Propensity Modeling for Email Marketing Campaign.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2019-10-16\n",
    "\n",
    "### Workflow\n",
    "\n",
    "* Classification: This is a binary classification problem in which we identify and classify whether a member will purchase miles or not after the marketing campaign.\n",
    "* Correlation: We can approach the problem based on available features within the training data. Which features contribute significantly to the target? Or is there a correlation between a feature and the target? In addition, we also want to determine correlation between independent features for multicollinearity check.\n",
    "* Preparation: This includes converting data types, determining how to deal with missing values, creating new features and so on. \n",
    "* EDA: Using the right visualization plots."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n"
     ]
    }
   ],
   "source": [
    "from scipy.stats import pearsonr\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.feature_selection import SelectFpr\n",
    "from sklearn.feature_selection import chi2\n",
    "from sklearn.preprocessing import MinMaxScaler\n",
    "from imblearn.ensemble import BalancedBaggingClassifier\n",
    "from imblearn.ensemble import BalancedRandomForestClassifier\n",
    "from sklearn.metrics import confusion_matrix\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.metrics import roc_auc_score, roc_curve, classification_report\n",
    "\n",
    "pd.set_option('display.max_columns', 100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_train = pd.read_csv('Training Data Set.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>balance</th>\n",
       "      <th>tier</th>\n",
       "      <th>aag_yr1</th>\n",
       "      <th>cardholder</th>\n",
       "      <th>email_subscriber</th>\n",
       "      <th>enrollment_date</th>\n",
       "      <th>nonflt_use</th>\n",
       "      <th>awd_use</th>\n",
       "      <th>most_recent_flt</th>\n",
       "      <th>most_recent_awd</th>\n",
       "      <th>flt_segs_12mo</th>\n",
       "      <th>flt_segs_6mo</th>\n",
       "      <th>flt_segs_3mo</th>\n",
       "      <th>nonflt_earn_12mo</th>\n",
       "      <th>nonflt_earn_6mo</th>\n",
       "      <th>nonflt_earn_3mo</th>\n",
       "      <th>lifetime_aag_base_miles</th>\n",
       "      <th>affinity_spend_12mo</th>\n",
       "      <th>affinity_spend_6mo</th>\n",
       "      <th>affinity_spend_3mo</th>\n",
       "      <th>flt_base_12mo</th>\n",
       "      <th>flt_base_6mo</th>\n",
       "      <th>flt_base_3mo</th>\n",
       "      <th>flt_promo_12mo</th>\n",
       "      <th>flt_promo_6mo</th>\n",
       "      <th>flt_promo_3mo</th>\n",
       "      <th>ptnr_miles_earned_12mo</th>\n",
       "      <th>ptnr_miles_earned_6mo</th>\n",
       "      <th>ptnr_miles_earned_3mo</th>\n",
       "      <th>ptnr_miles_redeemed_12mo</th>\n",
       "      <th>ptnr_miles_redeemed_6mo</th>\n",
       "      <th>ptnr_miles_redeemed_3mo</th>\n",
       "      <th>partner_offer_opt_in</th>\n",
       "      <th>estatement_opt_in</th>\n",
       "      <th>target</th>\n",
       "      <th>ID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "      <td>2002-08-26T04:00:00.000Z</td>\n",
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       "      <td>0</td>\n",
       "      <td>2016-12-22 00:00:00</td>\n",
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       "      <td>95599</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>349162</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>499921</td>\n",
       "      <td>3049968</td>\n",
       "      <td>Platinum</td>\n",
       "      <td>80386.0</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>1983-11-15T05:00:00.000Z</td>\n",
       "      <td>722</td>\n",
       "      <td>490000</td>\n",
       "      <td>2019-05-08 00:00:00</td>\n",
       "      <td>2019-04-23 00:00:00</td>\n",
       "      <td>57</td>\n",
       "      <td>24</td>\n",
       "      <td>10</td>\n",
       "      <td>381511</td>\n",
       "      <td>220862</td>\n",
       "      <td>64070</td>\n",
       "      <td>1005237</td>\n",
       "      <td>2746.04</td>\n",
       "      <td>1511.58</td>\n",
       "      <td>521.65</td>\n",
       "      <td>47434</td>\n",
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       "      <td>8433</td>\n",
       "      <td>80069</td>\n",
       "      <td>34230</td>\n",
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       "      <td>331510</td>\n",
       "      <td>170861</td>\n",
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       "      <td>340000</td>\n",
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       "      <td>True</td>\n",
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       "      <td>560363</td>\n",
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       "      <td>3219710</td>\n",
       "      <td>Platinum</td>\n",
       "      <td>69052.0</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>1993-08-17T04:00:00.000Z</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2019-05-10 00:00:00</td>\n",
       "      <td>2015-08-31 00:00:00</td>\n",
       "      <td>34</td>\n",
       "      <td>18</td>\n",
       "      <td>5</td>\n",
       "      <td>149463</td>\n",
       "      <td>99716</td>\n",
       "      <td>24701</td>\n",
       "      <td>727692</td>\n",
       "      <td>1455.41</td>\n",
       "      <td>964.44</td>\n",
       "      <td>245.51</td>\n",
       "      <td>47561</td>\n",
       "      <td>19040</td>\n",
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       "      <td>True</td>\n",
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       "      <td>531021</td>\n",
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       "    <tr>\n",
       "      <td>499923</td>\n",
       "      <td>4211165</td>\n",
       "      <td>Regular</td>\n",
       "      <td>3872.0</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>1993-03-31T05:00:00.000Z</td>\n",
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       "      <td>505000</td>\n",
       "      <td>2018-03-27 00:00:00</td>\n",
       "      <td>2019-03-22 00:00:00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>166809</td>\n",
       "      <td>48760</td>\n",
       "      <td>24057</td>\n",
       "      <td>32034</td>\n",
       "      <td>1666.55</td>\n",
       "      <td>486.28</td>\n",
       "      <td>239.69</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>166809</td>\n",
       "      <td>48760</td>\n",
       "      <td>24057</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>575985</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>499924</td>\n",
       "      <td>6202340</td>\n",
       "      <td>Gold</td>\n",
       "      <td>55561.0</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
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       "      <td>0</td>\n",
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       "      <td>2019-05-06 00:00:00</td>\n",
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       "      <td>68</td>\n",
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       "      <td>116941</td>\n",
       "      <td>80472</td>\n",
       "      <td>1226412</td>\n",
       "      <td>1856.72</td>\n",
       "      <td>938.01</td>\n",
       "      <td>657.84</td>\n",
       "      <td>38534</td>\n",
       "      <td>14369</td>\n",
       "      <td>9499</td>\n",
       "      <td>69588</td>\n",
       "      <td>30800</td>\n",
       "      <td>18761</td>\n",
       "      <td>235749</td>\n",
       "      <td>114440</td>\n",
       "      <td>80472</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>64434</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        balance       tier  aag_yr1  cardholder  email_subscriber  \\\n",
       "499920  2887080     Silver      0.0        True              True   \n",
       "499921  3049968  Platinum   80386.0        True              True   \n",
       "499922  3219710  Platinum   69052.0        True              True   \n",
       "499923  4211165    Regular   3872.0        True              True   \n",
       "499924  6202340       Gold  55561.0        True              True   \n",
       "\n",
       "                 enrollment_date  nonflt_use  awd_use      most_recent_flt  \\\n",
       "499920  2002-08-26T04:00:00.000Z           0        0  2016-12-22 00:00:00   \n",
       "499921  1983-11-15T05:00:00.000Z         722   490000  2019-05-08 00:00:00   \n",
       "499922  1993-08-17T04:00:00.000Z           0        0  2019-05-10 00:00:00   \n",
       "499923  1993-03-31T05:00:00.000Z           0   505000  2018-03-27 00:00:00   \n",
       "499924  1984-09-12T04:00:00.000Z           0        0  2019-05-06 00:00:00   \n",
       "\n",
       "            most_recent_awd  flt_segs_12mo  flt_segs_6mo  flt_segs_3mo  \\\n",
       "499920  2018-02-13 00:00:00              0             0             0   \n",
       "499921  2019-04-23 00:00:00             57            24            10   \n",
       "499922  2015-08-31 00:00:00             34            18             5   \n",
       "499923  2019-03-22 00:00:00              0             0             0   \n",
       "499924  2009-08-29 00:00:00             68            29            17   \n",
       "\n",
       "        nonflt_earn_12mo  nonflt_earn_6mo  nonflt_earn_3mo  \\\n",
       "499920            492283           297294            95599   \n",
       "499921            381511           220862            64070   \n",
       "499922            149463            99716            24701   \n",
       "499923            166809            48760            24057   \n",
       "499924            243250           116941            80472   \n",
       "\n",
       "        lifetime_aag_base_miles  affinity_spend_12mo  affinity_spend_6mo  \\\n",
       "499920                    47937              4892.80             2965.09   \n",
       "499921                  1005237              2746.04             1511.58   \n",
       "499922                   727692              1455.41              964.44   \n",
       "499923                    32034              1666.55              486.28   \n",
       "499924                  1226412              1856.72              938.01   \n",
       "\n",
       "        affinity_spend_3mo  flt_base_12mo  flt_base_6mo  flt_base_3mo  \\\n",
       "499920              948.14              0             0             0   \n",
       "499921              521.65          47434         20390          8433   \n",
       "499922              245.51          47561         19040          8527   \n",
       "499923              239.69              0             0             0   \n",
       "499924              657.84          38534         14369          9499   \n",
       "\n",
       "        flt_promo_12mo  flt_promo_6mo  flt_promo_3mo  ptnr_miles_earned_12mo  \\\n",
       "499920               0              0              0                  492283   \n",
       "499921           80069          34230          13196                  331510   \n",
       "499922          102463          38536          17357                  187735   \n",
       "499923               0              0              0                  166809   \n",
       "499924           69588          30800          18761                  235749   \n",
       "\n",
       "        ptnr_miles_earned_6mo  ptnr_miles_earned_3mo  \\\n",
       "499920                 297294                  95599   \n",
       "499921                 170861                  64069   \n",
       "499922                  97344                  24701   \n",
       "499923                  48760                  24057   \n",
       "499924                 114440                  80472   \n",
       "\n",
       "        ptnr_miles_redeemed_12mo  ptnr_miles_redeemed_6mo  \\\n",
       "499920                         0                        0   \n",
       "499921                    390000                   340000   \n",
       "499922                         0                        0   \n",
       "499923                         0                        0   \n",
       "499924                         0                        0   \n",
       "\n",
       "        ptnr_miles_redeemed_3mo  partner_offer_opt_in  estatement_opt_in  \\\n",
       "499920                        0                 False               True   \n",
       "499921                   200000                  True               True   \n",
       "499922                        0                  True               True   \n",
       "499923                        0                  True               True   \n",
       "499924                        0                  True               True   \n",
       "\n",
       "        target      ID  \n",
       "499920       0  349162  \n",
       "499921       0  560363  \n",
       "499922       0  531021  \n",
       "499923       0  575985  \n",
       "499924       0   64434  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_train.tail(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 499925 entries, 0 to 499924\n",
      "Data columns (total 36 columns):\n",
      "balance                     499925 non-null int64\n",
      "tier                        499925 non-null object\n",
      "aag_yr1                     499918 non-null float64\n",
      "cardholder                  499925 non-null bool\n",
      "email_subscriber            499925 non-null bool\n",
      "enrollment_date             499925 non-null object\n",
      "nonflt_use                  499925 non-null int64\n",
      "awd_use                     499925 non-null int64\n",
      "most_recent_flt             355490 non-null object\n",
      "most_recent_awd             149463 non-null object\n",
      "flt_segs_12mo               499925 non-null int64\n",
      "flt_segs_6mo                499925 non-null int64\n",
      "flt_segs_3mo                499925 non-null int64\n",
      "nonflt_earn_12mo            499925 non-null int64\n",
      "nonflt_earn_6mo             499925 non-null int64\n",
      "nonflt_earn_3mo             499925 non-null int64\n",
      "lifetime_aag_base_miles     499925 non-null int64\n",
      "affinity_spend_12mo         499925 non-null float64\n",
      "affinity_spend_6mo          499925 non-null float64\n",
      "affinity_spend_3mo          499925 non-null float64\n",
      "flt_base_12mo               499925 non-null int64\n",
      "flt_base_6mo                499925 non-null int64\n",
      "flt_base_3mo                499925 non-null int64\n",
      "flt_promo_12mo              499925 non-null int64\n",
      "flt_promo_6mo               499925 non-null int64\n",
      "flt_promo_3mo               499925 non-null int64\n",
      "ptnr_miles_earned_12mo      499925 non-null int64\n",
      "ptnr_miles_earned_6mo       499925 non-null int64\n",
      "ptnr_miles_earned_3mo       499925 non-null int64\n",
      "ptnr_miles_redeemed_12mo    499925 non-null int64\n",
      "ptnr_miles_redeemed_6mo     499925 non-null int64\n",
      "ptnr_miles_redeemed_3mo     499925 non-null int64\n",
      "partner_offer_opt_in        499925 non-null bool\n",
      "estatement_opt_in           499925 non-null bool\n",
      "target                      499925 non-null int64\n",
      "ID                          499925 non-null int64\n",
      "dtypes: bool(4), float64(4), int64(24), object(4)\n",
      "memory usage: 124.0+ MB\n"
     ]
    }
   ],
   "source": [
    "df_train.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data Preprocessing & preparation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Drop the column if there is only one unique value\n",
    "for col in df_train:\n",
    "    if df_train[col].nunique()==1:\n",
    "        df_train.drop(col,inplace=True,axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Bases on the assumption that missing \"most recent_flt\" and \"most_recent_aws\" are the dates that have not come yet. So, fill missing \"most_recent_flt\" and \"most_recent_awd\" with today's date.\n",
    "\n",
    "Fill the missing \"aag_yr1\" with zero. There are only a handful of them."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_train['most_recent_flt'].fillna('2019-10-16', inplace=True)\n",
    "df_train['most_recent_awd'].fillna('2019-10-16', inplace=True)\n",
    "df_train['aag_yr1'].fillna(0, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Covert three date columns to date time data type, and keep date only, then calculate number of days between dates before eventaully drop these date columns."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      ">> First enrollment day in training data 1913-01-11 00:00:00\n",
      ">> Last enrollment day in training data 2019-04-30 00:00:00\n",
      "\n",
      ">> First most recent flight date in training data 2004-02-24 00:00:00\n",
      ">> Last most recent flight date in training data 2019-10-16 00:00:00\n",
      "\n",
      ">> First most recent award date in training data 2004-12-08 00:00:00\n",
      ">> Last most recent award date in training data 2019-10-16 00:00:00\n"
     ]
    }
   ],
   "source": [
    "for i in ['enrollment_date', 'most_recent_flt', 'most_recent_awd']:\n",
    "    df_train[i] = pd.to_datetime(df_train[i])\n",
    "df_train['enrollment_date'] = df_train['enrollment_date'].dt.date\n",
    "df_train['most_recent_flt'] = df_train['most_recent_flt'].dt.date\n",
    "df_train['most_recent_awd'] = df_train['most_recent_awd'].dt.date\n",
    "\n",
    "for i in ['enrollment_date', 'most_recent_flt', 'most_recent_awd']:\n",
    "    df_train[i] = pd.to_datetime(df_train[i])\n",
    "    \n",
    "df_train['days_flt_enrollment'] = (df_train['most_recent_flt'] - df_train['enrollment_date']).dt.days\n",
    "df_train['days_awd_flt'] = (df_train['most_recent_awd'] - df_train['most_recent_flt']).dt.days\n",
    "\n",
    "print(f\">> First enrollment day in training data {df_train.enrollment_date.min()}\")\n",
    "print(f\">> Last enrollment day in training data {df_train.enrollment_date.max()}\")\n",
    "print()\n",
    "print(f\">> First most recent flight date in training data {df_train.most_recent_flt.min()}\")\n",
    "print(f\">> Last most recent flight date in training data {df_train.most_recent_flt.max()}\")\n",
    "print()\n",
    "print(f\">> First most recent award date in training data {df_train.most_recent_awd.min()}\")\n",
    "print(f\">> Last most recent award date in training data {df_train.most_recent_awd.max()}\")\n",
    "\n",
    "df_train.drop(['enrollment_date', 'most_recent_flt', 'most_recent_awd'], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Explore target feature\n",
    "\n",
    "Our target are imbalanced, and the ratio of non-purchase to purchase instances is 99.85: 0.15. Before we go ahead to balance the classes, Let's do some more exploration."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    499175\n",
       "1       750\n",
       "Name: target, dtype: int64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_train['target'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "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": [
    "sns.countplot(x = 'target', data=df_train)\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Percentage of members that did not purchase is 99.8499774966245\n",
      "Percentage members that did purchase is 0.15002250337550632\n"
     ]
    }
   ],
   "source": [
    "count_no_pur = len(df_train[df_train['target']==0])\n",
    "count_pur = len(df_train[df_train['target']==1])\n",
    "pct_of_no_pur = count_no_pur/(count_no_pur+count_pur)\n",
    "print(\"Percentage of members that did not purchase is\", pct_of_no_pur*100)\n",
    "pct_of_pur = count_pur/(count_no_pur+count_pur)\n",
    "print(\"Percentage members that did purchase is\", pct_of_pur*100)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We also add to our assumptions based on the analysis so far.\n",
    "\n",
    "* Members who are loyal are more likely to be influenced by marketing campaigns.\n",
    "* Members who are email subscribers and/or card holders are more likely to be influenced by marketing campaigns.\n",
    "* Members who have a lot of balance but just a little bit short for a desired vacation are more likely to be influenced by marketing campaigns.\n",
    "* Members who are active, incented to collect and redeem points are more likely to be influenced by marketing campaigns."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>balance</th>\n",
       "      <th>aag_yr1</th>\n",
       "      <th>cardholder</th>\n",
       "      <th>email_subscriber</th>\n",
       "      <th>nonflt_use</th>\n",
       "      <th>awd_use</th>\n",
       "      <th>flt_segs_12mo</th>\n",
       "      <th>flt_segs_6mo</th>\n",
       "      <th>flt_segs_3mo</th>\n",
       "      <th>nonflt_earn_12mo</th>\n",
       "      <th>nonflt_earn_6mo</th>\n",
       "      <th>nonflt_earn_3mo</th>\n",
       "      <th>lifetime_aag_base_miles</th>\n",
       "      <th>affinity_spend_12mo</th>\n",
       "      <th>affinity_spend_6mo</th>\n",
       "      <th>affinity_spend_3mo</th>\n",
       "      <th>flt_base_12mo</th>\n",
       "      <th>flt_base_6mo</th>\n",
       "      <th>flt_base_3mo</th>\n",
       "      <th>flt_promo_12mo</th>\n",
       "      <th>flt_promo_6mo</th>\n",
       "      <th>flt_promo_3mo</th>\n",
       "      <th>ptnr_miles_earned_12mo</th>\n",
       "      <th>ptnr_miles_earned_6mo</th>\n",
       "      <th>ptnr_miles_earned_3mo</th>\n",
       "      <th>ptnr_miles_redeemed_12mo</th>\n",
       "      <th>ptnr_miles_redeemed_6mo</th>\n",
       "      <th>ptnr_miles_redeemed_3mo</th>\n",
       "      <th>partner_offer_opt_in</th>\n",
       "      <th>estatement_opt_in</th>\n",
       "      <th>days_flt_enrollment</th>\n",
       "      <th>days_awd_flt</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>target</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
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       "      <td>0</td>\n",
       "      <td>29349.155807</td>\n",
       "      <td>3115.121757</td>\n",
       "      <td>0.247456</td>\n",
       "      <td>0.688308</td>\n",
       "      <td>144.020131</td>\n",
       "      <td>8481.063755</td>\n",
       "      <td>2.472107</td>\n",
       "      <td>1.231865</td>\n",
       "      <td>0.613835</td>\n",
       "      <td>7479.49332</td>\n",
       "      <td>3704.256619</td>\n",
       "      <td>1801.572158</td>\n",
       "      <td>21647.382413</td>\n",
       "      <td>52.088923</td>\n",
       "      <td>26.012359</td>\n",
       "      <td>12.726072</td>\n",
       "      <td>2976.892244</td>\n",
       "      <td>1501.010019</td>\n",
       "      <td>740.921697</td>\n",
       "      <td>1158.590372</td>\n",
       "      <td>591.210595</td>\n",
       "      <td>290.893775</td>\n",
       "      <td>7413.122733</td>\n",
       "      <td>3648.368885</td>\n",
       "      <td>1810.384526</td>\n",
       "      <td>1539.782365</td>\n",
       "      <td>866.079956</td>\n",
       "      <td>470.496643</td>\n",
       "      <td>0.498108</td>\n",
       "      <td>0.565772</td>\n",
       "      <td>1733.210041</td>\n",
       "      <td>123.405615</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>56068.060000</td>\n",
       "      <td>7044.352000</td>\n",
       "      <td>0.533333</td>\n",
       "      <td>0.865333</td>\n",
       "      <td>503.804000</td>\n",
       "      <td>63957.333333</td>\n",
       "      <td>5.600000</td>\n",
       "      <td>2.768000</td>\n",
       "      <td>1.332000</td>\n",
       "      <td>67277.05600</td>\n",
       "      <td>38520.105333</td>\n",
       "      <td>25039.137333</td>\n",
       "      <td>50610.089333</td>\n",
       "      <td>150.901920</td>\n",
       "      <td>80.022573</td>\n",
       "      <td>41.431747</td>\n",
       "      <td>6660.269333</td>\n",
       "      <td>3381.510667</td>\n",
       "      <td>1673.150667</td>\n",
       "      <td>4060.753333</td>\n",
       "      <td>2128.140000</td>\n",
       "      <td>1165.505333</td>\n",
       "      <td>27965.396000</td>\n",
       "      <td>13418.416000</td>\n",
       "      <td>7403.162667</td>\n",
       "      <td>32044.400000</td>\n",
       "      <td>21836.533333</td>\n",
       "      <td>12727.466667</td>\n",
       "      <td>0.672000</td>\n",
       "      <td>0.726667</td>\n",
       "      <td>2778.081333</td>\n",
       "      <td>70.760000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             balance      aag_yr1  cardholder  email_subscriber  nonflt_use  \\\n",
       "target                                                                        \n",
       "0       29349.155807  3115.121757    0.247456          0.688308  144.020131   \n",
       "1       56068.060000  7044.352000    0.533333          0.865333  503.804000   \n",
       "\n",
       "             awd_use  flt_segs_12mo  flt_segs_6mo  flt_segs_3mo  \\\n",
       "target                                                            \n",
       "0        8481.063755       2.472107      1.231865      0.613835   \n",
       "1       63957.333333       5.600000      2.768000      1.332000   \n",
       "\n",
       "        nonflt_earn_12mo  nonflt_earn_6mo  nonflt_earn_3mo  \\\n",
       "target                                                       \n",
       "0             7479.49332      3704.256619      1801.572158   \n",
       "1            67277.05600     38520.105333     25039.137333   \n",
       "\n",
       "        lifetime_aag_base_miles  affinity_spend_12mo  affinity_spend_6mo  \\\n",
       "target                                                                     \n",
       "0                  21647.382413            52.088923           26.012359   \n",
       "1                  50610.089333           150.901920           80.022573   \n",
       "\n",
       "        affinity_spend_3mo  flt_base_12mo  flt_base_6mo  flt_base_3mo  \\\n",
       "target                                                                  \n",
       "0                12.726072    2976.892244   1501.010019    740.921697   \n",
       "1                41.431747    6660.269333   3381.510667   1673.150667   \n",
       "\n",
       "        flt_promo_12mo  flt_promo_6mo  flt_promo_3mo  ptnr_miles_earned_12mo  \\\n",
       "target                                                                         \n",
       "0          1158.590372     591.210595     290.893775             7413.122733   \n",
       "1          4060.753333    2128.140000    1165.505333            27965.396000   \n",
       "\n",
       "        ptnr_miles_earned_6mo  ptnr_miles_earned_3mo  \\\n",
       "target                                                 \n",
       "0                 3648.368885            1810.384526   \n",
       "1                13418.416000            7403.162667   \n",
       "\n",
       "        ptnr_miles_redeemed_12mo  ptnr_miles_redeemed_6mo  \\\n",
       "target                                                      \n",
       "0                    1539.782365               866.079956   \n",
       "1                   32044.400000             21836.533333   \n",
       "\n",
       "        ptnr_miles_redeemed_3mo  partner_offer_opt_in  estatement_opt_in  \\\n",
       "target                                                                     \n",
       "0                    470.496643              0.498108           0.565772   \n",
       "1                  12727.466667              0.672000           0.726667   \n",
       "\n",
       "        days_flt_enrollment  days_awd_flt  \n",
       "target                                     \n",
       "0               1733.210041    123.405615  \n",
       "1               2778.081333     70.760000  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_train.drop('ID', axis=1).groupby('target').mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Observations:\n",
    "\n",
    "The average balance of members who purchased the miles is way higher than that of the members' who didn't. In fact, most of the  numeric features average values are higher for the members who bought miles. Its obvious that members who bought miles after marketing campaign are the ones with energy."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tier</th>\n",
       "      <th>target</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>Gold</td>\n",
       "      <td>0.006155</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>Silver</td>\n",
       "      <td>0.005222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>Platinum</td>\n",
       "      <td>0.004484</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Regular</td>\n",
       "      <td>0.001367</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        tier    target\n",
       "0       Gold  0.006155\n",
       "3     Silver  0.005222\n",
       "1  Platinum   0.004484\n",
       "2    Regular  0.001367"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_train[['tier', 'target']].groupby(['tier'], as_index=False).mean().sort_values(by='target', ascending=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Gold tier had a little bit higher purchase rate than Silver tier, Silver tier had a little bit higher purchase rate than Platinum tier. The tier that had the least purchase rate is Regular. This confirms my previous assumption that loyal members are more likely to be influenced by marketing campaign."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "\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>email_subscriber</th>\n",
       "      <th>target</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "      <td>0.001885</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>0.000649</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   email_subscriber    target\n",
       "1              True  0.001885\n",
       "0             False  0.000649"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_train[['email_subscriber', 'target']].groupby(['email_subscriber'], as_index=False).mean().sort_values(by='target', ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "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",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cardholder</th>\n",
       "      <th>target</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "      <td>0.003228</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>0.000931</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   cardholder    target\n",
       "1        True  0.003228\n",
       "0       False  0.000931"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_train[['cardholder', 'target']].groupby(['cardholder'], as_index=False).mean().sort_values(by='target', ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "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>partner_offer_opt_in</th>\n",
       "      <th>target</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "      <td>0.002023</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>0.000981</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   partner_offer_opt_in    target\n",
       "1                  True  0.002023\n",
       "0                 False  0.000981"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_train[['partner_offer_opt_in', 'target']].groupby(['partner_offer_opt_in'], as_index=False).mean().sort_values(by='target', ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "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>estatement_opt_in</th>\n",
       "      <th>target</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "      <td>0.001926</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>0.000945</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   estatement_opt_in    target\n",
       "1               True  0.001926\n",
       "0              False  0.000945"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_train[['estatement_opt_in', 'target']].groupby(['estatement_opt_in'], as_index=False).mean().sort_values(by='target', ascending=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It goes without saying that members who are email subscribers, card holders, actively engaged in the programs as well as partners progrmas have a higher purchase rate."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Distribution of numerical feature values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>balance</td>\n",
       "      <td>499925.0</td>\n",
       "      <td>29389.240176</td>\n",
       "      <td>77897.157236</td>\n",
       "      <td>-5627.0</td>\n",
       "      <td>1671.0</td>\n",
       "      <td>8501.0</td>\n",
       "      <td>28551.0</td>\n",
       "      <td>9001052.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>aag_yr1</td>\n",
       "      <td>499925.0</td>\n",
       "      <td>3121.016486</td>\n",
       "      <td>7031.475281</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3912.0</td>\n",
       "      <td>185331.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>nonflt_use</td>\n",
       "      <td>499925.0</td>\n",
       "      <td>144.559888</td>\n",
       "      <td>3144.383617</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>782045.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>awd_use</td>\n",
       "      <td>499925.0</td>\n",
       "      <td>8564.290644</td>\n",
       "      <td>55570.893458</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>20690000.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>flt_segs_12mo</td>\n",
       "      <td>499925.0</td>\n",
       "      <td>2.476800</td>\n",
       "      <td>5.774682</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>202.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>flt_segs_6mo</td>\n",
       "      <td>499925.0</td>\n",
       "      <td>1.234169</td>\n",
       "      <td>3.126119</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>122.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>flt_segs_3mo</td>\n",
       "      <td>499925.0</td>\n",
       "      <td>0.614912</td>\n",
       "      <td>1.777225</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>58.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>nonflt_earn_12mo</td>\n",
       "      <td>499925.0</td>\n",
       "      <td>7569.203120</td>\n",
       "      <td>33996.792770</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>500.0</td>\n",
       "      <td>10020653.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>nonflt_earn_6mo</td>\n",
       "      <td>499925.0</td>\n",
       "      <td>3756.488227</td>\n",
       "      <td>17105.293769</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5223880.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>nonflt_earn_3mo</td>\n",
       "      <td>499925.0</td>\n",
       "      <td>1836.433735</td>\n",
       "      <td>9051.818941</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2691455.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>lifetime_aag_base_miles</td>\n",
       "      <td>499925.0</td>\n",
       "      <td>21690.832991</td>\n",
       "      <td>61924.438491</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4106.0</td>\n",
       "      <td>16374.0</td>\n",
       "      <td>2254169.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>affinity_spend_12mo</td>\n",
       "      <td>499925.0</td>\n",
       "      <td>52.237165</td>\n",
       "      <td>239.129309</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>30698.71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>affinity_spend_6mo</td>\n",
       "      <td>499925.0</td>\n",
       "      <td>26.093387</td>\n",
       "      <td>119.053076</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>13469.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>affinity_spend_3mo</td>\n",
       "      <td>499925.0</td>\n",
       "      <td>12.769137</td>\n",
       "      <td>59.449266</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6648.58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>flt_base_12mo</td>\n",
       "      <td>499925.0</td>\n",
       "      <td>2982.418139</td>\n",
       "      <td>6606.717401</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3764.0</td>\n",
       "      <td>185728.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>flt_base_6mo</td>\n",
       "      <td>499925.0</td>\n",
       "      <td>1503.831193</td>\n",
       "      <td>3756.487913</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1448.0</td>\n",
       "      <td>105780.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>flt_base_3mo</td>\n",
       "      <td>499925.0</td>\n",
       "      <td>742.320250</td>\n",
       "      <td>2193.511174</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>70987.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>flt_promo_12mo</td>\n",
       "      <td>499925.0</td>\n",
       "      <td>1162.944270</td>\n",
       "      <td>7350.693046</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>416666.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>flt_promo_6mo</td>\n",
       "      <td>499925.0</td>\n",
       "      <td>593.516335</td>\n",
       "      <td>3943.699290</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>255472.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>flt_promo_3mo</td>\n",
       "      <td>499925.0</td>\n",
       "      <td>292.205889</td>\n",
       "      <td>2176.724341</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>188444.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>ptnr_miles_earned_12mo</td>\n",
       "      <td>499925.0</td>\n",
       "      <td>7443.955767</td>\n",
       "      <td>28175.566297</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>500.0</td>\n",
       "      <td>3079766.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>ptnr_miles_earned_6mo</td>\n",
       "      <td>499925.0</td>\n",
       "      <td>3663.026154</td>\n",
       "      <td>14323.359964</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1350000.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>ptnr_miles_earned_3mo</td>\n",
       "      <td>499925.0</td>\n",
       "      <td>1818.774952</td>\n",
       "      <td>7719.287491</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>717139.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>ptnr_miles_redeemed_12mo</td>\n",
       "      <td>499925.0</td>\n",
       "      <td>1585.546156</td>\n",
       "      <td>15374.841495</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1132500.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>ptnr_miles_redeemed_6mo</td>\n",
       "      <td>499925.0</td>\n",
       "      <td>897.540355</td>\n",
       "      <td>10840.296226</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1020000.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>ptnr_miles_redeemed_3mo</td>\n",
       "      <td>499925.0</td>\n",
       "      <td>488.884857</td>\n",
       "      <td>7744.958136</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1020000.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>target</td>\n",
       "      <td>499925.0</td>\n",
       "      <td>0.001500</td>\n",
       "      <td>0.038704</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>ID</td>\n",
       "      <td>499925.0</td>\n",
       "      <td>299908.391547</td>\n",
       "      <td>173179.086198</td>\n",
       "      <td>1.0</td>\n",
       "      <td>149948.0</td>\n",
       "      <td>299857.0</td>\n",
       "      <td>449931.0</td>\n",
       "      <td>599910.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>days_flt_enrollment</td>\n",
       "      <td>499925.0</td>\n",
       "      <td>1734.777583</td>\n",
       "      <td>2511.035596</td>\n",
       "      <td>-4754.0</td>\n",
       "      <td>294.0</td>\n",
       "      <td>808.0</td>\n",
       "      <td>1876.0</td>\n",
       "      <td>37483.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>days_awd_flt</td>\n",
       "      <td>499925.0</td>\n",
       "      <td>123.326635</td>\n",
       "      <td>777.551796</td>\n",
       "      <td>-5399.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>402.0</td>\n",
       "      <td>5713.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                             count           mean            std     min  \\\n",
       "balance                   499925.0   29389.240176   77897.157236 -5627.0   \n",
       "aag_yr1                   499925.0    3121.016486    7031.475281     0.0   \n",
       "nonflt_use                499925.0     144.559888    3144.383617     0.0   \n",
       "awd_use                   499925.0    8564.290644   55570.893458     0.0   \n",
       "flt_segs_12mo             499925.0       2.476800       5.774682     0.0   \n",
       "flt_segs_6mo              499925.0       1.234169       3.126119     0.0   \n",
       "flt_segs_3mo              499925.0       0.614912       1.777225     0.0   \n",
       "nonflt_earn_12mo          499925.0    7569.203120   33996.792770     0.0   \n",
       "nonflt_earn_6mo           499925.0    3756.488227   17105.293769     0.0   \n",
       "nonflt_earn_3mo           499925.0    1836.433735    9051.818941     0.0   \n",
       "lifetime_aag_base_miles   499925.0   21690.832991   61924.438491     0.0   \n",
       "affinity_spend_12mo       499925.0      52.237165     239.129309     0.0   \n",
       "affinity_spend_6mo        499925.0      26.093387     119.053076     0.0   \n",
       "affinity_spend_3mo        499925.0      12.769137      59.449266     0.0   \n",
       "flt_base_12mo             499925.0    2982.418139    6606.717401     0.0   \n",
       "flt_base_6mo              499925.0    1503.831193    3756.487913     0.0   \n",
       "flt_base_3mo              499925.0     742.320250    2193.511174     0.0   \n",
       "flt_promo_12mo            499925.0    1162.944270    7350.693046     0.0   \n",
       "flt_promo_6mo             499925.0     593.516335    3943.699290     0.0   \n",
       "flt_promo_3mo             499925.0     292.205889    2176.724341     0.0   \n",
       "ptnr_miles_earned_12mo    499925.0    7443.955767   28175.566297     0.0   \n",
       "ptnr_miles_earned_6mo     499925.0    3663.026154   14323.359964     0.0   \n",
       "ptnr_miles_earned_3mo     499925.0    1818.774952    7719.287491     0.0   \n",
       "ptnr_miles_redeemed_12mo  499925.0    1585.546156   15374.841495     0.0   \n",
       "ptnr_miles_redeemed_6mo   499925.0     897.540355   10840.296226     0.0   \n",
       "ptnr_miles_redeemed_3mo   499925.0     488.884857    7744.958136     0.0   \n",
       "target                    499925.0       0.001500       0.038704     0.0   \n",
       "ID                        499925.0  299908.391547  173179.086198     1.0   \n",
       "days_flt_enrollment       499925.0    1734.777583    2511.035596 -4754.0   \n",
       "days_awd_flt              499925.0     123.326635     777.551796 -5399.0   \n",
       "\n",
       "                               25%       50%       75%          max  \n",
       "balance                     1671.0    8501.0   28551.0   9001052.00  \n",
       "aag_yr1                        0.0       0.0    3912.0    185331.00  \n",
       "nonflt_use                     0.0       0.0       0.0    782045.00  \n",
       "awd_use                        0.0       0.0       0.0  20690000.00  \n",
       "flt_segs_12mo                  0.0       0.0       3.0       202.00  \n",
       "flt_segs_6mo                   0.0       0.0       2.0       122.00  \n",
       "flt_segs_3mo                   0.0       0.0       0.0        58.00  \n",
       "nonflt_earn_12mo               0.0       0.0     500.0  10020653.00  \n",
       "nonflt_earn_6mo                0.0       0.0       1.0   5223880.00  \n",
       "nonflt_earn_3mo                0.0       0.0       0.0   2691455.00  \n",
       "lifetime_aag_base_miles        0.0    4106.0   16374.0   2254169.00  \n",
       "affinity_spend_12mo            0.0       0.0       0.0     30698.71  \n",
       "affinity_spend_6mo             0.0       0.0       0.0     13469.12  \n",
       "affinity_spend_3mo             0.0       0.0       0.0      6648.58  \n",
       "flt_base_12mo                  0.0       0.0    3764.0    185728.00  \n",
       "flt_base_6mo                   0.0       0.0    1448.0    105780.00  \n",
       "flt_base_3mo                   0.0       0.0       0.0     70987.00  \n",
       "flt_promo_12mo                 0.0       0.0      20.0    416666.00  \n",
       "flt_promo_6mo                  0.0       0.0       0.0    255472.00  \n",
       "flt_promo_3mo                  0.0       0.0       0.0    188444.00  \n",
       "ptnr_miles_earned_12mo         0.0       0.0     500.0   3079766.00  \n",
       "ptnr_miles_earned_6mo          0.0       0.0       0.0   1350000.00  \n",
       "ptnr_miles_earned_3mo          0.0       0.0       0.0    717139.00  \n",
       "ptnr_miles_redeemed_12mo       0.0       0.0       0.0   1132500.00  \n",
       "ptnr_miles_redeemed_6mo        0.0       0.0       0.0   1020000.00  \n",
       "ptnr_miles_redeemed_3mo        0.0       0.0       0.0   1020000.00  \n",
       "target                         0.0       0.0       0.0         1.00  \n",
       "ID                        149948.0  299857.0  449931.0    599910.00  \n",
       "days_flt_enrollment          294.0     808.0    1876.0     37483.00  \n",
       "days_awd_flt                   0.0      26.0     402.0      5713.00  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_train.describe().T"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Multicollinearity\n",
    "\n",
    "Correlation between independent numeric features inside each segment."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "def corrfunc(x,y, ax=None, **kws):\n",
    "    \"\"\"Plot the correlation coefficient in the top left hand corner of a plot.\"\"\"\n",
    "    r, _ = pearsonr(x, y)\n",
    "    ax = ax or plt.gca()\n",
    "    # Unicode for lowercase rho (ρ)\n",
    "    rho = '\\u03C1'\n",
    "    ax.annotate(f'{rho} = {r:.2f}', xy=(.1, .9), xycoords=ax.transAxes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 540x540 with 12 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = sns.pairplot(df_train[['flt_segs_12mo', 'flt_segs_6mo', 'flt_segs_3mo']])\n",
    "g.map_lower(corrfunc)\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 540x540 with 12 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = sns.pairplot(df_train[['nonflt_earn_12mo', 'nonflt_earn_6mo', 'nonflt_earn_3mo']])\n",
    "g.map_lower(corrfunc)\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 540x540 with 12 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = sns.pairplot(df_train[['affinity_spend_12mo', 'affinity_spend_6mo', 'affinity_spend_3mo']])\n",
    "g.map_lower(corrfunc)\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 540x540 with 12 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = sns.pairplot(df_train[['flt_base_12mo', 'flt_base_6mo', 'flt_base_3mo']])\n",
    "g.map_lower(corrfunc)\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 540x540 with 12 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = sns.pairplot(df_train[['flt_promo_12mo', 'flt_promo_6mo', 'flt_promo_3mo']])\n",
    "g.map_lower(corrfunc)\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 540x540 with 12 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = sns.pairplot(df_train[['ptnr_miles_earned_12mo', 'ptnr_miles_earned_6mo', 'ptnr_miles_earned_3mo']])\n",
    "g.map_lower(corrfunc)\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 540x540 with 12 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = sns.pairplot(df_train[['ptnr_miles_redeemed_12mo', 'ptnr_miles_redeemed_6mo', 'ptnr_miles_redeemed_3mo']])\n",
    "g.map_lower(corrfunc)\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The three independent features in each of the above segments are correlated with each other. We will remove and keep one only for each segment before fitting the model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "cols_to_drop = ['nonflt_earn_12mo', 'nonflt_earn_6mo', 'ptnr_miles_redeemed_12mo', 'ptnr_miles_redeemed_6mo', 'ptnr_miles_earned_12mo', 'ptnr_miles_earned_6mo', 'flt_base_6mo', 'flt_base_3mo', 'flt_segs_6mo', 'flt_segs_3mo', 'flt_promo_12mo', 'flt_promo_6mo', 'affinity_spend_12mo', 'affinity_spend_6mo', 'ID']\n",
    "df_train.drop(cols_to_drop, axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "target                     1.000000\n",
       "nonflt_earn_3mo            0.099359\n",
       "ptnr_miles_redeemed_3mo    0.061251\n",
       "awd_use                    0.038638\n",
       "ptnr_miles_earned_3mo      0.028042\n",
       "cardholder                 0.025625\n",
       "aag_yr1                    0.021628\n",
       "flt_base_12mo              0.021578\n",
       "flt_segs_12mo              0.020964\n",
       "affinity_spend_3mo         0.018688\n",
       "lifetime_aag_base_miles    0.018102\n",
       "days_flt_enrollment        0.016105\n",
       "flt_promo_3mo              0.015551\n",
       "email_subscriber           0.014796\n",
       "partner_offer_opt_in       0.013461\n",
       "balance                    0.013275\n",
       "estatement_opt_in          0.012564\n",
       "nonflt_use                 0.004429\n",
       "days_awd_flt              -0.002621\n",
       "Name: target, dtype: float64"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_train.corr()['target'].sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# pd.set_option('precision',2)\n",
    "plt.figure(figsize=(10, 8))\n",
    "sns.heatmap(df_train.drop(['target'],axis=1).corr(), square=True)\n",
    "plt.suptitle(\"Pearson Correlation Heatmap\")\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are still some collinearities. I will remove a few more."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_train.drop(['estatement_opt_in', 'flt_base_12mo', 'ptnr_miles_earned_3mo', 'flt_segs_12mo'], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 8))\n",
    "sns.heatmap(df_train.drop(['target'],axis=1).corr(), square=True)\n",
    "plt.suptitle(\"Pearson Correlation Heatmap\")\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Categorical feature\n",
    "\n",
    "Distribution of categorical feature."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Regular      483477\n",
       "Silver        10723\n",
       "Gold           4387\n",
       "Platinum       1338\n",
       "Name: tier, dtype: int64"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_train.tier.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "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>tier</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>count</td>\n",
       "      <td>499925</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>unique</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>top</td>\n",
       "      <td>Regular</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>freq</td>\n",
       "      <td>483477</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           tier\n",
       "count    499925\n",
       "unique        4\n",
       "top     Regular\n",
       "freq     483477"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_train.describe(include=['O'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAncAAAEWCAYAAAAEirEAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjAsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+17YcXAAAeLElEQVR4nO3deZhlVX3u8e8riKCgTC0qjbaJaESNKC3gPF0RjbmoFxGi0iQo14hGMxgxuYrimGhi1DgRRSDRABINiCgSFIwDQjOEUWKHQRoZGhpFHFDgd//Yq+RQVhVV3X26mtXfz/PU0/v89rDWPnW66q21p1QVkiRJ6sM95rsDkiRJWnMMd5IkSR0x3EmSJHXEcCdJktQRw50kSVJHDHeSJEkdMdxJmhdJDk/yznlqO0k+neTGJGfMRx+mk+RtSf5lvvuxNiT5eJK3zHc/pN4Y7iQBkOTyJNcluc9I7ZVJTp3Hbo3LU4DnAAurauf57sz6IMl+Sb45WquqV1fVO+arT1KvDHeSRm0AvH6+OzFXSTaY4yoPAS6vqp+Ooz/riiQb9tjufO2XdHdhuJM06n3AXyTZfPKMJIuS1Ogv1iSnJnllm94vybeSfCDJj5JcmuRJrX5lGxVcMmmzWyc5OclPkpyW5CEj2/6dNm9lkkuS7DUy7/AkH0tyYpKfAs+cor8PSnJ8W39Zkle1+v7AJ4EnJrk5ydunWHdO+5LkXknen+QHSa5thxs3afOekWR5kr9s612d5IVJnp/kv1v//mpSFzZOcnR7X85O8thJ+/VvSVYkuSzJn4zMe1uSY5P8S5KbgP2S7JxkaZKbWt/+fvL+TurnXyW5vo3kvmyO+/imJNcAn5607UcCHx95z3808n1858hyL0hybnvPv53kd0fmXd62fx7wUwOeND3DnaRRS4FTgb9YxfV3Ac4DtgI+CxwFPAF4GPBy4B+TbDqy/MuAdwBbA+cCnwFoh4ZPbtu4P7A38NEkO4ys+wfAu4DNgDsd7muOApYDDwL2BN6d5FlV9Sng1cB3qmrTqjp4DezLe4GHAzu2+dsCbx3Z1gOAjUfq/9S2sRPwVOAtSR46svwewOeALVvb/57knknuAXwR+K+2rWcDb0jy3EnrHgts3t7PDwIfrKr7Ar8NHDPN/k70c+u27SXAoUkeMYd93JJhVPSA0Y1W1cXc+T2f6o+HxwGHAf+X4T3/BHB8knuNLLYP8HvA5lV16wz7Ia3XDHeSJnsr8LokC1Zh3cuq6tNVdRtwNLAdcEhV3VJVXwV+yRAMJnypqr5RVbcAf80wsrMd8AKGw6afrqpbq+oc4N+Al4yse1xVfauqbq+qX4x2om3jycCbquoXVXUuw2jdvmt6X5KEIcz8aVWtrKqfAO9mCKQTfgW8q6p+xRASt2YIXD+pqguBi4DHjix/VlUd25b/e4ZguCtDuFxQVYdU1S+r6lKGoDja1neq6t/b+/Lz1vbDkmxdVTdX1el3sd9vaft4GvAlYK9Z7uPtwMFt3Z/f9dv7Gw4APlFV362q26rqCOCWtt8TPlRVV67i9qX1hsPaku6kqi5IcgJwEHDxHFe/dmT65217k2ujI3dXjrR7c5KVDCNtDwF2mTh812wI/PNU607hQcBECJlwBbB4NjvRzHZfFgD3Bs4aMhAAYTh/ccINLST+eltTbH+69+X2JBMjkAU8aNL7sgHwn1Ot2+wPHAJ8L8llwNur6oTf2NvBjZPOQ7yitTubfVwxOWTP0UOAJUleN1LbqLU/YabvuaTGcCdpKgcDZwN/N1Kb+KV/b+CmNv2A1Wxnu4mJdohzS+CHDL/ET6uq58ywbs0w74fAlkk2Gwl4DwauWs3+TuV6hnD2qKpaU9sffV/uASxk2KdbGUYUt59h3Tu9L1X1fWCftp0XA8cm2Wqai0m2SHKfkXkPBi5gdvs40/djNvOvZBjdfNdqbEMSHpaVNIWqWsZwKPJPRmorGMLRy5NskOSPGM7hWh3PT/KUJBsxnHt3elVdCZwAPDzJK9q5ZvdM8oR2Yv5s+n8l8G3gPUk2bifm7w+s8fvHVdXtDIdGP5Dk/gBJtp10Htxc7ZTkxe2igTcwHJ48HTgD+Em7sGCT9n14dJInTLehJC9PsqD1c2LE7/YZ2n57ko2SPJXh8Pjn1tA+XgssbN/rqfwT8Ooku2RwnyS/l2SzObQhCcOdpOkdAtxnUu1VwBuBG4BHMQSo1fFZhlHClQwXF7wcoI227cZwTtcPgWuAvwHuNfVmprQPsKit/wWG88H+YzX7O503AcuA09tVqv8BPGLmVWZ0HPBS4EbgFcCLq+pX7dDuCxguariMYUTtk8D9ZtjW7sCFSW5muLhi7xnOWbumtflDhosxXl1V32vzVncfvwZcCFyT5PrJM6tqKcPn6x9bH5YB+81h+5KaVDnKLUnruyTPAP6lqhbOd18krR5H7iRJkjpiuJMkSeqIh2UlSZI64sidJElSR8b9cOfLgZ8AtwG3VtXiJFsy3GJhEXA5sFdV3djugP5B4PnAz4D9qurstp0lwP9rm31nu3M5SXYCDgc2AU4EXl9VNV0bM/V16623rkWLFq2J3ZYkSRqrs8466/qqmvJJQmM9LNvC3eKqun6k9rcMd45/b5KDgC2q6k1Jng+8jiHc7cLwaJ5dWlBbynBn+QLOAnZqgfAMhvtwfZch3H2oqr48XRsz9XXx4sW1dOnSNfwOSJIkrXlJzqqqKZ+6Mx+HZfcAjmjTRwAvHKkfWYPTgc2TPBB4LnBye57hjQwPE9+9zbtvVZ1eQ0I9ctK2pmpDkiSpa+MOdwV8NclZSQ5otW2q6uo2fQ2wTZveljs/N3B5q81UXz5FfaY2JEmSujbuZ8s+paquao+rOTnJ90ZntvPjxnq57kxttMB5AMCDH/zgcXZDkiRprRjryN3EA6ar6jqGx//sDFzbDqnS/r2uLX4VIw/LZnhQ9lV3UV84RZ0Z2pjcv0OranFVLV6wYMpzEiVJku5Wxhbu2kOfN5uYZnhO5AXA8cCSttgShmco0ur7tgdG7wr8uB1aPQnYLckWSbZo2zmpzbspya7tStt9J21rqjYkSZK6Ns7DstsAXxhyFxsCn62qryQ5Ezgmyf7AFcBebfkTGa6UXcZwK5Q/BKiqlUneAZzZljukqla26ddwx61Qvty+AN47TRuSJEld8wkVjbdCkSRJdxfr2q1QJEmSNCaGO0mSpI6M+1Yo3dvpjUfOdxe0is56377z3QVJktY4R+4kSZI6YriTJEnqiOFOkiSpI4Y7SZKkjhjuJEmSOmK4kyRJ6ojhTpIkqSOGO0mSpI4Y7iRJkjpiuJMkSeqI4U6SJKkjhjtJkqSOGO4kSZI6YriTJEnqiOFOkiSpI4Y7SZKkjhjuJEmSOmK4kyRJ6ojhTpIkqSOGO0mSpI4Y7iRJkjpiuJMkSeqI4U6SJKkjhjtJkqSOGO4kSZI6YriTJEnqiOFOkiSpI4Y7SZKkjhjuJEmSOmK4kyRJ6ojhTpIkqSNjD3dJNkhyTpIT2uuHJvlukmVJjk6yUavfq71e1uYvGtnGm1v9kiTPHanv3mrLkhw0Up+yDUmSpN6tjZG71wMXj7z+G+ADVfUw4EZg/1bfH7ix1T/QliPJDsDewKOA3YGPtsC4AfAR4HnADsA+bdmZ2pAkSeraWMNdkoXA7wGfbK8DPAs4ti1yBPDCNr1He02b/+y2/B7AUVV1S1VdBiwDdm5fy6rq0qr6JXAUsMddtCFJktS1cY/c/QPwl8Dt7fVWwI+q6tb2ejmwbZveFrgSoM3/cVv+1/VJ60xXn6mNO0lyQJKlSZauWLFiVfdRkiRpnTG2cJfkBcB1VXXWuNpYXVV1aFUtrqrFCxYsmO/uSJIkrbYNx7jtJwP/O8nzgY2B+wIfBDZPsmEbWVsIXNWWvwrYDlieZEPgfsANI/UJo+tMVb9hhjYkSZK6NraRu6p6c1UtrKpFDBdEfK2qXgZ8HdizLbYEOK5NH99e0+Z/raqq1fduV9M+FNgeOAM4E9i+XRm7UWvj+LbOdG1IkiR1bT7uc/cm4M+SLGM4P+5Trf4pYKtW/zPgIICquhA4BrgI+ApwYFXd1kblXgucxHA17jFt2ZnakCRJ6to4D8v+WlWdCpzapi9luNJ18jK/AF4yzfrvAt41Rf1E4MQp6lO2IUmS1DufUCFJktQRw50kSVJHDHeSJEkdMdxJkiR1xHAnSZLUEcOdJElSRwx3kiRJHTHcSZIkdcRwJ0mS1BHDnSRJUkcMd5IkSR0x3EmSJHXEcCdJktQRw50kSVJHDHeSJEkdMdxJkiR1xHAnSZLUEcOdJElSRwx3kiRJHTHcSZIkdcRwJ0mS1BHDnSRJUkcMd5IkSR0x3EmSJHXEcCdJktQRw50kSVJHDHeSJEkdMdxJkiR1xHAnSZLUEcOdJElSRwx3kiRJHTHcSZIkdcRwJ0mS1BHDnSRJUkfGFu6SbJzkjCT/leTCJG9v9Ycm+W6SZUmOTrJRq9+rvV7W5i8a2dabW/2SJM8dqe/easuSHDRSn7INSZKk3o1z5O4W4FlV9VhgR2D3JLsCfwN8oKoeBtwI7N+W3x+4sdU/0JYjyQ7A3sCjgN2BjybZIMkGwEeA5wE7APu0ZZmhDUmSpK6NLdzV4Ob28p7tq4BnAce2+hHAC9v0Hu01bf6zk6TVj6qqW6rqMmAZsHP7WlZVl1bVL4GjgD3aOtO1IUmS1LWxnnPXRtjOBa4DTgb+B/hRVd3aFlkObNumtwWuBGjzfwxsNVqftM509a1maGNy/w5IsjTJ0hUrVqzOrkqSJK0Txhruquq2qtoRWMgw0vY742xvrqrq0KpaXFWLFyxYMN/dkSRJWm1r5WrZqvoR8HXgicDmSTZssxYCV7Xpq4DtANr8+wE3jNYnrTNd/YYZ2pAkSeraOK+WXZBk8za9CfAc4GKGkLdnW2wJcFybPr69ps3/WlVVq+/drqZ9KLA9cAZwJrB9uzJ2I4aLLo5v60zXhiRJUtc2vOtFVtkDgSPaVa33AI6pqhOSXAQcleSdwDnAp9rynwL+OckyYCVDWKOqLkxyDHARcCtwYFXdBpDktcBJwAbAYVV1YdvWm6ZpQ5IkqWtjC3dVdR7wuCnqlzKcfze5/gvgJdNs613Au6aonwicONs2JEmSeucTKiRJkjpiuJMkSerIrMJdkifPpiZJkqT5NduRuw/PsiZJkqR5NOMFFUmeCDwJWJDkz0Zm3ZfhClVJkiStQ+7qatmNgE3bcpuN1G/ijvvISZIkaR0xY7irqtOA05IcXlVXrKU+SZIkaRXN9j5390pyKLBodJ2qetY4OiVJkqRVM9tw9zng48AngdvG1x1JkiStjtmGu1ur6mNj7YkkSZJW22xvhfLFJK9J8sAkW058jbVnkiRJmrPZjtwtaf++caRWwG+t2e5IkiRpdcwq3FXVQ8fdEUmSJK2+WYW7JPtOVa+qI9dsdyRJkrQ6ZntY9gkj0xsDzwbOBgx3kiRJ65DZHpZ93ejrJJsDR42lR5IkSVpls71adrKfAp6HJ0mStI6Z7Tl3X2S4OhZgA+CRwDHj6pQkSZJWzWzPuXv/yPStwBVVtXwM/ZEkSdJqmNVh2ao6DfgesBmwBfDLcXZKkiRJq2ZW4S7JXsAZwEuAvYDvJtlznB2TJEnS3M32sOxfA0+oqusAkiwA/gM4dlwdkyRJ0tzN9mrZe0wEu+aGOawrSZKktWS2I3dfSXIS8K/t9UuBE8fTJUmSJK2qGcNdkocB21TVG5O8GHhKm/Ud4DPj7pwkSZLm5q5G7v4BeDNAVX0e+DxAkse0eb8/1t5JkiRpTu7qvLltqur8ycVWWzSWHkmSJGmV3VW423yGeZusyY5IkiRp9d1VuFua5FWTi0leCZw1ni5JkiRpVd3VOXdvAL6Q5GXcEeYWAxsBLxpnxyRJkjR3M4a7qroWeFKSZwKPbuUvVdXXxt4zSZIkzdms7nNXVV8Hvj7mvkiSJGk1+ZQJSZKkjhjuJEmSOjK2cJdkuyRfT3JRkguTvL7Vt0xycpLvt3+3aPUk+VCSZUnOS/L4kW0tact/P8mSkfpOSc5v63woSWZqQ5IkqXfjHLm7FfjzqtoB2BU4MMkOwEHAKVW1PXBKew3wPGD79nUA8DEYghpwMLALsDNw8EhY+xjwqpH1dm/16dqQJEnq2tjCXVVdXVVnt+mfABcD2wJ7AEe0xY4AXtim9wCOrMHpwOZJHgg8Fzi5qlZW1Y3AycDubd59q+r0qirgyEnbmqoNSZKkrq2Vc+6SLAIeB3yX4ZFmV7dZ1wDbtOltgStHVlveajPVl09RZ4Y2JvfrgCRLkyxdsWLF3HdMkiRpHTP2cJdkU+DfgDdU1U2j89qIW42z/ZnaqKpDq2pxVS1esGDBOLshSZK0Vow13CW5J0Ow+0xVfb6Vr22HVGn/XtfqVwHbjay+sNVmqi+coj5TG5IkSV0b59WyAT4FXFxVfz8y63hg4orXJcBxI/V921WzuwI/bodWTwJ2S7JFu5BiN+CkNu+mJLu2tvadtK2p2pAkSerarJ5QsYqeDLwCOD/Jua32V8B7gWOS7A9cAezV5p0IPB9YBvwM+EOAqlqZ5B3AmW25Q6pqZZt+DXA4sAnw5fbFDG1IkiR1bWzhrqq+CWSa2c+eYvkCDpxmW4cBh01RX8odz7wdrd8wVRuSJEm98wkVkiRJHTHcSZIkdcRwJ0mS1BHDnSRJUkcMd5IkSR0x3EmSJHXEcCdJktQRw50kSVJHDHeSJEkdMdxJkiR1xHAnSZLUEcOdJElSRwx3kiRJHTHcSZIkdcRwJ0mS1BHDnSRJUkcMd5IkSR0x3EmSJHXEcCdJktQRw50kSVJHDHeSJEkdMdxJkiR1xHAnSZLUEcOdJElSRwx3kiRJHTHcSZIkdcRwJ0mS1BHDnSRJUkcMd5IkSR0x3EmSJHXEcCdJktQRw50kSVJHDHeSJEkdMdxJkiR1ZGzhLslhSa5LcsFIbcskJyf5fvt3i1ZPkg8lWZbkvCSPH1lnSVv++0mWjNR3SnJ+W+dDSTJTG5IkSeuDcY7cHQ7sPql2EHBKVW0PnNJeAzwP2L59HQB8DIagBhwM7ALsDBw8EtY+BrxqZL3d76INSZKk7o0t3FXVN4CVk8p7AEe06SOAF47Uj6zB6cDmSR4IPBc4uapWVtWNwMnA7m3efavq9Koq4MhJ25qqDUmSpO6t7XPutqmqq9v0NcA2bXpb4MqR5Za32kz15VPUZ2rjNyQ5IMnSJEtXrFixCrsjSZK0bpm3CyraiFvNZxtVdWhVLa6qxQsWLBhnVyRJktaKtR3urm2HVGn/XtfqVwHbjSy3sNVmqi+coj5TG5IkSd1b2+HueGDiitclwHEj9X3bVbO7Aj9uh1ZPAnZLskW7kGI34KQ276Yku7arZPedtK2p2pAkSerehuPacJJ/BZ4BbJ1kOcNVr+8FjkmyP3AFsFdb/ETg+cAy4GfAHwJU1cok7wDObMsdUlUTF2m8huGK3E2AL7cvZmhDkiSpe2MLd1W1zzSznj3FsgUcOM12DgMOm6K+FHj0FPUbpmpDkiRpfeATKiRJkjpiuJMkSeqI4U6SJKkjhjtJkqSOGO4kSZI6YriTJEnqiOFOkiSpI4Y7SZKkjhjuJEmSOmK4kyRJ6ojhTpIkqSOGO0mSpI4Y7iRJkjpiuJMkSeqI4U6SJKkjhjtJkqSOGO4kSZI6YriTJEnqiOFOkiSpI4Y7SZKkjhjuJEmSOmK4kyRJ6ojhTpIkqSOGO0mSpI4Y7iRJkjpiuJMkSeqI4U6SJKkjhjtJkqSOGO4kSZI6YriTJEnqiOFOkiSpI4Y7SZKkjmw43x2Q1hc/OOQx890FrYYHv/X8+e6CJM2KI3eSJEkd6TbcJdk9ySVJliU5aL77I0mStDZ0eVg2yQbAR4DnAMuBM5McX1UXzW/PJGl2nvzhJ893F7SKvvW6b813F7Se6zLcATsDy6rqUoAkRwF7AIY7SVJXTnva0+e7C1oNT//GaWt8m6mqNb7R+ZZkT2D3qnple/0KYJeqeu2k5Q4ADmgvHwFcslY7evewNXD9fHdCdwt+VjQXfl40W35WpvaQqlow1YxeR+5mpaoOBQ6d736sy5IsrarF890Prfv8rGgu/LxotvyszF2vF1RcBWw38nphq0mSJHWt13B3JrB9kocm2QjYGzh+nvskSZI0dl0elq2qW5O8FjgJ2AA4rKounOdu3V152Fqz5WdFc+HnRbPlZ2WOurygQpIkaX3V62FZSZKk9ZLhTpIkqSOGuw4luS3JuUkuSPLFJJuPoY1nJDlhTW9X644kf53kwiTntc/TLkk+mWSHNv/yJFvPdz+1bkmyTZLPJrk0yVlJvpPkRTMsP+3PEj9jdx+Tfu98Lsm9W/3mu1hv8ySvGXn9oCTHjru/vTPc9ennVbVjVT0aWAkcON8dStLlxTu9SvJE4AXA46vqd4H/BVxZVa9ck4/xy8CfQ51IEuDfgW9U1W9V1U4MdytYOL8901ow+nvnl8CrZ7ne5sCvw11V/bCq9hxHB9cn/lDt33eAbSdeJHljkjPbaMzbR+pvSXJJkm8m+dckf9HqpyZZ3Ka3TnL55AaS7Nz+Oj8nybeTPKLV90tyfJKvAaeMeT+1Zj0QuL6qbgGoquur6oejn4cJSd6b5MCR128b+fz8xuctyaL2WTsSuIA735NSd2/PAn5ZVR+fKFTVFVX14SQbJ/l0kvPbz4pnTl45yVZJvtpGjD8JZG12XmvMfwIPGy0k2TTJKUnObp+BPdqs9wK/3Ub93td+PlzQ1tkvyeeTfCXJ95P87cj2bh6Z3jPJ4W368CQfS3J6Gz1+RpLDklw8scz6wHDXsSQbAM+m3eMvyW7A9gzP3t0R2CnJ05I8Afg/wGOB5wFzvRP494CnVtXjgLcC7x6Z93hgz6ry4Yd3L18Ftkvy30k+mmSm79/RwF4jr/cCjp7u89aW2R74aFU9qqquGEP/NT8eBZw9zbwDgaqqxwD7AEck2XjSMgcD36yqRwFfAB48tp5qLNpRmucB50+a9QvgRVX1eOCZwN+1kd6DgP9po35vnGKTOwIvBR4DvDTJbP4Y3AJ4IvCnDL//PsDw2XxMkh1XYbfudjxU1qdNkpzLMGJ3MXByq+/Wvs5przdl+CW7GXBcVf0C+EWSL86xvfsx/KDeHijgniPzTq6qlau2G5ovVXVzkp2ApzL8ID46yUHTLHtOkvsneRCwALixqq5M8nqm/rz9ALiiqk4f+45oXiX5CPAUhsN0y4EPA1TV95JcATx80ipPA17clvlSkhvXYne1eiZ+78AwcvepSfMDvLv9gXc7w++nbWax3VOq6scASS4CHgJceRfrfLGqKsn5wLVVdX5b/0JgEXDuTCv3wHDXp59X1Y7thNaTGP5i/hDDf673VNUnRhdO8oYZtnUrd4zwTv4re8I7gK9X1YuSLAJOHZn30zn3XuuEqrqN4Xt5avshuWSGxT8H7Ak8gGEkD6b/vC3Cz0WvLmQ4CgBAVR3YLohYyhDu1K+fV9VMo2IvY/jjb6eq+lU7xWe63ymjbhmZvo07csvoTXonb2dindsnrX8760nu8bBsx6rqZ8CfAH/ehspPAv4oyaYASbZNcn/gW8Dvt3NiNmU4kX7C5cBObXq6k1zvxx3P7t1vje6E5kWSR7SR2Ak7AjMdPj2a4cT5PRmCHkz/eVO/vgZsnOSPR2r3bv/+J8MveJI8nOGQ6yWT1v8G8AdtmecxHF5TH+4HXNeC3TMZRuAAfsJw9Giurk3yyHZB1rRXY6+vDHedq6pzgPOAfarqq8Bnge+0kZhjgc2q6kyG8xLOA77McK7Ej9sm3g/8cZJzgOluSfC3wHvaMuvFX0XrgU0ZDrVflOQ8YAfgbdMt3B7vtxlwVVVd3WpTft7G3XHNnxoeefRC4OlJLktyBnAE8Cbgo8A92mfhaGC/iQt2RrwdeFo7fPZihkP46sNngMXt+78vw7naVNUNwLcy3ELlfXPY3kHACcC3gavXdGfv7nz8mIDhSqZ2ntW9Gf56PqCqpjsxWpIkraMcZdGEQzPcnHZj4AiDnSRJd0+O3EmSJHXEc+4kSZI6YriTJEnqiOFOkiSpI15QIUmrIMlW3PHM5Acw3GB1RXv9s6p60rx0TNJ6zwsqJGk1JXkbcHNVvX8V1g3Dz+Lb13jHJK2XPCwrSWtYkptHpt+Y5Mwk5yV5e6stSnJJkiOBC4DZPAxdkmbFw7KSNCZJdgO2B3ZmeNbu8e3B6T9o9SVVdfo8dlFShwx3kjQ+u7Wvc9rrTRlC3Q+AKwx2ksbBcCdJ4xPgPVX1iTsVk0XAT+ejQ5L65zl3kjQ+JwF/lGRTgCTbJrn/PPdJUuccuZOkMamqryZ5JPCd4aJYbgZeznDbFEkaC2+FIkmS1BEPy0qSJHXEcCdJktQRw50kSVJHDHeSJEkdMdxJkiR1xHAnSZLUEcOdJElSR/4/wFlaTa8F00QAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 720x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,4))\n",
    "sns.countplot(x=\"tier\", data=df_train, order = df_train['tier'].value_counts().index)\n",
    "plt.xlabel('Tier')\n",
    "plt.ylabel('Count')\n",
    "plt.title('Number of members per tier');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "just_dummies = pd.get_dummies(df_train['tier'])\n",
    "df_train = pd.concat([df_train, just_dummies], axis=1)      \n",
    "df_train.drop('tier', inplace=True, axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Nomalize the data and train test split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = df_train.drop('target', axis=1)\n",
    "y = df_train.target\n",
    "scaler = MinMaxScaler()\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, stratify=y, test_size=0.3)\n",
    "\n",
    "X_train = scaler.fit_transform(X_train)\n",
    "X_test= scaler.transform(X_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Modelding\n",
    "\n",
    "A bagging classifier with additional balancing."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "BalancedBaggingClassifier(base_estimator=DecisionTreeClassifier(class_weight=None,\n",
       "                                                                criterion='gini',\n",
       "                                                                max_depth=None,\n",
       "                                                                max_features=None,\n",
       "                                                                max_leaf_nodes=None,\n",
       "                                                                min_impurity_decrease=0.0,\n",
       "                                                                min_impurity_split=None,\n",
       "                                                                min_samples_leaf=1,\n",
       "                                                                min_samples_split=2,\n",
       "                                                                min_weight_fraction_leaf=0.0,\n",
       "                                                                presort=False,\n",
       "                                                                random_state=None,\n",
       "                                                                splitter='best'),\n",
       "                          bootstrap=True, bootstrap_features=False,\n",
       "                          max_features=1.0, max_samples=1.0, n_estimators=10,\n",
       "                          n_jobs=1, oob_score=False, random_state=0, ratio=None,\n",
       "                          replacement=False, sampling_strategy='auto',\n",
       "                          verbose=0, warm_start=False)"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bbc = BalancedBaggingClassifier(base_estimator=DecisionTreeClassifier(),                                \n",
    "                                sampling_strategy='auto',\n",
    "                                replacement=False,\n",
    "                                random_state=0)\n",
    "bbc.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[130365  19388]\n",
      " [    60    165]]\n"
     ]
    }
   ],
   "source": [
    "y_pred = bbc.predict(X_test)\n",
    "print(confusion_matrix(y_test, y_pred))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       1.00      0.87      0.93    149753\n",
      "           1       0.01      0.73      0.02       225\n",
      "\n",
      "    accuracy                           0.87    149978\n",
      "   macro avg       0.50      0.80      0.47    149978\n",
      "weighted avg       1.00      0.87      0.93    149978\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(classification_report(y_test, y_pred))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "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": [
    "bbc_roc_auc = roc_auc_score(y_test, bbc.predict(X_test))\n",
    "fpr, tpr, thresholds = roc_curve(y_test, bbc.predict_proba(X_test)[:,1])\n",
    "plt.figure()\n",
    "plt.plot(fpr, tpr, label='Balanced Bagging Classifier (area = %0.2f)' % bbc_roc_auc)\n",
    "plt.plot([0, 1], [0, 1],'r--')\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('Receiver operating characteristic')\n",
    "plt.legend(loc=\"lower right\")\n",
    "plt.savefig('Log_ROC')\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A balanced random forest classifier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "BalancedRandomForestClassifier(bootstrap=True, class_weight=None,\n",
       "                               criterion='gini', max_depth=None,\n",
       "                               max_features='auto', max_leaf_nodes=None,\n",
       "                               min_impurity_decrease=0.0, min_samples_leaf=2,\n",
       "                               min_samples_split=2,\n",
       "                               min_weight_fraction_leaf=0.0, n_estimators=100,\n",
       "                               n_jobs=1, oob_score=False, random_state=0,\n",
       "                               replacement=False, sampling_strategy='auto',\n",
       "                               verbose=0, warm_start=False)"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "brf = BalancedRandomForestClassifier(n_estimators=100, random_state=0)\n",
    "brf.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[114101  35652]\n",
      " [    38    187]]\n"
     ]
    }
   ],
   "source": [
    "y_pred = brf.predict(X_test)\n",
    "print(confusion_matrix(y_test, y_pred))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       1.00      0.76      0.86    149753\n",
      "           1       0.01      0.83      0.01       225\n",
      "\n",
      "    accuracy                           0.76    149978\n",
      "   macro avg       0.50      0.80      0.44    149978\n",
      "weighted avg       1.00      0.76      0.86    149978\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(classification_report(y_test, y_pred))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "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": [
    "brf_roc_auc = roc_auc_score(y_test, brf.predict(X_test))\n",
    "fpr, tpr, thresholds = roc_curve(y_test, brf.predict_proba(X_test)[:,1])\n",
    "plt.figure()\n",
    "plt.plot(fpr, tpr, label='Balanced Random Forest Classifier (area = %0.2f)' % brf_roc_auc)\n",
    "plt.plot([0, 1], [0, 1],'r--')\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('Receiver operating characteristic')\n",
    "plt.legend(loc=\"lower right\")\n",
    "plt.savefig('Log_ROC')\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I decided Balanced Random Forest Classifier will be my final model, simply because it has a little higher recall on 1. And I am using this model to predict and assign propensity score for the members in score data set."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pickle\n",
    "\n",
    "filename = 'propensity_model.sav'\n",
    "pickle.dump(brf, open(filename, 'wb'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Load the score data and sanity check whether there are same member in both training and score data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "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>balance_x</th>\n",
       "      <th>tier_x</th>\n",
       "      <th>aag_yr1_x</th>\n",
       "      <th>cardholder_x</th>\n",
       "      <th>email_subscriber_x</th>\n",
       "      <th>enrollment_date_x</th>\n",
       "      <th>nonflt_use_x</th>\n",
       "      <th>awd_use_x</th>\n",
       "      <th>most_recent_flt_x</th>\n",
       "      <th>most_recent_awd_x</th>\n",
       "      <th>flt_segs_12mo_x</th>\n",
       "      <th>flt_segs_6mo_x</th>\n",
       "      <th>flt_segs_3mo_x</th>\n",
       "      <th>nonflt_earn_12mo_x</th>\n",
       "      <th>nonflt_earn_6mo_x</th>\n",
       "      <th>nonflt_earn_3mo_x</th>\n",
       "      <th>lifetime_aag_base_miles_x</th>\n",
       "      <th>affinity_spend_12mo_x</th>\n",
       "      <th>affinity_spend_6mo_x</th>\n",
       "      <th>affinity_spend_3mo_x</th>\n",
       "      <th>flt_base_12mo_x</th>\n",
       "      <th>flt_base_6mo_x</th>\n",
       "      <th>flt_base_3mo_x</th>\n",
       "      <th>flt_promo_12mo_x</th>\n",
       "      <th>flt_promo_6mo_x</th>\n",
       "      <th>flt_promo_3mo_x</th>\n",
       "      <th>ptnr_miles_earned_12mo_x</th>\n",
       "      <th>ptnr_miles_earned_6mo_x</th>\n",
       "      <th>ptnr_miles_earned_3mo_x</th>\n",
       "      <th>ptnr_miles_redeemed_12mo_x</th>\n",
       "      <th>ptnr_miles_redeemed_6mo_x</th>\n",
       "      <th>ptnr_miles_redeemed_3mo_x</th>\n",
       "      <th>partner_offer_opt_in_x</th>\n",
       "      <th>estatement_opt_in_x</th>\n",
       "      <th>target</th>\n",
       "      <th>ID</th>\n",
       "      <th>balance_y</th>\n",
       "      <th>tier_y</th>\n",
       "      <th>aag_yr1_y</th>\n",
       "      <th>cardholder_y</th>\n",
       "      <th>email_subscriber_y</th>\n",
       "      <th>enrollment_date_y</th>\n",
       "      <th>nonflt_use_y</th>\n",
       "      <th>awd_use_y</th>\n",
       "      <th>most_recent_flt_y</th>\n",
       "      <th>most_recent_awd_y</th>\n",
       "      <th>flt_segs_12mo_y</th>\n",
       "      <th>flt_segs_6mo_y</th>\n",
       "      <th>flt_segs_3mo_y</th>\n",
       "      <th>nonflt_earn_12mo_y</th>\n",
       "      <th>nonflt_earn_6mo_y</th>\n",
       "      <th>nonflt_earn_3mo_y</th>\n",
       "      <th>lifetime_aag_base_miles_y</th>\n",
       "      <th>affinity_spend_12mo_y</th>\n",
       "      <th>affinity_spend_6mo_y</th>\n",
       "      <th>affinity_spend_3mo_y</th>\n",
       "      <th>flt_base_12mo_y</th>\n",
       "      <th>flt_base_6mo_y</th>\n",
       "      <th>flt_base_3mo_y</th>\n",
       "      <th>flt_promo_12mo_y</th>\n",
       "      <th>flt_promo_6mo_y</th>\n",
       "      <th>flt_promo_3mo_y</th>\n",
       "      <th>ptnr_miles_earned_12mo_y</th>\n",
       "      <th>ptnr_miles_earned_6mo_y</th>\n",
       "      <th>ptnr_miles_earned_3mo_y</th>\n",
       "      <th>ptnr_miles_redeemed_12mo_y</th>\n",
       "      <th>ptnr_miles_redeemed_6mo_y</th>\n",
       "      <th>ptnr_miles_redeemed_3mo_y</th>\n",
       "      <th>partner_offer_opt_in_y</th>\n",
       "      <th>estatement_opt_in_y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [balance_x, tier_x, aag_yr1_x, cardholder_x, email_subscriber_x, enrollment_date_x, nonflt_use_x, awd_use_x, most_recent_flt_x, most_recent_awd_x, flt_segs_12mo_x, flt_segs_6mo_x, flt_segs_3mo_x, nonflt_earn_12mo_x, nonflt_earn_6mo_x, nonflt_earn_3mo_x, lifetime_aag_base_miles_x, affinity_spend_12mo_x, affinity_spend_6mo_x, affinity_spend_3mo_x, flt_base_12mo_x, flt_base_6mo_x, flt_base_3mo_x, flt_promo_12mo_x, flt_promo_6mo_x, flt_promo_3mo_x, ptnr_miles_earned_12mo_x, ptnr_miles_earned_6mo_x, ptnr_miles_earned_3mo_x, ptnr_miles_redeemed_12mo_x, ptnr_miles_redeemed_6mo_x, ptnr_miles_redeemed_3mo_x, partner_offer_opt_in_x, estatement_opt_in_x, target, ID, balance_y, tier_y, aag_yr1_y, cardholder_y, email_subscriber_y, enrollment_date_y, nonflt_use_y, awd_use_y, most_recent_flt_y, most_recent_awd_y, flt_segs_12mo_y, flt_segs_6mo_y, flt_segs_3mo_y, nonflt_earn_12mo_y, nonflt_earn_6mo_y, nonflt_earn_3mo_y, lifetime_aag_base_miles_y, affinity_spend_12mo_y, affinity_spend_6mo_y, affinity_spend_3mo_y, flt_base_12mo_y, flt_base_6mo_y, flt_base_3mo_y, flt_promo_12mo_y, flt_promo_6mo_y, flt_promo_3mo_y, ptnr_miles_earned_12mo_y, ptnr_miles_earned_6mo_y, ptnr_miles_earned_3mo_y, ptnr_miles_redeemed_12mo_y, ptnr_miles_redeemed_6mo_y, ptnr_miles_redeemed_3mo_y, partner_offer_opt_in_y, estatement_opt_in_y]\n",
       "Index: []"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_score = pd.read_csv('Scoring Data Set.csv')\n",
    "df_train = pd.read_csv('Training Data Set.csv')\n",
    "merged_df = pd.merge(df_train, df_score, on=['ID'], how='inner')\n",
    "merged_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Good."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_result = df_score.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      ">> First enrollment day in score data 1935-02-26 00:00:00\n",
      ">> Last enrollment day in score data 2019-04-30 00:00:00\n",
      "\n",
      ">> First most recent flight date in score data 2005-06-08 00:00:00\n",
      ">> Last most recent flight date in score data 2019-10-16 00:00:00\n",
      "\n",
      ">> First most recent award date in score data 2005-11-23 00:00:00\n",
      ">> Last most recent award date in score data 2019-10-16 00:00:00\n"
     ]
    }
   ],
   "source": [
    "df_score['most_recent_flt'].fillna('2019-10-16', inplace=True)\n",
    "df_score['most_recent_awd'].fillna('2019-10-16', inplace=True)\n",
    "df_score['aag_yr1'].fillna(0, inplace=True)\n",
    "\n",
    "for i in ['enrollment_date', 'most_recent_flt', 'most_recent_awd']:\n",
    "    df_score[i] = pd.to_datetime(df_score[i])\n",
    "df_score['enrollment_date'] = df_score['enrollment_date'].dt.date\n",
    "df_score['most_recent_flt'] = df_score['most_recent_flt'].dt.date\n",
    "df_score['most_recent_awd'] = df_score['most_recent_awd'].dt.date\n",
    "\n",
    "for i in ['enrollment_date', 'most_recent_flt', 'most_recent_awd']:\n",
    "    df_score[i] = pd.to_datetime(df_score[i])\n",
    "    \n",
    "df_score['days_flt_enrollment'] = (df_score['most_recent_flt'] - df_score['enrollment_date']).dt.days\n",
    "df_score['days_awd_flt'] = (df_score['most_recent_awd'] - df_score['most_recent_flt']).dt.days\n",
    "\n",
    "print(f\">> First enrollment day in score data {df_score.enrollment_date.min()}\")\n",
    "print(f\">> Last enrollment day in score data {df_score.enrollment_date.max()}\")\n",
    "print()\n",
    "print(f\">> First most recent flight date in score data {df_score.most_recent_flt.min()}\")\n",
    "print(f\">> Last most recent flight date in score data {df_score.most_recent_flt.max()}\")\n",
    "print()\n",
    "print(f\">> First most recent award date in score data {df_score.most_recent_awd.min()}\")\n",
    "print(f\">> Last most recent award date in score data {df_score.most_recent_awd.max()}\")\n",
    "\n",
    "df_score.drop(['enrollment_date', 'most_recent_flt', 'most_recent_awd'], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "cols_to_drop = ['nonflt_earn_12mo', 'nonflt_earn_6mo', 'ptnr_miles_redeemed_12mo', 'ptnr_miles_redeemed_6mo', 'ptnr_miles_earned_12mo', 'ptnr_miles_earned_6mo', 'flt_base_6mo', 'flt_base_3mo', 'flt_segs_6mo', 'flt_segs_3mo', 'flt_promo_12mo', 'flt_promo_6mo', 'affinity_spend_12mo', 'affinity_spend_6mo', 'estatement_opt_in', 'flt_base_12mo', 'ptnr_miles_earned_3mo', 'flt_segs_12mo']\n",
    "df_score.drop(cols_to_drop, axis=1, inplace=True)\n",
    "\n",
    "just_dummies = pd.get_dummies(df_score['tier'])\n",
    "\n",
    "df_score = pd.concat([df_score, just_dummies], axis=1)      \n",
    "df_score.drop('tier', inplace=True, axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_score = df_score.drop(['ID'], axis=1)\n",
    "df_score = scaler.transform(df_score)\n",
    "df_result['propensity'] = brf.predict_proba(df_score)[:,1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    .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>balance</th>\n",
       "      <th>tier</th>\n",
       "      <th>aag_yr1</th>\n",
       "      <th>cardholder</th>\n",
       "      <th>email_subscriber</th>\n",
       "      <th>enrollment_date</th>\n",
       "      <th>nonflt_use</th>\n",
       "      <th>awd_use</th>\n",
       "      <th>most_recent_flt</th>\n",
       "      <th>most_recent_awd</th>\n",
       "      <th>flt_segs_12mo</th>\n",
       "      <th>flt_segs_6mo</th>\n",
       "      <th>flt_segs_3mo</th>\n",
       "      <th>nonflt_earn_12mo</th>\n",
       "      <th>nonflt_earn_6mo</th>\n",
       "      <th>nonflt_earn_3mo</th>\n",
       "      <th>lifetime_aag_base_miles</th>\n",
       "      <th>affinity_spend_12mo</th>\n",
       "      <th>affinity_spend_6mo</th>\n",
       "      <th>affinity_spend_3mo</th>\n",
       "      <th>flt_base_12mo</th>\n",
       "      <th>flt_base_6mo</th>\n",
       "      <th>flt_base_3mo</th>\n",
       "      <th>flt_promo_12mo</th>\n",
       "      <th>flt_promo_6mo</th>\n",
       "      <th>flt_promo_3mo</th>\n",
       "      <th>ptnr_miles_earned_12mo</th>\n",
       "      <th>ptnr_miles_earned_6mo</th>\n",
       "      <th>ptnr_miles_earned_3mo</th>\n",
       "      <th>ptnr_miles_redeemed_12mo</th>\n",
       "      <th>ptnr_miles_redeemed_6mo</th>\n",
       "      <th>ptnr_miles_redeemed_3mo</th>\n",
       "      <th>partner_offer_opt_in</th>\n",
       "      <th>estatement_opt_in</th>\n",
       "      <th>ID</th>\n",
       "      <th>propensity</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
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       "      <td>89433</td>\n",
       "      <td>160000</td>\n",
       "      <td>160000</td>\n",
       "      <td>160000</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>327884</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>97760</td>\n",
       "      <td>98512</td>\n",
       "      <td>Regular</td>\n",
       "      <td>0.0</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>2018-03-31T04:00:00.000Z</td>\n",
       "      <td>0</td>\n",
       "      <td>125000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019-04-29 00:00:00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>223512</td>\n",
       "      <td>223400</td>\n",
       "      <td>64400</td>\n",
       "      <td>0</td>\n",
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       "      <td>125000</td>\n",
       "      <td>125000</td>\n",
       "      <td>100000</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <td>99338</td>\n",
       "      <td>220500</td>\n",
       "      <td>Regular</td>\n",
       "      <td>0.0</td>\n",
       "      <td>False</td>\n",
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       "      <td>2019-04-19T04:00:00.000Z</td>\n",
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       "      <td>11718</td>\n",
       "      <td>600</td>\n",
       "      <td>Regular</td>\n",
       "      <td>0.0</td>\n",
       "      <td>False</td>\n",
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       "      <td>75000</td>\n",
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       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>257025</td>\n",
       "      <td>0.992500</td>\n",
       "    </tr>\n",
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       "      <td>50856</td>\n",
       "      <td>15501</td>\n",
       "      <td>Regular</td>\n",
       "      <td>0.0</td>\n",
       "      <td>False</td>\n",
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       "      <td>2016-12-26T05:00:00.000Z</td>\n",
       "      <td>0</td>\n",
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       "      <td>150000</td>\n",
       "      <td>150000</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>173059</td>\n",
       "      <td>0.990000</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <td>27364</td>\n",
       "      <td>2894</td>\n",
       "      <td>Regular</td>\n",
       "      <td>2894.0</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>2018-01-13T05:00:00.000Z</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2018-02-02 00:00:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2894</td>\n",
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       "      <td>0.0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>370707</td>\n",
       "      <td>0.008774</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>37494</td>\n",
       "      <td>6902</td>\n",
       "      <td>Regular</td>\n",
       "      <td>0.0</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>2015-12-09T05:00:00.000Z</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2017-08-23 00:00:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4402</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>131828</td>\n",
       "      <td>0.008246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>29231</td>\n",
       "      <td>4433</td>\n",
       "      <td>Regular</td>\n",
       "      <td>933.0</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>2016-09-15T04:00:00.000Z</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2018-05-12 00:00:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>4433</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>933</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>162197</td>\n",
       "      <td>0.008246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>37620</td>\n",
       "      <td>7015</td>\n",
       "      <td>Regular</td>\n",
       "      <td>0.0</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>2016-04-30T04:00:00.000Z</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2019-02-08 00:00:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>7014</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1873</td>\n",
       "      <td>1873</td>\n",
       "      <td>1873</td>\n",
       "      <td>187</td>\n",
       "      <td>187</td>\n",
       "      <td>187</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>147323</td>\n",
       "      <td>0.007427</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>82003</td>\n",
       "      <td>7155</td>\n",
       "      <td>Regular</td>\n",
       "      <td>0.0</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>2016-01-24T05:00:00.000Z</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2019-01-13 00:00:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7030</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2798</td>\n",
       "      <td>2798</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>136297</td>\n",
       "      <td>0.007427</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>99985 rows × 36 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       balance     tier  aag_yr1  cardholder  email_subscriber  \\\n",
       "45488      844  Regular      0.0       False             False   \n",
       "97760    98512  Regular      0.0       False              True   \n",
       "99338   220500  Regular      0.0       False              True   \n",
       "11718      600  Regular      0.0       False              True   \n",
       "50856    15501  Regular      0.0       False              True   \n",
       "...        ...      ...      ...         ...               ...   \n",
       "27364     2894  Regular   2894.0       False             False   \n",
       "37494     6902  Regular      0.0       False             False   \n",
       "29231     4433  Regular    933.0       False             False   \n",
       "37620     7015  Regular      0.0       False             False   \n",
       "82003     7155  Regular      0.0       False             False   \n",
       "\n",
       "                enrollment_date  nonflt_use  awd_use      most_recent_flt  \\\n",
       "45488  2016-12-18T05:00:00.000Z           0   160000                  NaN   \n",
       "97760  2018-03-31T04:00:00.000Z           0   125000                  NaN   \n",
       "99338  2019-04-19T04:00:00.000Z           0        0                  NaN   \n",
       "11718  2017-09-16T04:00:00.000Z           0    75000                  NaN   \n",
       "50856  2016-12-26T05:00:00.000Z           0   207500                  NaN   \n",
       "...                         ...         ...      ...                  ...   \n",
       "27364  2018-01-13T05:00:00.000Z           0        0  2018-02-02 00:00:00   \n",
       "37494  2015-12-09T05:00:00.000Z           0        0  2017-08-23 00:00:00   \n",
       "29231  2016-09-15T04:00:00.000Z           0        0  2018-05-12 00:00:00   \n",
       "37620  2016-04-30T04:00:00.000Z           0        0  2019-02-08 00:00:00   \n",
       "82003  2016-01-24T05:00:00.000Z           0        0  2019-01-13 00:00:00   \n",
       "\n",
       "           most_recent_awd  flt_segs_12mo  flt_segs_6mo  flt_segs_3mo  \\\n",
       "45488  2019-03-20 00:00:00              0             0             0   \n",
       "97760  2019-04-29 00:00:00              0             0             0   \n",
       "99338                  NaN              0             0             0   \n",
       "11718  2019-02-14 00:00:00              0             0             0   \n",
       "50856  2019-03-13 00:00:00              0             0             0   \n",
       "...                    ...            ...           ...           ...   \n",
       "27364                  NaN              0             0             0   \n",
       "37494                  NaN              0             0             0   \n",
       "29231                  NaN              1             0             0   \n",
       "37620                  NaN              3             3             3   \n",
       "82003                  NaN              2             2             0   \n",
       "\n",
       "       nonflt_earn_12mo  nonflt_earn_6mo  nonflt_earn_3mo  \\\n",
       "45488            145433            90433            90433   \n",
       "97760            223512           223400            64400   \n",
       "99338            220500           220500           220500   \n",
       "11718             75600            75600            75600   \n",
       "50856            108000           105000            90000   \n",
       "...                 ...              ...              ...   \n",
       "27364                 0                0                0   \n",
       "37494                 0                0                0   \n",
       "29231                 0                0                0   \n",
       "37620                 1                1                0   \n",
       "82003                 0                0                0   \n",
       "\n",
       "       lifetime_aag_base_miles  affinity_spend_12mo  affinity_spend_6mo  \\\n",
       "45488                        0                  0.0                 0.0   \n",
       "97760                        0                  0.0                 0.0   \n",
       "99338                        0                  0.0                 0.0   \n",
       "11718                        0                  0.0                 0.0   \n",
       "50856                        0                  0.0                 0.0   \n",
       "...                        ...                  ...                 ...   \n",
       "27364                     2894                  0.0                 0.0   \n",
       "37494                     4402                  0.0                 0.0   \n",
       "29231                     4433                  0.0                 0.0   \n",
       "37620                     7014                  0.0                 0.0   \n",
       "82003                     7030                  0.0                 0.0   \n",
       "\n",
       "       affinity_spend_3mo  flt_base_12mo  flt_base_6mo  flt_base_3mo  \\\n",
       "45488                 0.0              0             0             0   \n",
       "97760                 0.0              0             0             0   \n",
       "99338                 0.0              0             0             0   \n",
       "11718                 0.0              0             0             0   \n",
       "50856                 0.0              0             0             0   \n",
       "...                   ...            ...           ...           ...   \n",
       "27364                 0.0              0             0             0   \n",
       "37494                 0.0              0             0             0   \n",
       "29231                 0.0            933             0             0   \n",
       "37620                 0.0           1873          1873          1873   \n",
       "82003                 0.0           2798          2798             0   \n",
       "\n",
       "       flt_promo_12mo  flt_promo_6mo  flt_promo_3mo  ptnr_miles_earned_12mo  \\\n",
       "45488               0              0              0                  144433   \n",
       "97760               0              0              0                   75000   \n",
       "99338               0              0              0                       0   \n",
       "11718               0              0              0                       0   \n",
       "50856               0              0              0                   90000   \n",
       "...               ...            ...            ...                     ...   \n",
       "27364               0              0              0                       0   \n",
       "37494               0              0              0                       0   \n",
       "29231               0              0              0                       0   \n",
       "37620             187            187            187                       0   \n",
       "82003               0              0              0                       0   \n",
       "\n",
       "       ptnr_miles_earned_6mo  ptnr_miles_earned_3mo  ptnr_miles_redeemed_12mo  \\\n",
       "45488                  89433                  89433                    160000   \n",
       "97760                  75000                      0                    125000   \n",
       "99338                      0                      0                         0   \n",
       "11718                      0                      0                     75000   \n",
       "50856                  90000                  90000                    207500   \n",
       "...                      ...                    ...                       ...   \n",
       "27364                      0                      0                         0   \n",
       "37494                      0                      0                         0   \n",
       "29231                      0                      0                         0   \n",
       "37620                      0                      0                         0   \n",
       "82003                      0                      0                         0   \n",
       "\n",
       "       ptnr_miles_redeemed_6mo  ptnr_miles_redeemed_3mo  partner_offer_opt_in  \\\n",
       "45488                   160000                   160000                 False   \n",
       "97760                   125000                   100000                  True   \n",
       "99338                        0                        0                  True   \n",
       "11718                    75000                    75000                  True   \n",
       "50856                   150000                   150000                  True   \n",
       "...                        ...                      ...                   ...   \n",
       "27364                        0                        0                 False   \n",
       "37494                        0                        0                 False   \n",
       "29231                        0                        0                 False   \n",
       "37620                        0                        0                 False   \n",
       "82003                        0                        0                 False   \n",
       "\n",
       "       estatement_opt_in      ID  propensity  \n",
       "45488              False  327884    1.000000  \n",
       "97760               True  398273    1.000000  \n",
       "99338               True  523458    0.993830  \n",
       "11718               True  257025    0.992500  \n",
       "50856               True  173059    0.990000  \n",
       "...                  ...     ...         ...  \n",
       "27364              False  370707    0.008774  \n",
       "37494              False  131828    0.008246  \n",
       "29231              False  162197    0.008246  \n",
       "37620              False  147323    0.007427  \n",
       "82003              False  136297    0.007427  \n",
       "\n",
       "[99985 rows x 36 columns]"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_result.sort_values(by=['propensity'], ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>131828</td>\n",
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       "      <td>29231</td>\n",
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       "      <td>37620</td>\n",
       "      <td>147323</td>\n",
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       "    <tr>\n",
       "      <td>82003</td>\n",
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       "<p>99985 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           ID  propensity\n",
       "45488  327884    1.000000\n",
       "97760  398273    1.000000\n",
       "99338  523458    0.993830\n",
       "11718  257025    0.992500\n",
       "50856  173059    0.990000\n",
       "...       ...         ...\n",
       "27364  370707    0.008774\n",
       "37494  131828    0.008246\n",
       "29231  162197    0.008246\n",
       "37620  147323    0.007427\n",
       "82003  136297    0.007427\n",
       "\n",
       "[99985 rows x 2 columns]"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_result.sort_values(by=['propensity'], ascending=False)[['ID', 'propensity']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_result.sort_values(by=['propensity'], ascending=False)[['ID', 'propensity']].to_csv('propensity_score_result.csv', index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Feature importance techniques\n",
    "\n",
    "Using False Positive Rate test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>p_val</th>\n",
       "      <th>features</th>\n",
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       "  <tbody>\n",
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       "      <td>10</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>ptnr_miles_redeemed_3mo</td>\n",
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       "      <td>2</td>\n",
       "      <td>0.0000</td>\n",
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       "      <td>Silver</td>\n",
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       "      <td>6</td>\n",
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       "      <td>14</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>Gold</td>\n",
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       "      <td>11</td>\n",
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       "      <td>1</td>\n",
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       "      <td>aag_yr1</td>\n",
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       "      <td>7</td>\n",
       "      <td>0.0006</td>\n",
       "      <td>lifetime_aag_base_miles</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>0.0014</td>\n",
       "      <td>flt_promo_3mo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>15</td>\n",
       "      <td>0.0020</td>\n",
       "      <td>Platinum</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>0.0028</td>\n",
       "      <td>awd_use</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>0.0250</td>\n",
       "      <td>affinity_spend_3mo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>16</td>\n",
       "      <td>0.0511</td>\n",
       "      <td>Regular</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>0.1122</td>\n",
       "      <td>balance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>12</td>\n",
       "      <td>0.1413</td>\n",
       "      <td>days_flt_enrollment</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>0.4815</td>\n",
       "      <td>nonflt_use</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>13</td>\n",
       "      <td>0.9584</td>\n",
       "      <td>days_awd_flt</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    p_val                 features\n",
       "10 0.0000  ptnr_miles_redeemed_3mo\n",
       "2  0.0000               cardholder\n",
       "17 0.0000                   Silver\n",
       "6  0.0000          nonflt_earn_3mo\n",
       "14 0.0000                     Gold\n",
       "11 0.0000     partner_offer_opt_in\n",
       "3  0.0000         email_subscriber\n",
       "1  0.0001                  aag_yr1\n",
       "7  0.0006  lifetime_aag_base_miles\n",
       "9  0.0014            flt_promo_3mo\n",
       "15 0.0020                Platinum \n",
       "5  0.0028                  awd_use\n",
       "8  0.0250       affinity_spend_3mo\n",
       "16 0.0511                  Regular\n",
       "0  0.1122                  balance\n",
       "12 0.1413      days_flt_enrollment\n",
       "4  0.4815               nonflt_use\n",
       "13 0.9584             days_awd_flt"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.options.display.float_format = '{:.4f}'.format\n",
    "fpr= SelectFpr(chi2, alpha=0.001)\n",
    "fpr = fpr.fit(X_train,y_train)\n",
    "fpr_df=pd.DataFrame({'p_val':fpr.pvalues_,'features':X.columns.tolist()})\n",
    "fpr_df.sort_values('p_val',ascending=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "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>p_val</th>\n",
       "      <th>features</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>0.0001</td>\n",
       "      <td>aag_yr1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>cardholder</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>email_subscriber</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>0.0028</td>\n",
       "      <td>awd_use</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>nonflt_earn_3mo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>0.0006</td>\n",
       "      <td>lifetime_aag_base_miles</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>0.0250</td>\n",
       "      <td>affinity_spend_3mo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>0.0014</td>\n",
       "      <td>flt_promo_3mo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>10</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>ptnr_miles_redeemed_3mo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>11</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>partner_offer_opt_in</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>14</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>Gold</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>15</td>\n",
       "      <td>0.0020</td>\n",
       "      <td>Platinum</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>17</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>Silver</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    p_val                 features\n",
       "1  0.0001                  aag_yr1\n",
       "2  0.0000               cardholder\n",
       "3  0.0000         email_subscriber\n",
       "5  0.0028                  awd_use\n",
       "6  0.0000          nonflt_earn_3mo\n",
       "7  0.0006  lifetime_aag_base_miles\n",
       "8  0.0250       affinity_spend_3mo\n",
       "9  0.0014            flt_promo_3mo\n",
       "10 0.0000  ptnr_miles_redeemed_3mo\n",
       "11 0.0000     partner_offer_opt_in\n",
       "14 0.0000                     Gold\n",
       "15 0.0020                Platinum \n",
       "17 0.0000                   Silver"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fpr_df[fpr_df['p_val']<=0.05]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The end."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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