NDA.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import warnings\n",
    "import os\n",
    "from sklearn.naive_bayes import GaussianNB\n",
    "from sklearn.model_selection import StratifiedShuffleSplit\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import accuracy_score\n",
    "from sklearn.metrics import precision_recall_fscore_support\n",
    "from sklearn.metrics import mean_squared_error\n",
    "import math\n",
    "from sklearn import model_selection\n",
    "from sklearn.metrics import confusion_matrix\n",
    "from sklearn.metrics import classification_report"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'/Users/abir.pattnaik/Desktop'"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "os.getcwd()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "os.chdir(\"/Users/abir.pattnaik/Desktop\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "transaction_data=pd.read_excel('Fraud_Analytics_Dataset.xlsx',0)\n",
    "customer_data=pd.read_excel('Fraud_Analytics_Dataset.xlsx',1)\n",
    "sales_data=pd.read_excel('Fraud_Analytics_Dataset.xlsx',2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Transaction_Id</th>\n",
       "      <th>First Time Customers.</th>\n",
       "      <th>Bigger than Average Orders.</th>\n",
       "      <th>Fast Shipping</th>\n",
       "      <th>Unusual Location.</th>\n",
       "      <th>Large quantity of Same Product .</th>\n",
       "      <th>Multiple Shipping Addresses.</th>\n",
       "      <th>Shipping and Billing Address are not the same.</th>\n",
       "      <th>Several Cards used from the Same Ip Address.</th>\n",
       "      <th>Payment Information typed with Capital letters.</th>\n",
       "      <th>Many Transactions in a short time period.</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>235360</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>234773</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>235242</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>235350</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>234914</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Transaction_Id First Time Customers.  Bigger than Average Orders.   \\\n",
       "0          235360                     No                           No   \n",
       "1          234773                     No                           No   \n",
       "2          235242                     No                           No   \n",
       "3          235350                     No                          Yes   \n",
       "4          234914                     No                           No   \n",
       "\n",
       "  Fast Shipping  Unusual Location.  Large quantity of Same Product .   \\\n",
       "0             No                 No                                No   \n",
       "1             No                 No                                No   \n",
       "2             No                 No                                No   \n",
       "3            Yes                 No                                No   \n",
       "4             No                 No                                No   \n",
       "\n",
       "   Multiple Shipping Addresses.  \\\n",
       "0                            No   \n",
       "1                            No   \n",
       "2                            No   \n",
       "3                           Yes   \n",
       "4                            No   \n",
       "\n",
       "  Shipping and Billing Address are not the same.  \\\n",
       "0                                             No   \n",
       "1                                             No   \n",
       "2                                             No   \n",
       "3                                            Yes   \n",
       "4                                             No   \n",
       "\n",
       "  Several Cards used from the Same Ip Address.  \\\n",
       "0                                           No   \n",
       "1                                           No   \n",
       "2                                           No   \n",
       "3                                          Yes   \n",
       "4                                           No   \n",
       "\n",
       "  Payment Information typed with Capital letters.   \\\n",
       "0                                               No   \n",
       "1                                               No   \n",
       "2                                               No   \n",
       "3                                              Yes   \n",
       "4                                               No   \n",
       "\n",
       "  Many Transactions in a short time period.   \n",
       "0                                         No  \n",
       "1                                         No  \n",
       "2                                         No  \n",
       "3                                        Yes  \n",
       "4                                         No  "
      ]
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     "output_type": "display_data"
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>CUSTOMER_ID</th>\n",
       "      <th>LOYALTY_ID</th>\n",
       "      <th>MEMBERSHIP_TYPE__ID</th>\n",
       "      <th>MEMBERSHIP_TYPE</th>\n",
       "      <th>MEMBERSHIP_TYPE_SC</th>\n",
       "      <th>CUSTOMER_FLG</th>\n",
       "      <th>Customer_Type</th>\n",
       "      <th>customer_type_id</th>\n",
       "      <th>customer_type_sc</th>\n",
       "      <th>behavior_segment</th>\n",
       "      <th>...</th>\n",
       "      <th>BIRTH_MONTH</th>\n",
       "      <th>BIRTH_YEAR</th>\n",
       "      <th>BIRTH_QUARTER</th>\n",
       "      <th>PLACE_OF_BIRTH</th>\n",
       "      <th>COUNTRY_OF_BIRTH_SC</th>\n",
       "      <th>EVER_BANKRUPT_FLG</th>\n",
       "      <th>NO_TIMES_DELINQUENT_in_365_days</th>\n",
       "      <th>BLACKLISTED_FLG</th>\n",
       "      <th>NO_OF_DEPENDANTS</th>\n",
       "      <th>Record_created_By</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>76565665</td>\n",
       "      <td>LID877073</td>\n",
       "      <td>901.0</td>\n",
       "      <td>Gold</td>\n",
       "      <td>GLD</td>\n",
       "      <td>Y</td>\n",
       "      <td>Small/Medium Enterprise</td>\n",
       "      <td>1002.0</td>\n",
       "      <td>ENT</td>\n",
       "      <td>High Value</td>\n",
       "      <td>...</td>\n",
       "      <td>April</td>\n",
       "      <td>2004</td>\n",
       "      <td>2</td>\n",
       "      <td>Bellevue</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>N</td>\n",
       "      <td>3</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>76565666</td>\n",
       "      <td>LID877029</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Y</td>\n",
       "      <td>Individual</td>\n",
       "      <td>1003.0</td>\n",
       "      <td>INDV</td>\n",
       "      <td>Low Value</td>\n",
       "      <td>...</td>\n",
       "      <td>December</td>\n",
       "      <td>1984</td>\n",
       "      <td>4</td>\n",
       "      <td>Jackson</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>\\n</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>76565667</td>\n",
       "      <td>LID876876</td>\n",
       "      <td>902.0</td>\n",
       "      <td>Silver</td>\n",
       "      <td>SLV</td>\n",
       "      <td>Y</td>\n",
       "      <td>Small/Medium Enterprise</td>\n",
       "      <td>1002.0</td>\n",
       "      <td>ENT</td>\n",
       "      <td>Medium Value</td>\n",
       "      <td>...</td>\n",
       "      <td>February</td>\n",
       "      <td>1999</td>\n",
       "      <td>1</td>\n",
       "      <td>Chattanooga</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>N</td>\n",
       "      <td>3</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>76565668</td>\n",
       "      <td>LID876841</td>\n",
       "      <td>902.0</td>\n",
       "      <td>Silver</td>\n",
       "      <td>SLV</td>\n",
       "      <td>Y</td>\n",
       "      <td>Small/Medium Enterprise</td>\n",
       "      <td>1002.0</td>\n",
       "      <td>ENT</td>\n",
       "      <td>Low Value</td>\n",
       "      <td>...</td>\n",
       "      <td>December</td>\n",
       "      <td>1997</td>\n",
       "      <td>4</td>\n",
       "      <td>Worcester</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
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       "      <td>76565669</td>\n",
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       "      <td>902.0</td>\n",
       "      <td>Silver</td>\n",
       "      <td>SLV</td>\n",
       "      <td>Y</td>\n",
       "      <td>Individual</td>\n",
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       "      <td>INDV</td>\n",
       "      <td>Medium Value</td>\n",
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       "      <td>1</td>\n",
       "      <td>Los Angeles</td>\n",
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       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
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       "<p>5 rows × 94 columns</p>\n",
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      ],
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       "   CUSTOMER_ID LOYALTY_ID  MEMBERSHIP_TYPE__ID MEMBERSHIP_TYPE  \\\n",
       "0     76565665  LID877073                901.0            Gold   \n",
       "1     76565666  LID877029                  NaN             NaN   \n",
       "2     76565667  LID876876                902.0          Silver   \n",
       "3     76565668  LID876841                902.0          Silver   \n",
       "4     76565669  LID877001                902.0          Silver   \n",
       "\n",
       "  MEMBERSHIP_TYPE_SC CUSTOMER_FLG            Customer_Type  customer_type_id  \\\n",
       "0                GLD            Y  Small/Medium Enterprise            1002.0   \n",
       "1                NaN            Y               Individual            1003.0   \n",
       "2                SLV            Y  Small/Medium Enterprise            1002.0   \n",
       "3                SLV            Y  Small/Medium Enterprise            1002.0   \n",
       "4                SLV            Y               Individual            1003.0   \n",
       "\n",
       "  customer_type_sc behavior_segment        ...         BIRTH_MONTH  \\\n",
       "0              ENT       High Value        ...               April   \n",
       "1             INDV        Low Value        ...            December   \n",
       "2              ENT     Medium Value        ...            February   \n",
       "3              ENT        Low Value        ...            December   \n",
       "4             INDV     Medium Value        ...             January   \n",
       "\n",
       "   BIRTH_YEAR BIRTH_QUARTER PLACE_OF_BIRTH COUNTRY_OF_BIRTH_SC  \\\n",
       "0        2004             2       Bellevue                  US   \n",
       "1        1984             4        Jackson                  US   \n",
       "2        1999             1    Chattanooga                  US   \n",
       "3        1997             4      Worcester                  US   \n",
       "4        1992             1    Los Angeles                  US   \n",
       "\n",
       "   EVER_BANKRUPT_FLG  NO_TIMES_DELINQUENT_in_365_days BLACKLISTED_FLG  \\\n",
       "0                  N                                1               N   \n",
       "1                  N                                1               N   \n",
       "2                  N                                1               N   \n",
       "3                  N                                0               N   \n",
       "4                  N                                1               N   \n",
       "\n",
       "  NO_OF_DEPENDANTS  Record_created_By  \n",
       "0                3                 \\n  \n",
       "1                1                 \\n  \n",
       "2                3                 \\n  \n",
       "3                1                 \\n  \n",
       "4                1                 \\n  \n",
       "\n",
       "[5 rows x 94 columns]"
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Transaction_Id</th>\n",
       "      <th>Invoice_Id</th>\n",
       "      <th>Order_Id</th>\n",
       "      <th>Customer_Id</th>\n",
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       "      <th>Cancel_Description</th>\n",
       "      <th>Return_Flag</th>\n",
       "      <th>Return_Dt</th>\n",
       "      <th>Return_Amt</th>\n",
       "      <th>Order_Returnpaid_Gross_Amt</th>\n",
       "      <th>Lastmodified_Dt</th>\n",
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       "      <th>0</th>\n",
       "      <td>234825</td>\n",
       "      <td>88371</td>\n",
       "      <td>88371</td>\n",
       "      <td>76565900</td>\n",
       "      <td>954421840</td>\n",
       "      <td>LID876561</td>\n",
       "      <td>FEMALE</td>\n",
       "      <td>26</td>\n",
       "      <td>904.0</td>\n",
       "      <td>Platinum</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Y</td>\n",
       "      <td>2016-05-08</td>\n",
       "      <td>1953</td>\n",
       "      <td>1406</td>\n",
       "      <td>2016-04-01</td>\n",
       "      <td>NaN</td>\n",
       "      <td>\\n</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>234666</td>\n",
       "      <td>88234</td>\n",
       "      <td>88234</td>\n",
       "      <td>76566122</td>\n",
       "      <td>965982087</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MALE</td>\n",
       "      <td>22</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N</td>\n",
       "      <td>2016-04-26</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2016-11-14</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>Yes</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>234823</td>\n",
       "      <td>88153</td>\n",
       "      <td>88153</td>\n",
       "      <td>76565906</td>\n",
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       "      <td>LID876543</td>\n",
       "      <td>MALE</td>\n",
       "      <td>19</td>\n",
       "      <td>904.0</td>\n",
       "      <td>Platinum</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N</td>\n",
       "      <td>2016-05-16</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2016-08-25</td>\n",
       "      <td>John</td>\n",
       "      <td>S101\\n</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>235342</td>\n",
       "      <td>87867</td>\n",
       "      <td>87867</td>\n",
       "      <td>76566458</td>\n",
       "      <td>924245622</td>\n",
       "      <td>LID876557</td>\n",
       "      <td>MALE</td>\n",
       "      <td>26</td>\n",
       "      <td>901.0</td>\n",
       "      <td>Gold</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N</td>\n",
       "      <td>2016-05-14</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2016-04-17</td>\n",
       "      <td>NaN</td>\n",
       "      <td>\\n</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>234739</td>\n",
       "      <td>87945</td>\n",
       "      <td>87945</td>\n",
       "      <td>76566387</td>\n",
       "      <td>966653489</td>\n",
       "      <td>LID876640</td>\n",
       "      <td>MALE</td>\n",
       "      <td>37</td>\n",
       "      <td>901.0</td>\n",
       "      <td>Gold</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Y</td>\n",
       "      <td>2016-05-26</td>\n",
       "      <td>1322</td>\n",
       "      <td>952</td>\n",
       "      <td>2016-07-04</td>\n",
       "      <td>John</td>\n",
       "      <td>S101\\n</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 54 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Transaction_Id  Invoice_Id  Order_Id  Customer_Id  Mdm_Customer_Id  \\\n",
       "0          234825       88371     88371     76565900        954421840   \n",
       "1          234666       88234     88234     76566122        965982087   \n",
       "2          234823       88153     88153     76565906        953091566   \n",
       "3          235342       87867     87867     76566458        924245622   \n",
       "4          234739       87945     87945     76566387        966653489   \n",
       "\n",
       "  Loyalty_Id  Gender  Age  Membership_Id Membership_Type  ...   \\\n",
       "0  LID876561  FEMALE   26          904.0        Platinum  ...    \n",
       "1        NaN    MALE   22            NaN             NaN  ...    \n",
       "2  LID876543    MALE   19          904.0        Platinum  ...    \n",
       "3  LID876557    MALE   26          901.0            Gold  ...    \n",
       "4  LID876640    MALE   37          901.0            Gold  ...    \n",
       "\n",
       "  Cancel_Reason_Code  Cancel_Description  Return_Flag  Return_Dt Return_Amt  \\\n",
       "0                  0                 NaN            Y 2016-05-08       1953   \n",
       "1                  0                 NaN            N 2016-04-26          0   \n",
       "2                  0                 NaN            N 2016-05-16          0   \n",
       "3                  0                 NaN            N 2016-05-14          0   \n",
       "4                  0                 NaN            Y 2016-05-26       1322   \n",
       "\n",
       "   Order_Returnpaid_Gross_Amt  Lastmodified_Dt  Sales_Rep_Name  Sales_Rep_Id  \\\n",
       "0                        1406       2016-04-01             NaN            \\n   \n",
       "1                           0       2016-11-14             NaN            \\n   \n",
       "2                           0       2016-08-25            John        S101\\n   \n",
       "3                           0       2016-04-17             NaN            \\n   \n",
       "4                         952       2016-07-04            John        S101\\n   \n",
       "\n",
       "  Fraud  \n",
       "0    No  \n",
       "1   Yes  \n",
       "2    No  \n",
       "3    No  \n",
       "4   Yes  \n",
       "\n",
       "[5 rows x 54 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(transaction_data.head())\n",
    "display(customer_data.head())\n",
    "display(sales_data.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"\\nIndex([u'Transaction_Id', u'Invoice_Id', u'Order_Id', u'Customer_Id',\\n       u'Mdm_Customer_Id', u'Loyalty_Id', u'Gender', u'Age', u'Membership_Id',\\n       u'Membership_Type', u'Membership_SC', u'Product_Id', u'Channel_Id',\\n       u'Sub_Channel_Id', u'Brand_Cd', u'Gender_Age_Id', u'Size_Id',\\n       u'Color_Id', u'Campaign_Id', u'Campaign_Desc', u'Store_Id',\\n       u'Store_Short_Code', u'Store_Description', u'Sale_Dt', u'City',\\n       u'City_Id', u'City_Sc', u'Country_Id', u'Country_Sc', u'Country',\\n       u'Business_Week', u'Day', u'No_Of_Items', u'Shipment_Flg',\\n       u'Order_Item_Paidprice_Gross_Amt_', u'Order_Item_Listprice_Gross_Amt_',\\n       u'Currency', u'Discount_Percentage', u'Discount_Amt',\\n       u'Mode_Of_Payment', u'Quantity_Returned', u'No_Of_Items_After_Return',\\n       u'Cancel_Date', u'Expiry_Date', u'Cancel_Reason_Code',\\n       u'Cancel_Description', u'Return_Flag', u'Return_Dt', u'Return_Amt',\\n       u'Order_Returnpaid_Gross_Amt', u'Lastmodified_Dt', u'Sales_Rep_Name',\\n       u'Sales_Rep_Id', u'Fraud'],\\n      dtype='object')\\n\""
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Column Names\n",
    "#transaction_data.columns\n",
    "#customer_data.columns\n",
    "#sales_data.columns\n",
    "\n",
    "'''\n",
    "Index([u'Transaction_Id', u'First Time Customers. ',\n",
    "       u'Bigger than Average Orders. ', u'Fast Shipping ',\n",
    "       u'Unusual Location. ', u'Large quantity of Same Product . ',\n",
    "       u' Multiple Shipping Addresses.',\n",
    "       u'Shipping and Billing Address are not the same.',\n",
    "       u'Several Cards used from the Same Ip Address.',\n",
    "       u'Payment Information typed with Capital letters. ',\n",
    "       u'Many Transactions in a short time period. '],\n",
    "      dtype='object')\n",
    "'''\n",
    "'''\n",
    "Index([u'CUSTOMER_ID', u'LOYALTY_ID', u'MEMBERSHIP_TYPE__ID',\n",
    "       u'MEMBERSHIP_TYPE', u'MEMBERSHIP_TYPE_SC', u'CUSTOMER_FLG',\n",
    "       u'Customer_Type', u'customer_type_id', u'customer_type_sc',\n",
    "       u'behavior_segment', u'SALUTATION', u'GENDER_ID', u'GENDER',\n",
    "       u'GENDER_SC', u'BIRTH_DATE', u'AGE', u'age_at_joining', u'age_range',\n",
    "       u'PLACE_OF_BITRH', u'CUSTOMER_STATUS_ID', u'CUSTOMER_STATUS_SC',\n",
    "       u'CUSTOMER_STATUS', u'CUSTOMER_CREATED_DT', u'LOYALITY_FLG',\n",
    "       u'DEVICE_ID', u'APP_ID', u'MARITAL_STATUS_ID', u'MARITAL_STATUS',\n",
    "       u'MARITAL_STATUS_SC', u'ANNIVERSARY_DT', u'INCOME_RANGE', u'INCOME',\n",
    "       u'PROFESSION', u'PROFESSION_TYPE_SC', u'PROFESSION_TYPE_ID',\n",
    "       u'education', u'REGION', u'LANGUAGE', u'PREF_COMM_LANG_ID',\n",
    "       u'PREF_COMM_LANG', u'PREF_COMM_LANG_SC', u'PREF_ADDR',\n",
    "       u'Residence_Address_Line_1', u'Residence_Address_Line_2',\n",
    "       u'Residence_Address_Line_3', u'Residence_City', u'Residence_Province',\n",
    "       u'Residence_Country', u'Residence_Zip_CD', u'Residence_phone',\n",
    "       u'residence_fax_number', u'Office_Address_Line_1',\n",
    "       u'Office_Address_Line_2', u'Office_Address_Line_3', u'Office_City',\n",
    "       u'OFFICE_PROVIENCE', u'OFFICE_COUNTRY', u'OFFICE__ZIP_CD',\n",
    "       u'OFFICE_PHONE_NO', u'office_fax_number', u'Preferred_email_ID',\n",
    "       u'Preferred_Comm_Channel', u'Preferred_Comm_Sub_Channel',\n",
    "       u'Preferred_Comm_Sub_Channel_SC', u'PREF_CONTACT_TIME',\n",
    "       u'Acquistion_Channel_ID', u'Acquistion_Channel_SC',\n",
    "       u'Acquistion_Channel_Description', u'acquisition_subchannel_id',\n",
    "       u'acquisition_subchannel_type_sc', u'acquisition_subchannel',\n",
    "       u'INFLUENCE', u'fbck_user_FLG', u'fbck_following_CNT',\n",
    "       u'fbck_follower_CNT', u'twt_user_FLG', u'twt_follower_CNT',\n",
    "       u'twt_following_CNT', u'Interests_1', u'Interest_2', u'Friends_Count',\n",
    "       u'credit_risk_score', u'credit_risk_rating', u'DRIVING_LICENSE_NO',\n",
    "       u'BIRTH_MONTH', u'BIRTH_YEAR', u'BIRTH_QUARTER', u'PLACE_OF_BIRTH',\n",
    "       u'COUNTRY_OF_BIRTH_SC', u'EVER_BANKRUPT_FLG',\n",
    "       u'NO_TIMES_DELINQUENT_in_365_days', u'BLACKLISTED_FLG',\n",
    "       u'NO_OF_DEPENDANTS', u'Record_created_By'],\n",
    "      dtype='object')\n",
    "'''\n",
    "\n",
    "'''\n",
    "Index([u'Transaction_Id', u'Invoice_Id', u'Order_Id', u'Customer_Id',\n",
    "       u'Mdm_Customer_Id', u'Loyalty_Id', u'Gender', u'Age', u'Membership_Id',\n",
    "       u'Membership_Type', u'Membership_SC', u'Product_Id', u'Channel_Id',\n",
    "       u'Sub_Channel_Id', u'Brand_Cd', u'Gender_Age_Id', u'Size_Id',\n",
    "       u'Color_Id', u'Campaign_Id', u'Campaign_Desc', u'Store_Id',\n",
    "       u'Store_Short_Code', u'Store_Description', u'Sale_Dt', u'City',\n",
    "       u'City_Id', u'City_Sc', u'Country_Id', u'Country_Sc', u'Country',\n",
    "       u'Business_Week', u'Day', u'No_Of_Items', u'Shipment_Flg',\n",
    "       u'Order_Item_Paidprice_Gross_Amt_', u'Order_Item_Listprice_Gross_Amt_',\n",
    "       u'Currency', u'Discount_Percentage', u'Discount_Amt',\n",
    "       u'Mode_Of_Payment', u'Quantity_Returned', u'No_Of_Items_After_Return',\n",
    "       u'Cancel_Date', u'Expiry_Date', u'Cancel_Reason_Code',\n",
    "       u'Cancel_Description', u'Return_Flag', u'Return_Dt', u'Return_Amt',\n",
    "       u'Order_Returnpaid_Gross_Amt', u'Lastmodified_Dt', u'Sales_Rep_Name',\n",
    "       u'Sales_Rep_Id', u'Fraud'],\n",
    "      dtype='object')\n",
    "'''\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "###Converting transaction_data columns into binary columns\n",
    "\n",
    "for col_name in transaction_data.columns:\n",
    "    if(transaction_data[col_name].dtype == 'object'):\n",
    "        transaction_data[col_name]= transaction_data[col_name].astype('category')\n",
    "        transaction_data[col_name] = transaction_data[col_name].cat.codes\n",
    "        \n",
    "#replacing the colums name\n",
    "transaction_data.columns = transaction_data.columns.str.replace(' ','')\n",
    "transaction_data.columns = transaction_data.columns.str.replace('.','')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>CUSTOMER_ID</th>\n",
       "      <th>LOYALTY_ID</th>\n",
       "      <th>MEMBERSHIP_TYPE__ID</th>\n",
       "      <th>MEMBERSHIP_TYPE</th>\n",
       "      <th>MEMBERSHIP_TYPE_SC</th>\n",
       "      <th>CUSTOMER_FLG</th>\n",
       "      <th>Customer_Type</th>\n",
       "      <th>customer_type_id</th>\n",
       "      <th>customer_type_sc</th>\n",
       "      <th>behavior_segment</th>\n",
       "      <th>...</th>\n",
       "      <th>BIRTH_MONTH</th>\n",
       "      <th>BIRTH_YEAR</th>\n",
       "      <th>BIRTH_QUARTER</th>\n",
       "      <th>PLACE_OF_BIRTH</th>\n",
       "      <th>COUNTRY_OF_BIRTH_SC</th>\n",
       "      <th>EVER_BANKRUPT_FLG</th>\n",
       "      <th>NO_TIMES_DELINQUENT_in_365_days</th>\n",
       "      <th>BLACKLISTED_FLG</th>\n",
       "      <th>NO_OF_DEPENDANTS</th>\n",
       "      <th>Record_created_By</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>76565665</td>\n",
       "      <td>LID877073</td>\n",
       "      <td>901.0</td>\n",
       "      <td>Gold</td>\n",
       "      <td>GLD</td>\n",
       "      <td>Y</td>\n",
       "      <td>Small/Medium Enterprise</td>\n",
       "      <td>1002.0</td>\n",
       "      <td>ENT</td>\n",
       "      <td>High Value</td>\n",
       "      <td>...</td>\n",
       "      <td>April</td>\n",
       "      <td>2004</td>\n",
       "      <td>2</td>\n",
       "      <td>Bellevue</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>N</td>\n",
       "      <td>3</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>76565666</td>\n",
       "      <td>LID877029</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Y</td>\n",
       "      <td>Individual</td>\n",
       "      <td>1003.0</td>\n",
       "      <td>INDV</td>\n",
       "      <td>Low Value</td>\n",
       "      <td>...</td>\n",
       "      <td>December</td>\n",
       "      <td>1984</td>\n",
       "      <td>4</td>\n",
       "      <td>Jackson</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>76565669</td>\n",
       "      <td>LID877001</td>\n",
       "      <td>902.0</td>\n",
       "      <td>Silver</td>\n",
       "      <td>SLV</td>\n",
       "      <td>Y</td>\n",
       "      <td>Individual</td>\n",
       "      <td>1003.0</td>\n",
       "      <td>INDV</td>\n",
       "      <td>Medium Value</td>\n",
       "      <td>...</td>\n",
       "      <td>January</td>\n",
       "      <td>1992</td>\n",
       "      <td>1</td>\n",
       "      <td>Los Angeles</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>76565670</td>\n",
       "      <td>LID877275</td>\n",
       "      <td>901.0</td>\n",
       "      <td>Gold</td>\n",
       "      <td>GLD</td>\n",
       "      <td>Y</td>\n",
       "      <td>Individual</td>\n",
       "      <td>1003.0</td>\n",
       "      <td>INDV</td>\n",
       "      <td>High Value</td>\n",
       "      <td>...</td>\n",
       "      <td>February</td>\n",
       "      <td>2004</td>\n",
       "      <td>1</td>\n",
       "      <td>Fremont</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>0</td>\n",
       "      <td>N</td>\n",
       "      <td>2</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>76565671</td>\n",
       "      <td>LID876961</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Y</td>\n",
       "      <td>Individual</td>\n",
       "      <td>1003.0</td>\n",
       "      <td>INDV</td>\n",
       "      <td>Low Value</td>\n",
       "      <td>...</td>\n",
       "      <td>July</td>\n",
       "      <td>1986</td>\n",
       "      <td>3</td>\n",
       "      <td>Scottsdale</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>0</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>76565672</td>\n",
       "      <td>LID877158</td>\n",
       "      <td>903.0</td>\n",
       "      <td>Bronze</td>\n",
       "      <td>BRZ</td>\n",
       "      <td>Y</td>\n",
       "      <td>Individual</td>\n",
       "      <td>1003.0</td>\n",
       "      <td>INDV</td>\n",
       "      <td>High Value</td>\n",
       "      <td>...</td>\n",
       "      <td>April</td>\n",
       "      <td>1989</td>\n",
       "      <td>2</td>\n",
       "      <td>Santa Ana</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>0</td>\n",
       "      <td>N</td>\n",
       "      <td>2</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>76565675</td>\n",
       "      <td>LID876903</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Y</td>\n",
       "      <td>Individual</td>\n",
       "      <td>1003.0</td>\n",
       "      <td>INDV</td>\n",
       "      <td>Medium Value</td>\n",
       "      <td>...</td>\n",
       "      <td>July</td>\n",
       "      <td>1993</td>\n",
       "      <td>3</td>\n",
       "      <td>Chattanooga</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>N</td>\n",
       "      <td>3</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>76565678</td>\n",
       "      <td>LID877395</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Y</td>\n",
       "      <td>Small/Medium Enterprise</td>\n",
       "      <td>1002.0</td>\n",
       "      <td>ENT</td>\n",
       "      <td>Low Value</td>\n",
       "      <td>...</td>\n",
       "      <td>September</td>\n",
       "      <td>1985</td>\n",
       "      <td>3</td>\n",
       "      <td>Stamford</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>N</td>\n",
       "      <td>3</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>76565679</td>\n",
       "      <td>LID877184</td>\n",
       "      <td>903.0</td>\n",
       "      <td>Bronze</td>\n",
       "      <td>BRZ</td>\n",
       "      <td>Y</td>\n",
       "      <td>Small/Medium Enterprise</td>\n",
       "      <td>1002.0</td>\n",
       "      <td>ENT</td>\n",
       "      <td>Medium Value</td>\n",
       "      <td>...</td>\n",
       "      <td>November</td>\n",
       "      <td>1993</td>\n",
       "      <td>4</td>\n",
       "      <td>Charlotte</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>N</td>\n",
       "      <td>2</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>76565680</td>\n",
       "      <td>LID876955</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Y</td>\n",
       "      <td>Small/Medium Enterprise</td>\n",
       "      <td>1002.0</td>\n",
       "      <td>ENT</td>\n",
       "      <td>Medium Value</td>\n",
       "      <td>...</td>\n",
       "      <td>December</td>\n",
       "      <td>1986</td>\n",
       "      <td>4</td>\n",
       "      <td>Norfolk</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>76565681</td>\n",
       "      <td>LID876749</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Y</td>\n",
       "      <td>Small/Medium Enterprise</td>\n",
       "      <td>1002.0</td>\n",
       "      <td>ENT</td>\n",
       "      <td>Medium Value</td>\n",
       "      <td>...</td>\n",
       "      <td>November</td>\n",
       "      <td>1998</td>\n",
       "      <td>4</td>\n",
       "      <td>Yonkers</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>N</td>\n",
       "      <td>2</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>76565682</td>\n",
       "      <td>LID877078</td>\n",
       "      <td>903.0</td>\n",
       "      <td>Bronze</td>\n",
       "      <td>BRZ</td>\n",
       "      <td>Y</td>\n",
       "      <td>Small/Medium Enterprise</td>\n",
       "      <td>1002.0</td>\n",
       "      <td>ENT</td>\n",
       "      <td>Medium Value</td>\n",
       "      <td>...</td>\n",
       "      <td>June</td>\n",
       "      <td>1988</td>\n",
       "      <td>2</td>\n",
       "      <td>St. Paul</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>0</td>\n",
       "      <td>N</td>\n",
       "      <td>3</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>76565683</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>76565685</td>\n",
       "      <td>LID877040</td>\n",
       "      <td>903.0</td>\n",
       "      <td>Bronze</td>\n",
       "      <td>BRZ</td>\n",
       "      <td>Y</td>\n",
       "      <td>Small/Medium Enterprise</td>\n",
       "      <td>1002.0</td>\n",
       "      <td>ENT</td>\n",
       "      <td>High Value</td>\n",
       "      <td>...</td>\n",
       "      <td>February</td>\n",
       "      <td>1983</td>\n",
       "      <td>1</td>\n",
       "      <td>Surprise</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>0</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>76565687</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>76565689</td>\n",
       "      <td>LID876896</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Y</td>\n",
       "      <td>Individual</td>\n",
       "      <td>1003.0</td>\n",
       "      <td>INDV</td>\n",
       "      <td>High Value</td>\n",
       "      <td>...</td>\n",
       "      <td>September</td>\n",
       "      <td>2000</td>\n",
       "      <td>3</td>\n",
       "      <td>Bakersfield</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>0</td>\n",
       "      <td>N</td>\n",
       "      <td>2</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>76565692</td>\n",
       "      <td>LID876934</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Y</td>\n",
       "      <td>Individual</td>\n",
       "      <td>1003.0</td>\n",
       "      <td>INDV</td>\n",
       "      <td>Low Value</td>\n",
       "      <td>...</td>\n",
       "      <td>December</td>\n",
       "      <td>1983</td>\n",
       "      <td>4</td>\n",
       "      <td>Honolulu</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>0</td>\n",
       "      <td>N</td>\n",
       "      <td>3</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>76565694</td>\n",
       "      <td>LID877420</td>\n",
       "      <td>902.0</td>\n",
       "      <td>Silver</td>\n",
       "      <td>SLV</td>\n",
       "      <td>Y</td>\n",
       "      <td>Small/Medium Enterprise</td>\n",
       "      <td>1002.0</td>\n",
       "      <td>ENT</td>\n",
       "      <td>Low Value</td>\n",
       "      <td>...</td>\n",
       "      <td>July</td>\n",
       "      <td>2000</td>\n",
       "      <td>3</td>\n",
       "      <td>Aurora</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>N</td>\n",
       "      <td>2</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>76565695</td>\n",
       "      <td>LID877167</td>\n",
       "      <td>903.0</td>\n",
       "      <td>Bronze</td>\n",
       "      <td>BRZ</td>\n",
       "      <td>Y</td>\n",
       "      <td>Small/Medium Enterprise</td>\n",
       "      <td>1002.0</td>\n",
       "      <td>ENT</td>\n",
       "      <td>Low Value</td>\n",
       "      <td>...</td>\n",
       "      <td>December</td>\n",
       "      <td>1985</td>\n",
       "      <td>4</td>\n",
       "      <td>Augusta</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>76565696</td>\n",
       "      <td>LID877076</td>\n",
       "      <td>903.0</td>\n",
       "      <td>Bronze</td>\n",
       "      <td>BRZ</td>\n",
       "      <td>Y</td>\n",
       "      <td>Small/Medium Enterprise</td>\n",
       "      <td>1002.0</td>\n",
       "      <td>ENT</td>\n",
       "      <td>High Value</td>\n",
       "      <td>...</td>\n",
       "      <td>March</td>\n",
       "      <td>2003</td>\n",
       "      <td>1</td>\n",
       "      <td>Aurora</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>0</td>\n",
       "      <td>N</td>\n",
       "      <td>3</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>76565697</td>\n",
       "      <td>LID877094</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Y</td>\n",
       "      <td>Small/Medium Enterprise</td>\n",
       "      <td>1002.0</td>\n",
       "      <td>ENT</td>\n",
       "      <td>High Value</td>\n",
       "      <td>...</td>\n",
       "      <td>October</td>\n",
       "      <td>1992</td>\n",
       "      <td>4</td>\n",
       "      <td>Surprise</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>N</td>\n",
       "      <td>2</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>76565698</td>\n",
       "      <td>LID876948</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Y</td>\n",
       "      <td>Individual</td>\n",
       "      <td>1003.0</td>\n",
       "      <td>INDV</td>\n",
       "      <td>Medium Value</td>\n",
       "      <td>...</td>\n",
       "      <td>August</td>\n",
       "      <td>1989</td>\n",
       "      <td>3</td>\n",
       "      <td>St. Louis</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>0</td>\n",
       "      <td>N</td>\n",
       "      <td>2</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>76565700</td>\n",
       "      <td>LID877108</td>\n",
       "      <td>904.0</td>\n",
       "      <td>Platinum</td>\n",
       "      <td>PLT</td>\n",
       "      <td>Y</td>\n",
       "      <td>Small/Medium Enterprise</td>\n",
       "      <td>1002.0</td>\n",
       "      <td>ENT</td>\n",
       "      <td>High Value</td>\n",
       "      <td>...</td>\n",
       "      <td>March</td>\n",
       "      <td>1985</td>\n",
       "      <td>1</td>\n",
       "      <td>Jackson</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>76565705</td>\n",
       "      <td>LID876915</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Y</td>\n",
       "      <td>Small/Medium Enterprise</td>\n",
       "      <td>1002.0</td>\n",
       "      <td>ENT</td>\n",
       "      <td>Low Value</td>\n",
       "      <td>...</td>\n",
       "      <td>October</td>\n",
       "      <td>2002</td>\n",
       "      <td>4</td>\n",
       "      <td>Atlanta</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>76565706</td>\n",
       "      <td>LID877015</td>\n",
       "      <td>904.0</td>\n",
       "      <td>Platinum</td>\n",
       "      <td>PLT</td>\n",
       "      <td>Y</td>\n",
       "      <td>Individual</td>\n",
       "      <td>1003.0</td>\n",
       "      <td>INDV</td>\n",
       "      <td>Medium Value</td>\n",
       "      <td>...</td>\n",
       "      <td>January</td>\n",
       "      <td>2003</td>\n",
       "      <td>1</td>\n",
       "      <td>Tempe</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>76565707</td>\n",
       "      <td>LID877153</td>\n",
       "      <td>904.0</td>\n",
       "      <td>Platinum</td>\n",
       "      <td>PLT</td>\n",
       "      <td>Y</td>\n",
       "      <td>Small/Medium Enterprise</td>\n",
       "      <td>1002.0</td>\n",
       "      <td>ENT</td>\n",
       "      <td>Low Value</td>\n",
       "      <td>...</td>\n",
       "      <td>March</td>\n",
       "      <td>1978</td>\n",
       "      <td>1</td>\n",
       "      <td>Fargo</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>N</td>\n",
       "      <td>2</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>76565712</td>\n",
       "      <td>LID876960</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Y</td>\n",
       "      <td>Small/Medium Enterprise</td>\n",
       "      <td>1002.0</td>\n",
       "      <td>ENT</td>\n",
       "      <td>High Value</td>\n",
       "      <td>...</td>\n",
       "      <td>July</td>\n",
       "      <td>1991</td>\n",
       "      <td>3</td>\n",
       "      <td>Augusta</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>0</td>\n",
       "      <td>N</td>\n",
       "      <td>3</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>76565713</td>\n",
       "      <td>LID877060</td>\n",
       "      <td>904.0</td>\n",
       "      <td>Platinum</td>\n",
       "      <td>PLT</td>\n",
       "      <td>Y</td>\n",
       "      <td>Individual</td>\n",
       "      <td>1003.0</td>\n",
       "      <td>INDV</td>\n",
       "      <td>High Value</td>\n",
       "      <td>...</td>\n",
       "      <td>April</td>\n",
       "      <td>1996</td>\n",
       "      <td>2</td>\n",
       "      <td>Salem</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>0</td>\n",
       "      <td>N</td>\n",
       "      <td>3</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>76565714</td>\n",
       "      <td>LID877098</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Y</td>\n",
       "      <td>Individual</td>\n",
       "      <td>1003.0</td>\n",
       "      <td>INDV</td>\n",
       "      <td>Medium Value</td>\n",
       "      <td>...</td>\n",
       "      <td>August</td>\n",
       "      <td>2002</td>\n",
       "      <td>3</td>\n",
       "      <td>Worcester</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>N</td>\n",
       "      <td>3</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>76565715</td>\n",
       "      <td>LID876625</td>\n",
       "      <td>903.0</td>\n",
       "      <td>Bronze</td>\n",
       "      <td>BRZ</td>\n",
       "      <td>Y</td>\n",
       "      <td>Individual</td>\n",
       "      <td>1003.0</td>\n",
       "      <td>INDV</td>\n",
       "      <td>High Value</td>\n",
       "      <td>...</td>\n",
       "      <td>August</td>\n",
       "      <td>1998</td>\n",
       "      <td>3</td>\n",
       "      <td>Los Angeles</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>0</td>\n",
       "      <td>N</td>\n",
       "      <td>3</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>970</th>\n",
       "      <td>76566635</td>\n",
       "      <td>LID877343</td>\n",
       "      <td>903.0</td>\n",
       "      <td>Bronze</td>\n",
       "      <td>BRZ</td>\n",
       "      <td>Y</td>\n",
       "      <td>Small/Medium Enterprise</td>\n",
       "      <td>1002.0</td>\n",
       "      <td>ENT</td>\n",
       "      <td>Low Value</td>\n",
       "      <td>...</td>\n",
       "      <td>December</td>\n",
       "      <td>1991</td>\n",
       "      <td>4</td>\n",
       "      <td>Hialeah</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>N</td>\n",
       "      <td>2</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>971</th>\n",
       "      <td>76566636</td>\n",
       "      <td>LID877271</td>\n",
       "      <td>904.0</td>\n",
       "      <td>Platinum</td>\n",
       "      <td>PLT</td>\n",
       "      <td>Y</td>\n",
       "      <td>Small/Medium Enterprise</td>\n",
       "      <td>1002.0</td>\n",
       "      <td>ENT</td>\n",
       "      <td>High Value</td>\n",
       "      <td>...</td>\n",
       "      <td>July</td>\n",
       "      <td>1995</td>\n",
       "      <td>3</td>\n",
       "      <td>Fayetteville</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>N</td>\n",
       "      <td>2</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>972</th>\n",
       "      <td>76566637</td>\n",
       "      <td>LID877383</td>\n",
       "      <td>903.0</td>\n",
       "      <td>Bronze</td>\n",
       "      <td>BRZ</td>\n",
       "      <td>Y</td>\n",
       "      <td>Small/Medium Enterprise</td>\n",
       "      <td>1002.0</td>\n",
       "      <td>ENT</td>\n",
       "      <td>Low Value</td>\n",
       "      <td>...</td>\n",
       "      <td>June</td>\n",
       "      <td>1996</td>\n",
       "      <td>2</td>\n",
       "      <td>Montgomery</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>0</td>\n",
       "      <td>N</td>\n",
       "      <td>2</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>973</th>\n",
       "      <td>76566638</td>\n",
       "      <td>LID877307</td>\n",
       "      <td>903.0</td>\n",
       "      <td>Bronze</td>\n",
       "      <td>BRZ</td>\n",
       "      <td>Y</td>\n",
       "      <td>Individual</td>\n",
       "      <td>1003.0</td>\n",
       "      <td>INDV</td>\n",
       "      <td>Low Value</td>\n",
       "      <td>...</td>\n",
       "      <td>February</td>\n",
       "      <td>1998</td>\n",
       "      <td>1</td>\n",
       "      <td>Columbus</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>0</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>974</th>\n",
       "      <td>76566639</td>\n",
       "      <td>LID877466</td>\n",
       "      <td>903.0</td>\n",
       "      <td>Bronze</td>\n",
       "      <td>BRZ</td>\n",
       "      <td>Y</td>\n",
       "      <td>Small/Medium Enterprise</td>\n",
       "      <td>1002.0</td>\n",
       "      <td>ENT</td>\n",
       "      <td>Medium Value</td>\n",
       "      <td>...</td>\n",
       "      <td>December</td>\n",
       "      <td>2001</td>\n",
       "      <td>4</td>\n",
       "      <td>Orlando</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>0</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>975</th>\n",
       "      <td>76566640</td>\n",
       "      <td>LID877258</td>\n",
       "      <td>902.0</td>\n",
       "      <td>Silver</td>\n",
       "      <td>SLV</td>\n",
       "      <td>Y</td>\n",
       "      <td>Small/Medium Enterprise</td>\n",
       "      <td>1002.0</td>\n",
       "      <td>ENT</td>\n",
       "      <td>High Value</td>\n",
       "      <td>...</td>\n",
       "      <td>June</td>\n",
       "      <td>1991</td>\n",
       "      <td>2</td>\n",
       "      <td>Chattanooga</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>N</td>\n",
       "      <td>2</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>976</th>\n",
       "      <td>76566641</td>\n",
       "      <td>LID877262</td>\n",
       "      <td>902.0</td>\n",
       "      <td>Silver</td>\n",
       "      <td>SLV</td>\n",
       "      <td>Y</td>\n",
       "      <td>Small/Medium Enterprise</td>\n",
       "      <td>1002.0</td>\n",
       "      <td>ENT</td>\n",
       "      <td>Low Value</td>\n",
       "      <td>...</td>\n",
       "      <td>June</td>\n",
       "      <td>1996</td>\n",
       "      <td>2</td>\n",
       "      <td>Moreno Valley</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>N</td>\n",
       "      <td>3</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>977</th>\n",
       "      <td>76566642</td>\n",
       "      <td>LID877539</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Y</td>\n",
       "      <td>Small/Medium Enterprise</td>\n",
       "      <td>1002.0</td>\n",
       "      <td>ENT</td>\n",
       "      <td>Medium Value</td>\n",
       "      <td>...</td>\n",
       "      <td>December</td>\n",
       "      <td>2003</td>\n",
       "      <td>4</td>\n",
       "      <td>Kansas City</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>N</td>\n",
       "      <td>2</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>978</th>\n",
       "      <td>76566643</td>\n",
       "      <td>LID877478</td>\n",
       "      <td>904.0</td>\n",
       "      <td>Platinum</td>\n",
       "      <td>PLT</td>\n",
       "      <td>Y</td>\n",
       "      <td>Small/Medium Enterprise</td>\n",
       "      <td>1002.0</td>\n",
       "      <td>ENT</td>\n",
       "      <td>High Value</td>\n",
       "      <td>...</td>\n",
       "      <td>May</td>\n",
       "      <td>1997</td>\n",
       "      <td>2</td>\n",
       "      <td>Cedar Rapids</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>0</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>979</th>\n",
       "      <td>76566644</td>\n",
       "      <td>LID877214</td>\n",
       "      <td>904.0</td>\n",
       "      <td>Platinum</td>\n",
       "      <td>PLT</td>\n",
       "      <td>Y</td>\n",
       "      <td>Individual</td>\n",
       "      <td>1003.0</td>\n",
       "      <td>INDV</td>\n",
       "      <td>High Value</td>\n",
       "      <td>...</td>\n",
       "      <td>July</td>\n",
       "      <td>1999</td>\n",
       "      <td>3</td>\n",
       "      <td>Ann Arbor</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>N</td>\n",
       "      <td>2</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>980</th>\n",
       "      <td>76566645</td>\n",
       "      <td>LID877266</td>\n",
       "      <td>902.0</td>\n",
       "      <td>Silver</td>\n",
       "      <td>SLV</td>\n",
       "      <td>Y</td>\n",
       "      <td>Small/Medium Enterprise</td>\n",
       "      <td>1002.0</td>\n",
       "      <td>ENT</td>\n",
       "      <td>Low Value</td>\n",
       "      <td>...</td>\n",
       "      <td>October</td>\n",
       "      <td>1998</td>\n",
       "      <td>4</td>\n",
       "      <td>Manchester</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>N</td>\n",
       "      <td>3</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>981</th>\n",
       "      <td>76566646</td>\n",
       "      <td>LID877299</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Y</td>\n",
       "      <td>Individual</td>\n",
       "      <td>1003.0</td>\n",
       "      <td>INDV</td>\n",
       "      <td>Medium Value</td>\n",
       "      <td>...</td>\n",
       "      <td>February</td>\n",
       "      <td>1980</td>\n",
       "      <td>1</td>\n",
       "      <td>Sioux Falls</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>0</td>\n",
       "      <td>N</td>\n",
       "      <td>3</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>982</th>\n",
       "      <td>76566647</td>\n",
       "      <td>LID877489</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Y</td>\n",
       "      <td>Small/Medium Enterprise</td>\n",
       "      <td>1002.0</td>\n",
       "      <td>ENT</td>\n",
       "      <td>Low Value</td>\n",
       "      <td>...</td>\n",
       "      <td>April</td>\n",
       "      <td>2002</td>\n",
       "      <td>2</td>\n",
       "      <td>Fort Collins</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>N</td>\n",
       "      <td>3</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>983</th>\n",
       "      <td>76566648</td>\n",
       "      <td>LID877503</td>\n",
       "      <td>904.0</td>\n",
       "      <td>Platinum</td>\n",
       "      <td>PLT</td>\n",
       "      <td>Y</td>\n",
       "      <td>Small/Medium Enterprise</td>\n",
       "      <td>1002.0</td>\n",
       "      <td>ENT</td>\n",
       "      <td>Low Value</td>\n",
       "      <td>...</td>\n",
       "      <td>December</td>\n",
       "      <td>1993</td>\n",
       "      <td>4</td>\n",
       "      <td>Aurora</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>N</td>\n",
       "      <td>3</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>984</th>\n",
       "      <td>76566649</td>\n",
       "      <td>LID877438</td>\n",
       "      <td>904.0</td>\n",
       "      <td>Platinum</td>\n",
       "      <td>PLT</td>\n",
       "      <td>Y</td>\n",
       "      <td>Individual</td>\n",
       "      <td>1003.0</td>\n",
       "      <td>INDV</td>\n",
       "      <td>Low Value</td>\n",
       "      <td>...</td>\n",
       "      <td>July</td>\n",
       "      <td>1986</td>\n",
       "      <td>3</td>\n",
       "      <td>Charlotte</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>0</td>\n",
       "      <td>N</td>\n",
       "      <td>3</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>985</th>\n",
       "      <td>76566650</td>\n",
       "      <td>LID877393</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Y</td>\n",
       "      <td>Individual</td>\n",
       "      <td>1003.0</td>\n",
       "      <td>INDV</td>\n",
       "      <td>Low Value</td>\n",
       "      <td>...</td>\n",
       "      <td>June</td>\n",
       "      <td>1980</td>\n",
       "      <td>2</td>\n",
       "      <td>Anchorage</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>0</td>\n",
       "      <td>N</td>\n",
       "      <td>2</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>986</th>\n",
       "      <td>76566651</td>\n",
       "      <td>LID877523</td>\n",
       "      <td>902.0</td>\n",
       "      <td>Silver</td>\n",
       "      <td>SLV</td>\n",
       "      <td>Y</td>\n",
       "      <td>Small/Medium Enterprise</td>\n",
       "      <td>1002.0</td>\n",
       "      <td>ENT</td>\n",
       "      <td>Low Value</td>\n",
       "      <td>...</td>\n",
       "      <td>November</td>\n",
       "      <td>1987</td>\n",
       "      <td>4</td>\n",
       "      <td>St. Petersburg</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>0</td>\n",
       "      <td>N</td>\n",
       "      <td>3</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>987</th>\n",
       "      <td>76566652</td>\n",
       "      <td>LID877524</td>\n",
       "      <td>901.0</td>\n",
       "      <td>Gold</td>\n",
       "      <td>GLD</td>\n",
       "      <td>Y</td>\n",
       "      <td>Individual</td>\n",
       "      <td>1003.0</td>\n",
       "      <td>INDV</td>\n",
       "      <td>Medium Value</td>\n",
       "      <td>...</td>\n",
       "      <td>June</td>\n",
       "      <td>1978</td>\n",
       "      <td>2</td>\n",
       "      <td>Alexandria</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>0</td>\n",
       "      <td>N</td>\n",
       "      <td>3</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>988</th>\n",
       "      <td>76566653</td>\n",
       "      <td>LID877351</td>\n",
       "      <td>902.0</td>\n",
       "      <td>Silver</td>\n",
       "      <td>SLV</td>\n",
       "      <td>Y</td>\n",
       "      <td>Small/Medium Enterprise</td>\n",
       "      <td>1002.0</td>\n",
       "      <td>ENT</td>\n",
       "      <td>High Value</td>\n",
       "      <td>...</td>\n",
       "      <td>July</td>\n",
       "      <td>1985</td>\n",
       "      <td>3</td>\n",
       "      <td>Lincoln</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>N</td>\n",
       "      <td>2</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>989</th>\n",
       "      <td>76566654</td>\n",
       "      <td>LID877374</td>\n",
       "      <td>902.0</td>\n",
       "      <td>Silver</td>\n",
       "      <td>SLV</td>\n",
       "      <td>Y</td>\n",
       "      <td>Small/Medium Enterprise</td>\n",
       "      <td>1002.0</td>\n",
       "      <td>ENT</td>\n",
       "      <td>Low Value</td>\n",
       "      <td>...</td>\n",
       "      <td>December</td>\n",
       "      <td>1986</td>\n",
       "      <td>4</td>\n",
       "      <td>Yonkers</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>0</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>990</th>\n",
       "      <td>76566655</td>\n",
       "      <td>LID877292</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Y</td>\n",
       "      <td>Individual</td>\n",
       "      <td>1003.0</td>\n",
       "      <td>INDV</td>\n",
       "      <td>High Value</td>\n",
       "      <td>...</td>\n",
       "      <td>March</td>\n",
       "      <td>1996</td>\n",
       "      <td>1</td>\n",
       "      <td>Murfreesboro</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>N</td>\n",
       "      <td>3</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>991</th>\n",
       "      <td>76566656</td>\n",
       "      <td>LID877468</td>\n",
       "      <td>903.0</td>\n",
       "      <td>Bronze</td>\n",
       "      <td>BRZ</td>\n",
       "      <td>Y</td>\n",
       "      <td>Individual</td>\n",
       "      <td>1003.0</td>\n",
       "      <td>INDV</td>\n",
       "      <td>Medium Value</td>\n",
       "      <td>...</td>\n",
       "      <td>December</td>\n",
       "      <td>1985</td>\n",
       "      <td>4</td>\n",
       "      <td>Honolulu</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>0</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>992</th>\n",
       "      <td>76566657</td>\n",
       "      <td>LID877504</td>\n",
       "      <td>901.0</td>\n",
       "      <td>Gold</td>\n",
       "      <td>GLD</td>\n",
       "      <td>Y</td>\n",
       "      <td>Individual</td>\n",
       "      <td>1003.0</td>\n",
       "      <td>INDV</td>\n",
       "      <td>High Value</td>\n",
       "      <td>...</td>\n",
       "      <td>June</td>\n",
       "      <td>1983</td>\n",
       "      <td>2</td>\n",
       "      <td>Tucson</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>N</td>\n",
       "      <td>3</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>993</th>\n",
       "      <td>76566658</td>\n",
       "      <td>LID877454</td>\n",
       "      <td>903.0</td>\n",
       "      <td>Bronze</td>\n",
       "      <td>BRZ</td>\n",
       "      <td>Y</td>\n",
       "      <td>Individual</td>\n",
       "      <td>1003.0</td>\n",
       "      <td>INDV</td>\n",
       "      <td>Medium Value</td>\n",
       "      <td>...</td>\n",
       "      <td>July</td>\n",
       "      <td>2001</td>\n",
       "      <td>3</td>\n",
       "      <td>Raleigh</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>N</td>\n",
       "      <td>2</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>994</th>\n",
       "      <td>76566659</td>\n",
       "      <td>LID877244</td>\n",
       "      <td>904.0</td>\n",
       "      <td>Platinum</td>\n",
       "      <td>PLT</td>\n",
       "      <td>Y</td>\n",
       "      <td>Individual</td>\n",
       "      <td>1003.0</td>\n",
       "      <td>INDV</td>\n",
       "      <td>High Value</td>\n",
       "      <td>...</td>\n",
       "      <td>May</td>\n",
       "      <td>1996</td>\n",
       "      <td>2</td>\n",
       "      <td>West Valley City</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>0</td>\n",
       "      <td>N</td>\n",
       "      <td>3</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>995</th>\n",
       "      <td>76566660</td>\n",
       "      <td>LID877405</td>\n",
       "      <td>904.0</td>\n",
       "      <td>Platinum</td>\n",
       "      <td>PLT</td>\n",
       "      <td>Y</td>\n",
       "      <td>Small/Medium Enterprise</td>\n",
       "      <td>1002.0</td>\n",
       "      <td>ENT</td>\n",
       "      <td>Medium Value</td>\n",
       "      <td>...</td>\n",
       "      <td>September</td>\n",
       "      <td>1983</td>\n",
       "      <td>3</td>\n",
       "      <td>Mobile</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>0</td>\n",
       "      <td>N</td>\n",
       "      <td>3</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>996</th>\n",
       "      <td>76566661</td>\n",
       "      <td>LID877306</td>\n",
       "      <td>903.0</td>\n",
       "      <td>Bronze</td>\n",
       "      <td>BRZ</td>\n",
       "      <td>Y</td>\n",
       "      <td>Small/Medium Enterprise</td>\n",
       "      <td>1002.0</td>\n",
       "      <td>ENT</td>\n",
       "      <td>High Value</td>\n",
       "      <td>...</td>\n",
       "      <td>December</td>\n",
       "      <td>1997</td>\n",
       "      <td>4</td>\n",
       "      <td>Cary</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>0</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>997</th>\n",
       "      <td>76566662</td>\n",
       "      <td>LID877204</td>\n",
       "      <td>901.0</td>\n",
       "      <td>Gold</td>\n",
       "      <td>GLD</td>\n",
       "      <td>Y</td>\n",
       "      <td>Individual</td>\n",
       "      <td>1003.0</td>\n",
       "      <td>INDV</td>\n",
       "      <td>Medium Value</td>\n",
       "      <td>...</td>\n",
       "      <td>March</td>\n",
       "      <td>1985</td>\n",
       "      <td>1</td>\n",
       "      <td>Orlando</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>998</th>\n",
       "      <td>76566663</td>\n",
       "      <td>LID877488</td>\n",
       "      <td>902.0</td>\n",
       "      <td>Silver</td>\n",
       "      <td>SLV</td>\n",
       "      <td>Y</td>\n",
       "      <td>Individual</td>\n",
       "      <td>1003.0</td>\n",
       "      <td>INDV</td>\n",
       "      <td>Low Value</td>\n",
       "      <td>...</td>\n",
       "      <td>October</td>\n",
       "      <td>1997</td>\n",
       "      <td>4</td>\n",
       "      <td>Las Vegas</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>N</td>\n",
       "      <td>3</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>999</th>\n",
       "      <td>76566664</td>\n",
       "      <td>LID877217</td>\n",
       "      <td>901.0</td>\n",
       "      <td>Gold</td>\n",
       "      <td>GLD</td>\n",
       "      <td>Y</td>\n",
       "      <td>Small/Medium Enterprise</td>\n",
       "      <td>1002.0</td>\n",
       "      <td>ENT</td>\n",
       "      <td>High Value</td>\n",
       "      <td>...</td>\n",
       "      <td>February</td>\n",
       "      <td>1995</td>\n",
       "      <td>1</td>\n",
       "      <td>Ann Arbor</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>N</td>\n",
       "      <td>3</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>726 rows × 94 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     CUSTOMER_ID LOYALTY_ID  MEMBERSHIP_TYPE__ID MEMBERSHIP_TYPE  \\\n",
       "0       76565665  LID877073                901.0            Gold   \n",
       "1       76565666  LID877029                  NaN             NaN   \n",
       "4       76565669  LID877001                902.0          Silver   \n",
       "5       76565670  LID877275                901.0            Gold   \n",
       "6       76565671  LID876961                  NaN             NaN   \n",
       "7       76565672  LID877158                903.0          Bronze   \n",
       "10      76565675  LID876903                  NaN             NaN   \n",
       "13      76565678  LID877395                  NaN             NaN   \n",
       "14      76565679  LID877184                903.0          Bronze   \n",
       "15      76565680  LID876955                  NaN             NaN   \n",
       "16      76565681  LID876749                  NaN             NaN   \n",
       "17      76565682  LID877078                903.0          Bronze   \n",
       "18      76565683        NaN                  NaN             NaN   \n",
       "20      76565685  LID877040                903.0          Bronze   \n",
       "22      76565687        NaN                  NaN             NaN   \n",
       "24      76565689  LID876896                  NaN             NaN   \n",
       "27      76565692  LID876934                  NaN             NaN   \n",
       "29      76565694  LID877420                902.0          Silver   \n",
       "30      76565695  LID877167                903.0          Bronze   \n",
       "31      76565696  LID877076                903.0          Bronze   \n",
       "32      76565697  LID877094                  NaN             NaN   \n",
       "33      76565698  LID876948                  NaN             NaN   \n",
       "35      76565700  LID877108                904.0        Platinum   \n",
       "40      76565705  LID876915                  NaN             NaN   \n",
       "41      76565706  LID877015                904.0        Platinum   \n",
       "42      76565707  LID877153                904.0        Platinum   \n",
       "47      76565712  LID876960                  NaN             NaN   \n",
       "48      76565713  LID877060                904.0        Platinum   \n",
       "49      76565714  LID877098                  NaN             NaN   \n",
       "50      76565715  LID876625                903.0          Bronze   \n",
       "..           ...        ...                  ...             ...   \n",
       "970     76566635  LID877343                903.0          Bronze   \n",
       "971     76566636  LID877271                904.0        Platinum   \n",
       "972     76566637  LID877383                903.0          Bronze   \n",
       "973     76566638  LID877307                903.0          Bronze   \n",
       "974     76566639  LID877466                903.0          Bronze   \n",
       "975     76566640  LID877258                902.0          Silver   \n",
       "976     76566641  LID877262                902.0          Silver   \n",
       "977     76566642  LID877539                  NaN             NaN   \n",
       "978     76566643  LID877478                904.0        Platinum   \n",
       "979     76566644  LID877214                904.0        Platinum   \n",
       "980     76566645  LID877266                902.0          Silver   \n",
       "981     76566646  LID877299                  NaN             NaN   \n",
       "982     76566647  LID877489                  NaN             NaN   \n",
       "983     76566648  LID877503                904.0        Platinum   \n",
       "984     76566649  LID877438                904.0        Platinum   \n",
       "985     76566650  LID877393                  NaN             NaN   \n",
       "986     76566651  LID877523                902.0          Silver   \n",
       "987     76566652  LID877524                901.0            Gold   \n",
       "988     76566653  LID877351                902.0          Silver   \n",
       "989     76566654  LID877374                902.0          Silver   \n",
       "990     76566655  LID877292                  NaN             NaN   \n",
       "991     76566656  LID877468                903.0          Bronze   \n",
       "992     76566657  LID877504                901.0            Gold   \n",
       "993     76566658  LID877454                903.0          Bronze   \n",
       "994     76566659  LID877244                904.0        Platinum   \n",
       "995     76566660  LID877405                904.0        Platinum   \n",
       "996     76566661  LID877306                903.0          Bronze   \n",
       "997     76566662  LID877204                901.0            Gold   \n",
       "998     76566663  LID877488                902.0          Silver   \n",
       "999     76566664  LID877217                901.0            Gold   \n",
       "\n",
       "    MEMBERSHIP_TYPE_SC CUSTOMER_FLG            Customer_Type  \\\n",
       "0                  GLD            Y  Small/Medium Enterprise   \n",
       "1                  NaN            Y               Individual   \n",
       "4                  SLV            Y               Individual   \n",
       "5                  GLD            Y               Individual   \n",
       "6                  NaN            Y               Individual   \n",
       "7                  BRZ            Y               Individual   \n",
       "10                 NaN            Y               Individual   \n",
       "13                 NaN            Y  Small/Medium Enterprise   \n",
       "14                 BRZ            Y  Small/Medium Enterprise   \n",
       "15                 NaN            Y  Small/Medium Enterprise   \n",
       "16                 NaN            Y  Small/Medium Enterprise   \n",
       "17                 BRZ            Y  Small/Medium Enterprise   \n",
       "18                 NaN            N                      NaN   \n",
       "20                 BRZ            Y  Small/Medium Enterprise   \n",
       "22                 NaN            N                      NaN   \n",
       "24                 NaN            Y               Individual   \n",
       "27                 NaN            Y               Individual   \n",
       "29                 SLV            Y  Small/Medium Enterprise   \n",
       "30                 BRZ            Y  Small/Medium Enterprise   \n",
       "31                 BRZ            Y  Small/Medium Enterprise   \n",
       "32                 NaN            Y  Small/Medium Enterprise   \n",
       "33                 NaN            Y               Individual   \n",
       "35                 PLT            Y  Small/Medium Enterprise   \n",
       "40                 NaN            Y  Small/Medium Enterprise   \n",
       "41                 PLT            Y               Individual   \n",
       "42                 PLT            Y  Small/Medium Enterprise   \n",
       "47                 NaN            Y  Small/Medium Enterprise   \n",
       "48                 PLT            Y               Individual   \n",
       "49                 NaN            Y               Individual   \n",
       "50                 BRZ            Y               Individual   \n",
       "..                 ...          ...                      ...   \n",
       "970                BRZ            Y  Small/Medium Enterprise   \n",
       "971                PLT            Y  Small/Medium Enterprise   \n",
       "972                BRZ            Y  Small/Medium Enterprise   \n",
       "973                BRZ            Y               Individual   \n",
       "974                BRZ            Y  Small/Medium Enterprise   \n",
       "975                SLV            Y  Small/Medium Enterprise   \n",
       "976                SLV            Y  Small/Medium Enterprise   \n",
       "977                NaN            Y  Small/Medium Enterprise   \n",
       "978                PLT            Y  Small/Medium Enterprise   \n",
       "979                PLT            Y               Individual   \n",
       "980                SLV            Y  Small/Medium Enterprise   \n",
       "981                NaN            Y               Individual   \n",
       "982                NaN            Y  Small/Medium Enterprise   \n",
       "983                PLT            Y  Small/Medium Enterprise   \n",
       "984                PLT            Y               Individual   \n",
       "985                NaN            Y               Individual   \n",
       "986                SLV            Y  Small/Medium Enterprise   \n",
       "987                GLD            Y               Individual   \n",
       "988                SLV            Y  Small/Medium Enterprise   \n",
       "989                SLV            Y  Small/Medium Enterprise   \n",
       "990                NaN            Y               Individual   \n",
       "991                BRZ            Y               Individual   \n",
       "992                GLD            Y               Individual   \n",
       "993                BRZ            Y               Individual   \n",
       "994                PLT            Y               Individual   \n",
       "995                PLT            Y  Small/Medium Enterprise   \n",
       "996                BRZ            Y  Small/Medium Enterprise   \n",
       "997                GLD            Y               Individual   \n",
       "998                SLV            Y               Individual   \n",
       "999                GLD            Y  Small/Medium Enterprise   \n",
       "\n",
       "     customer_type_id customer_type_sc behavior_segment        ...          \\\n",
       "0              1002.0              ENT       High Value        ...           \n",
       "1              1003.0             INDV        Low Value        ...           \n",
       "4              1003.0             INDV     Medium Value        ...           \n",
       "5              1003.0             INDV       High Value        ...           \n",
       "6              1003.0             INDV        Low Value        ...           \n",
       "7              1003.0             INDV       High Value        ...           \n",
       "10             1003.0             INDV     Medium Value        ...           \n",
       "13             1002.0              ENT        Low Value        ...           \n",
       "14             1002.0              ENT     Medium Value        ...           \n",
       "15             1002.0              ENT     Medium Value        ...           \n",
       "16             1002.0              ENT     Medium Value        ...           \n",
       "17             1002.0              ENT     Medium Value        ...           \n",
       "18                NaN              NaN              NaN        ...           \n",
       "20             1002.0              ENT       High Value        ...           \n",
       "22                NaN              NaN              NaN        ...           \n",
       "24             1003.0             INDV       High Value        ...           \n",
       "27             1003.0             INDV        Low Value        ...           \n",
       "29             1002.0              ENT        Low Value        ...           \n",
       "30             1002.0              ENT        Low Value        ...           \n",
       "31             1002.0              ENT       High Value        ...           \n",
       "32             1002.0              ENT       High Value        ...           \n",
       "33             1003.0             INDV     Medium Value        ...           \n",
       "35             1002.0              ENT       High Value        ...           \n",
       "40             1002.0              ENT        Low Value        ...           \n",
       "41             1003.0             INDV     Medium Value        ...           \n",
       "42             1002.0              ENT        Low Value        ...           \n",
       "47             1002.0              ENT       High Value        ...           \n",
       "48             1003.0             INDV       High Value        ...           \n",
       "49             1003.0             INDV     Medium Value        ...           \n",
       "50             1003.0             INDV       High Value        ...           \n",
       "..                ...              ...              ...        ...           \n",
       "970            1002.0              ENT        Low Value        ...           \n",
       "971            1002.0              ENT       High Value        ...           \n",
       "972            1002.0              ENT        Low Value        ...           \n",
       "973            1003.0             INDV        Low Value        ...           \n",
       "974            1002.0              ENT     Medium Value        ...           \n",
       "975            1002.0              ENT       High Value        ...           \n",
       "976            1002.0              ENT        Low Value        ...           \n",
       "977            1002.0              ENT     Medium Value        ...           \n",
       "978            1002.0              ENT       High Value        ...           \n",
       "979            1003.0             INDV       High Value        ...           \n",
       "980            1002.0              ENT        Low Value        ...           \n",
       "981            1003.0             INDV     Medium Value        ...           \n",
       "982            1002.0              ENT        Low Value        ...           \n",
       "983            1002.0              ENT        Low Value        ...           \n",
       "984            1003.0             INDV        Low Value        ...           \n",
       "985            1003.0             INDV        Low Value        ...           \n",
       "986            1002.0              ENT        Low Value        ...           \n",
       "987            1003.0             INDV     Medium Value        ...           \n",
       "988            1002.0              ENT       High Value        ...           \n",
       "989            1002.0              ENT        Low Value        ...           \n",
       "990            1003.0             INDV       High Value        ...           \n",
       "991            1003.0             INDV     Medium Value        ...           \n",
       "992            1003.0             INDV       High Value        ...           \n",
       "993            1003.0             INDV     Medium Value        ...           \n",
       "994            1003.0             INDV       High Value        ...           \n",
       "995            1002.0              ENT     Medium Value        ...           \n",
       "996            1002.0              ENT       High Value        ...           \n",
       "997            1003.0             INDV     Medium Value        ...           \n",
       "998            1003.0             INDV        Low Value        ...           \n",
       "999            1002.0              ENT       High Value        ...           \n",
       "\n",
       "    BIRTH_MONTH  BIRTH_YEAR BIRTH_QUARTER    PLACE_OF_BIRTH  \\\n",
       "0         April        2004             2          Bellevue   \n",
       "1      December        1984             4           Jackson   \n",
       "4       January        1992             1       Los Angeles   \n",
       "5      February        2004             1           Fremont   \n",
       "6          July        1986             3        Scottsdale   \n",
       "7         April        1989             2         Santa Ana   \n",
       "10         July        1993             3       Chattanooga   \n",
       "13    September        1985             3          Stamford   \n",
       "14     November        1993             4         Charlotte   \n",
       "15     December        1986             4           Norfolk   \n",
       "16     November        1998             4           Yonkers   \n",
       "17         June        1988             2          St. Paul   \n",
       "18          NaN           0             0               NaN   \n",
       "20     February        1983             1          Surprise   \n",
       "22          NaN           0             0               NaN   \n",
       "24    September        2000             3       Bakersfield   \n",
       "27     December        1983             4          Honolulu   \n",
       "29         July        2000             3            Aurora   \n",
       "30     December        1985             4           Augusta   \n",
       "31        March        2003             1            Aurora   \n",
       "32      October        1992             4          Surprise   \n",
       "33       August        1989             3         St. Louis   \n",
       "35        March        1985             1           Jackson   \n",
       "40      October        2002             4           Atlanta   \n",
       "41      January        2003             1             Tempe   \n",
       "42        March        1978             1             Fargo   \n",
       "47         July        1991             3           Augusta   \n",
       "48        April        1996             2             Salem   \n",
       "49       August        2002             3         Worcester   \n",
       "50       August        1998             3       Los Angeles   \n",
       "..          ...         ...           ...               ...   \n",
       "970    December        1991             4           Hialeah   \n",
       "971        July        1995             3      Fayetteville   \n",
       "972        June        1996             2        Montgomery   \n",
       "973    February        1998             1          Columbus   \n",
       "974    December        2001             4           Orlando   \n",
       "975        June        1991             2       Chattanooga   \n",
       "976        June        1996             2     Moreno Valley   \n",
       "977    December        2003             4       Kansas City   \n",
       "978         May        1997             2      Cedar Rapids   \n",
       "979        July        1999             3         Ann Arbor   \n",
       "980     October        1998             4        Manchester   \n",
       "981    February        1980             1       Sioux Falls   \n",
       "982       April        2002             2      Fort Collins   \n",
       "983    December        1993             4            Aurora   \n",
       "984        July        1986             3         Charlotte   \n",
       "985        June        1980             2         Anchorage   \n",
       "986    November        1987             4    St. Petersburg   \n",
       "987        June        1978             2        Alexandria   \n",
       "988        July        1985             3           Lincoln   \n",
       "989    December        1986             4           Yonkers   \n",
       "990       March        1996             1      Murfreesboro   \n",
       "991    December        1985             4          Honolulu   \n",
       "992        June        1983             2            Tucson   \n",
       "993        July        2001             3           Raleigh   \n",
       "994         May        1996             2  West Valley City   \n",
       "995   September        1983             3            Mobile   \n",
       "996    December        1997             4              Cary   \n",
       "997       March        1985             1           Orlando   \n",
       "998     October        1997             4         Las Vegas   \n",
       "999    February        1995             1         Ann Arbor   \n",
       "\n",
       "    COUNTRY_OF_BIRTH_SC  EVER_BANKRUPT_FLG  NO_TIMES_DELINQUENT_in_365_days  \\\n",
       "0                    US                  N                                1   \n",
       "1                    US                  N                                1   \n",
       "4                    US                  N                                1   \n",
       "5                    US                  N                                0   \n",
       "6                    US                  N                                0   \n",
       "7                    US                  N                                0   \n",
       "10                   US                  N                                1   \n",
       "13                   US                  N                                1   \n",
       "14                   US                  N                                1   \n",
       "15                   US                  N                                1   \n",
       "16                   US                  N                                1   \n",
       "17                   US                  N                                0   \n",
       "18                  NaN                NaN                                0   \n",
       "20                   US                  N                                0   \n",
       "22                  NaN                NaN                                0   \n",
       "24                   US                  N                                0   \n",
       "27                   US                  N                                0   \n",
       "29                   US                  N                                1   \n",
       "30                   US                  N                                1   \n",
       "31                   US                  N                                0   \n",
       "32                   US                  N                                1   \n",
       "33                   US                  N                                0   \n",
       "35                   US                  N                                1   \n",
       "40                   US                  N                                1   \n",
       "41                   US                  N                                1   \n",
       "42                   US                  N                                1   \n",
       "47                   US                  N                                0   \n",
       "48                   US                  N                                0   \n",
       "49                   US                  N                                1   \n",
       "50                   US                  N                                0   \n",
       "..                  ...                ...                              ...   \n",
       "970                  US                  N                                1   \n",
       "971                  US                  N                                1   \n",
       "972                  US                  N                                0   \n",
       "973                  US                  N                                0   \n",
       "974                  US                  N                                0   \n",
       "975                  US                  N                                1   \n",
       "976                  US                  N                                1   \n",
       "977                  US                  N                                1   \n",
       "978                  US                  N                                0   \n",
       "979                  US                  N                                1   \n",
       "980                  US                  N                                1   \n",
       "981                  US                  N                                0   \n",
       "982                  US                  N                                1   \n",
       "983                  US                  N                                1   \n",
       "984                  US                  N                                0   \n",
       "985                  US                  N                                0   \n",
       "986                  US                  N                                0   \n",
       "987                  US                  N                                0   \n",
       "988                  US                  N                                1   \n",
       "989                  US                  N                                0   \n",
       "990                  US                  N                                1   \n",
       "991                  US                  N                                0   \n",
       "992                  US                  N                                1   \n",
       "993                  US                  N                                1   \n",
       "994                  US                  N                                0   \n",
       "995                  US                  N                                0   \n",
       "996                  US                  N                                0   \n",
       "997                  US                  N                                1   \n",
       "998                  US                  N                                1   \n",
       "999                  US                  N                                1   \n",
       "\n",
       "    BLACKLISTED_FLG NO_OF_DEPENDANTS  Record_created_By  \n",
       "0                 N                3                 \\n  \n",
       "1                 N                1                 \\n  \n",
       "4                 N                1                 \\n  \n",
       "5                 N                2                 \\n  \n",
       "6                 N                1                 \\n  \n",
       "7                 N                2                 \\n  \n",
       "10                N                3                 \\n  \n",
       "13                N                3                 \\n  \n",
       "14                N                2                 \\n  \n",
       "15                N                1                 \\n  \n",
       "16                N                2                 \\n  \n",
       "17                N                3                 \\n  \n",
       "18              NaN                0                 \\n  \n",
       "20                N                1                 \\n  \n",
       "22              NaN                0                 \\n  \n",
       "24                N                2                 \\n  \n",
       "27                N                3                 \\n  \n",
       "29                N                2                 \\n  \n",
       "30                N                1                 \\n  \n",
       "31                N                3                 \\n  \n",
       "32                N                2                 \\n  \n",
       "33                N                2                 \\n  \n",
       "35                N                1                 \\n  \n",
       "40                N                1                 \\n  \n",
       "41                N                1                 \\n  \n",
       "42                N                2                 \\n  \n",
       "47                N                3                 \\n  \n",
       "48                N                3                 \\n  \n",
       "49                N                3                 \\n  \n",
       "50                N                3                 \\n  \n",
       "..              ...              ...                ...  \n",
       "970               N                2                 \\n  \n",
       "971               N                2                 \\n  \n",
       "972               N                2                 \\n  \n",
       "973               N                1                 \\n  \n",
       "974               N                1                 \\n  \n",
       "975               N                2                 \\n  \n",
       "976               N                3                 \\n  \n",
       "977               N                2                 \\n  \n",
       "978               N                1                 \\n  \n",
       "979               N                2                 \\n  \n",
       "980               N                3                 \\n  \n",
       "981               N                3                 \\n  \n",
       "982               N                3                 \\n  \n",
       "983               N                3                 \\n  \n",
       "984               N                3                 \\n  \n",
       "985               N                2                 \\n  \n",
       "986               N                3                 \\n  \n",
       "987               N                3                 \\n  \n",
       "988               N                2                 \\n  \n",
       "989               N                1                 \\n  \n",
       "990               N                3                 \\n  \n",
       "991               N                1                 \\n  \n",
       "992               N                3                 \\n  \n",
       "993               N                2                 \\n  \n",
       "994               N                3                 \\n  \n",
       "995               N                3                 \\n  \n",
       "996               N                1                 \\n  \n",
       "997               N                1                 \\n  \n",
       "998               N                3                 \\n  \n",
       "999               N                3                 \\n  \n",
       "\n",
       "[726 rows x 94 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "##Looking out for null values\n",
    "null_data = customer_data[customer_data.isnull().any(axis=1)]\n",
    "display(null_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "'''\n",
    "Joining all the 3 sheets\n",
    "'''\n",
    "#caller.join(other.set_index('key'), on='key')\n",
    "f1=sales_data.join(transaction_data.set_index('Transaction_Id'),on='Transaction_Id')\n",
    "master_data = f1.join(customer_data.set_index('CUSTOMER_ID'),on='Customer_Id')\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 947 entries, 0 to 946\n",
      "Columns: 157 entries, Transaction_Id to Record_created_By\n",
      "dtypes: datetime64[ns](3), float64(13), int64(39), int8(10), object(92)\n",
      "memory usage: 1.1+ MB\n"
     ]
    }
   ],
   "source": [
    "master_data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Transaction_Id</th>\n",
       "      <th>Invoice_Id</th>\n",
       "      <th>Order_Id</th>\n",
       "      <th>Customer_Id</th>\n",
       "      <th>Mdm_Customer_Id</th>\n",
       "      <th>Loyalty_Id</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Age</th>\n",
       "      <th>Membership_Id</th>\n",
       "      <th>Membership_Type</th>\n",
       "      <th>...</th>\n",
       "      <th>BIRTH_MONTH</th>\n",
       "      <th>BIRTH_YEAR</th>\n",
       "      <th>BIRTH_QUARTER</th>\n",
       "      <th>PLACE_OF_BIRTH</th>\n",
       "      <th>COUNTRY_OF_BIRTH_SC</th>\n",
       "      <th>EVER_BANKRUPT_FLG</th>\n",
       "      <th>NO_TIMES_DELINQUENT_in_365_days</th>\n",
       "      <th>BLACKLISTED_FLG</th>\n",
       "      <th>NO_OF_DEPENDANTS</th>\n",
       "      <th>Record_created_By</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>234825</td>\n",
       "      <td>88371</td>\n",
       "      <td>88371</td>\n",
       "      <td>76565900</td>\n",
       "      <td>954421840</td>\n",
       "      <td>LID876561</td>\n",
       "      <td>FEMALE</td>\n",
       "      <td>26</td>\n",
       "      <td>904.0</td>\n",
       "      <td>Platinum</td>\n",
       "      <td>...</td>\n",
       "      <td>July</td>\n",
       "      <td>1984</td>\n",
       "      <td>3</td>\n",
       "      <td>Miami</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>N</td>\n",
       "      <td>3</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>234666</td>\n",
       "      <td>88234</td>\n",
       "      <td>88234</td>\n",
       "      <td>76566122</td>\n",
       "      <td>965982087</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MALE</td>\n",
       "      <td>22</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>June</td>\n",
       "      <td>1984</td>\n",
       "      <td>2</td>\n",
       "      <td>Newark</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>0</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>234823</td>\n",
       "      <td>88153</td>\n",
       "      <td>88153</td>\n",
       "      <td>76565906</td>\n",
       "      <td>953091566</td>\n",
       "      <td>LID876543</td>\n",
       "      <td>MALE</td>\n",
       "      <td>19</td>\n",
       "      <td>904.0</td>\n",
       "      <td>Platinum</td>\n",
       "      <td>...</td>\n",
       "      <td>June</td>\n",
       "      <td>1986</td>\n",
       "      <td>2</td>\n",
       "      <td>Anchorage</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>N</td>\n",
       "      <td>3</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>235342</td>\n",
       "      <td>87867</td>\n",
       "      <td>87867</td>\n",
       "      <td>76566458</td>\n",
       "      <td>924245622</td>\n",
       "      <td>LID876557</td>\n",
       "      <td>MALE</td>\n",
       "      <td>26</td>\n",
       "      <td>901.0</td>\n",
       "      <td>Gold</td>\n",
       "      <td>...</td>\n",
       "      <td>January</td>\n",
       "      <td>1991</td>\n",
       "      <td>1</td>\n",
       "      <td>Anchorage</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>N</td>\n",
       "      <td>3</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>234739</td>\n",
       "      <td>87945</td>\n",
       "      <td>87945</td>\n",
       "      <td>76566387</td>\n",
       "      <td>966653489</td>\n",
       "      <td>LID876640</td>\n",
       "      <td>MALE</td>\n",
       "      <td>37</td>\n",
       "      <td>901.0</td>\n",
       "      <td>Gold</td>\n",
       "      <td>...</td>\n",
       "      <td>July</td>\n",
       "      <td>1977</td>\n",
       "      <td>3</td>\n",
       "      <td>Columbia</td>\n",
       "      <td>US</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>N</td>\n",
       "      <td>3</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 157 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Transaction_Id  Invoice_Id  Order_Id  Customer_Id  Mdm_Customer_Id  \\\n",
       "0          234825       88371     88371     76565900        954421840   \n",
       "1          234666       88234     88234     76566122        965982087   \n",
       "2          234823       88153     88153     76565906        953091566   \n",
       "3          235342       87867     87867     76566458        924245622   \n",
       "4          234739       87945     87945     76566387        966653489   \n",
       "\n",
       "  Loyalty_Id  Gender  Age  Membership_Id Membership_Type        ...         \\\n",
       "0  LID876561  FEMALE   26          904.0        Platinum        ...          \n",
       "1        NaN    MALE   22            NaN             NaN        ...          \n",
       "2  LID876543    MALE   19          904.0        Platinum        ...          \n",
       "3  LID876557    MALE   26          901.0            Gold        ...          \n",
       "4  LID876640    MALE   37          901.0            Gold        ...          \n",
       "\n",
       "  BIRTH_MONTH  BIRTH_YEAR  BIRTH_QUARTER  PLACE_OF_BIRTH COUNTRY_OF_BIRTH_SC  \\\n",
       "0        July        1984              3           Miami                  US   \n",
       "1        June        1984              2          Newark                  US   \n",
       "2        June        1986              2       Anchorage                  US   \n",
       "3     January        1991              1       Anchorage                  US   \n",
       "4        July        1977              3        Columbia                  US   \n",
       "\n",
       "   EVER_BANKRUPT_FLG  NO_TIMES_DELINQUENT_in_365_days  BLACKLISTED_FLG  \\\n",
       "0                  N                                1                N   \n",
       "1                  N                                0                N   \n",
       "2                  N                                1                N   \n",
       "3                  N                                1                N   \n",
       "4                  N                                1                N   \n",
       "\n",
       "   NO_OF_DEPENDANTS Record_created_By  \n",
       "0                 3                \\n  \n",
       "1                 1                \\n  \n",
       "2                 3                \\n  \n",
       "3                 3                \\n  \n",
       "4                 3                \\n  \n",
       "\n",
       "[5 rows x 157 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(master_data.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "'''\n",
    "Removing the following columns as these are redundant columns and won't help in our analysis .\n",
    "'''\n",
    "column_list_removal=['City','City_Id','MEMBERSHIP_TYPE__ID','MEMBERSHIP_TYPE','Customer_Type','customer_type_id','SALUTATION','GENDER_ID','GENDER_SC','CUSTOMER_STATUS_ID','CUSTOMER_STATUS','CUSTOMER_CREATED_DT','DEVICE_ID','APP_ID','MARITAL_STATUS_ID','MARITAL_STATUS','ANNIVERSARY_DT','INCOME_RANGE','PROFESSION','PROFESSION_TYPE_ID','PREF_COMM_LANG_ID','PREF_COMM_LANG','Residence_Country','Preferred_Comm_Sub_Channel','Acquistion_Channel_ID','Acquistion_Channel_Description','acquisition_subchannel_id','acquisition_subchannel','COUNTRY_OF_BIRTH_SC','Membership_Id','Membership_Type','Campaign_Desc','Store_Id','Store_Description','Country_Id','Country','Currency','Cancel_Description','Sales_Rep_Id']\n",
    "\n",
    "# dividing test and train data \n",
    "for column_name in column_list_removal:\n",
    "    master_data=master_data.drop(column_name,axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 947 entries, 0 to 946\n",
      "Columns: 118 entries, Transaction_Id to Record_created_By\n",
      "dtypes: datetime64[ns](3), float64(3), int64(36), int8(10), object(66)\n",
      "memory usage: 808.3+ KB\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "39"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "master_data.info()\n",
    "len(column_list_removal)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Transaction_Id\n",
      "Invoice_Id\n",
      "Order_Id\n",
      "Customer_Id\n",
      "Mdm_Customer_Id\n",
      "Loyalty_Id\n",
      "Gender\n",
      "Age\n",
      "Membership_SC\n",
      "Product_Id\n",
      "Channel_Id\n",
      "Sub_Channel_Id\n",
      "Brand_Cd\n",
      "Gender_Age_Id\n",
      "Size_Id\n",
      "Color_Id\n",
      "Campaign_Id\n",
      "Store_Short_Code\n",
      "Sale_Dt\n",
      "City_Sc\n",
      "Country_Sc\n",
      "Business_Week\n",
      "Day\n",
      "No_Of_Items\n",
      "Shipment_Flg\n",
      "Order_Item_Paidprice_Gross_Amt_\n",
      "Order_Item_Listprice_Gross_Amt_\n",
      "Discount_Percentage\n",
      "Discount_Amt\n",
      "Mode_Of_Payment\n",
      "Quantity_Returned\n",
      "No_Of_Items_After_Return\n",
      "Cancel_Date\n",
      "Expiry_Date\n",
      "Cancel_Reason_Code\n",
      "Return_Flag\n",
      "Return_Dt\n",
      "Return_Amt\n",
      "Order_Returnpaid_Gross_Amt\n",
      "Lastmodified_Dt\n",
      "Sales_Rep_Name\n",
      "Fraud\n",
      "FirstTimeCustomers\n",
      "BiggerthanAverageOrders\n",
      "FastShipping\n",
      "UnusualLocation\n",
      "LargequantityofSameProduct\n",
      "MultipleShippingAddresses\n",
      "ShippingandBillingAddressarenotthesame\n",
      "SeveralCardsusedfromtheSameIpAddress\n",
      "PaymentInformationtypedwithCapitalletters\n",
      "ManyTransactionsinashorttimeperiod\n",
      "LOYALTY_ID\n",
      "MEMBERSHIP_TYPE_SC\n",
      "CUSTOMER_FLG\n",
      "customer_type_sc\n",
      "behavior_segment\n",
      "GENDER\n",
      "BIRTH_DATE\n",
      "AGE\n",
      "age_at_joining\n",
      "age_range\n",
      "PLACE_OF_BITRH\n",
      "CUSTOMER_STATUS_SC\n",
      "LOYALITY_FLG\n",
      "MARITAL_STATUS_SC\n",
      "INCOME\n",
      "PROFESSION_TYPE_SC\n",
      "education\n",
      "REGION\n",
      "LANGUAGE\n",
      "PREF_COMM_LANG_SC\n",
      "PREF_ADDR\n",
      "Residence_Address_Line_1\n",
      "Residence_Address_Line_2\n",
      "Residence_Address_Line_3\n",
      "Residence_City\n",
      "Residence_Province\n",
      "Residence_Zip_CD\n",
      "Residence_phone\n",
      "residence_fax_number\n",
      "Office_Address_Line_1\n",
      "Office_Address_Line_2\n",
      "Office_Address_Line_3\n",
      "Office_City\n",
      "OFFICE_PROVIENCE\n",
      "OFFICE_COUNTRY\n",
      "OFFICE__ZIP_CD\n",
      "OFFICE_PHONE_NO\n",
      "office_fax_number\n",
      "Preferred_email_ID\n",
      "Preferred_Comm_Channel\n",
      "Preferred_Comm_Sub_Channel_SC\n",
      "PREF_CONTACT_TIME\n",
      "Acquistion_Channel_SC\n",
      "acquisition_subchannel_type_sc\n",
      "INFLUENCE\n",
      "fbck_user_FLG\n",
      "fbck_following_CNT\n",
      "fbck_follower_CNT\n",
      "twt_user_FLG\n",
      "twt_follower_CNT\n",
      "twt_following_CNT\n",
      "Interests_1\n",
      "Interest_2\n",
      "Friends_Count\n",
      "credit_risk_score\n",
      "credit_risk_rating\n",
      "DRIVING_LICENSE_NO\n",
      "BIRTH_MONTH\n",
      "BIRTH_YEAR\n",
      "BIRTH_QUARTER\n",
      "PLACE_OF_BIRTH\n",
      "EVER_BANKRUPT_FLG\n",
      "NO_TIMES_DELINQUENT_in_365_days\n",
      "BLACKLISTED_FLG\n",
      "NO_OF_DEPENDANTS\n",
      "Record_created_By\n"
     ]
    }
   ],
   "source": [
    "for col_name in master_data.columns:\n",
    "    master_data[col_name].dtype == 'object'\n",
    "    print(col_name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Transaction_Id\n",
      "Invoice_Id\n",
      "Order_Id\n",
      "Customer_Id\n",
      "Mdm_Customer_Id\n",
      "Loyalty_Id\n",
      "Gender\n",
      "Age\n",
      "Membership_SC\n",
      "Product_Id\n",
      "Channel_Id\n",
      "Sub_Channel_Id\n",
      "Brand_Cd\n",
      "Gender_Age_Id\n",
      "Size_Id\n",
      "Color_Id\n",
      "Campaign_Id\n",
      "Store_Short_Code\n",
      "Sale_Dt\n",
      "City_Sc\n",
      "Country_Sc\n",
      "Business_Week\n",
      "Day\n",
      "No_Of_Items\n",
      "Shipment_Flg\n",
      "Order_Item_Paidprice_Gross_Amt_\n",
      "Order_Item_Listprice_Gross_Amt_\n",
      "Discount_Percentage\n",
      "Discount_Amt\n",
      "Mode_Of_Payment\n",
      "Quantity_Returned\n",
      "No_Of_Items_After_Return\n",
      "Cancel_Date\n",
      "Expiry_Date\n",
      "Cancel_Reason_Code\n",
      "Return_Flag\n",
      "Return_Dt\n",
      "Return_Amt\n",
      "Order_Returnpaid_Gross_Amt\n",
      "Lastmodified_Dt\n",
      "Sales_Rep_Name\n",
      "Fraud\n",
      "FirstTimeCustomers\n",
      "BiggerthanAverageOrders\n",
      "FastShipping\n",
      "UnusualLocation\n",
      "LargequantityofSameProduct\n",
      "MultipleShippingAddresses\n",
      "ShippingandBillingAddressarenotthesame\n",
      "SeveralCardsusedfromtheSameIpAddress\n",
      "PaymentInformationtypedwithCapitalletters\n",
      "ManyTransactionsinashorttimeperiod\n",
      "LOYALTY_ID\n",
      "MEMBERSHIP_TYPE_SC\n",
      "CUSTOMER_FLG\n",
      "customer_type_sc\n",
      "behavior_segment\n",
      "GENDER\n",
      "BIRTH_DATE\n",
      "AGE\n",
      "age_at_joining\n",
      "age_range\n",
      "PLACE_OF_BITRH\n",
      "CUSTOMER_STATUS_SC\n",
      "LOYALITY_FLG\n",
      "MARITAL_STATUS_SC\n",
      "INCOME\n",
      "PROFESSION_TYPE_SC\n",
      "education\n",
      "REGION\n",
      "LANGUAGE\n",
      "PREF_COMM_LANG_SC\n",
      "PREF_ADDR\n",
      "Residence_Address_Line_1\n",
      "Residence_Address_Line_2\n",
      "Residence_Address_Line_3\n",
      "Residence_City\n",
      "Residence_Province\n",
      "Residence_Zip_CD\n",
      "Residence_phone\n",
      "residence_fax_number\n",
      "Office_Address_Line_1\n",
      "Office_Address_Line_2\n",
      "Office_Address_Line_3\n",
      "Office_City\n",
      "OFFICE_PROVIENCE\n",
      "OFFICE_COUNTRY\n",
      "OFFICE__ZIP_CD\n",
      "OFFICE_PHONE_NO\n",
      "office_fax_number\n",
      "Preferred_email_ID\n",
      "Preferred_Comm_Channel\n",
      "Preferred_Comm_Sub_Channel_SC\n",
      "PREF_CONTACT_TIME\n",
      "Acquistion_Channel_SC\n",
      "acquisition_subchannel_type_sc\n",
      "INFLUENCE\n",
      "fbck_user_FLG\n",
      "fbck_following_CNT\n",
      "fbck_follower_CNT\n",
      "twt_user_FLG\n",
      "twt_follower_CNT\n",
      "twt_following_CNT\n",
      "Interests_1\n",
      "Interest_2\n",
      "Friends_Count\n",
      "credit_risk_score\n",
      "credit_risk_rating\n",
      "DRIVING_LICENSE_NO\n",
      "BIRTH_MONTH\n",
      "BIRTH_YEAR\n",
      "BIRTH_QUARTER\n",
      "PLACE_OF_BIRTH\n",
      "EVER_BANKRUPT_FLG\n",
      "NO_TIMES_DELINQUENT_in_365_days\n",
      "BLACKLISTED_FLG\n",
      "NO_OF_DEPENDANTS\n",
      "Record_created_By\n"
     ]
    }
   ],
   "source": [
    "#Converting data type to int\n",
    "convert_to_int=['Transaction_Id','Invoice_Id','Order_Id','Customer_Id','Age','Product_Id','Business_Week','No_Of_Items',\n",
    "                'Order_Item_Paidprice_Gross_Amt_','Order_Item_Listprice_Gross_Amt_','Discount_Percentage',\n",
    "                'Discount_Amt','Quantity_Returned','No_Of_Items_After_Return','Return_Amt','Order_Returnpaid_Gross_Amt',\n",
    "                'INCOME','Residence_Zip_CD','fbck_following_CNT','fbck_follower_CNT','twt_follower_CNT','twt_following_CNT','Friends_Count','credit_risk_score','BIRTH_QUARTER','BIRTH_YEAR']\n",
    "\n",
    "\n",
    "\n",
    "convert_to_string=['Loyalty_Id','City','LOYALTY_ID','Residence_Address_Line_1','Residence_Address_Line_2','Residence_Address_Line_3','Residence_City','Residence_Province','Residence_phone','residence_fax_number','Office_Address_Line_1','Office_Address_Line_2','Office_Address_Line_3','Office_City','OFFICE_PROVIENCE','OFFICE_COUNTRY','OFFICE__ZIP_CD','OFFICE_PHONE_NO','Preferred_email_ID','Interests_1','Interest_2','DRIVING_LICENSE_NO','BIRTH_MONTH']\n",
    "\n",
    "\n",
    "\n",
    "ordinals=['Membership_SC','Sub_Channel_Id','Brand_Cd','Gender_Age_Id','Size_Id','Color_Id','Campaign_Id','Store_Short_Code','City_Sc','Country_Sc','Mode_Of_Payment','Cancel_Reason_Code','Sales_Rep_Name','PROFESSION_TYPE_SC','education','REGION','LANGUAGE','MARITAL_STATUS_SC','Preferred_Comm_Channel','Preferred_Comm_Sub_Channel_SC','PREF_CONTACT_TIME','Acquistion_Channel_SC','acquisition_subchannel_type_sc','INFLUENCE','credit_risk_rating']\n",
    "\n",
    "\n",
    "\n",
    "binary_category=['Gender','Channel_Id','Shipment_Flg','Return_Flag','Fraud','FirstTimeCustomers','BiggerthanAverageOrders','FastShipping','UnusualLocation','LargequantityofSameProduct',\n",
    "'MultipleShippingAddresses','ShippingandBillingAddressarenotthesame',\n",
    "'SeveralCardsusedfromtheSameIpAddress','SeveralCardsusedfromtheSameIpAddress','PaymentInformationtypedwithCapitalletters','ManyTransactionsinashorttimeperiod','PREF_COMM_LANG_SC',\n",
    "'PREF_ADDR','fbck_user_FLG','twt_user_FLG','EVER_BANKRUPT_FLG','NO_TIMES_DELINQUENT_in_365_days','BLACKLISTED_FLG']\n",
    "\n",
    "#Record_created_BY<--REMOVE THIS COLUMN\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "to_date=['Sale_Dt','Cancel_Date','Expiry_Date','Return_Dt','Lastmodified_Dt']\n",
    "\n",
    "\n",
    "#master_data['Transaction_Id'].astype('int')\n",
    "#master_data['Transaction_Id'].dtype\n",
    "#\n",
    "\n",
    "for column_name in master_data.columns:\n",
    "    print(column_name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "for binary_cat in binary_category:\n",
    "    master_data[binary_cat]=master_data[binary_cat].astype('category')\n",
    "    master_data[binary_cat]=master_data[binary_cat].cat.codes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "#print(master_data.X.describe())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "#for binary_cat in ordinals:\n",
    "#    master_data[binary_cat]=master_data[binary_cat].astype('category')\n",
    "#    master_data[binary_cat]=master_data[binary_cat].cat.codes\n",
    "    \n",
    "    \n",
    "variables_to_be_removed=['Order_Id','Customer_Id','Mdm_Customer_Id','Gender','Gender_Age_Id','Brand_Cd','Size_Id','Color_Id','Sale_Dt','Country_Sc','Discount_Percentage','Discount_Amt','No_Of_Items_After_Return','Cancel_Date','Expiry_Date','Return_Dt','Lastmodified_Dt','Sales_Rep_Name','GENDER','BIRTH_DATE','AGE','PLACE_OF_BITRH','MARITAL_STATUS_SC','REGION','Residence_Address_Line_1','Residence_Address_Line_2','Residence_Address_Line_3','Residence_City','Residence_Province','Residence_Zip_CD','Residence_phone','residence_fax_number','Office_Address_Line_1','Office_Address_Line_2','Office_Address_Line_3','Office_City','OFFICE_PROVIENCE','OFFICE_COUNTRY','OFFICE__ZIP_CD','OFFICE_PHONE_NO','office_fax_number','Preferred_email_ID','Acquistion_Channel_SC','acquisition_subchannel_type_sc','fbck_following_CNT','fbck_follower_CNT','twt_follower_CNT','twt_following_CNT','Interests_1','Interest_2','Friends_Count','DRIVING_LICENSE_NO','BIRTH_MONTH','BIRTH_YEAR','BIRTH_QUARTER','PLACE_OF_BIRTH','EVER_BANKRUPT_FLG','BLACKLISTED_FLG','Record_created_By','NO_OF_DEPENDANTS']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "for column_name in variables_to_be_removed:\n",
    "    master_data=master_data.drop(column_name,axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 947 entries, 0 to 946\n",
      "Data columns (total 58 columns):\n",
      "Transaction_Id                               947 non-null int64\n",
      "Invoice_Id                                   947 non-null int64\n",
      "Loyalty_Id                                   775 non-null object\n",
      "Age                                          947 non-null int64\n",
      "Membership_SC                                775 non-null object\n",
      "Product_Id                                   947 non-null int64\n",
      "Channel_Id                                   947 non-null int8\n",
      "Sub_Channel_Id                               947 non-null int64\n",
      "Campaign_Id                                  947 non-null int64\n",
      "Store_Short_Code                             193 non-null object\n",
      "City_Sc                                      947 non-null object\n",
      "Business_Week                                947 non-null int64\n",
      "Day                                          947 non-null int64\n",
      "No_Of_Items                                  947 non-null int64\n",
      "Shipment_Flg                                 947 non-null int8\n",
      "Order_Item_Paidprice_Gross_Amt_              947 non-null int64\n",
      "Order_Item_Listprice_Gross_Amt_              947 non-null int64\n",
      "Mode_Of_Payment                              947 non-null object\n",
      "Quantity_Returned                            947 non-null int64\n",
      "Cancel_Reason_Code                           947 non-null int64\n",
      "Return_Flag                                  947 non-null int8\n",
      "Return_Amt                                   947 non-null int64\n",
      "Order_Returnpaid_Gross_Amt                   947 non-null int64\n",
      "Fraud                                        947 non-null int8\n",
      "FirstTimeCustomers                           947 non-null int8\n",
      "BiggerthanAverageOrders                      947 non-null int8\n",
      "FastShipping                                 947 non-null int8\n",
      "UnusualLocation                              947 non-null int8\n",
      "LargequantityofSameProduct                   947 non-null int8\n",
      "MultipleShippingAddresses                    947 non-null int8\n",
      "ShippingandBillingAddressarenotthesame       947 non-null int8\n",
      "SeveralCardsusedfromtheSameIpAddress         947 non-null int8\n",
      "PaymentInformationtypedwithCapitalletters    947 non-null int8\n",
      "ManyTransactionsinashorttimeperiod           947 non-null int8\n",
      "LOYALTY_ID                                   921 non-null object\n",
      "MEMBERSHIP_TYPE_SC                           674 non-null object\n",
      "CUSTOMER_FLG                                 947 non-null object\n",
      "customer_type_sc                             921 non-null object\n",
      "behavior_segment                             921 non-null object\n",
      "age_at_joining                               947 non-null int64\n",
      "age_range                                    921 non-null object\n",
      "CUSTOMER_STATUS_SC                           921 non-null object\n",
      "LOYALITY_FLG                                 921 non-null object\n",
      "INCOME                                       921 non-null object\n",
      "PROFESSION_TYPE_SC                           921 non-null object\n",
      "education                                    921 non-null object\n",
      "LANGUAGE                                     921 non-null object\n",
      "PREF_COMM_LANG_SC                            947 non-null int8\n",
      "PREF_ADDR                                    947 non-null int8\n",
      "Preferred_Comm_Channel                       921 non-null object\n",
      "Preferred_Comm_Sub_Channel_SC                921 non-null object\n",
      "PREF_CONTACT_TIME                            921 non-null object\n",
      "INFLUENCE                                    921 non-null object\n",
      "fbck_user_FLG                                947 non-null int8\n",
      "twt_user_FLG                                 947 non-null int8\n",
      "credit_risk_score                            947 non-null int64\n",
      "credit_risk_rating                           921 non-null object\n",
      "NO_TIMES_DELINQUENT_in_365_days              947 non-null int8\n",
      "dtypes: int64(17), int8(19), object(22)\n",
      "memory usage: 306.2+ KB\n"
     ]
    }
   ],
   "source": [
    "master_data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "###Performing stratified shuffle split on the data\n",
    "y=range(947)\n",
    "X_train, X_test, y_train, y_test = train_test_split(master_data, y, test_size=0.3, random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [],
   "source": [
    "##Converting variables to int\n",
    "##taking only few variables\n",
    "subset_data=X_train[['Business_Week','No_Of_Items','Shipment_Flg','Order_Item_Paidprice_Gross_Amt_','Order_Item_Listprice_Gross_Amt_','Quantity_Returned','Return_Flag','Return_Amt','Order_Returnpaid_Gross_Amt','FirstTimeCustomers','BiggerthanAverageOrders','ShippingandBillingAddressarenotthesame','SeveralCardsusedfromtheSameIpAddress','PaymentInformationtypedwithCapitalletters','ManyTransactionsinashorttimeperiod','age_at_joining','PREF_ADDR','credit_risk_score']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [],
   "source": [
    "gnb = GaussianNB()\n",
    "#predicted_variable=X_train.Fraud\n",
    "#X_train=X_train.drop('Fraud',axis=1)\n",
    "y_pred = gnb.fit(subset_data, predicted_variable).predict(subset_data)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.824773413897281\n",
      "(0.824773413897281, 0.824773413897281, 0.824773413897281, None)\n",
      "(array([0.89      , 0.19354839]), array([0.91438356, 0.15384615]), array([0.90202703, 0.17142857]), array([584,  78]))\n",
      "0.418600747853\n"
     ]
    }
   ],
   "source": [
    "print accuracy_score(predicted_variable, y_pred)\n",
    "#print precision_recall_fscore_support(predicted_variable, y_pred, average='macro')\n",
    "print precision_recall_fscore_support(predicted_variable, y_pred, average='micro')\n",
    "print precision_recall_fscore_support(predicted_variable, y_pred, average=None)\n",
    "#print precision_recall_fscore_support(predicted_variable, y_pred, average='weighted')\n",
    "\n",
    "print math.sqrt(mean_squared_error(predicted_variable, y_pred))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy: 0.808 (0.050)\n",
      "neg_log_loss: -0.642 (0.149)\n",
      "AUC: 0.554 (0.146)\n",
      "[[534  50]\n",
      " [ 66  12]]\n",
      "             precision    recall  f1-score   support\n",
      "\n",
      "          0       0.89      0.91      0.90       584\n",
      "          1       0.19      0.15      0.17        78\n",
      "\n",
      "avg / total       0.81      0.82      0.82       662\n",
      "\n"
     ]
    }
   ],
   "source": [
    "kfold = model_selection.KFold(n_splits=10, random_state=48)\n",
    "#model = LogisticRegression()\n",
    "scoring = 'accuracy'\n",
    "results = model_selection.cross_val_score(gnb, subset_data, predicted_variable, cv=kfold, scoring=scoring)\n",
    "print(\"Accuracy: %.3f (%.3f)\") % (results.mean(), results.std())\n",
    "\n",
    "\n",
    "scoring = 'neg_log_loss'\n",
    "results = model_selection.cross_val_score(gnb, subset_data, predicted_variable, cv=kfold, scoring=scoring)\n",
    "print(\"neg_log_loss: %.3f (%.3f)\") % (results.mean(), results.std())\n",
    "\n",
    "scoring = 'roc_auc'\n",
    "results = model_selection.cross_val_score(gnb, subset_data, predicted_variable, cv=kfold, scoring=scoring)\n",
    "print(\"AUC: %.3f (%.3f)\") % (results.mean(), results.std())\n",
    "\n",
    "matrix = confusion_matrix(predicted_variable, y_pred)\n",
    "print(matrix)\n",
    "\n",
    "report = classification_report(predicted_variable, y_pred)\n",
    "print(report)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "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>Business_Week</th>\n",
       "      <th>No_Of_Items</th>\n",
       "      <th>Shipment_Flg</th>\n",
       "      <th>Order_Item_Paidprice_Gross_Amt_</th>\n",
       "      <th>Order_Item_Listprice_Gross_Amt_</th>\n",
       "      <th>Quantity_Returned</th>\n",
       "      <th>Return_Flag</th>\n",
       "      <th>Return_Amt</th>\n",
       "      <th>Order_Returnpaid_Gross_Amt</th>\n",
       "      <th>FirstTimeCustomers</th>\n",
       "      <th>BiggerthanAverageOrders</th>\n",
       "      <th>ShippingandBillingAddressarenotthesame</th>\n",
       "      <th>SeveralCardsusedfromtheSameIpAddress</th>\n",
       "      <th>PaymentInformationtypedwithCapitalletters</th>\n",
       "      <th>ManyTransactionsinashorttimeperiod</th>\n",
       "      <th>ManyTransactionsinashorttimeperiod</th>\n",
       "      <th>age_at_joining</th>\n",
       "      <th>PREF_ADDR</th>\n",
       "      <th>credit_risk_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [Business_Week, No_Of_Items, Shipment_Flg, Order_Item_Paidprice_Gross_Amt_, Order_Item_Listprice_Gross_Amt_, Quantity_Returned, Return_Flag, Return_Amt, Order_Returnpaid_Gross_Amt, FirstTimeCustomers, BiggerthanAverageOrders, ShippingandBillingAddressarenotthesame, SeveralCardsusedfromtheSameIpAddress, PaymentInformationtypedwithCapitalletters, ManyTransactionsinashorttimeperiod, ManyTransactionsinashorttimeperiod, age_at_joining, PREF_ADDR, credit_risk_score]\n",
       "Index: []"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "null_data = subset_data[subset_data.isnull().any(axis=1)]\n",
    "display(null_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f,ax=plt.subplots(figsize=(15, 15))\n",
    "sns.heatmap(data=transaction_data.corr(),annot=True,linewidths=.5,fmt= '.1f',ax=ax)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_test_split"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. Feature Listing\n",
    "2. Feature Engineering\n",
    "3. Select K Best\n",
    "4. Grid Search CV\n",
    "5. Model Building"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.15"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}