...                  70   \n",
       "29               106             25.57   ...                 131   \n",
       "31                74             17.14   ...                  88   \n",
       "32               131             23.48   ...                 128   \n",
       "36               113             23.39   ...                  75   \n",
       "38               125             28.25   ...                  78   \n",
       "40                76             43.91   ...                  88   \n",
       "45                48             28.75   ...                  62   \n",
       "46               111             32.42   ...                 103   \n",
       "47               120             40.73   ...                 110   \n",
       "51                95             19.13   ...                  67   \n",
       "55               103             30.62   ...                 148   \n",
       "59                65             36.02   ...                  95   \n",
       "60                95             13.94   ...                 103   \n",
       "62                56             51.78   ...                 101   \n",
       "65                75             33.75   ...                  92   \n",
       "66                57             35.55   ...                 111   \n",
       "68                95             33.34   ...                  88   \n",
       "72                86             30.31   ...                  99   \n",
       "73                92             30.91   ...                  63   \n",
       "..               ...               ...   ...                 ...   \n",
       "171              106             27.93   ...                  97   \n",
       "172               77             15.20   ...                 128   \n",
       "175               68             23.58   ...                 102   \n",
       "177               86             31.86   ...                 116   \n",
       "178              105             35.04   ...                 104   \n",
       "180              103             20.42   ...                 132   \n",
       "184               90             26.95   ...                  67   \n",
       "186               97             39.07   ...                 133   \n",
       "187              102             41.07   ...                 100   \n",
       "192               81             44.40   ...                 130   \n",
       "193              117             44.98   ...                 121   \n",
       "197              112             41.09   ...                  78   \n",
       "199               92             36.19   ...                 124   \n",
       "204              102             28.65   ...                 130   \n",
       "205              110             13.84   ...                 150   \n",
       "209               80             29.24   ...                  76   \n",
       "211              114             25.45   ...                  72   \n",
       "212               61             31.59   ...                 131   \n",
       "213              112             36.45   ...                  97   \n",
       "214               91             41.58   ...                  70   \n",
       "215               83             51.44   ...                 106   \n",
       "218              119             20.23   ...                 115   \n",
       "219              116             41.79   ...                  97   \n",
       "220              148             22.27   ...                 126   \n",
       "226               94             25.91   ...                  91   \n",
       "228              112             36.50   ...                 115   \n",
       "229               99             30.67   ...                 114   \n",
       "230               84             27.90   ...                 109   \n",
       "234               76             28.37   ...                 113   \n",
       "239              119             41.65   ...                  91   \n",
       "\n",
       "     total eve charge  total night minutes  total night calls  \\\n",
       "3               10.74                220.6                 82   \n",
       "4               10.54                204.5                107   \n",
       "5               12.04                223.0                 90   \n",
       "7               19.08                310.8                106   \n",
       "11              16.80                219.8                 94   \n",
       "13               9.77                177.8                119   \n",
       "14              17.67                108.2                 89   \n",
       "15              16.08                279.6                 90   \n",
       "17              19.38                254.3                106   \n",
       "24              14.05                235.1                 80   \n",
       "27              20.40                333.5                105   \n",
       "29              16.92                109.7                103   \n",
       "31              19.87                208.7                 79   \n",
       "32              14.93                192.7                119   \n",
       "36              15.27                172.8                 71   \n",
       "38              23.75                181.0                 85   \n",
       "40              26.01                241.8                106   \n",
       "45              18.68                193.5                105   \n",
       "46              20.54                278.1                 95   \n",
       "47              19.58                153.0                 82   \n",
       "51              17.95                227.5                 96   \n",
       "55              16.44                251.2                109   \n",
       "59              19.09                233.0                 81   \n",
       "60              10.64                171.3                107   \n",
       "62              13.40                188.2                116   \n",
       "65              15.28                234.1                119   \n",
       "66               9.41                113.3                113   \n",
       "68              19.41                243.6                 95   \n",
       "72              15.00                187.1                 83   \n",
       "73              13.57                232.4                 78   \n",
       "..                ...                  ...                ...   \n",
       "171             15.50                183.9                 93   \n",
       "172             24.56                162.9                 93   \n",
       "175             17.48                231.2                108   \n",
       "177             14.39                153.4                 88   \n",
       "178             20.96                254.6                 83   \n",
       "180             15.23                127.3                 82   \n",
       "184             21.62                178.4                104   \n",
       "186             18.51                243.5                 53   \n",
       "187             11.81                148.8                129   \n",
       "192             17.77                281.1                121   \n",
       "193             22.45                 77.1                 89   \n",
       "197             21.39                105.0                 82   \n",
       "199             22.11                177.6                 85   \n",
       "204             25.26                244.7                117   \n",
       "205             22.41                219.7                107   \n",
       "209             18.62                169.8                108   \n",
       "211              8.88                227.9                 87   \n",
       "212             10.04                257.5                 70   \n",
       "213             22.23                280.8                112   \n",
       "214             10.63                303.4                104   \n",
       "215             14.20                209.8                 79   \n",
       "218             11.43                298.6                 75   \n",
       "219             11.51                190.9                 73   \n",
       "220             20.20                281.3                111   \n",
       "226             14.13                199.2                 84   \n",
       "228             22.35                228.9                 68   \n",
       "229             11.48                206.0                 98   \n",
       "230             27.00                241.5                 87   \n",
       "234             19.01                188.9                 87   \n",
       "239             16.62                165.7                 87   \n",
       "\n",
       "     total night charge  total intl minutes  total intl calls  \\\n",
       "3                  9.93                15.7                 2   \n",
       "4                  9.20                 7.7                 4   \n",
       "5                 10.04                 6.9                 5   \n",
       "7                 13.99                11.1                 6   \n",
       "11                 9.89                10.5                 2   \n",
       "13                 8.00                 7.2                 6   \n",
       "14                 4.87                12.9                 5   \n",
       "15                12.58                 7.4                 2   \n",
       "17                11.44                11.7                 3   \n",
       "24                10.58                 5.2                 5   \n",
       "27                15.01                11.1                 6   \n",
       "29                 4.94                12.3                 3   \n",
       "31                 9.39                12.6                 3   \n",
       "32                 8.67                10.0                 3   \n",
       "36                 7.78                10.7                 2   \n",
       "38                 8.15                13.4                 6   \n",
       "40                10.88                13.6                 4   \n",
       "45                 8.71                10.7                 8   \n",
       "46                12.51                 4.4                 3   \n",
       "47                 6.89                 8.6                 3   \n",
       "51                10.24                11.1                 8   \n",
       "55                11.30                13.4                 5   \n",
       "59                10.49                 9.9                 3   \n",
       "60                 7.71                 8.0                 4   \n",
       "62                 8.47                12.4                 1   \n",
       "65                10.53                10.6                 6   \n",
       "66                 5.10                12.8                 4   \n",
       "68                10.96                 7.6                 3   \n",
       "72                 8.42                13.8                 2   \n",
       "73                10.46                 7.0                 6   \n",
       "..                  ...                 ...               ...   \n",
       "171                8.28                12.1                 2   \n",
       "172                7.33                10.4                 2   \n",
       "175               10.40                13.6                 3   \n",
       "177                6.90                11.7                 3   \n",
       "178               11.46                12.1                 7   \n",
       "180                5.73                 6.3                 4   \n",
       "184                8.03                14.8                 5   \n",
       "186               10.96                 8.9                 2   \n",
       "187                6.70                 9.8                 6   \n",
       "192               12.65                11.3                 1   \n",
       "193                3.47                 8.1                 4   \n",
       "197                4.72                11.3                 2   \n",
       "199                7.99                 8.6                 2   \n",
       "204               11.01                 8.8                 6   \n",
       "205                9.89                12.2                 3   \n",
       "209                7.64                10.3                 3   \n",
       "211               10.26                 9.0                 2   \n",
       "212               11.59                11.8                 4   \n",
       "213               12.64                14.8                 3   \n",
       "214               13.65                12.0                 5   \n",
       "215                9.44                10.4                 7   \n",
       "218               13.44                 9.0                 6   \n",
       "219                8.59                 9.9                 7   \n",
       "220               12.66                12.6                 4   \n",
       "226                8.96                10.2                 1   \n",
       "228               10.30                11.6                 2   \n",
       "229                9.27                 9.5                 6   \n",
       "230               10.87                13.3                 4   \n",
       "234                8.50                14.2                 5   \n",
       "239                7.46                 7.8                 7   \n",
       "\n",
       "     total intl charge  number customer service calls    Churn  \n",
       "3                 4.24                              1   False.  \n",
       "4                 2.08                              2   False.  \n",
       "5                 1.86                              1   False.  \n",
       "7                 3.00                              0   False.  \n",
       "11                2.84                              1   False.  \n",
       "13                1.94                              3   False.  \n",
       "14                3.48                              1   False.  \n",
       "15                2.00                              1   False.  \n",
       "17                3.16                              1   False.  \n",
       "24                1.40                              1   False.  \n",
       "27                3.00                              0   False.  \n",
       "29                3.32                              3   False.  \n",
       "31                3.40                              2   False.  \n",
       "32                2.70                              3   False.  \n",
       "36                2.89                              1    True.  \n",
       "38                3.62                              1   False.  \n",
       "40                3.67                              1    True.  \n",
       "45                2.89                              3   False.  \n",
       "46                1.19                              1   False.  \n",
       "47                2.32                              1   False.  \n",
       "51                3.00                              0   False.  \n",
       "55                3.62                              0   False.  \n",
       "59                2.67                              2   False.  \n",
       "60                2.16                              1   False.  \n",
       "62                3.35                              1    True.  \n",
       "65                2.86                              0   False.  \n",
       "66                3.46                              1   False.  \n",
       "68                2.05                              3   False.  \n",
       "72                3.73                              1   False.  \n",
       "73                1.89                              0   False.  \n",
       "..                 ...                            ...      ...  \n",
       "171               3.27                              1   False.  \n",
       "172               2.81                              3   False.  \n",
       "175               3.67                              2   False.  \n",
       "177               3.16                              1   False.  \n",
       "178               3.27                              2   False.  \n",
       "180               1.70                              1   False.  \n",
       "184               4.00                              2   False.  \n",
       "186               2.40                              1   False.  \n",
       "187               2.65                              1   False.  \n",
       "192               3.05                              2    True.  \n",
       "193               2.19                              0   False.  \n",
       "197               3.05                              2   False.  \n",
       "199               2.32                              2   False.  \n",
       "204               2.38                              3   False.  \n",
       "205               3.29                              1   False.  \n",
       "209               2.78                              0   False.  \n",
       "211               2.43                              2   False.  \n",
       "212               3.19                              1   False.  \n",
       "213               4.00                              0    True.  \n",
       "214               3.24                              0   False.  \n",
       "215               2.81                              1    True.  \n",
       "218               2.43                              2    True.  \n",
       "219               2.67                              1   False.  \n",
       "220               3.40                              3   False.  \n",
       "226               2.75                              1   False.  \n",
       "228               3.13                              1   False.  \n",
       "229               2.57                              1   False.  \n",
       "230               3.59                              1   False.  \n",
       "234               3.83                              1   False.  \n",
       "239               2.11                              1   False.  \n",
       "\n",
       "[100 rows x 21 columns]"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Test.head(100)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Lets change Categorical Data into Numeric Codes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Lets create a function!\n",
    "def cat_to_code(data , cat_columns):\n",
    "    for col in cat_columns:\n",
    "        data[col]=data[col].astype(\"category\")\n",
    "        data[col]=data[col].cat.codes\n",
    "    return data\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "scrolled": true
   },
   "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",
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       "    .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>state</th>\n",
       "      <th>account length</th>\n",
       "      <th>area code</th>\n",
       "      <th>international plan</th>\n",
       "      <th>voice mail plan</th>\n",
       "      <th>number vmail messages</th>\n",
       "      <th>total day minutes</th>\n",
       "      <th>total day calls</th>\n",
       "      <th>total day charge</th>\n",
       "      <th>total eve minutes</th>\n",
       "      <th>total eve calls</th>\n",
       "      <th>total eve charge</th>\n",
       "      <th>total night minutes</th>\n",
       "      <th>total night calls</th>\n",
       "      <th>total night charge</th>\n",
       "      <th>total intl minutes</th>\n",
       "      <th>total intl calls</th>\n",
       "      <th>total intl charge</th>\n",
       "      <th>number customer service calls</th>\n",
       "      <th>Churn</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>11</td>\n",
       "      <td>101</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>70.9</td>\n",
       "      <td>123</td>\n",
       "      <td>12.05</td>\n",
       "      <td>211.9</td>\n",
       "      <td>73</td>\n",
       "      <td>18.01</td>\n",
       "      <td>236.0</td>\n",
       "      <td>73</td>\n",
       "      <td>10.62</td>\n",
       "      <td>10.6</td>\n",
       "      <td>3</td>\n",
       "      <td>2.86</td>\n",
       "      <td>3</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>26</td>\n",
       "      <td>137</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>223.6</td>\n",
       "      <td>86</td>\n",
       "      <td>38.01</td>\n",
       "      <td>244.8</td>\n",
       "      <td>139</td>\n",
       "      <td>20.81</td>\n",
       "      <td>94.2</td>\n",
       "      <td>81</td>\n",
       "      <td>4.24</td>\n",
       "      <td>9.5</td>\n",
       "      <td>7</td>\n",
       "      <td>2.57</td>\n",
       "      <td>0</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>35</td>\n",
       "      <td>103</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>29</td>\n",
       "      <td>294.7</td>\n",
       "      <td>95</td>\n",
       "      <td>50.10</td>\n",
       "      <td>237.3</td>\n",
       "      <td>105</td>\n",
       "      <td>20.17</td>\n",
       "      <td>300.3</td>\n",
       "      <td>127</td>\n",
       "      <td>13.51</td>\n",
       "      <td>13.7</td>\n",
       "      <td>6</td>\n",
       "      <td>3.70</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>32</td>\n",
       "      <td>99</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>216.8</td>\n",
       "      <td>123</td>\n",
       "      <td>36.86</td>\n",
       "      <td>126.4</td>\n",
       "      <td>88</td>\n",
       "      <td>10.74</td>\n",
       "      <td>220.6</td>\n",
       "      <td>82</td>\n",
       "      <td>9.93</td>\n",
       "      <td>15.7</td>\n",
       "      <td>2</td>\n",
       "      <td>4.24</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>40</td>\n",
       "      <td>108</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>197.4</td>\n",
       "      <td>78</td>\n",
       "      <td>33.56</td>\n",
       "      <td>124.0</td>\n",
       "      <td>101</td>\n",
       "      <td>10.54</td>\n",
       "      <td>204.5</td>\n",
       "      <td>107</td>\n",
       "      <td>9.20</td>\n",
       "      <td>7.7</td>\n",
       "      <td>4</td>\n",
       "      <td>2.08</td>\n",
       "      <td>2</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>12</td>\n",
       "      <td>117</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>226.5</td>\n",
       "      <td>85</td>\n",
       "      <td>38.51</td>\n",
       "      <td>141.6</td>\n",
       "      <td>68</td>\n",
       "      <td>12.04</td>\n",
       "      <td>223.0</td>\n",
       "      <td>90</td>\n",
       "      <td>10.04</td>\n",
       "      <td>6.9</td>\n",
       "      <td>5</td>\n",
       "      <td>1.86</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>28</td>\n",
       "      <td>63</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>32</td>\n",
       "      <td>218.9</td>\n",
       "      <td>124</td>\n",
       "      <td>37.21</td>\n",
       "      <td>214.3</td>\n",
       "      <td>125</td>\n",
       "      <td>18.22</td>\n",
       "      <td>260.3</td>\n",
       "      <td>120</td>\n",
       "      <td>11.71</td>\n",
       "      <td>12.9</td>\n",
       "      <td>3</td>\n",
       "      <td>3.48</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>18</td>\n",
       "      <td>94</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>157.5</td>\n",
       "      <td>97</td>\n",
       "      <td>26.78</td>\n",
       "      <td>224.5</td>\n",
       "      <td>112</td>\n",
       "      <td>19.08</td>\n",
       "      <td>310.8</td>\n",
       "      <td>106</td>\n",
       "      <td>13.99</td>\n",
       "      <td>11.1</td>\n",
       "      <td>6</td>\n",
       "      <td>3.00</td>\n",
       "      <td>0</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>24</td>\n",
       "      <td>138</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>89.1</td>\n",
       "      <td>117</td>\n",
       "      <td>15.15</td>\n",
       "      <td>126.8</td>\n",
       "      <td>46</td>\n",
       "      <td>10.78</td>\n",
       "      <td>190.5</td>\n",
       "      <td>71</td>\n",
       "      <td>8.57</td>\n",
       "      <td>9.9</td>\n",
       "      <td>4</td>\n",
       "      <td>2.67</td>\n",
       "      <td>2</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>43</td>\n",
       "      <td>128</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>43</td>\n",
       "      <td>177.8</td>\n",
       "      <td>100</td>\n",
       "      <td>30.23</td>\n",
       "      <td>147.3</td>\n",
       "      <td>89</td>\n",
       "      <td>12.52</td>\n",
       "      <td>194.2</td>\n",
       "      <td>92</td>\n",
       "      <td>8.74</td>\n",
       "      <td>11.9</td>\n",
       "      <td>1</td>\n",
       "      <td>3.21</td>\n",
       "      <td>0</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2</td>\n",
       "      <td>113</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>39</td>\n",
       "      <td>209.8</td>\n",
       "      <td>77</td>\n",
       "      <td>35.67</td>\n",
       "      <td>164.1</td>\n",
       "      <td>90</td>\n",
       "      <td>13.95</td>\n",
       "      <td>159.7</td>\n",
       "      <td>100</td>\n",
       "      <td>7.19</td>\n",
       "      <td>9.0</td>\n",
       "      <td>4</td>\n",
       "      <td>2.43</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>43</td>\n",
       "      <td>140</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>93.2</td>\n",
       "      <td>109</td>\n",
       "      <td>15.84</td>\n",
       "      <td>197.6</td>\n",
       "      <td>116</td>\n",
       "      <td>16.80</td>\n",
       "      <td>219.8</td>\n",
       "      <td>94</td>\n",
       "      <td>9.89</td>\n",
       "      <td>10.5</td>\n",
       "      <td>2</td>\n",
       "      <td>2.84</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>21</td>\n",
       "      <td>102</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>228.1</td>\n",
       "      <td>86</td>\n",
       "      <td>38.78</td>\n",
       "      <td>156.0</td>\n",
       "      <td>97</td>\n",
       "      <td>13.26</td>\n",
       "      <td>227.9</td>\n",
       "      <td>124</td>\n",
       "      <td>10.26</td>\n",
       "      <td>10.6</td>\n",
       "      <td>9</td>\n",
       "      <td>2.86</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>28</td>\n",
       "      <td>108</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>112.6</td>\n",
       "      <td>86</td>\n",
       "      <td>19.14</td>\n",
       "      <td>114.9</td>\n",
       "      <td>101</td>\n",
       "      <td>9.77</td>\n",
       "      <td>177.8</td>\n",
       "      <td>119</td>\n",
       "      <td>8.00</td>\n",
       "      <td>7.2</td>\n",
       "      <td>6</td>\n",
       "      <td>1.94</td>\n",
       "      <td>3</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>8</td>\n",
       "      <td>60</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>207.3</td>\n",
       "      <td>77</td>\n",
       "      <td>35.24</td>\n",
       "      <td>207.9</td>\n",
       "      <td>105</td>\n",
       "      <td>17.67</td>\n",
       "      <td>108.2</td>\n",
       "      <td>89</td>\n",
       "      <td>4.87</td>\n",
       "      <td>12.9</td>\n",
       "      <td>5</td>\n",
       "      <td>3.48</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>23</td>\n",
       "      <td>96</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>208.1</td>\n",
       "      <td>93</td>\n",
       "      <td>35.38</td>\n",
       "      <td>189.2</td>\n",
       "      <td>107</td>\n",
       "      <td>16.08</td>\n",
       "      <td>279.6</td>\n",
       "      <td>90</td>\n",
       "      <td>12.58</td>\n",
       "      <td>7.4</td>\n",
       "      <td>2</td>\n",
       "      <td>2.00</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>16</td>\n",
       "      <td>178</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>22</td>\n",
       "      <td>112.8</td>\n",
       "      <td>66</td>\n",
       "      <td>19.18</td>\n",
       "      <td>232.6</td>\n",
       "      <td>100</td>\n",
       "      <td>19.77</td>\n",
       "      <td>194.8</td>\n",
       "      <td>119</td>\n",
       "      <td>8.77</td>\n",
       "      <td>14.3</td>\n",
       "      <td>3</td>\n",
       "      <td>3.86</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>23</td>\n",
       "      <td>75</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>225.3</td>\n",
       "      <td>124</td>\n",
       "      <td>38.30</td>\n",
       "      <td>228.0</td>\n",
       "      <td>81</td>\n",
       "      <td>19.38</td>\n",
       "      <td>254.3</td>\n",
       "      <td>106</td>\n",
       "      <td>11.44</td>\n",
       "      <td>11.7</td>\n",
       "      <td>3</td>\n",
       "      <td>3.16</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>27</td>\n",
       "      <td>106</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>25</td>\n",
       "      <td>169.4</td>\n",
       "      <td>105</td>\n",
       "      <td>28.80</td>\n",
       "      <td>240.5</td>\n",
       "      <td>108</td>\n",
       "      <td>20.44</td>\n",
       "      <td>159.4</td>\n",
       "      <td>114</td>\n",
       "      <td>7.17</td>\n",
       "      <td>13.9</td>\n",
       "      <td>5</td>\n",
       "      <td>3.75</td>\n",
       "      <td>4</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>11</td>\n",
       "      <td>158</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>193.3</td>\n",
       "      <td>121</td>\n",
       "      <td>32.86</td>\n",
       "      <td>208.1</td>\n",
       "      <td>97</td>\n",
       "      <td>17.69</td>\n",
       "      <td>228.1</td>\n",
       "      <td>99</td>\n",
       "      <td>10.26</td>\n",
       "      <td>7.1</td>\n",
       "      <td>9</td>\n",
       "      <td>1.92</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>33</td>\n",
       "      <td>111</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>35</td>\n",
       "      <td>161.2</td>\n",
       "      <td>142</td>\n",
       "      <td>27.40</td>\n",
       "      <td>159.1</td>\n",
       "      <td>104</td>\n",
       "      <td>13.52</td>\n",
       "      <td>167.9</td>\n",
       "      <td>98</td>\n",
       "      <td>7.56</td>\n",
       "      <td>14.7</td>\n",
       "      <td>5</td>\n",
       "      <td>3.97</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>5</td>\n",
       "      <td>102</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>95.6</td>\n",
       "      <td>88</td>\n",
       "      <td>16.25</td>\n",
       "      <td>167.6</td>\n",
       "      <td>106</td>\n",
       "      <td>14.25</td>\n",
       "      <td>177.3</td>\n",
       "      <td>95</td>\n",
       "      <td>7.98</td>\n",
       "      <td>9.8</td>\n",
       "      <td>2</td>\n",
       "      <td>2.65</td>\n",
       "      <td>3</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>42</td>\n",
       "      <td>92</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>25</td>\n",
       "      <td>79.8</td>\n",
       "      <td>99</td>\n",
       "      <td>13.57</td>\n",
       "      <td>313.6</td>\n",
       "      <td>120</td>\n",
       "      <td>26.66</td>\n",
       "      <td>135.5</td>\n",
       "      <td>104</td>\n",
       "      <td>6.10</td>\n",
       "      <td>9.3</td>\n",
       "      <td>8</td>\n",
       "      <td>2.51</td>\n",
       "      <td>2</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>8</td>\n",
       "      <td>42</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>31</td>\n",
       "      <td>170.8</td>\n",
       "      <td>101</td>\n",
       "      <td>29.04</td>\n",
       "      <td>233.4</td>\n",
       "      <td>104</td>\n",
       "      <td>19.84</td>\n",
       "      <td>174.2</td>\n",
       "      <td>121</td>\n",
       "      <td>7.84</td>\n",
       "      <td>11.0</td>\n",
       "      <td>3</td>\n",
       "      <td>2.97</td>\n",
       "      <td>2</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>35</td>\n",
       "      <td>69</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>229.2</td>\n",
       "      <td>111</td>\n",
       "      <td>38.96</td>\n",
       "      <td>165.3</td>\n",
       "      <td>104</td>\n",
       "      <td>14.05</td>\n",
       "      <td>235.1</td>\n",
       "      <td>80</td>\n",
       "      <td>10.58</td>\n",
       "      <td>5.2</td>\n",
       "      <td>5</td>\n",
       "      <td>1.40</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>37</td>\n",
       "      <td>117</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>38</td>\n",
       "      <td>259.3</td>\n",
       "      <td>94</td>\n",
       "      <td>44.08</td>\n",
       "      <td>245.6</td>\n",
       "      <td>71</td>\n",
       "      <td>20.88</td>\n",
       "      <td>269.3</td>\n",
       "      <td>125</td>\n",
       "      <td>12.12</td>\n",
       "      <td>9.2</td>\n",
       "      <td>1</td>\n",
       "      <td>2.48</td>\n",
       "      <td>3</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>29</td>\n",
       "      <td>76</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>41</td>\n",
       "      <td>212.6</td>\n",
       "      <td>110</td>\n",
       "      <td>36.14</td>\n",
       "      <td>172.7</td>\n",
       "      <td>97</td>\n",
       "      <td>14.68</td>\n",
       "      <td>186.3</td>\n",
       "      <td>78</td>\n",
       "      <td>8.38</td>\n",
       "      <td>10.1</td>\n",
       "      <td>5</td>\n",
       "      <td>2.73</td>\n",
       "      <td>0</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>13</td>\n",
       "      <td>72</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>101.0</td>\n",
       "      <td>110</td>\n",
       "      <td>17.17</td>\n",
       "      <td>240.0</td>\n",
       "      <td>70</td>\n",
       "      <td>20.40</td>\n",
       "      <td>333.5</td>\n",
       "      <td>105</td>\n",
       "      <td>15.01</td>\n",
       "      <td>11.1</td>\n",
       "      <td>6</td>\n",
       "      <td>3.00</td>\n",
       "      <td>0</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>50</td>\n",
       "      <td>115</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>140.1</td>\n",
       "      <td>125</td>\n",
       "      <td>23.82</td>\n",
       "      <td>157.9</td>\n",
       "      <td>100</td>\n",
       "      <td>13.42</td>\n",
       "      <td>249.4</td>\n",
       "      <td>96</td>\n",
       "      <td>11.22</td>\n",
       "      <td>10.1</td>\n",
       "      <td>3</td>\n",
       "      <td>2.73</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>20</td>\n",
       "      <td>68</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>150.4</td>\n",
       "      <td>106</td>\n",
       "      <td>25.57</td>\n",
       "      <td>199.0</td>\n",
       "      <td>131</td>\n",
       "      <td>16.92</td>\n",
       "      <td>109.7</td>\n",
       "      <td>103</td>\n",
       "      <td>4.94</td>\n",
       "      <td>12.3</td>\n",
       "      <td>3</td>\n",
       "      <td>3.32</td>\n",
       "      <td>3</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <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>1637</th>\n",
       "      <td>20</td>\n",
       "      <td>133</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>173.1</td>\n",
       "      <td>126</td>\n",
       "      <td>29.43</td>\n",
       "      <td>200.0</td>\n",
       "      <td>98</td>\n",
       "      <td>17.00</td>\n",
       "      <td>231.0</td>\n",
       "      <td>103</td>\n",
       "      <td>10.40</td>\n",
       "      <td>10.8</td>\n",
       "      <td>1</td>\n",
       "      <td>2.92</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1638</th>\n",
       "      <td>11</td>\n",
       "      <td>128</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>28</td>\n",
       "      <td>115.4</td>\n",
       "      <td>96</td>\n",
       "      <td>19.62</td>\n",
       "      <td>185.4</td>\n",
       "      <td>94</td>\n",
       "      <td>15.76</td>\n",
       "      <td>209.3</td>\n",
       "      <td>69</td>\n",
       "      <td>9.42</td>\n",
       "      <td>17.7</td>\n",
       "      <td>4</td>\n",
       "      <td>4.78</td>\n",
       "      <td>0</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1639</th>\n",
       "      <td>9</td>\n",
       "      <td>81</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>190.9</td>\n",
       "      <td>92</td>\n",
       "      <td>32.45</td>\n",
       "      <td>208.7</td>\n",
       "      <td>132</td>\n",
       "      <td>17.74</td>\n",
       "      <td>120.8</td>\n",
       "      <td>98</td>\n",
       "      <td>5.44</td>\n",
       "      <td>11.4</td>\n",
       "      <td>6</td>\n",
       "      <td>3.08</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1640</th>\n",
       "      <td>28</td>\n",
       "      <td>81</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>234.1</td>\n",
       "      <td>105</td>\n",
       "      <td>39.80</td>\n",
       "      <td>237.4</td>\n",
       "      <td>88</td>\n",
       "      <td>20.18</td>\n",
       "      <td>240.6</td>\n",
       "      <td>85</td>\n",
       "      <td>10.83</td>\n",
       "      <td>11.4</td>\n",
       "      <td>4</td>\n",
       "      <td>3.08</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1641</th>\n",
       "      <td>18</td>\n",
       "      <td>96</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>102.1</td>\n",
       "      <td>74</td>\n",
       "      <td>17.36</td>\n",
       "      <td>93.7</td>\n",
       "      <td>88</td>\n",
       "      <td>7.96</td>\n",
       "      <td>236.2</td>\n",
       "      <td>125</td>\n",
       "      <td>10.63</td>\n",
       "      <td>14.0</td>\n",
       "      <td>2</td>\n",
       "      <td>3.78</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1642</th>\n",
       "      <td>2</td>\n",
       "      <td>93</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>131.9</td>\n",
       "      <td>91</td>\n",
       "      <td>22.42</td>\n",
       "      <td>203.8</td>\n",
       "      <td>92</td>\n",
       "      <td>17.32</td>\n",
       "      <td>205.6</td>\n",
       "      <td>121</td>\n",
       "      <td>9.25</td>\n",
       "      <td>6.8</td>\n",
       "      <td>3</td>\n",
       "      <td>1.84</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1643</th>\n",
       "      <td>17</td>\n",
       "      <td>145</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>135.0</td>\n",
       "      <td>122</td>\n",
       "      <td>22.95</td>\n",
       "      <td>206.3</td>\n",
       "      <td>88</td>\n",
       "      <td>17.54</td>\n",
       "      <td>210.4</td>\n",
       "      <td>90</td>\n",
       "      <td>9.47</td>\n",
       "      <td>19.7</td>\n",
       "      <td>4</td>\n",
       "      <td>5.32</td>\n",
       "      <td>0</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1644</th>\n",
       "      <td>11</td>\n",
       "      <td>53</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>145.0</td>\n",
       "      <td>80</td>\n",
       "      <td>24.65</td>\n",
       "      <td>228.4</td>\n",
       "      <td>82</td>\n",
       "      <td>19.41</td>\n",
       "      <td>169.4</td>\n",
       "      <td>109</td>\n",
       "      <td>7.62</td>\n",
       "      <td>8.9</td>\n",
       "      <td>5</td>\n",
       "      <td>2.40</td>\n",
       "      <td>0</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1645</th>\n",
       "      <td>16</td>\n",
       "      <td>108</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>170.3</td>\n",
       "      <td>48</td>\n",
       "      <td>28.95</td>\n",
       "      <td>187.7</td>\n",
       "      <td>146</td>\n",
       "      <td>15.95</td>\n",
       "      <td>204.0</td>\n",
       "      <td>84</td>\n",
       "      <td>9.18</td>\n",
       "      <td>16.1</td>\n",
       "      <td>4</td>\n",
       "      <td>4.35</td>\n",
       "      <td>3</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1646</th>\n",
       "      <td>43</td>\n",
       "      <td>52</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>188.7</td>\n",
       "      <td>99</td>\n",
       "      <td>32.08</td>\n",
       "      <td>210.4</td>\n",
       "      <td>89</td>\n",
       "      <td>17.88</td>\n",
       "      <td>191.4</td>\n",
       "      <td>103</td>\n",
       "      <td>8.61</td>\n",
       "      <td>10.8</td>\n",
       "      <td>2</td>\n",
       "      <td>2.92</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1647</th>\n",
       "      <td>47</td>\n",
       "      <td>73</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>177.2</td>\n",
       "      <td>118</td>\n",
       "      <td>30.12</td>\n",
       "      <td>270.5</td>\n",
       "      <td>84</td>\n",
       "      <td>22.99</td>\n",
       "      <td>241.8</td>\n",
       "      <td>112</td>\n",
       "      <td>10.88</td>\n",
       "      <td>12.3</td>\n",
       "      <td>2</td>\n",
       "      <td>3.32</td>\n",
       "      <td>3</td>\n",
       "      <td>True.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1648</th>\n",
       "      <td>27</td>\n",
       "      <td>61</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.2</td>\n",
       "      <td>97</td>\n",
       "      <td>1.22</td>\n",
       "      <td>221.8</td>\n",
       "      <td>78</td>\n",
       "      <td>18.85</td>\n",
       "      <td>174.5</td>\n",
       "      <td>94</td>\n",
       "      <td>7.85</td>\n",
       "      <td>12.0</td>\n",
       "      <td>4</td>\n",
       "      <td>3.24</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1649</th>\n",
       "      <td>43</td>\n",
       "      <td>86</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>181.1</td>\n",
       "      <td>124</td>\n",
       "      <td>30.79</td>\n",
       "      <td>229.5</td>\n",
       "      <td>105</td>\n",
       "      <td>19.51</td>\n",
       "      <td>122.2</td>\n",
       "      <td>91</td>\n",
       "      <td>5.50</td>\n",
       "      <td>5.6</td>\n",
       "      <td>6</td>\n",
       "      <td>1.51</td>\n",
       "      <td>5</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1650</th>\n",
       "      <td>18</td>\n",
       "      <td>137</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>151.8</td>\n",
       "      <td>90</td>\n",
       "      <td>25.81</td>\n",
       "      <td>229.6</td>\n",
       "      <td>68</td>\n",
       "      <td>19.52</td>\n",
       "      <td>171.8</td>\n",
       "      <td>122</td>\n",
       "      <td>7.73</td>\n",
       "      <td>10.8</td>\n",
       "      <td>5</td>\n",
       "      <td>2.92</td>\n",
       "      <td>2</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1651</th>\n",
       "      <td>42</td>\n",
       "      <td>74</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>159.4</td>\n",
       "      <td>86</td>\n",
       "      <td>27.10</td>\n",
       "      <td>210.0</td>\n",
       "      <td>122</td>\n",
       "      <td>17.85</td>\n",
       "      <td>172.4</td>\n",
       "      <td>99</td>\n",
       "      <td>7.76</td>\n",
       "      <td>8.5</td>\n",
       "      <td>2</td>\n",
       "      <td>2.30</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1652</th>\n",
       "      <td>27</td>\n",
       "      <td>118</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>31</td>\n",
       "      <td>226.6</td>\n",
       "      <td>99</td>\n",
       "      <td>38.52</td>\n",
       "      <td>164.9</td>\n",
       "      <td>136</td>\n",
       "      <td>14.02</td>\n",
       "      <td>189.3</td>\n",
       "      <td>120</td>\n",
       "      <td>8.52</td>\n",
       "      <td>10.2</td>\n",
       "      <td>5</td>\n",
       "      <td>2.75</td>\n",
       "      <td>3</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1653</th>\n",
       "      <td>35</td>\n",
       "      <td>125</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>214.7</td>\n",
       "      <td>115</td>\n",
       "      <td>36.50</td>\n",
       "      <td>260.6</td>\n",
       "      <td>94</td>\n",
       "      <td>22.15</td>\n",
       "      <td>266.3</td>\n",
       "      <td>123</td>\n",
       "      <td>11.98</td>\n",
       "      <td>7.4</td>\n",
       "      <td>6</td>\n",
       "      <td>2.00</td>\n",
       "      <td>3</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1654</th>\n",
       "      <td>2</td>\n",
       "      <td>127</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>27</td>\n",
       "      <td>157.6</td>\n",
       "      <td>107</td>\n",
       "      <td>26.79</td>\n",
       "      <td>280.6</td>\n",
       "      <td>49</td>\n",
       "      <td>23.85</td>\n",
       "      <td>75.1</td>\n",
       "      <td>77</td>\n",
       "      <td>3.38</td>\n",
       "      <td>8.0</td>\n",
       "      <td>4</td>\n",
       "      <td>2.16</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1655</th>\n",
       "      <td>47</td>\n",
       "      <td>80</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>157.0</td>\n",
       "      <td>101</td>\n",
       "      <td>26.69</td>\n",
       "      <td>208.8</td>\n",
       "      <td>127</td>\n",
       "      <td>17.75</td>\n",
       "      <td>113.3</td>\n",
       "      <td>109</td>\n",
       "      <td>5.10</td>\n",
       "      <td>16.2</td>\n",
       "      <td>2</td>\n",
       "      <td>4.37</td>\n",
       "      <td>2</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1656</th>\n",
       "      <td>23</td>\n",
       "      <td>150</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>170.0</td>\n",
       "      <td>115</td>\n",
       "      <td>28.90</td>\n",
       "      <td>162.7</td>\n",
       "      <td>138</td>\n",
       "      <td>13.83</td>\n",
       "      <td>267.2</td>\n",
       "      <td>77</td>\n",
       "      <td>12.02</td>\n",
       "      <td>8.3</td>\n",
       "      <td>2</td>\n",
       "      <td>2.24</td>\n",
       "      <td>0</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1657</th>\n",
       "      <td>28</td>\n",
       "      <td>140</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>244.7</td>\n",
       "      <td>115</td>\n",
       "      <td>41.60</td>\n",
       "      <td>258.6</td>\n",
       "      <td>101</td>\n",
       "      <td>21.98</td>\n",
       "      <td>231.3</td>\n",
       "      <td>112</td>\n",
       "      <td>10.41</td>\n",
       "      <td>7.5</td>\n",
       "      <td>6</td>\n",
       "      <td>2.03</td>\n",
       "      <td>1</td>\n",
       "      <td>True.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1658</th>\n",
       "      <td>3</td>\n",
       "      <td>97</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>252.6</td>\n",
       "      <td>89</td>\n",
       "      <td>42.94</td>\n",
       "      <td>340.3</td>\n",
       "      <td>91</td>\n",
       "      <td>28.93</td>\n",
       "      <td>256.5</td>\n",
       "      <td>67</td>\n",
       "      <td>11.54</td>\n",
       "      <td>8.8</td>\n",
       "      <td>5</td>\n",
       "      <td>2.38</td>\n",
       "      <td>1</td>\n",
       "      <td>True.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1659</th>\n",
       "      <td>26</td>\n",
       "      <td>83</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>188.3</td>\n",
       "      <td>70</td>\n",
       "      <td>32.01</td>\n",
       "      <td>243.8</td>\n",
       "      <td>88</td>\n",
       "      <td>20.72</td>\n",
       "      <td>213.7</td>\n",
       "      <td>79</td>\n",
       "      <td>9.62</td>\n",
       "      <td>10.3</td>\n",
       "      <td>6</td>\n",
       "      <td>2.78</td>\n",
       "      <td>0</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1660</th>\n",
       "      <td>49</td>\n",
       "      <td>73</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>177.9</td>\n",
       "      <td>89</td>\n",
       "      <td>30.24</td>\n",
       "      <td>131.2</td>\n",
       "      <td>82</td>\n",
       "      <td>11.15</td>\n",
       "      <td>186.2</td>\n",
       "      <td>89</td>\n",
       "      <td>8.38</td>\n",
       "      <td>11.5</td>\n",
       "      <td>6</td>\n",
       "      <td>3.11</td>\n",
       "      <td>3</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1661</th>\n",
       "      <td>27</td>\n",
       "      <td>75</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>170.7</td>\n",
       "      <td>101</td>\n",
       "      <td>29.02</td>\n",
       "      <td>193.1</td>\n",
       "      <td>126</td>\n",
       "      <td>16.41</td>\n",
       "      <td>129.1</td>\n",
       "      <td>104</td>\n",
       "      <td>5.81</td>\n",
       "      <td>6.9</td>\n",
       "      <td>7</td>\n",
       "      <td>1.86</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1662</th>\n",
       "      <td>11</td>\n",
       "      <td>50</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>40</td>\n",
       "      <td>235.7</td>\n",
       "      <td>127</td>\n",
       "      <td>40.07</td>\n",
       "      <td>223.0</td>\n",
       "      <td>126</td>\n",
       "      <td>18.96</td>\n",
       "      <td>297.5</td>\n",
       "      <td>116</td>\n",
       "      <td>13.39</td>\n",
       "      <td>9.9</td>\n",
       "      <td>5</td>\n",
       "      <td>2.67</td>\n",
       "      <td>2</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1663</th>\n",
       "      <td>49</td>\n",
       "      <td>152</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>184.2</td>\n",
       "      <td>90</td>\n",
       "      <td>31.31</td>\n",
       "      <td>256.8</td>\n",
       "      <td>73</td>\n",
       "      <td>21.83</td>\n",
       "      <td>213.6</td>\n",
       "      <td>113</td>\n",
       "      <td>9.61</td>\n",
       "      <td>14.7</td>\n",
       "      <td>2</td>\n",
       "      <td>3.97</td>\n",
       "      <td>3</td>\n",
       "      <td>True.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1664</th>\n",
       "      <td>7</td>\n",
       "      <td>61</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>140.6</td>\n",
       "      <td>89</td>\n",
       "      <td>23.90</td>\n",
       "      <td>172.8</td>\n",
       "      <td>128</td>\n",
       "      <td>14.69</td>\n",
       "      <td>212.4</td>\n",
       "      <td>97</td>\n",
       "      <td>9.56</td>\n",
       "      <td>13.6</td>\n",
       "      <td>4</td>\n",
       "      <td>3.67</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1665</th>\n",
       "      <td>7</td>\n",
       "      <td>109</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>188.8</td>\n",
       "      <td>67</td>\n",
       "      <td>32.10</td>\n",
       "      <td>171.7</td>\n",
       "      <td>92</td>\n",
       "      <td>14.59</td>\n",
       "      <td>224.4</td>\n",
       "      <td>89</td>\n",
       "      <td>10.10</td>\n",
       "      <td>8.5</td>\n",
       "      <td>6</td>\n",
       "      <td>2.30</td>\n",
       "      <td>0</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1666</th>\n",
       "      <td>46</td>\n",
       "      <td>86</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>34</td>\n",
       "      <td>129.4</td>\n",
       "      <td>102</td>\n",
       "      <td>22.00</td>\n",
       "      <td>267.1</td>\n",
       "      <td>104</td>\n",
       "      <td>22.70</td>\n",
       "      <td>154.8</td>\n",
       "      <td>100</td>\n",
       "      <td>6.97</td>\n",
       "      <td>9.3</td>\n",
       "      <td>16</td>\n",
       "      <td>2.51</td>\n",
       "      <td>0</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1667 rows × 20 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      state  account length  area code  international plan  voice mail plan  \\\n",
       "0        11             101          2                   0                0   \n",
       "1        26             137          2                   0                0   \n",
       "2        35             103          0                   0                1   \n",
       "3        32              99          1                   0                0   \n",
       "4        40             108          1                   0                0   \n",
       "5        12             117          1                   0                0   \n",
       "6        28              63          1                   0                1   \n",
       "7        18              94          0                   0                0   \n",
       "8        24             138          2                   0                0   \n",
       "9        43             128          1                   0                1   \n",
       "10        2             113          2                   0                1   \n",
       "11       43             140          1                   0                0   \n",
       "12       21             102          1                   0                0   \n",
       "13       28             108          1                   0                0   \n",
       "14        8              60          0                   0                0   \n",
       "15       23              96          0                   0                0   \n",
       "16       16             178          1                   0                1   \n",
       "17       23              75          1                   0                0   \n",
       "18       27             106          1                   0                1   \n",
       "19       11             158          2                   0                0   \n",
       "20       33             111          1                   0                1   \n",
       "21        5             102          2                   0                0   \n",
       "22       42              92          2                   0                1   \n",
       "23        8              42          1                   0                1   \n",
       "24       35              69          1                   0                0   \n",
       "25       37             117          1                   0                1   \n",
       "26       29              76          1                   0                1   \n",
       "27       13              72          1                   1                0   \n",
       "28       50             115          1                   1                1   \n",
       "29       20              68          0                   0                0   \n",
       "...     ...             ...        ...                 ...              ...   \n",
       "1637     20             133          1                   0                0   \n",
       "1638     11             128          2                   0                1   \n",
       "1639      9              81          0                   0                0   \n",
       "1640     28              81          1                   0                0   \n",
       "1641     18              96          0                   0                0   \n",
       "1642      2              93          1                   0                0   \n",
       "1643     17             145          0                   0                0   \n",
       "1644     11              53          2                   1                0   \n",
       "1645     16             108          0                   0                0   \n",
       "1646     43              52          1                   0                0   \n",
       "1647     47              73          0                   0                0   \n",
       "1648     27              61          2                   0                0   \n",
       "1649     43              86          0                   0                0   \n",
       "1650     18             137          0                   0                0   \n",
       "1651     42              74          2                   0                0   \n",
       "1652     27             118          2                   0                1   \n",
       "1653     35             125          1                   0                0   \n",
       "1654      2             127          1                   0                1   \n",
       "1655     47              80          2                   0                0   \n",
       "1656     23             150          0                   0                0   \n",
       "1657     28             140          2                   0                0   \n",
       "1658      3              97          2                   0                0   \n",
       "1659     26              83          1                   0                0   \n",
       "1660     49              73          0                   0                0   \n",
       "1661     27              75          0                   0                0   \n",
       "1662     11              50          0                   0                1   \n",
       "1663     49             152          1                   0                0   \n",
       "1664      7              61          1                   0                0   \n",
       "1665      7             109          2                   0                0   \n",
       "1666     46              86          1                   0                1   \n",
       "\n",
       "      number vmail messages  total day minutes  total day calls  \\\n",
       "0                         0               70.9              123   \n",
       "1                         0              223.6               86   \n",
       "2                        29              294.7               95   \n",
       "3                         0              216.8              123   \n",
       "4                         0              197.4               78   \n",
       "5                         0              226.5               85   \n",
       "6                        32              218.9              124   \n",
       "7                         0              157.5               97   \n",
       "8                         0               89.1              117   \n",
       "9                        43              177.8              100   \n",
       "10                       39              209.8               77   \n",
       "11                        0               93.2              109   \n",
       "12                        0              228.1               86   \n",
       "13                        0              112.6               86   \n",
       "14                        0              207.3               77   \n",
       "15                        0              208.1               93   \n",
       "16                       22              112.8               66   \n",
       "17                        0              225.3              124   \n",
       "18                       25              169.4              105   \n",
       "19                        0              193.3              121   \n",
       "20                       35              161.2              142   \n",
       "21                        0               95.6               88   \n",
       "22                       25               79.8               99   \n",
       "23                       31              170.8              101   \n",
       "24                        0              229.2              111   \n",
       "25                       38              259.3               94   \n",
       "26                       41              212.6              110   \n",
       "27                        0              101.0              110   \n",
       "28                        6              140.1              125   \n",
       "29                        0              150.4              106   \n",
       "...                     ...                ...              ...   \n",
       "1637                      0              173.1              126   \n",
       "1638                     28              115.4               96   \n",
       "1639                      0              190.9               92   \n",
       "1640                      0              234.1              105   \n",
       "1641                      0              102.1               74   \n",
       "1642                      0              131.9               91   \n",
       "1643                      0              135.0              122   \n",
       "1644                      0              145.0               80   \n",
       "1645                      0              170.3               48   \n",
       "1646                      0              188.7               99   \n",
       "1647                      0              177.2              118   \n",
       "1648                      0                7.2               97   \n",
       "1649                      0              181.1              124   \n",
       "1650                      0              151.8               90   \n",
       "1651                      0              159.4               86   \n",
       "1652                     31              226.6               99   \n",
       "1653                      0              214.7              115   \n",
       "1654                     27              157.6              107   \n",
       "1655                      0              157.0              101   \n",
       "1656                      0              170.0              115   \n",
       "1657                      0              244.7              115   \n",
       "1658                      0              252.6               89   \n",
       "1659                      0              188.3               70   \n",
       "1660                      0              177.9               89   \n",
       "1661                      0              170.7              101   \n",
       "1662                     40              235.7              127   \n",
       "1663                      0              184.2               90   \n",
       "1664                      0              140.6               89   \n",
       "1665                      0              188.8               67   \n",
       "1666                     34              129.4              102   \n",
       "\n",
       "      total day charge  total eve minutes  total eve calls  total eve charge  \\\n",
       "0                12.05              211.9               73             18.01   \n",
       "1                38.01              244.8              139             20.81   \n",
       "2                50.10              237.3              105             20.17   \n",
       "3                36.86              126.4               88             10.74   \n",
       "4                33.56              124.0              101             10.54   \n",
       "5                38.51              141.6               68             12.04   \n",
       "6                37.21              214.3              125             18.22   \n",
       "7                26.78              224.5              112             19.08   \n",
       "8                15.15              126.8               46             10.78   \n",
       "9                30.23              147.3               89             12.52   \n",
       "10               35.67              164.1               90             13.95   \n",
       "11               15.84              197.6              116             16.80   \n",
       "12               38.78              156.0               97             13.26   \n",
       "13               19.14              114.9              101              9.77   \n",
       "14               35.24              207.9              105             17.67   \n",
       "15               35.38              189.2              107             16.08   \n",
       "16               19.18              232.6              100             19.77   \n",
       "17               38.30              228.0               81             19.38   \n",
       "18               28.80              240.5              108             20.44   \n",
       "19               32.86              208.1               97             17.69   \n",
       "20               27.40              159.1              104             13.52   \n",
       "21               16.25              167.6              106             14.25   \n",
       "22               13.57              313.6              120             26.66   \n",
       "23               29.04              233.4              104             19.84   \n",
       "24               38.96              165.3              104             14.05   \n",
       "25               44.08              245.6               71             20.88   \n",
       "26               36.14              172.7               97             14.68   \n",
       "27               17.17              240.0               70             20.40   \n",
       "28               23.82              157.9              100             13.42   \n",
       "29               25.57              199.0              131             16.92   \n",
       "...                ...                ...              ...               ...   \n",
       "1637             29.43              200.0               98             17.00   \n",
       "1638             19.62              185.4               94             15.76   \n",
       "1639             32.45              208.7              132             17.74   \n",
       "1640             39.80              237.4               88             20.18   \n",
       "1641             17.36               93.7               88              7.96   \n",
       "1642             22.42              203.8               92             17.32   \n",
       "1643             22.95              206.3               88             17.54   \n",
       "1644             24.65              228.4               82             19.41   \n",
       "1645             28.95              187.7              146             15.95   \n",
       "1646             32.08              210.4               89             17.88   \n",
       "1647             30.12              270.5               84             22.99   \n",
       "1648              1.22              221.8               78             18.85   \n",
       "1649             30.79              229.5              105             19.51   \n",
       "1650             25.81              229.6               68             19.52   \n",
       "1651             27.10              210.0              122             17.85   \n",
       "1652             38.52              164.9              136             14.02   \n",
       "1653             36.50              260.6               94             22.15   \n",
       "1654             26.79              280.6               49             23.85   \n",
       "1655             26.69              208.8              127             17.75   \n",
       "1656             28.90              162.7              138             13.83   \n",
       "1657             41.60              258.6              101             21.98   \n",
       "1658             42.94              340.3               91             28.93   \n",
       "1659             32.01              243.8               88             20.72   \n",
       "1660             30.24              131.2               82             11.15   \n",
       "1661             29.02              193.1              126             16.41   \n",
       "1662             40.07              223.0              126             18.96   \n",
       "1663             31.31              256.8               73             21.83   \n",
       "1664             23.90              172.8              128             14.69   \n",
       "1665             32.10              171.7               92             14.59   \n",
       "1666             22.00              267.1              104             22.70   \n",
       "\n",
       "      total night minutes  total night calls  total night charge  \\\n",
       "0                   236.0                 73               10.62   \n",
       "1                    94.2                 81                4.24   \n",
       "2                   300.3                127               13.51   \n",
       "3                   220.6                 82                9.93   \n",
       "4                   204.5                107                9.20   \n",
       "5                   223.0                 90               10.04   \n",
       "6                   260.3                120               11.71   \n",
       "7                   310.8                106               13.99   \n",
       "8                   190.5                 71                8.57   \n",
       "9                   194.2                 92                8.74   \n",
       "10                  159.7                100                7.19   \n",
       "11                  219.8                 94                9.89   \n",
       "12                  227.9                124               10.26   \n",
       "13                  177.8                119                8.00   \n",
       "14                  108.2                 89                4.87   \n",
       "15                  279.6                 90               12.58   \n",
       "16                  194.8                119                8.77   \n",
       "17                  254.3                106               11.44   \n",
       "18                  159.4                114                7.17   \n",
       "19                  228.1                 99               10.26   \n",
       "20                  167.9                 98                7.56   \n",
       "21                  177.3                 95                7.98   \n",
       "22                  135.5                104                6.10   \n",
       "23                  174.2                121                7.84   \n",
       "24                  235.1                 80               10.58   \n",
       "25                  269.3                125               12.12   \n",
       "26                  186.3                 78                8.38   \n",
       "27                  333.5                105               15.01   \n",
       "28                  249.4                 96               11.22   \n",
       "29                  109.7                103                4.94   \n",
       "...                   ...                ...                 ...   \n",
       "1637                231.0                103               10.40   \n",
       "1638                209.3                 69                9.42   \n",
       "1639                120.8                 98                5.44   \n",
       "1640                240.6                 85               10.83   \n",
       "1641                236.2                125               10.63   \n",
       "1642                205.6                121                9.25   \n",
       "1643                210.4                 90                9.47   \n",
       "1644                169.4                109                7.62   \n",
       "1645                204.0                 84                9.18   \n",
       "1646                191.4                103                8.61   \n",
       "1647                241.8                112               10.88   \n",
       "1648                174.5                 94                7.85   \n",
       "1649                122.2                 91                5.50   \n",
       "1650                171.8                122                7.73   \n",
       "1651                172.4                 99                7.76   \n",
       "1652                189.3                120                8.52   \n",
       "1653                266.3                123               11.98   \n",
       "1654                 75.1                 77                3.38   \n",
       "1655                113.3                109                5.10   \n",
       "1656                267.2                 77               12.02   \n",
       "1657                231.3                112               10.41   \n",
       "1658                256.5                 67               11.54   \n",
       "1659                213.7                 79                9.62   \n",
       "1660                186.2                 89                8.38   \n",
       "1661                129.1                104                5.81   \n",
       "1662                297.5                116               13.39   \n",
       "1663                213.6                113                9.61   \n",
       "1664                212.4                 97                9.56   \n",
       "1665                224.4                 89               10.10   \n",
       "1666                154.8                100                6.97   \n",
       "\n",
       "      total intl minutes  total intl calls  total intl charge  \\\n",
       "0                   10.6                 3               2.86   \n",
       "1                    9.5                 7               2.57   \n",
       "2                   13.7                 6               3.70   \n",
       "3                   15.7                 2               4.24   \n",
       "4                    7.7                 4               2.08   \n",
       "5                    6.9                 5               1.86   \n",
       "6                   12.9                 3               3.48   \n",
       "7                   11.1                 6               3.00   \n",
       "8                    9.9                 4               2.67   \n",
       "9                   11.9                 1               3.21   \n",
       "10                   9.0                 4               2.43   \n",
       "11                  10.5                 2               2.84   \n",
       "12                  10.6                 9               2.86   \n",
       "13                   7.2                 6               1.94   \n",
       "14                  12.9                 5               3.48   \n",
       "15                   7.4                 2               2.00   \n",
       "16                  14.3                 3               3.86   \n",
       "17                  11.7                 3               3.16   \n",
       "18                  13.9                 5               3.75   \n",
       "19                   7.1                 9               1.92   \n",
       "20                  14.7                 5               3.97   \n",
       "21                   9.8                 2               2.65   \n",
       "22                   9.3                 8               2.51   \n",
       "23                  11.0                 3               2.97   \n",
       "24                   5.2                 5               1.40   \n",
       "25                   9.2                 1               2.48   \n",
       "26                  10.1                 5               2.73   \n",
       "27                  11.1                 6               3.00   \n",
       "28                  10.1                 3               2.73   \n",
       "29                  12.3                 3               3.32   \n",
       "...                  ...               ...                ...   \n",
       "1637                10.8                 1               2.92   \n",
       "1638                17.7                 4               4.78   \n",
       "1639                11.4                 6               3.08   \n",
       "1640                11.4                 4               3.08   \n",
       "1641                14.0                 2               3.78   \n",
       "1642                 6.8                 3               1.84   \n",
       "1643                19.7                 4               5.32   \n",
       "1644                 8.9                 5               2.40   \n",
       "1645                16.1                 4               4.35   \n",
       "1646                10.8                 2               2.92   \n",
       "1647                12.3                 2               3.32   \n",
       "1648                12.0                 4               3.24   \n",
       "1649                 5.6                 6               1.51   \n",
       "1650                10.8                 5               2.92   \n",
       "1651                 8.5                 2               2.30   \n",
       "1652                10.2                 5               2.75   \n",
       "1653                 7.4                 6               2.00   \n",
       "1654                 8.0                 4               2.16   \n",
       "1655                16.2                 2               4.37   \n",
       "1656                 8.3                 2               2.24   \n",
       "1657                 7.5                 6               2.03   \n",
       "1658                 8.8                 5               2.38   \n",
       "1659                10.3                 6               2.78   \n",
       "1660                11.5                 6               3.11   \n",
       "1661                 6.9                 7               1.86   \n",
       "1662                 9.9                 5               2.67   \n",
       "1663                14.7                 2               3.97   \n",
       "1664                13.6                 4               3.67   \n",
       "1665                 8.5                 6               2.30   \n",
       "1666                 9.3                16               2.51   \n",
       "\n",
       "      number customer service calls    Churn  \n",
       "0                                 3   False.  \n",
       "1                                 0   False.  \n",
       "2                                 1   False.  \n",
       "3                                 1   False.  \n",
       "4                                 2   False.  \n",
       "5                                 1   False.  \n",
       "6                                 1   False.  \n",
       "7                                 0   False.  \n",
       "8                                 2   False.  \n",
       "9                                 0   False.  \n",
       "10                                1   False.  \n",
       "11                                1   False.  \n",
       "12                                1   False.  \n",
       "13                                3   False.  \n",
       "14                                1   False.  \n",
       "15                                1   False.  \n",
       "16                                1   False.  \n",
       "17                                1   False.  \n",
       "18                                4   False.  \n",
       "19                                1   False.  \n",
       "20                                1   False.  \n",
       "21                                3   False.  \n",
       "22                                2   False.  \n",
       "23                                2   False.  \n",
       "24                                1   False.  \n",
       "25                                3   False.  \n",
       "26                                0   False.  \n",
       "27                                0   False.  \n",
       "28                                1   False.  \n",
       "29                                3   False.  \n",
       "...                             ...      ...  \n",
       "1637                              1   False.  \n",
       "1638                              0   False.  \n",
       "1639                              1   False.  \n",
       "1640                              1   False.  \n",
       "1641                              1   False.  \n",
       "1642                              1   False.  \n",
       "1643                              0   False.  \n",
       "1644                              0   False.  \n",
       "1645                              3   False.  \n",
       "1646                              1   False.  \n",
       "1647                              3    True.  \n",
       "1648                              1   False.  \n",
       "1649                              5   False.  \n",
       "1650                              2   False.  \n",
       "1651                              1   False.  \n",
       "1652                              3   False.  \n",
       "1653                              3   False.  \n",
       "1654                              1   False.  \n",
       "1655                              2   False.  \n",
       "1656                              0   False.  \n",
       "1657                              1    True.  \n",
       "1658                              1    True.  \n",
       "1659                              0   False.  \n",
       "1660                              3   False.  \n",
       "1661                              1   False.  \n",
       "1662                              2   False.  \n",
       "1663                              3    True.  \n",
       "1664                              1   False.  \n",
       "1665                              0   False.  \n",
       "1666                              0   False.  \n",
       "\n",
       "[1667 rows x 20 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cat_to_code(Train,cat_variable)\n",
    "cat_to_code(Test,cat_variable01)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "state                            0\n",
       "account length                   0\n",
       "area code                        0\n",
       "international plan               0\n",
       "voice mail plan                  0\n",
       "number vmail messages            0\n",
       "total day minutes                0\n",
       "total day calls                  0\n",
       "total day charge                 0\n",
       "total eve minutes                0\n",
       "total eve calls                  0\n",
       "total eve charge                 0\n",
       "total night minutes              0\n",
       "total night calls                0\n",
       "total night charge               0\n",
       "total intl minutes               0\n",
       "total intl calls                 0\n",
       "total intl charge                0\n",
       "number customer service calls    0\n",
       "Churn                            0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Test.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# FEATURE SELECTION"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x1080 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Lets see which variables are important to be fed to model\n",
    "#Set Pane (Width and Height)\n",
    "a,ax=plt.subplots(figsize=(18,15))\n",
    "\n",
    "#Generate Correlation Chart\n",
    "corr=Train[num_variable].corr()\n",
    "\n",
    "#Plot using seaborn library\n",
    "\n",
    "sns.heatmap(corr,mask=np.zeros_like(corr,dtype=np.bool),cmap=sns.diverging_palette(220,10,as_cmap=True),\\\n",
    "            square=True,ax=ax,annot=True,linewidths=1,linecolor='black',vmin=-1,vmax=1)\n",
    "plt.show()\n",
    "\n",
    "#save the fig\n",
    "#plt.savefig('Correlation')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# CHI-SQUARE FOR CATEGORICAL VARIABLE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "#important library\n",
    "from scipy.stats import chi2_contingency\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "state\n",
      "0.002296221552011188\n",
      "area code\n",
      "0.9150556960243712\n",
      "international plan\n",
      "2.4931077033159556e-50\n",
      "voice mail plan\n",
      "5.15063965903898e-09\n"
     ]
    }
   ],
   "source": [
    "for i in cat_variable:\n",
    "    print(i)\n",
    "    chi2,p,dof,ex=chi2_contingency(pd.crosstab(Train['Churn'],Train[i]))\n",
    "    print(p)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Lets Remove Highly Correlated Varibles\n",
    "remove=['state']\n",
    "Train=Train.drop(remove,axis=1)\n",
    "Test=Test.drop(remove,axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": true
   },
   "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>account length</th>\n",
       "      <th>area code</th>\n",
       "      <th>international plan</th>\n",
       "      <th>voice mail plan</th>\n",
       "      <th>number vmail messages</th>\n",
       "      <th>total day minutes</th>\n",
       "      <th>total day calls</th>\n",
       "      <th>total day charge</th>\n",
       "      <th>total eve minutes</th>\n",
       "      <th>total eve calls</th>\n",
       "      <th>total eve charge</th>\n",
       "      <th>total night minutes</th>\n",
       "      <th>total night calls</th>\n",
       "      <th>total night charge</th>\n",
       "      <th>total intl minutes</th>\n",
       "      <th>total intl calls</th>\n",
       "      <th>total intl charge</th>\n",
       "      <th>number customer service calls</th>\n",
       "      <th>Churn</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>128</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>25</td>\n",
       "      <td>265.1</td>\n",
       "      <td>110</td>\n",
       "      <td>45.07</td>\n",
       "      <td>197.4</td>\n",
       "      <td>99</td>\n",
       "      <td>16.78</td>\n",
       "      <td>244.7</td>\n",
       "      <td>91</td>\n",
       "      <td>11.01</td>\n",
       "      <td>10.0</td>\n",
       "      <td>3</td>\n",
       "      <td>2.70</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>107</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>26</td>\n",
       "      <td>161.6</td>\n",
       "      <td>123</td>\n",
       "      <td>27.47</td>\n",
       "      <td>195.5</td>\n",
       "      <td>103</td>\n",
       "      <td>16.62</td>\n",
       "      <td>254.4</td>\n",
       "      <td>103</td>\n",
       "      <td>11.45</td>\n",
       "      <td>13.7</td>\n",
       "      <td>3</td>\n",
       "      <td>3.70</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>137</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>243.4</td>\n",
       "      <td>114</td>\n",
       "      <td>41.38</td>\n",
       "      <td>121.2</td>\n",
       "      <td>110</td>\n",
       "      <td>10.30</td>\n",
       "      <td>162.6</td>\n",
       "      <td>104</td>\n",
       "      <td>7.32</td>\n",
       "      <td>12.2</td>\n",
       "      <td>5</td>\n",
       "      <td>3.29</td>\n",
       "      <td>0</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>84</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>299.4</td>\n",
       "      <td>71</td>\n",
       "      <td>50.90</td>\n",
       "      <td>61.9</td>\n",
       "      <td>88</td>\n",
       "      <td>5.26</td>\n",
       "      <td>196.9</td>\n",
       "      <td>89</td>\n",
       "      <td>8.86</td>\n",
       "      <td>6.6</td>\n",
       "      <td>7</td>\n",
       "      <td>1.78</td>\n",
       "      <td>2</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>75</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>166.7</td>\n",
       "      <td>113</td>\n",
       "      <td>28.34</td>\n",
       "      <td>148.3</td>\n",
       "      <td>122</td>\n",
       "      <td>12.61</td>\n",
       "      <td>186.9</td>\n",
       "      <td>121</td>\n",
       "      <td>8.41</td>\n",
       "      <td>10.1</td>\n",
       "      <td>3</td>\n",
       "      <td>2.73</td>\n",
       "      <td>3</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>118</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>223.4</td>\n",
       "      <td>98</td>\n",
       "      <td>37.98</td>\n",
       "      <td>220.6</td>\n",
       "      <td>101</td>\n",
       "      <td>18.75</td>\n",
       "      <td>203.9</td>\n",
       "      <td>118</td>\n",
       "      <td>9.18</td>\n",
       "      <td>6.3</td>\n",
       "      <td>6</td>\n",
       "      <td>1.70</td>\n",
       "      <td>0</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>121</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>24</td>\n",
       "      <td>218.2</td>\n",
       "      <td>88</td>\n",
       "      <td>37.09</td>\n",
       "      <td>348.5</td>\n",
       "      <td>108</td>\n",
       "      <td>29.62</td>\n",
       "      <td>212.6</td>\n",
       "      <td>118</td>\n",
       "      <td>9.57</td>\n",
       "      <td>7.5</td>\n",
       "      <td>7</td>\n",
       "      <td>2.03</td>\n",
       "      <td>3</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>147</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>157.0</td>\n",
       "      <td>79</td>\n",
       "      <td>26.69</td>\n",
       "      <td>103.1</td>\n",
       "      <td>94</td>\n",
       "      <td>8.76</td>\n",
       "      <td>211.8</td>\n",
       "      <td>96</td>\n",
       "      <td>9.53</td>\n",
       "      <td>7.1</td>\n",
       "      <td>6</td>\n",
       "      <td>1.92</td>\n",
       "      <td>0</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>117</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>184.5</td>\n",
       "      <td>97</td>\n",
       "      <td>31.37</td>\n",
       "      <td>351.6</td>\n",
       "      <td>80</td>\n",
       "      <td>29.89</td>\n",
       "      <td>215.8</td>\n",
       "      <td>90</td>\n",
       "      <td>9.71</td>\n",
       "      <td>8.7</td>\n",
       "      <td>4</td>\n",
       "      <td>2.35</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>141</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>37</td>\n",
       "      <td>258.6</td>\n",
       "      <td>84</td>\n",
       "      <td>43.96</td>\n",
       "      <td>222.0</td>\n",
       "      <td>111</td>\n",
       "      <td>18.87</td>\n",
       "      <td>326.4</td>\n",
       "      <td>97</td>\n",
       "      <td>14.69</td>\n",
       "      <td>11.2</td>\n",
       "      <td>5</td>\n",
       "      <td>3.02</td>\n",
       "      <td>0</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   account length  area code  international plan  voice mail plan  \\\n",
       "0             128          1                   0                1   \n",
       "1             107          1                   0                1   \n",
       "2             137          1                   0                0   \n",
       "3              84          0                   1                0   \n",
       "4              75          1                   1                0   \n",
       "5             118          2                   1                0   \n",
       "6             121          2                   0                1   \n",
       "7             147          1                   1                0   \n",
       "8             117          0                   0                0   \n",
       "9             141          1                   1                1   \n",
       "\n",
       "   number vmail messages  total day minutes  total day calls  \\\n",
       "0                     25              265.1              110   \n",
       "1                     26              161.6              123   \n",
       "2                      0              243.4              114   \n",
       "3                      0              299.4               71   \n",
       "4                      0              166.7              113   \n",
       "5                      0              223.4               98   \n",
       "6                     24              218.2               88   \n",
       "7                      0              157.0               79   \n",
       "8                      0              184.5               97   \n",
       "9                     37              258.6               84   \n",
       "\n",
       "   total day charge  total eve minutes  total eve calls  total eve charge  \\\n",
       "0             45.07              197.4               99             16.78   \n",
       "1             27.47              195.5              103             16.62   \n",
       "2             41.38              121.2              110             10.30   \n",
       "3             50.90               61.9               88              5.26   \n",
       "4             28.34              148.3              122             12.61   \n",
       "5             37.98              220.6              101             18.75   \n",
       "6             37.09              348.5              108             29.62   \n",
       "7             26.69              103.1               94              8.76   \n",
       "8             31.37              351.6               80             29.89   \n",
       "9             43.96              222.0              111             18.87   \n",
       "\n",
       "   total night minutes  total night calls  total night charge  \\\n",
       "0                244.7                 91               11.01   \n",
       "1                254.4                103               11.45   \n",
       "2                162.6                104                7.32   \n",
       "3                196.9                 89                8.86   \n",
       "4                186.9                121                8.41   \n",
       "5                203.9                118                9.18   \n",
       "6                212.6                118                9.57   \n",
       "7                211.8                 96                9.53   \n",
       "8                215.8                 90                9.71   \n",
       "9                326.4                 97               14.69   \n",
       "\n",
       "   total intl minutes  total intl calls  total intl charge  \\\n",
       "0                10.0                 3               2.70   \n",
       "1                13.7                 3               3.70   \n",
       "2                12.2                 5               3.29   \n",
       "3                 6.6                 7               1.78   \n",
       "4                10.1                 3               2.73   \n",
       "5                 6.3                 6               1.70   \n",
       "6                 7.5                 7               2.03   \n",
       "7                 7.1                 6               1.92   \n",
       "8                 8.7                 4               2.35   \n",
       "9                11.2                 5               3.02   \n",
       "\n",
       "   number customer service calls    Churn  \n",
       "0                              1   False.  \n",
       "1                              1   False.  \n",
       "2                              0   False.  \n",
       "3                              2   False.  \n",
       "4                              3   False.  \n",
       "5                              0   False.  \n",
       "6                              3   False.  \n",
       "7                              0   False.  \n",
       "8                              1   False.  \n",
       "9                              0   False.  "
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Train.head(10)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Updated Variables\n",
    "numerical=['account length', 'number vmail messages', 'total day minutes',\n",
    "       'total day calls', 'total eve minutes',\n",
    "       'total eve calls',  'total night minutes',\n",
    "       'total night calls', 'total intl minutes',\n",
    "       'total intl calls','number customer service calls']\n",
    "\n",
    "categorical=['area code', 'international plan', 'voice mail plan']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Lets go for Feature Scaling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "scrolled": true
   },
   "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>account length</th>\n",
       "      <th>area code</th>\n",
       "      <th>international plan</th>\n",
       "      <th>voice mail plan</th>\n",
       "      <th>number vmail messages</th>\n",
       "      <th>total day minutes</th>\n",
       "      <th>total day calls</th>\n",
       "      <th>total day charge</th>\n",
       "      <th>total eve minutes</th>\n",
       "      <th>total eve calls</th>\n",
       "      <th>total eve charge</th>\n",
       "      <th>total night minutes</th>\n",
       "      <th>total night calls</th>\n",
       "      <th>total night charge</th>\n",
       "      <th>total intl minutes</th>\n",
       "      <th>total intl calls</th>\n",
       "      <th>total intl charge</th>\n",
       "      <th>number customer service calls</th>\n",
       "      <th>Churn</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>128</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>25</td>\n",
       "      <td>265.1</td>\n",
       "      <td>110</td>\n",
       "      <td>45.07</td>\n",
       "      <td>197.4</td>\n",
       "      <td>99</td>\n",
       "      <td>16.78</td>\n",
       "      <td>244.7</td>\n",
       "      <td>91</td>\n",
       "      <td>11.01</td>\n",
       "      <td>10.0</td>\n",
       "      <td>3</td>\n",
       "      <td>2.7</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>107</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>26</td>\n",
       "      <td>161.6</td>\n",
       "      <td>123</td>\n",
       "      <td>27.47</td>\n",
       "      <td>195.5</td>\n",
       "      <td>103</td>\n",
       "      <td>16.62</td>\n",
       "      <td>254.4</td>\n",
       "      <td>103</td>\n",
       "      <td>11.45</td>\n",
       "      <td>13.7</td>\n",
       "      <td>3</td>\n",
       "      <td>3.7</td>\n",
       "      <td>1</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   account length  area code  international plan  voice mail plan  \\\n",
       "0             128          1                   0                1   \n",
       "1             107          1                   0                1   \n",
       "\n",
       "   number vmail messages  total day minutes  total day calls  \\\n",
       "0                     25              265.1              110   \n",
       "1                     26              161.6              123   \n",
       "\n",
       "   total day charge  total eve minutes  total eve calls  total eve charge  \\\n",
       "0             45.07              197.4               99             16.78   \n",
       "1             27.47              195.5              103             16.62   \n",
       "\n",
       "   total night minutes  total night calls  total night charge  \\\n",
       "0                244.7                 91               11.01   \n",
       "1                254.4                103               11.45   \n",
       "\n",
       "   total intl minutes  total intl calls  total intl charge  \\\n",
       "0                10.0                 3                2.7   \n",
       "1                13.7                 3                3.7   \n",
       "\n",
       "   number customer service calls    Churn  \n",
       "0                              1   False.  \n",
       "1                              1   False.  "
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 12 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "Train[numerical].hist(figsize=(20,20),color='g',alpha=0.7)\n",
    "plt.show\n",
    "\n",
    "Train.head(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# As we can see most data is uniformly distributed we will use Z score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "account length\n",
      "number vmail messages\n",
      "total day minutes\n",
      "total day calls\n",
      "total eve minutes\n",
      "total eve calls\n",
      "total night minutes\n",
      "total night calls\n",
      "total intl minutes\n",
      "total intl calls\n",
      "number customer service calls\n"
     ]
    }
   ],
   "source": [
    "#Let's Use Z-Score\n",
    "for i in numerical:\n",
    "        print(i)\n",
    "        Train[i]=(Train[i]-Train[i].mean())/Train[i].std()\n",
    "        \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "account length\n",
      "number vmail messages\n",
      "total day minutes\n",
      "total day calls\n",
      "total eve minutes\n",
      "total eve calls\n",
      "total night minutes\n",
      "total night calls\n",
      "total intl minutes\n",
      "total intl calls\n",
      "number customer service calls\n"
     ]
    }
   ],
   "source": [
    "for i in numerical:\n",
    "        print(i)\n",
    "        Test[i]=(Test[i]-Test[i].mean())/Test[i].std()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>account length</th>\n",
       "      <th>area code</th>\n",
       "      <th>international plan</th>\n",
       "      <th>voice mail plan</th>\n",
       "      <th>number vmail messages</th>\n",
       "      <th>total day minutes</th>\n",
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       "      <th>total eve minutes</th>\n",
       "      <th>total eve calls</th>\n",
       "      <th>total eve charge</th>\n",
       "      <th>total night minutes</th>\n",
       "      <th>total night calls</th>\n",
       "      <th>total night charge</th>\n",
       "      <th>total intl minutes</th>\n",
       "      <th>total intl calls</th>\n",
       "      <th>total intl charge</th>\n",
       "      <th>number customer service calls</th>\n",
       "      <th>Churn</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
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       "      <td>1</td>\n",
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       "      <td>False.</td>\n",
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       "      <td>1.124334</td>\n",
       "      <td>27.47</td>\n",
       "      <td>-0.108064</td>\n",
       "      <td>0.144845</td>\n",
       "      <td>16.62</td>\n",
       "      <td>1.058412</td>\n",
       "      <td>0.147802</td>\n",
       "      <td>11.45</td>\n",
       "      <td>1.240296</td>\n",
       "      <td>-0.601105</td>\n",
       "      <td>3.7</td>\n",
       "      <td>-0.427868</td>\n",
       "      <td>False.</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   account length  area code  international plan  voice mail plan  \\\n",
       "0        0.676388          1                   0                1   \n",
       "1        0.149043          1                   0                1   \n",
       "\n",
       "   number vmail messages  total day minutes  total day calls  \\\n",
       "0               1.234697           1.566532         0.476572   \n",
       "1               1.307752          -0.333688         1.124334   \n",
       "\n",
       "   total day charge  total eve minutes  total eve calls  total eve charge  \\\n",
       "0             45.07          -0.070599        -0.055932             16.78   \n",
       "1             27.47          -0.108064         0.144845             16.62   \n",
       "\n",
       "   total night minutes  total night calls  total night charge  \\\n",
       "0             0.866613          -0.465425               11.01   \n",
       "1             1.058412           0.147802               11.45   \n",
       "\n",
       "   total intl minutes  total intl calls  total intl charge  \\\n",
       "0           -0.084995         -0.601105                2.7   \n",
       "1            1.240296         -0.601105                3.7   \n",
       "\n",
       "   number customer service calls    Churn  \n",
       "0                      -0.427868   False.  \n",
       "1                      -0.427868   False.  "
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Train.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Lets apply\n",
    "\n",
    "Train=Train.drop(['total day charge','total eve charge','total night charge','total intl charge'],axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "Test=Test.drop(['total day charge','total eve charge','total night charge','total intl charge'],axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
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       "      <td>False.</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0.100500</td>\n",
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       "      <td>-0.967062</td>\n",
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      "text/plain": [
       "   account length  area code  international plan  voice mail plan  \\\n",
       "0        0.059728          2                   0                0   \n",
       "1        0.973416          2                   0                0   \n",
       "2        0.110488          0                   0                1   \n",
       "3        0.008968          1                   0                0   \n",
       "4        0.237390          1                   0                0   \n",
       "\n",
       "   number vmail messages  total day minutes  total day calls  \\\n",
       "0              -0.534011          -2.093906         1.230541   \n",
       "1              -0.534011           0.801860        -0.683865   \n",
       "2               1.657103           2.150183        -0.218199   \n",
       "3              -0.534011           0.672906         1.230541   \n",
       "4              -0.534011           0.305009        -1.097790   \n",
       "\n",
       "   total eve minutes  total eve calls  total night minutes  total night calls  \\\n",
       "0           0.237908        -1.392424             0.725042          -1.281157   \n",
       "1           0.892858         1.968418            -2.086386          -0.895009   \n",
       "2           0.743553         0.237075             1.999899           1.325343   \n",
       "3          -1.464165        -0.628596             0.419710          -0.846740   \n",
       "4          -1.511942         0.033388             0.100500           0.359972   \n",
       "\n",
       "   total intl minutes  total intl calls  number customer service calls  \\\n",
       "0            0.107148         -0.550528                       1.098075   \n",
       "1           -0.300311          1.084626                      -1.230794   \n",
       "2            1.255441          0.675838                      -0.454504   \n",
       "3            1.996275         -0.959317                      -0.454504   \n",
       "4           -0.967062         -0.141740                       0.321785   \n",
       "\n",
       "     Churn  \n",
       "0   False.  \n",
       "1   False.  \n",
       "2   False.  \n",
       "3   False.  \n",
       "4   False.  "
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Test.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Let's convert Categorical values into Continuous Varibles\n",
    "#Train[\"international plan\"] = Train[\"international plan\"].replace(\" yes\",1)\n",
    "#Train[\"voice mail plan\"] = Train[\"voice mail plan\"].replace(\" yes\",1)\n",
    "#Train[\"international plan\"] = Train[\"international plan\"].replace(\" no\",0)\n",
    "#Train[\"voice mail plan\"] = Train[\"voice mail plan\"].replace(\" no\",0)\n",
    "Train[\"Churn\"] = Train[\"Churn\"].replace(\" False.\",0)\n",
    "Train[\"Churn\"] = Train[\"Churn\"].replace(\" True.\",1)\n",
    "Test[\"Churn\"] = Test[\"Churn\"].replace(\" False.\",0)\n",
    "Test[\"Churn\"] = Test[\"Churn\"].replace(\" True.\",1)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Sampling for feeding our data to Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Lets divide our data into TRAIN AND TEST\n",
    "\n",
    "X_Train=Train.iloc[:,0:14]\n",
    "Y_Train=Train.iloc[:,14]\n",
    "X_Test=Test.iloc[:,0:14]\n",
    "Y_Test=Test.iloc[:,14]\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "X contains all Independent Variables,Y contains Dependent Variable"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Now we will use SMOTE to nullify Over-Sampling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Load Library\n",
    "from imblearn.over_sampling import SMOTE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Smote=SMOTE(random_state=101)\n",
    "X_Train_Sm,Y_Train_Sm=SMOTE().fit_sample(X_Train,Y_Train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
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       "      <td>0.626055</td>\n",
       "      <td>-1.038776</td>\n",
       "      <td>1.098534</td>\n",
       "      <td>-0.276270</td>\n",
       "      <td>1.067643</td>\n",
       "      <td>-0.049177</td>\n",
       "      <td>-0.601105</td>\n",
       "      <td>1.092477</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.425271</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.591671</td>\n",
       "      <td>0.800936</td>\n",
       "      <td>-0.121363</td>\n",
       "      <td>0.386870</td>\n",
       "      <td>0.044456</td>\n",
       "      <td>0.059872</td>\n",
       "      <td>0.914336</td>\n",
       "      <td>-1.410287</td>\n",
       "      <td>0.617806</td>\n",
       "      <td>-1.188040</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.500606</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1.161643</td>\n",
       "      <td>0.705466</td>\n",
       "      <td>-0.619642</td>\n",
       "      <td>2.908864</td>\n",
       "      <td>0.395816</td>\n",
       "      <td>0.231898</td>\n",
       "      <td>0.914336</td>\n",
       "      <td>-0.980462</td>\n",
       "      <td>1.024109</td>\n",
       "      <td>1.092477</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1.153510</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.591671</td>\n",
       "      <td>-0.418142</td>\n",
       "      <td>-1.068093</td>\n",
       "      <td>-1.930052</td>\n",
       "      <td>-0.306903</td>\n",
       "      <td>0.216079</td>\n",
       "      <td>-0.209913</td>\n",
       "      <td>-1.123737</td>\n",
       "      <td>0.617806</td>\n",
       "      <td>-1.188040</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.400159</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.591671</td>\n",
       "      <td>0.086747</td>\n",
       "      <td>-0.171191</td>\n",
       "      <td>2.969991</td>\n",
       "      <td>-1.009622</td>\n",
       "      <td>0.295172</td>\n",
       "      <td>-0.516527</td>\n",
       "      <td>-0.550638</td>\n",
       "      <td>-0.194801</td>\n",
       "      <td>-0.427868</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1.002840</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2.111354</td>\n",
       "      <td>1.447194</td>\n",
       "      <td>-0.818953</td>\n",
       "      <td>0.414476</td>\n",
       "      <td>0.546398</td>\n",
       "      <td>2.482073</td>\n",
       "      <td>-0.158811</td>\n",
       "      <td>0.344829</td>\n",
       "      <td>0.211502</td>\n",
       "      <td>-1.188040</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>-0.905648</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.591671</td>\n",
       "      <td>-0.930375</td>\n",
       "      <td>1.821925</td>\n",
       "      <td>0.542646</td>\n",
       "      <td>-0.859039</td>\n",
       "      <td>0.156760</td>\n",
       "      <td>0.556621</td>\n",
       "      <td>0.882109</td>\n",
       "      <td>0.617806</td>\n",
       "      <td>1.852649</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>-0.679643</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.591671</td>\n",
       "      <td>0.145498</td>\n",
       "      <td>1.323646</td>\n",
       "      <td>-0.741027</td>\n",
       "      <td>2.403583</td>\n",
       "      <td>-0.096335</td>\n",
       "      <td>-0.312118</td>\n",
       "      <td>-0.407364</td>\n",
       "      <td>0.211502</td>\n",
       "      <td>-1.188040</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1.680855</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.591671</td>\n",
       "      <td>-0.935883</td>\n",
       "      <td>-0.221019</td>\n",
       "      <td>-1.894559</td>\n",
       "      <td>-1.461369</td>\n",
       "      <td>-1.181876</td>\n",
       "      <td>1.425359</td>\n",
       "      <td>0.344829</td>\n",
       "      <td>-1.007408</td>\n",
       "      <td>-0.427868</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>-0.152297</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.591671</td>\n",
       "      <td>-0.425486</td>\n",
       "      <td>-0.619642</td>\n",
       "      <td>0.919269</td>\n",
       "      <td>-1.260592</td>\n",
       "      <td>-0.169495</td>\n",
       "      <td>0.761030</td>\n",
       "      <td>0.738834</td>\n",
       "      <td>0.211502</td>\n",
       "      <td>1.092477</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>-0.980983</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.591671</td>\n",
       "      <td>-1.084596</td>\n",
       "      <td>-1.516544</td>\n",
       "      <td>2.094490</td>\n",
       "      <td>-1.210398</td>\n",
       "      <td>0.042076</td>\n",
       "      <td>-0.056607</td>\n",
       "      <td>1.025384</td>\n",
       "      <td>0.617806</td>\n",
       "      <td>1.852649</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>1.505073</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.591671</td>\n",
       "      <td>2.811313</td>\n",
       "      <td>-1.666027</td>\n",
       "      <td>2.303506</td>\n",
       "      <td>-0.156320</td>\n",
       "      <td>-0.796302</td>\n",
       "      <td>1.425359</td>\n",
       "      <td>-1.732655</td>\n",
       "      <td>1.836716</td>\n",
       "      <td>1.852649</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>-0.403414</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1.380807</td>\n",
       "      <td>0.305227</td>\n",
       "      <td>1.921580</td>\n",
       "      <td>1.575894</td>\n",
       "      <td>-0.507680</td>\n",
       "      <td>-2.206121</td>\n",
       "      <td>-1.283061</td>\n",
       "      <td>1.276114</td>\n",
       "      <td>-0.194801</td>\n",
       "      <td>-0.427868</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>-0.202521</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.591671</td>\n",
       "      <td>0.200577</td>\n",
       "      <td>0.675883</td>\n",
       "      <td>0.339545</td>\n",
       "      <td>0.546398</td>\n",
       "      <td>-1.409267</td>\n",
       "      <td>1.067643</td>\n",
       "      <td>-0.765550</td>\n",
       "      <td>-0.601105</td>\n",
       "      <td>1.092477</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>-0.629419</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1.819135</td>\n",
       "      <td>0.182217</td>\n",
       "      <td>-1.715855</td>\n",
       "      <td>0.233066</td>\n",
       "      <td>-1.762534</td>\n",
       "      <td>-0.695459</td>\n",
       "      <td>0.403314</td>\n",
       "      <td>-0.084995</td>\n",
       "      <td>0.211502</td>\n",
       "      <td>-0.427868</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>-0.704754</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.591671</td>\n",
       "      <td>0.819296</td>\n",
       "      <td>-0.519986</td>\n",
       "      <td>-0.817929</td>\n",
       "      <td>-0.608068</td>\n",
       "      <td>-0.159609</td>\n",
       "      <td>-1.334163</td>\n",
       "      <td>0.989565</td>\n",
       "      <td>-1.007408</td>\n",
       "      <td>-0.427868</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>1.153510</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.591671</td>\n",
       "      <td>-0.453025</td>\n",
       "      <td>0.825367</td>\n",
       "      <td>0.763493</td>\n",
       "      <td>-0.357097</td>\n",
       "      <td>0.156760</td>\n",
       "      <td>1.680870</td>\n",
       "      <td>0.129917</td>\n",
       "      <td>-0.194801</td>\n",
       "      <td>-1.188040</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>-0.604308</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.591671</td>\n",
       "      <td>-2.154961</td>\n",
       "      <td>-0.569814</td>\n",
       "      <td>-0.612857</td>\n",
       "      <td>1.048340</td>\n",
       "      <td>0.172579</td>\n",
       "      <td>-1.845185</td>\n",
       "      <td>-1.625199</td>\n",
       "      <td>0.617806</td>\n",
       "      <td>2.612822</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>0.726611</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.591671</td>\n",
       "      <td>0.059208</td>\n",
       "      <td>0.576227</td>\n",
       "      <td>-2.525550</td>\n",
       "      <td>-0.055932</td>\n",
       "      <td>-0.377113</td>\n",
       "      <td>-1.129754</td>\n",
       "      <td>-0.264089</td>\n",
       "      <td>5.899751</td>\n",
       "      <td>-1.188040</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>0.249489</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.591671</td>\n",
       "      <td>-1.273700</td>\n",
       "      <td>0.127776</td>\n",
       "      <td>-1.255680</td>\n",
       "      <td>0.094651</td>\n",
       "      <td>-0.222883</td>\n",
       "      <td>0.250007</td>\n",
       "      <td>-0.908825</td>\n",
       "      <td>0.617806</td>\n",
       "      <td>0.332305</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>0.776835</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.591671</td>\n",
       "      <td>-1.811636</td>\n",
       "      <td>-0.719298</td>\n",
       "      <td>0.871944</td>\n",
       "      <td>-1.411175</td>\n",
       "      <td>0.714361</td>\n",
       "      <td>0.761030</td>\n",
       "      <td>0.022461</td>\n",
       "      <td>-1.007408</td>\n",
       "      <td>-1.188040</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>1.831525</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.591671</td>\n",
       "      <td>-1.018501</td>\n",
       "      <td>-1.217576</td>\n",
       "      <td>1.500964</td>\n",
       "      <td>0.596592</td>\n",
       "      <td>0.985252</td>\n",
       "      <td>0.761030</td>\n",
       "      <td>1.885032</td>\n",
       "      <td>0.211502</td>\n",
       "      <td>1.092477</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>-1.106541</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2.257464</td>\n",
       "      <td>0.609996</td>\n",
       "      <td>0.725711</td>\n",
       "      <td>-0.194825</td>\n",
       "      <td>0.596592</td>\n",
       "      <td>-0.359317</td>\n",
       "      <td>0.761030</td>\n",
       "      <td>-0.264089</td>\n",
       "      <td>-0.601105</td>\n",
       "      <td>-1.188040</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>-1.181876</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.591671</td>\n",
       "      <td>-0.834905</td>\n",
       "      <td>-1.367060</td>\n",
       "      <td>-0.896803</td>\n",
       "      <td>-0.005738</td>\n",
       "      <td>-1.953026</td>\n",
       "      <td>-1.640776</td>\n",
       "      <td>1.598482</td>\n",
       "      <td>-0.194801</td>\n",
       "      <td>1.092477</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>-2.035674</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.591671</td>\n",
       "      <td>0.187725</td>\n",
       "      <td>0.426744</td>\n",
       "      <td>1.128285</td>\n",
       "      <td>-0.808845</td>\n",
       "      <td>-0.383045</td>\n",
       "      <td>0.096700</td>\n",
       "      <td>-1.410287</td>\n",
       "      <td>0.617806</td>\n",
       "      <td>-1.188040</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>-1.307435</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.591671</td>\n",
       "      <td>-1.110299</td>\n",
       "      <td>0.825367</td>\n",
       "      <td>0.278418</td>\n",
       "      <td>0.446010</td>\n",
       "      <td>-0.438409</td>\n",
       "      <td>-0.516527</td>\n",
       "      <td>0.309010</td>\n",
       "      <td>-1.413712</td>\n",
       "      <td>-0.427868</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3303</th>\n",
       "      <td>0.324824</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1.307752</td>\n",
       "      <td>-0.783498</td>\n",
       "      <td>-0.619642</td>\n",
       "      <td>-0.892860</td>\n",
       "      <td>1.249117</td>\n",
       "      <td>0.923955</td>\n",
       "      <td>-0.312118</td>\n",
       "      <td>0.452285</td>\n",
       "      <td>1.024109</td>\n",
       "      <td>0.332305</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3304</th>\n",
       "      <td>-0.754978</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.591671</td>\n",
       "      <td>0.116123</td>\n",
       "      <td>0.675883</td>\n",
       "      <td>-0.046937</td>\n",
       "      <td>2.002030</td>\n",
       "      <td>0.111282</td>\n",
       "      <td>-1.027549</td>\n",
       "      <td>1.276114</td>\n",
       "      <td>0.211502</td>\n",
       "      <td>1.852649</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3305</th>\n",
       "      <td>-1.081430</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1.015533</td>\n",
       "      <td>0.813788</td>\n",
       "      <td>1.323646</td>\n",
       "      <td>0.745746</td>\n",
       "      <td>-0.758651</td>\n",
       "      <td>-0.527388</td>\n",
       "      <td>-0.720936</td>\n",
       "      <td>0.452285</td>\n",
       "      <td>1.024109</td>\n",
       "      <td>0.332305</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3306</th>\n",
       "      <td>0.123931</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1.526916</td>\n",
       "      <td>-1.765737</td>\n",
       "      <td>1.522957</td>\n",
       "      <td>0.057571</td>\n",
       "      <td>1.550282</td>\n",
       "      <td>0.566063</td>\n",
       "      <td>-1.385265</td>\n",
       "      <td>-0.765550</td>\n",
       "      <td>-0.601105</td>\n",
       "      <td>-0.427868</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3307</th>\n",
       "      <td>1.781302</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.591671</td>\n",
       "      <td>0.442924</td>\n",
       "      <td>0.426744</td>\n",
       "      <td>0.651097</td>\n",
       "      <td>1.148729</td>\n",
       "      <td>-0.794324</td>\n",
       "      <td>-1.794083</td>\n",
       "      <td>2.708861</td>\n",
       "      <td>-0.194801</td>\n",
       "      <td>1.852649</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3308</th>\n",
       "      <td>-1.407882</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.591671</td>\n",
       "      <td>0.578785</td>\n",
       "      <td>-0.669470</td>\n",
       "      <td>-0.695675</td>\n",
       "      <td>-0.156320</td>\n",
       "      <td>1.285802</td>\n",
       "      <td>-1.436367</td>\n",
       "      <td>1.097021</td>\n",
       "      <td>0.617806</td>\n",
       "      <td>-0.427868</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3309</th>\n",
       "      <td>-0.026739</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.591671</td>\n",
       "      <td>0.727498</td>\n",
       "      <td>0.576227</td>\n",
       "      <td>0.487434</td>\n",
       "      <td>0.094651</td>\n",
       "      <td>1.076208</td>\n",
       "      <td>-0.261016</td>\n",
       "      <td>0.631378</td>\n",
       "      <td>-0.194801</td>\n",
       "      <td>1.852649</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3310</th>\n",
       "      <td>-0.177409</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.591671</td>\n",
       "      <td>0.195069</td>\n",
       "      <td>-0.470158</td>\n",
       "      <td>-2.148927</td>\n",
       "      <td>0.345622</td>\n",
       "      <td>0.473129</td>\n",
       "      <td>0.403314</td>\n",
       "      <td>1.204477</td>\n",
       "      <td>5.087144</td>\n",
       "      <td>0.332305</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3311</th>\n",
       "      <td>0.676388</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.591671</td>\n",
       "      <td>-0.588886</td>\n",
       "      <td>-0.320675</td>\n",
       "      <td>1.623219</td>\n",
       "      <td>-0.859039</td>\n",
       "      <td>-0.248588</td>\n",
       "      <td>1.220950</td>\n",
       "      <td>-1.195374</td>\n",
       "      <td>0.211502</td>\n",
       "      <td>0.332305</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3312</th>\n",
       "      <td>2.007307</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.591671</td>\n",
       "      <td>0.920274</td>\n",
       "      <td>1.473129</td>\n",
       "      <td>-1.115679</td>\n",
       "      <td>-0.357097</td>\n",
       "      <td>1.216596</td>\n",
       "      <td>0.505518</td>\n",
       "      <td>1.419389</td>\n",
       "      <td>-0.194801</td>\n",
       "      <td>0.332305</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3313</th>\n",
       "      <td>0.651276</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.591671</td>\n",
       "      <td>-1.413233</td>\n",
       "      <td>1.373474</td>\n",
       "      <td>-1.129481</td>\n",
       "      <td>-0.256709</td>\n",
       "      <td>-0.187291</td>\n",
       "      <td>-0.158811</td>\n",
       "      <td>-0.084995</td>\n",
       "      <td>0.211502</td>\n",
       "      <td>-0.427868</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3314</th>\n",
       "      <td>-0.302968</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.591671</td>\n",
       "      <td>-0.019738</td>\n",
       "      <td>-0.968437</td>\n",
       "      <td>0.645182</td>\n",
       "      <td>-1.310787</td>\n",
       "      <td>-1.363789</td>\n",
       "      <td>1.016541</td>\n",
       "      <td>-0.407364</td>\n",
       "      <td>-0.194801</td>\n",
       "      <td>-0.427868</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3315</th>\n",
       "      <td>1.203733</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.723314</td>\n",
       "      <td>-0.574199</td>\n",
       "      <td>0.277260</td>\n",
       "      <td>-1.705261</td>\n",
       "      <td>0.295427</td>\n",
       "      <td>-0.446318</td>\n",
       "      <td>-0.107709</td>\n",
       "      <td>-1.338649</td>\n",
       "      <td>-0.194801</td>\n",
       "      <td>-1.188040</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3316</th>\n",
       "      <td>0.048596</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1.526916</td>\n",
       "      <td>-0.287789</td>\n",
       "      <td>0.526400</td>\n",
       "      <td>0.357292</td>\n",
       "      <td>-0.206515</td>\n",
       "      <td>0.384150</td>\n",
       "      <td>0.403314</td>\n",
       "      <td>0.738834</td>\n",
       "      <td>1.836716</td>\n",
       "      <td>-1.188040</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3317</th>\n",
       "      <td>1.555297</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.591671</td>\n",
       "      <td>0.319914</td>\n",
       "      <td>-0.519986</td>\n",
       "      <td>-0.246094</td>\n",
       "      <td>0.646787</td>\n",
       "      <td>0.202238</td>\n",
       "      <td>-0.312118</td>\n",
       "      <td>-0.873006</td>\n",
       "      <td>1.430413</td>\n",
       "      <td>-0.427868</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3318</th>\n",
       "      <td>-1.232100</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.591671</td>\n",
       "      <td>-1.007485</td>\n",
       "      <td>1.522957</td>\n",
       "      <td>1.962376</td>\n",
       "      <td>0.897758</td>\n",
       "      <td>-0.165541</td>\n",
       "      <td>0.301109</td>\n",
       "      <td>0.488103</td>\n",
       "      <td>-0.194801</td>\n",
       "      <td>0.332305</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3319</th>\n",
       "      <td>-0.302968</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.591671</td>\n",
       "      <td>-1.181902</td>\n",
       "      <td>-0.071535</td>\n",
       "      <td>0.175882</td>\n",
       "      <td>0.747175</td>\n",
       "      <td>1.582398</td>\n",
       "      <td>0.607723</td>\n",
       "      <td>2.028306</td>\n",
       "      <td>0.617806</td>\n",
       "      <td>1.092477</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3320</th>\n",
       "      <td>0.525718</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.591671</td>\n",
       "      <td>-0.730255</td>\n",
       "      <td>0.028121</td>\n",
       "      <td>-0.090318</td>\n",
       "      <td>-1.160204</td>\n",
       "      <td>-1.597111</td>\n",
       "      <td>1.680870</td>\n",
       "      <td>-0.192452</td>\n",
       "      <td>-0.194801</td>\n",
       "      <td>1.852649</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3321</th>\n",
       "      <td>-1.031206</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.591671</td>\n",
       "      <td>0.259328</td>\n",
       "      <td>0.875195</td>\n",
       "      <td>-2.286956</td>\n",
       "      <td>0.496204</td>\n",
       "      <td>0.182465</td>\n",
       "      <td>1.731972</td>\n",
       "      <td>1.061202</td>\n",
       "      <td>1.430413</td>\n",
       "      <td>1.092477</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3322</th>\n",
       "      <td>-0.980983</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.591671</td>\n",
       "      <td>2.594670</td>\n",
       "      <td>0.227432</td>\n",
       "      <td>1.272230</td>\n",
       "      <td>1.098534</td>\n",
       "      <td>-0.402818</td>\n",
       "      <td>-1.436367</td>\n",
       "      <td>0.452285</td>\n",
       "      <td>-1.007408</td>\n",
       "      <td>1.852649</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3323</th>\n",
       "      <td>0.400159</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.591671</td>\n",
       "      <td>-1.126823</td>\n",
       "      <td>1.273818</td>\n",
       "      <td>0.952790</td>\n",
       "      <td>-0.156320</td>\n",
       "      <td>0.516630</td>\n",
       "      <td>-2.254003</td>\n",
       "      <td>1.204477</td>\n",
       "      <td>-0.601105</td>\n",
       "      <td>2.612822</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3324</th>\n",
       "      <td>1.454850</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.591671</td>\n",
       "      <td>-0.183139</td>\n",
       "      <td>0.675883</td>\n",
       "      <td>-0.064683</td>\n",
       "      <td>0.245233</td>\n",
       "      <td>-0.141813</td>\n",
       "      <td>-0.925345</td>\n",
       "      <td>0.488103</td>\n",
       "      <td>-0.194801</td>\n",
       "      <td>-0.427868</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3325</th>\n",
       "      <td>-0.579196</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.591671</td>\n",
       "      <td>0.250148</td>\n",
       "      <td>-0.071535</td>\n",
       "      <td>-1.657937</td>\n",
       "      <td>-0.608068</td>\n",
       "      <td>0.838931</td>\n",
       "      <td>0.454416</td>\n",
       "      <td>-0.335726</td>\n",
       "      <td>-0.194801</td>\n",
       "      <td>0.332305</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3326</th>\n",
       "      <td>-0.127186</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.591671</td>\n",
       "      <td>-1.343466</td>\n",
       "      <td>1.373474</td>\n",
       "      <td>1.652796</td>\n",
       "      <td>-0.658262</td>\n",
       "      <td>-0.434455</td>\n",
       "      <td>-0.414322</td>\n",
       "      <td>1.670120</td>\n",
       "      <td>1.024109</td>\n",
       "      <td>-0.427868</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3327</th>\n",
       "      <td>-0.554084</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.591671</td>\n",
       "      <td>-0.827561</td>\n",
       "      <td>-0.121363</td>\n",
       "      <td>-0.222431</td>\n",
       "      <td>-1.611952</td>\n",
       "      <td>0.405901</td>\n",
       "      <td>1.425359</td>\n",
       "      <td>0.559741</td>\n",
       "      <td>0.211502</td>\n",
       "      <td>0.332305</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3328</th>\n",
       "      <td>2.283536</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2.038300</td>\n",
       "      <td>-0.432830</td>\n",
       "      <td>-1.167749</td>\n",
       "      <td>0.286305</td>\n",
       "      <td>1.299311</td>\n",
       "      <td>1.546807</td>\n",
       "      <td>-0.874243</td>\n",
       "      <td>-0.120814</td>\n",
       "      <td>0.617806</td>\n",
       "      <td>0.332305</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3329</th>\n",
       "      <td>-0.830313</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.591671</td>\n",
       "      <td>0.942305</td>\n",
       "      <td>-2.164306</td>\n",
       "      <td>-0.938212</td>\n",
       "      <td>-2.264476</td>\n",
       "      <td>-0.189269</td>\n",
       "      <td>1.169848</td>\n",
       "      <td>-0.228270</td>\n",
       "      <td>-0.194801</td>\n",
       "      <td>1.092477</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3330</th>\n",
       "      <td>-1.834780</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.591671</td>\n",
       "      <td>0.018817</td>\n",
       "      <td>0.426744</td>\n",
       "      <td>1.731670</td>\n",
       "      <td>-2.113894</td>\n",
       "      <td>-0.177405</td>\n",
       "      <td>-0.465425</td>\n",
       "      <td>1.383570</td>\n",
       "      <td>0.617806</td>\n",
       "      <td>0.332305</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3331</th>\n",
       "      <td>2.082642</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.591671</td>\n",
       "      <td>0.624684</td>\n",
       "      <td>0.227432</td>\n",
       "      <td>-0.815958</td>\n",
       "      <td>-0.808845</td>\n",
       "      <td>-1.219445</td>\n",
       "      <td>1.885279</td>\n",
       "      <td>-1.875929</td>\n",
       "      <td>2.243020</td>\n",
       "      <td>0.332305</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3332</th>\n",
       "      <td>-0.679643</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1.234697</td>\n",
       "      <td>1.002892</td>\n",
       "      <td>0.626055</td>\n",
       "      <td>1.280117</td>\n",
       "      <td>-0.909233</td>\n",
       "      <td>0.801362</td>\n",
       "      <td>-1.180856</td>\n",
       "      <td>1.240296</td>\n",
       "      <td>-0.194801</td>\n",
       "      <td>-1.188040</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3333 rows × 15 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      account length  area code  international plan  voice mail plan  \\\n",
       "0           0.676388          1                   0                1   \n",
       "1           0.149043          1                   0                1   \n",
       "2           0.902393          1                   0                0   \n",
       "3          -0.428526          0                   1                0   \n",
       "4          -0.654531          1                   1                0   \n",
       "5           0.425271          2                   1                0   \n",
       "6           0.500606          2                   0                1   \n",
       "7           1.153510          1                   1                0   \n",
       "8           0.400159          0                   0                0   \n",
       "9           1.002840          1                   1                1   \n",
       "10         -0.905648          1                   0                0   \n",
       "11         -0.679643          1                   0                0   \n",
       "12          1.680855          0                   0                0   \n",
       "13         -0.152297          2                   0                0   \n",
       "14         -0.980983          1                   0                0   \n",
       "15          1.505073          1                   0                0   \n",
       "16         -0.403414          0                   0                1   \n",
       "17         -0.202521          2                   0                0   \n",
       "18         -0.629419          2                   0                1   \n",
       "19         -0.704754          1                   0                0   \n",
       "20          1.153510          1                   0                0   \n",
       "21         -0.604308          0                   0                0   \n",
       "22          0.726611          1                   0                0   \n",
       "23          0.249489          1                   0                0   \n",
       "24          0.776835          2                   0                0   \n",
       "25          1.831525          1                   0                0   \n",
       "26         -1.106541          0                   0                1   \n",
       "27         -1.181876          0                   0                0   \n",
       "28         -2.035674          1                   0                0   \n",
       "29         -1.307435          2                   0                0   \n",
       "...              ...        ...                 ...              ...   \n",
       "3303        0.324824          1                   0                1   \n",
       "3304       -0.754978          2                   1                0   \n",
       "3305       -1.081430          1                   0                1   \n",
       "3306        0.123931          0                   0                1   \n",
       "3307        1.781302          0                   0                0   \n",
       "3308       -1.407882          1                   0                0   \n",
       "3309       -0.026739          0                   1                0   \n",
       "3310       -0.177409          1                   0                0   \n",
       "3311        0.676388          1                   0                0   \n",
       "3312        2.007307          0                   0                0   \n",
       "3313        0.651276          0                   0                0   \n",
       "3314       -0.302968          1                   0                0   \n",
       "3315        1.203733          1                   0                1   \n",
       "3316        0.048596          2                   0                1   \n",
       "3317        1.555297          1                   1                0   \n",
       "3318       -1.232100          1                   0                0   \n",
       "3319       -0.302968          1                   0                0   \n",
       "3320        0.525718          2                   1                0   \n",
       "3321       -1.031206          1                   0                0   \n",
       "3322       -0.980983          0                   0                0   \n",
       "3323        0.400159          1                   0                0   \n",
       "3324        1.454850          1                   0                0   \n",
       "3325       -0.579196          0                   0                0   \n",
       "3326       -0.127186          1                   0                0   \n",
       "3327       -0.554084          1                   0                0   \n",
       "3328        2.283536          1                   0                1   \n",
       "3329       -0.830313          1                   0                0   \n",
       "3330       -1.834780          2                   0                0   \n",
       "3331        2.082642          2                   1                0   \n",
       "3332       -0.679643          1                   0                1   \n",
       "\n",
       "      number vmail messages  total day minutes  total day calls  \\\n",
       "0                  1.234697           1.566532         0.476572   \n",
       "1                  1.307752          -0.333688         1.124334   \n",
       "2                 -0.591671           1.168128         0.675883   \n",
       "3                 -0.591671           2.196267        -1.466716   \n",
       "4                 -0.591671          -0.240054         0.626055   \n",
       "5                 -0.591671           0.800936        -0.121363   \n",
       "6                  1.161643           0.705466        -0.619642   \n",
       "7                 -0.591671          -0.418142        -1.068093   \n",
       "8                 -0.591671           0.086747        -0.171191   \n",
       "9                  2.111354           1.447194        -0.818953   \n",
       "10                -0.591671          -0.930375         1.821925   \n",
       "11                -0.591671           0.145498         1.323646   \n",
       "12                -0.591671          -0.935883        -0.221019   \n",
       "13                -0.591671          -0.425486        -0.619642   \n",
       "14                -0.591671          -1.084596        -1.516544   \n",
       "15                -0.591671           2.811313        -1.666027   \n",
       "16                 1.380807           0.305227         1.921580   \n",
       "17                -0.591671           0.200577         0.675883   \n",
       "18                 1.819135           0.182217        -1.715855   \n",
       "19                -0.591671           0.819296        -0.519986   \n",
       "20                -0.591671          -0.453025         0.825367   \n",
       "21                -0.591671          -2.154961        -0.569814   \n",
       "22                -0.591671           0.059208         0.576227   \n",
       "23                -0.591671          -1.273700         0.127776   \n",
       "24                -0.591671          -1.811636        -0.719298   \n",
       "25                -0.591671          -1.018501        -1.217576   \n",
       "26                 2.257464           0.609996         0.725711   \n",
       "27                -0.591671          -0.834905        -1.367060   \n",
       "28                -0.591671           0.187725         0.426744   \n",
       "29                -0.591671          -1.110299         0.825367   \n",
       "...                     ...                ...              ...   \n",
       "3303               1.307752          -0.783498        -0.619642   \n",
       "3304              -0.591671           0.116123         0.675883   \n",
       "3305               1.015533           0.813788         1.323646   \n",
       "3306               1.526916          -1.765737         1.522957   \n",
       "3307              -0.591671           0.442924         0.426744   \n",
       "3308              -0.591671           0.578785        -0.669470   \n",
       "3309              -0.591671           0.727498         0.576227   \n",
       "3310              -0.591671           0.195069        -0.470158   \n",
       "3311              -0.591671          -0.588886        -0.320675   \n",
       "3312              -0.591671           0.920274         1.473129   \n",
       "3313              -0.591671          -1.413233         1.373474   \n",
       "3314              -0.591671          -0.019738        -0.968437   \n",
       "3315               0.723314          -0.574199         0.277260   \n",
       "3316               1.526916          -0.287789         0.526400   \n",
       "3317              -0.591671           0.319914        -0.519986   \n",
       "3318              -0.591671          -1.007485         1.522957   \n",
       "3319              -0.591671          -1.181902        -0.071535   \n",
       "3320              -0.591671          -0.730255         0.028121   \n",
       "3321              -0.591671           0.259328         0.875195   \n",
       "3322              -0.591671           2.594670         0.227432   \n",
       "3323              -0.591671          -1.126823         1.273818   \n",
       "3324              -0.591671          -0.183139         0.675883   \n",
       "3325              -0.591671           0.250148        -0.071535   \n",
       "3326              -0.591671          -1.343466         1.373474   \n",
       "3327              -0.591671          -0.827561        -0.121363   \n",
       "3328               2.038300          -0.432830        -1.167749   \n",
       "3329              -0.591671           0.942305        -2.164306   \n",
       "3330              -0.591671           0.018817         0.426744   \n",
       "3331              -0.591671           0.624684         0.227432   \n",
       "3332               1.234697           1.002892         0.626055   \n",
       "\n",
       "      total eve minutes  total eve calls  total night minutes  \\\n",
       "0             -0.070599        -0.055932             0.866613   \n",
       "1             -0.108064         0.144845             1.058412   \n",
       "2             -1.573147         0.496204            -0.756756   \n",
       "3             -2.742453        -0.608068            -0.078539   \n",
       "4             -1.038776         1.098534            -0.276270   \n",
       "5              0.386870         0.044456             0.059872   \n",
       "6              2.908864         0.395816             0.231898   \n",
       "7             -1.930052        -0.306903             0.216079   \n",
       "8              2.969991        -1.009622             0.295172   \n",
       "9              0.414476         0.546398             2.482073   \n",
       "10             0.542646        -0.859039             0.156760   \n",
       "11            -0.741027         2.403583            -0.096335   \n",
       "12            -1.894559        -1.461369            -1.181876   \n",
       "13             0.919269        -1.260592            -0.169495   \n",
       "14             2.094490        -1.210398             0.042076   \n",
       "15             2.303506        -0.156320            -0.796302   \n",
       "16             1.575894        -0.507680            -2.206121   \n",
       "17             0.339545         0.546398            -1.409267   \n",
       "18             0.233066        -1.762534            -0.695459   \n",
       "19            -0.817929        -0.608068            -0.159609   \n",
       "20             0.763493        -0.357097             0.156760   \n",
       "21            -0.612857         1.048340             0.172579   \n",
       "22            -2.525550        -0.055932            -0.377113   \n",
       "23            -1.255680         0.094651            -0.222883   \n",
       "24             0.871944        -1.411175             0.714361   \n",
       "25             1.500964         0.596592             0.985252   \n",
       "26            -0.194825         0.596592            -0.359317   \n",
       "27            -0.896803        -0.005738            -1.953026   \n",
       "28             1.128285        -0.808845            -0.383045   \n",
       "29             0.278418         0.446010            -0.438409   \n",
       "...                 ...              ...                  ...   \n",
       "3303          -0.892860         1.249117             0.923955   \n",
       "3304          -0.046937         2.002030             0.111282   \n",
       "3305           0.745746        -0.758651            -0.527388   \n",
       "3306           0.057571         1.550282             0.566063   \n",
       "3307           0.651097         1.148729            -0.794324   \n",
       "3308          -0.695675        -0.156320             1.285802   \n",
       "3309           0.487434         0.094651             1.076208   \n",
       "3310          -2.148927         0.345622             0.473129   \n",
       "3311           1.623219        -0.859039            -0.248588   \n",
       "3312          -1.115679        -0.357097             1.216596   \n",
       "3313          -1.129481        -0.256709            -0.187291   \n",
       "3314           0.645182        -1.310787            -1.363789   \n",
       "3315          -1.705261         0.295427            -0.446318   \n",
       "3316           0.357292        -0.206515             0.384150   \n",
       "3317          -0.246094         0.646787             0.202238   \n",
       "3318           1.962376         0.897758            -0.165541   \n",
       "3319           0.175882         0.747175             1.582398   \n",
       "3320          -0.090318        -1.160204            -1.597111   \n",
       "3321          -2.286956         0.496204             0.182465   \n",
       "3322           1.272230         1.098534            -0.402818   \n",
       "3323           0.952790        -0.156320             0.516630   \n",
       "3324          -0.064683         0.245233            -0.141813   \n",
       "3325          -1.657937        -0.608068             0.838931   \n",
       "3326           1.652796        -0.658262            -0.434455   \n",
       "3327          -0.222431        -1.611952             0.405901   \n",
       "3328           0.286305         1.299311             1.546807   \n",
       "3329          -0.938212        -2.264476            -0.189269   \n",
       "3330           1.731670        -2.113894            -0.177405   \n",
       "3331          -0.815958        -0.808845            -1.219445   \n",
       "3332           1.280117        -0.909233             0.801362   \n",
       "\n",
       "      total night calls  total intl minutes  total intl calls  \\\n",
       "0             -0.465425           -0.084995         -0.601105   \n",
       "1              0.147802            1.240296         -0.601105   \n",
       "2              0.198905            0.703015          0.211502   \n",
       "3             -0.567629           -1.302831          1.024109   \n",
       "4              1.067643           -0.049177         -0.601105   \n",
       "5              0.914336           -1.410287          0.617806   \n",
       "6              0.914336           -0.980462          1.024109   \n",
       "7             -0.209913           -1.123737          0.617806   \n",
       "8             -0.516527           -0.550638         -0.194801   \n",
       "9             -0.158811            0.344829          0.211502   \n",
       "10             0.556621            0.882109          0.617806   \n",
       "11            -0.312118           -0.407364          0.211502   \n",
       "12             1.425359            0.344829         -1.007408   \n",
       "13             0.761030            0.738834          0.211502   \n",
       "14            -0.056607            1.025384          0.617806   \n",
       "15             1.425359           -1.732655          1.836716   \n",
       "16            -1.283061            1.276114         -0.194801   \n",
       "17             1.067643           -0.765550         -0.601105   \n",
       "18             0.403314           -0.084995          0.211502   \n",
       "19            -1.334163            0.989565         -1.007408   \n",
       "20             1.680870            0.129917         -0.194801   \n",
       "21            -1.845185           -1.625199          0.617806   \n",
       "22            -1.129754           -0.264089          5.899751   \n",
       "23             0.250007           -0.908825          0.617806   \n",
       "24             0.761030            0.022461         -1.007408   \n",
       "25             0.761030            1.885032          0.211502   \n",
       "26             0.761030           -0.264089         -0.601105   \n",
       "27            -1.640776            1.598482         -0.194801   \n",
       "28             0.096700           -1.410287          0.617806   \n",
       "29            -0.516527            0.309010         -1.413712   \n",
       "...                 ...                 ...               ...   \n",
       "3303          -0.312118            0.452285          1.024109   \n",
       "3304          -1.027549            1.276114          0.211502   \n",
       "3305          -0.720936            0.452285          1.024109   \n",
       "3306          -1.385265           -0.765550         -0.601105   \n",
       "3307          -1.794083            2.708861         -0.194801   \n",
       "3308          -1.436367            1.097021          0.617806   \n",
       "3309          -0.261016            0.631378         -0.194801   \n",
       "3310           0.403314            1.204477          5.087144   \n",
       "3311           1.220950           -1.195374          0.211502   \n",
       "3312           0.505518            1.419389         -0.194801   \n",
       "3313          -0.158811           -0.084995          0.211502   \n",
       "3314           1.016541           -0.407364         -0.194801   \n",
       "3315          -0.107709           -1.338649         -0.194801   \n",
       "3316           0.403314            0.738834          1.836716   \n",
       "3317          -0.312118           -0.873006          1.430413   \n",
       "3318           0.301109            0.488103         -0.194801   \n",
       "3319           0.607723            2.028306          0.617806   \n",
       "3320           1.680870           -0.192452         -0.194801   \n",
       "3321           1.731972            1.061202          1.430413   \n",
       "3322          -1.436367            0.452285         -1.007408   \n",
       "3323          -2.254003            1.204477         -0.601105   \n",
       "3324          -0.925345            0.488103         -0.194801   \n",
       "3325           0.454416           -0.335726         -0.194801   \n",
       "3326          -0.414322            1.670120          1.024109   \n",
       "3327           1.425359            0.559741          0.211502   \n",
       "3328          -0.874243           -0.120814          0.617806   \n",
       "3329           1.169848           -0.228270         -0.194801   \n",
       "3330          -0.465425            1.383570          0.617806   \n",
       "3331           1.885279           -1.875929          2.243020   \n",
       "3332          -1.180856            1.240296         -0.194801   \n",
       "\n",
       "      number customer service calls  Churn  \n",
       "0                         -0.427868      0  \n",
       "1                         -0.427868      0  \n",
       "2                         -1.188040      0  \n",
       "3                          0.332305      0  \n",
       "4                          1.092477      0  \n",
       "5                         -1.188040      0  \n",
       "6                          1.092477      0  \n",
       "7                         -1.188040      0  \n",
       "8                         -0.427868      0  \n",
       "9                         -1.188040      0  \n",
       "10                         1.852649      1  \n",
       "11                        -1.188040      0  \n",
       "12                        -0.427868      0  \n",
       "13                         1.092477      0  \n",
       "14                         1.852649      0  \n",
       "15                         1.852649      1  \n",
       "16                        -0.427868      0  \n",
       "17                         1.092477      0  \n",
       "18                        -0.427868      0  \n",
       "19                        -0.427868      0  \n",
       "20                        -1.188040      0  \n",
       "21                         2.612822      1  \n",
       "22                        -1.188040      0  \n",
       "23                         0.332305      0  \n",
       "24                        -1.188040      0  \n",
       "25                         1.092477      0  \n",
       "26                        -1.188040      0  \n",
       "27                         1.092477      0  \n",
       "28                        -1.188040      0  \n",
       "29                        -0.427868      0  \n",
       "...                             ...    ...  \n",
       "3303                       0.332305      0  \n",
       "3304                       1.852649      1  \n",
       "3305                       0.332305      0  \n",
       "3306                      -0.427868      0  \n",
       "3307                       1.852649      0  \n",
       "3308                      -0.427868      0  \n",
       "3309                       1.852649      0  \n",
       "3310                       0.332305      0  \n",
       "3311                       0.332305      0  \n",
       "3312                       0.332305      0  \n",
       "3313                      -0.427868      0  \n",
       "3314                      -0.427868      0  \n",
       "3315                      -1.188040      0  \n",
       "3316                      -1.188040      0  \n",
       "3317                      -0.427868      0  \n",
       "3318                       0.332305      0  \n",
       "3319                       1.092477      0  \n",
       "3320                       1.852649      1  \n",
       "3321                       1.092477      0  \n",
       "3322                       1.852649      1  \n",
       "3323                       2.612822      1  \n",
       "3324                      -0.427868      0  \n",
       "3325                       0.332305      0  \n",
       "3326                      -0.427868      0  \n",
       "3327                       0.332305      0  \n",
       "3328                       0.332305      0  \n",
       "3329                       1.092477      0  \n",
       "3330                       0.332305      0  \n",
       "3331                       0.332305      0  \n",
       "3332                      -1.188040      0  \n",
       "\n",
       "[3333 rows x 15 columns]"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Lets check the shape now\n",
    "#Y_Train_Sm.shape\n",
    "\n",
    "#Train['Churn']=Train['Churn'].astype('category')\n",
    "Train"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Test['Churn']=Test['Churn'].astype('category')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Lets Build Random Forest Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [],
   "source": [
    "rf_model=RandomForestClassifier(n_estimators=500,random_state=101).fit(X_Train,Y_Train)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Lets apply model on Test Data by Ignoring Target Variable\n",
    "Predictions_rf=rf_model.predict(X_Test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Lets apply model on Test Data by Ignoring Target Variable\n",
    "#Lets build a fucntion for calculation of Confusion Matrix\n",
    "def CONFUSION_MATRIX(model,test):\n",
    "    cm=pd.crosstab(model,test)\n",
    "    TN = cm.iloc[0,0]\n",
    "    FN = cm.iloc[1,0]\n",
    "    \n",
    "    TP = cm.iloc[1,1]\n",
    "    FP = cm.iloc[0,1]\n",
    "    print()\n",
    "    print()\n",
    "    print('Accuracy :- ', round(((TP+TN)*100)/(TP+TN+FP+FN),2))\n",
    "    print()\n",
    "    print('Specificity //  True Negative Rate :- ',round((TN*100)/(TN+FP),2))\n",
    "    print()\n",
    "    print('Sensivity // True Positive Rate // Recall :- ',round((TP*100)/(FN+TP),2))\n",
    "    print()\n",
    "    print('False Negative Rate :- ',round((FN*100)/(FN+TP),2))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "Accuracy :-  95.74\n",
      "\n",
      "Specificity //  True Negative Rate :-  99.51\n",
      "\n",
      "Sensivity // True Positive Rate // Recall :-  71.43\n",
      "\n",
      "False Negative Rate :-  28.57\n"
     ]
    }
   ],
   "source": [
    "CONFUSION_MATRIX(Y_Test,Predictions_rf)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Lets Build Logistic Regression Model\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "from sklearn.linear_model import LogisticRegression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\akshay.hirpara\\AppData\\Local\\Continuum\\anaconda3\\lib\\site-packages\\sklearn\\linear_model\\logistic.py:433: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,\n",
       "          intercept_scaling=1, max_iter=100, multi_class='warn',\n",
       "          n_jobs=None, penalty='l2', random_state=101, solver='warn',\n",
       "          tol=0.0001, verbose=0, warm_start=False)"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "Logistic_Model=LogisticRegression(random_state=101).fit(X_Train,Y_Train)\n",
    "Logistic_Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [],
   "source": [
    "Predictions_LM=Logistic_Model.predict(X_Test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 0, 0, ..., 0, 0, 0], dtype=int64)"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Predictions_LM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "Accuracy :-  87.1\n",
      "\n",
      "Specificity //  True Negative Rate :-  97.64\n",
      "\n",
      "Sensivity // True Positive Rate // Recall :-  19.2\n",
      "\n",
      "False Negative Rate :-  80.8\n"
     ]
    }
   ],
   "source": [
    "CONFUSION_MATRIX(Y_Test,Predictions_LM)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Lets build Naive Bayes "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Lets Load Library\n",
    "\n",
    "from sklearn.naive_bayes import GaussianNB\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [],
   "source": [
    "NaiveBayes=GaussianNB().fit(X_Train,Y_Train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "GaussianNB(priors=None, var_smoothing=1e-09)"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "NaiveBayes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 0, 0, ..., 0, 0, 0], dtype=int64)"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Predictions_NB=NaiveBayes.predict(X_Test)\n",
    "Predictions_NB"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "Accuracy :-  86.02\n",
      "\n",
      "Specificity //  True Negative Rate :-  93.07\n",
      "\n",
      "Sensivity // True Positive Rate // Recall :-  40.62\n",
      "\n",
      "False Negative Rate :-  59.38\n"
     ]
    }
   ],
   "source": [
    "CONFUSION_MATRIX(Y_Test,Predictions_NB)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# KNN Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Lets Load Library\n",
    "from sklearn.neighbors import KNeighborsClassifier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [],
   "source": [
    "KNN_Model=KNeighborsClassifier(n_neighbors=3).fit(X_Train,Y_Train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'KNN_Model' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-2-34737f288b48>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[1;31m#Lets Predict Test Cases\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[0mPredictions_KNN\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mKNN_Model\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpredict\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mX_Test\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      3\u001b[0m \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mPredicitons_KNN\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mNameError\u001b[0m: name 'KNN_Model' is not defined"
     ]
    }
   ],
   "source": [
    "#Lets Predict Test Cases\n",
    "Predictions_KNN=KNN_Model.predict(X_Test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "Accuracy :-  89.08\n",
      "\n",
      "Specificity //  True Negative Rate :-  89.83\n",
      "\n",
      "Sensivity // True Positive Rate // Recall :-  75.0\n",
      "\n",
      "False Negative Rate :-  25.0\n"
     ]
    }
   ],
   "source": [
    "CONFUSION_MATRIX(Predictions_KNN,Y_Test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Lets Build a Model With SMOTE, Applying SMOTE on Random Forest"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "rf_model01=RandomForestClassifier(n_estimators=500,random_state=101).fit(X_Train_Sm,Y_Train_Sm)\n",
    "\n",
    "\n",
    "#Lets apply model on Test Data by Ignoring Target Variable\n",
    "Predictions_rf01=rf_model01.predict(X_Test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "Accuracy :-  93.46\n",
      "\n",
      "Specificity //  True Negative Rate :-  96.97\n",
      "\n",
      "Sensivity // True Positive Rate // Recall :-  73.28\n",
      "\n",
      "False Negative Rate :-  26.72\n"
     ]
    }
   ],
   "source": [
    "CONFUSION_MATRIX(Predictions_rf01,Y_Test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Lets see ROC and AUC curve\n",
    "\n",
    "fpr,tpr,thresholds=roc_curve(Y_Test,Predictions_rf01)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Now calculate AUC\n",
    "auc=roc_auc_score(Y_Test,Predictions_rf01)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ROC AUC: 0.88\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "print ('ROC AUC: %0.2f' % auc)\n",
    "\n",
    "# Plot of a ROC curve for a specific class\n",
    "plt.figure()\n",
    "plt.plot(fpr, tpr, label='ROC curve (area = %0.2f)' % auc)\n",
    "plt.plot([0, 1], [0, 1], 'k--')\n",
    "plt.xlim([0.0, 1.0])\n",
    "plt.ylim([0.0, 1.05])\n",
    "plt.xlabel('False Positive Rate')\n",
    "    plt.ylabel('True Positive Rate')\n",
    "    plt.title('ROC Curve')\n",
    "    plt.legend(loc=\"lower right\")\n",
    "    plt.show()"
   ]
  },
  {
   "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": "3.7.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}