Fin_CatBoost.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "d7f8d2e6",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import accuracy_score\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "from sklearn.preprocessing import MinMaxScaler"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "54962771",
   "metadata": {},
   "outputs": [],
   "source": [
    "train = pd.read_csv('Train.csv')\n",
    "test = pd.read_csv('Test.csv')\n",
    "ss = pd.read_csv('SampleSubmission.csv')\n",
    "variables = pd.read_csv('VariableDefinitions.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "2a566be8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "train data shape : (23524, 13)\n",
      "test data shape : (10086, 12)\n"
     ]
    }
   ],
   "source": [
    "print('train data shape :', train.shape)\n",
    "print('test data shape :', test.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "1089ffaa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>country</th>\n",
       "      <th>year</th>\n",
       "      <th>uniqueid</th>\n",
       "      <th>bank_account</th>\n",
       "      <th>location_type</th>\n",
       "      <th>cellphone_access</th>\n",
       "      <th>household_size</th>\n",
       "      <th>age_of_respondent</th>\n",
       "      <th>gender_of_respondent</th>\n",
       "      <th>relationship_with_head</th>\n",
       "      <th>marital_status</th>\n",
       "      <th>education_level</th>\n",
       "      <th>job_type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Kenya</td>\n",
       "      <td>2018</td>\n",
       "      <td>uniqueid_1</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Rural</td>\n",
       "      <td>Yes</td>\n",
       "      <td>3</td>\n",
       "      <td>24</td>\n",
       "      <td>Female</td>\n",
       "      <td>Spouse</td>\n",
       "      <td>Married/Living together</td>\n",
       "      <td>Secondary education</td>\n",
       "      <td>Self employed</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Kenya</td>\n",
       "      <td>2018</td>\n",
       "      <td>uniqueid_2</td>\n",
       "      <td>No</td>\n",
       "      <td>Rural</td>\n",
       "      <td>No</td>\n",
       "      <td>5</td>\n",
       "      <td>70</td>\n",
       "      <td>Female</td>\n",
       "      <td>Head of Household</td>\n",
       "      <td>Widowed</td>\n",
       "      <td>No formal education</td>\n",
       "      <td>Government Dependent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Kenya</td>\n",
       "      <td>2018</td>\n",
       "      <td>uniqueid_3</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Urban</td>\n",
       "      <td>Yes</td>\n",
       "      <td>5</td>\n",
       "      <td>26</td>\n",
       "      <td>Male</td>\n",
       "      <td>Other relative</td>\n",
       "      <td>Single/Never Married</td>\n",
       "      <td>Vocational/Specialised training</td>\n",
       "      <td>Self employed</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Kenya</td>\n",
       "      <td>2018</td>\n",
       "      <td>uniqueid_4</td>\n",
       "      <td>No</td>\n",
       "      <td>Rural</td>\n",
       "      <td>Yes</td>\n",
       "      <td>5</td>\n",
       "      <td>34</td>\n",
       "      <td>Female</td>\n",
       "      <td>Head of Household</td>\n",
       "      <td>Married/Living together</td>\n",
       "      <td>Primary education</td>\n",
       "      <td>Formally employed Private</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Kenya</td>\n",
       "      <td>2018</td>\n",
       "      <td>uniqueid_5</td>\n",
       "      <td>No</td>\n",
       "      <td>Urban</td>\n",
       "      <td>No</td>\n",
       "      <td>8</td>\n",
       "      <td>26</td>\n",
       "      <td>Male</td>\n",
       "      <td>Child</td>\n",
       "      <td>Single/Never Married</td>\n",
       "      <td>Primary education</td>\n",
       "      <td>Informally employed</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  country  year    uniqueid bank_account location_type cellphone_access  \\\n",
       "0   Kenya  2018  uniqueid_1          Yes         Rural              Yes   \n",
       "1   Kenya  2018  uniqueid_2           No         Rural               No   \n",
       "2   Kenya  2018  uniqueid_3          Yes         Urban              Yes   \n",
       "3   Kenya  2018  uniqueid_4           No         Rural              Yes   \n",
       "4   Kenya  2018  uniqueid_5           No         Urban               No   \n",
       "\n",
       "   household_size  age_of_respondent gender_of_respondent  \\\n",
       "0               3                 24               Female   \n",
       "1               5                 70               Female   \n",
       "2               5                 26                 Male   \n",
       "3               5                 34               Female   \n",
       "4               8                 26                 Male   \n",
       "\n",
       "  relationship_with_head           marital_status  \\\n",
       "0                 Spouse  Married/Living together   \n",
       "1      Head of Household                  Widowed   \n",
       "2         Other relative     Single/Never Married   \n",
       "3      Head of Household  Married/Living together   \n",
       "4                  Child     Single/Never Married   \n",
       "\n",
       "                   education_level                   job_type  \n",
       "0              Secondary education              Self employed  \n",
       "1              No formal education       Government Dependent  \n",
       "2  Vocational/Specialised training              Self employed  \n",
       "3                Primary education  Formally employed Private  \n",
       "4                Primary education        Informally employed  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "84756ad6",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>country</th>\n",
       "      <th>year</th>\n",
       "      <th>uniqueid</th>\n",
       "      <th>location_type</th>\n",
       "      <th>cellphone_access</th>\n",
       "      <th>household_size</th>\n",
       "      <th>age_of_respondent</th>\n",
       "      <th>gender_of_respondent</th>\n",
       "      <th>relationship_with_head</th>\n",
       "      <th>marital_status</th>\n",
       "      <th>education_level</th>\n",
       "      <th>job_type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Kenya</td>\n",
       "      <td>2018</td>\n",
       "      <td>uniqueid_6056</td>\n",
       "      <td>Urban</td>\n",
       "      <td>Yes</td>\n",
       "      <td>3</td>\n",
       "      <td>30</td>\n",
       "      <td>Male</td>\n",
       "      <td>Head of Household</td>\n",
       "      <td>Married/Living together</td>\n",
       "      <td>Secondary education</td>\n",
       "      <td>Formally employed Government</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Kenya</td>\n",
       "      <td>2018</td>\n",
       "      <td>uniqueid_6060</td>\n",
       "      <td>Urban</td>\n",
       "      <td>Yes</td>\n",
       "      <td>7</td>\n",
       "      <td>51</td>\n",
       "      <td>Male</td>\n",
       "      <td>Head of Household</td>\n",
       "      <td>Married/Living together</td>\n",
       "      <td>Vocational/Specialised training</td>\n",
       "      <td>Formally employed Private</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Kenya</td>\n",
       "      <td>2018</td>\n",
       "      <td>uniqueid_6065</td>\n",
       "      <td>Rural</td>\n",
       "      <td>No</td>\n",
       "      <td>3</td>\n",
       "      <td>77</td>\n",
       "      <td>Female</td>\n",
       "      <td>Parent</td>\n",
       "      <td>Married/Living together</td>\n",
       "      <td>No formal education</td>\n",
       "      <td>Remittance Dependent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Kenya</td>\n",
       "      <td>2018</td>\n",
       "      <td>uniqueid_6072</td>\n",
       "      <td>Rural</td>\n",
       "      <td>No</td>\n",
       "      <td>6</td>\n",
       "      <td>39</td>\n",
       "      <td>Female</td>\n",
       "      <td>Head of Household</td>\n",
       "      <td>Married/Living together</td>\n",
       "      <td>Primary education</td>\n",
       "      <td>Remittance Dependent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Kenya</td>\n",
       "      <td>2018</td>\n",
       "      <td>uniqueid_6073</td>\n",
       "      <td>Urban</td>\n",
       "      <td>No</td>\n",
       "      <td>3</td>\n",
       "      <td>16</td>\n",
       "      <td>Male</td>\n",
       "      <td>Child</td>\n",
       "      <td>Single/Never Married</td>\n",
       "      <td>Secondary education</td>\n",
       "      <td>Remittance Dependent</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  country  year       uniqueid location_type cellphone_access  household_size  \\\n",
       "0   Kenya  2018  uniqueid_6056         Urban              Yes               3   \n",
       "1   Kenya  2018  uniqueid_6060         Urban              Yes               7   \n",
       "2   Kenya  2018  uniqueid_6065         Rural               No               3   \n",
       "3   Kenya  2018  uniqueid_6072         Rural               No               6   \n",
       "4   Kenya  2018  uniqueid_6073         Urban               No               3   \n",
       "\n",
       "   age_of_respondent gender_of_respondent relationship_with_head  \\\n",
       "0                 30                 Male      Head of Household   \n",
       "1                 51                 Male      Head of Household   \n",
       "2                 77               Female                 Parent   \n",
       "3                 39               Female      Head of Household   \n",
       "4                 16                 Male                  Child   \n",
       "\n",
       "            marital_status                  education_level  \\\n",
       "0  Married/Living together              Secondary education   \n",
       "1  Married/Living together  Vocational/Specialised training   \n",
       "2  Married/Living together              No formal education   \n",
       "3  Married/Living together                Primary education   \n",
       "4     Single/Never Married              Secondary education   \n",
       "\n",
       "                       job_type  \n",
       "0  Formally employed Government  \n",
       "1     Formally employed Private  \n",
       "2          Remittance Dependent  \n",
       "3          Remittance Dependent  \n",
       "4          Remittance Dependent  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "2c1913e4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0        1\n",
      "1        0\n",
      "2        1\n",
      "3        0\n",
      "4        0\n",
      "        ..\n",
      "23519    0\n",
      "23520    0\n",
      "23521    0\n",
      "23522    0\n",
      "23523    0\n",
      "Name: bank_account, Length: 23524, dtype: int32\n"
     ]
    }
   ],
   "source": [
    "# Convert target label to numerical Data\n",
    "le = LabelEncoder()\n",
    "train['bank_account'] = le.fit_transform(train['bank_account'])\n",
    "\n",
    "#Separate training features from target\n",
    "X_train = train.drop(['bank_account'], axis=1)\n",
    "y_train = train['bank_account']\n",
    "\n",
    "print(y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "eecf29c2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
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       "\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>year</th>\n",
       "      <th>location_type</th>\n",
       "      <th>cellphone_access</th>\n",
       "      <th>age_of_respondent</th>\n",
       "      <th>gender_of_respondent</th>\n",
       "      <th>marital_status_Divorced/Seperated</th>\n",
       "      <th>marital_status_Dont know</th>\n",
       "      <th>marital_status_Married/Living together</th>\n",
       "      <th>marital_status_Single/Never Married</th>\n",
       "      <th>marital_status_Widowed</th>\n",
       "      <th>...</th>\n",
       "      <th>job_type_Government Dependent</th>\n",
       "      <th>job_type_Informally employed</th>\n",
       "      <th>job_type_No Income</th>\n",
       "      <th>job_type_Other Income</th>\n",
       "      <th>job_type_Remittance Dependent</th>\n",
       "      <th>job_type_Self employed</th>\n",
       "      <th>country_Kenya</th>\n",
       "      <th>country_Rwanda</th>\n",
       "      <th>country_Tanzania</th>\n",
       "      <th>country_Uganda</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>24</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2018</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>70</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2018</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>26</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2018</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>34</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2018</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>26</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   year  location_type  cellphone_access  age_of_respondent  \\\n",
       "0  2018              0                 1                 24   \n",
       "1  2018              0                 0                 70   \n",
       "2  2018              1                 1                 26   \n",
       "3  2018              0                 1                 34   \n",
       "4  2018              1                 0                 26   \n",
       "\n",
       "   gender_of_respondent  marital_status_Divorced/Seperated  \\\n",
       "0                     0                                  0   \n",
       "1                     0                                  0   \n",
       "2                     1                                  0   \n",
       "3                     0                                  0   \n",
       "4                     1                                  0   \n",
       "\n",
       "   marital_status_Dont know  marital_status_Married/Living together  \\\n",
       "0                         0                                       1   \n",
       "1                         0                                       0   \n",
       "2                         0                                       0   \n",
       "3                         0                                       1   \n",
       "4                         0                                       0   \n",
       "\n",
       "   marital_status_Single/Never Married  marital_status_Widowed  ...  \\\n",
       "0                                    0                       0  ...   \n",
       "1                                    0                       1  ...   \n",
       "2                                    1                       0  ...   \n",
       "3                                    0                       0  ...   \n",
       "4                                    1                       0  ...   \n",
       "\n",
       "   job_type_Government Dependent  job_type_Informally employed  \\\n",
       "0                              0                             0   \n",
       "1                              1                             0   \n",
       "2                              0                             0   \n",
       "3                              0                             0   \n",
       "4                              0                             1   \n",
       "\n",
       "   job_type_No Income  job_type_Other Income  job_type_Remittance Dependent  \\\n",
       "0                   0                      0                              0   \n",
       "1                   0                      0                              0   \n",
       "2                   0                      0                              0   \n",
       "3                   0                      0                              0   \n",
       "4                   0                      0                              0   \n",
       "\n",
       "   job_type_Self employed  country_Kenya  country_Rwanda  country_Tanzania  \\\n",
       "0                       1              1               0                 0   \n",
       "1                       0              1               0                 0   \n",
       "2                       1              1               0                 0   \n",
       "3                       0              1               0                 0   \n",
       "4                       0              1               0                 0   \n",
       "\n",
       "   country_Uganda  \n",
       "0               0  \n",
       "1               0  \n",
       "2               0  \n",
       "3               0  \n",
       "4               0  \n",
       "\n",
       "[5 rows x 30 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    " # Convert the following numerical labels from interger to float\n",
    "float_array = X_train[[\"age_of_respondent\", \"year\"]].values.astype(float)\n",
    "    \n",
    "# categorical features to be onverted to One Hot Encoding\n",
    "categ = [\"marital_status\",\n",
    "             \"education_level\",\n",
    "             \"job_type\",\n",
    "             \"country\"]\n",
    "    \n",
    "# One Hot Encoding conversion\n",
    "X_train = pd.get_dummies(X_train, prefix_sep=\"_\", columns=categ)\n",
    "    \n",
    "# Label Encoder conversion\n",
    "X_train[\"location_type\"] = le.fit_transform(X_train[\"location_type\"])\n",
    "X_train[\"cellphone_access\"] = le.fit_transform(X_train[\"cellphone_access\"])\n",
    "X_train[\"gender_of_respondent\"] = le.fit_transform(X_train[\"gender_of_respondent\"])\n",
    "    \n",
    "# drop uniquid column\n",
    "X_train = X_train.drop([\"uniqueid\", \"household_size\", \"relationship_with_head\"], axis=1)\n",
    "    \n",
    "X_train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "6c688e31",
   "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>year</th>\n",
       "      <th>location_type</th>\n",
       "      <th>cellphone_access</th>\n",
       "      <th>age_of_respondent</th>\n",
       "      <th>gender_of_respondent</th>\n",
       "      <th>marital_status_Divorced/Seperated</th>\n",
       "      <th>marital_status_Dont know</th>\n",
       "      <th>marital_status_Married/Living together</th>\n",
       "      <th>marital_status_Single/Never Married</th>\n",
       "      <th>marital_status_Widowed</th>\n",
       "      <th>...</th>\n",
       "      <th>job_type_Government Dependent</th>\n",
       "      <th>job_type_Informally employed</th>\n",
       "      <th>job_type_No Income</th>\n",
       "      <th>job_type_Other Income</th>\n",
       "      <th>job_type_Remittance Dependent</th>\n",
       "      <th>job_type_Self employed</th>\n",
       "      <th>country_Kenya</th>\n",
       "      <th>country_Rwanda</th>\n",
       "      <th>country_Tanzania</th>\n",
       "      <th>country_Uganda</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>year</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.214621</td>\n",
       "      <td>-0.066505</td>\n",
       "      <td>-0.019330</td>\n",
       "      <td>0.000317</td>\n",
       "      <td>0.017146</td>\n",
       "      <td>0.022291</td>\n",
       "      <td>-0.005174</td>\n",
       "      <td>0.022470</td>\n",
       "      <td>-0.041787</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.006426</td>\n",
       "      <td>-0.156028</td>\n",
       "      <td>0.081631</td>\n",
       "      <td>0.101870</td>\n",
       "      <td>0.095070</td>\n",
       "      <td>0.180932</td>\n",
       "      <td>0.712544</td>\n",
       "      <td>-0.885158</td>\n",
       "      <td>0.017770</td>\n",
       "      <td>0.378473</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>location_type</th>\n",
       "      <td>0.214621</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.085238</td>\n",
       "      <td>-0.047373</td>\n",
       "      <td>0.012924</td>\n",
       "      <td>0.023893</td>\n",
       "      <td>0.008875</td>\n",
       "      <td>-0.236190</td>\n",
       "      <td>0.268959</td>\n",
       "      <td>-0.052119</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.002052</td>\n",
       "      <td>-0.071098</td>\n",
       "      <td>0.045064</td>\n",
       "      <td>0.011032</td>\n",
       "      <td>0.054247</td>\n",
       "      <td>0.296278</td>\n",
       "      <td>0.031225</td>\n",
       "      <td>-0.389062</td>\n",
       "      <td>0.431626</td>\n",
       "      <td>-0.069356</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cellphone_access</th>\n",
       "      <td>-0.066505</td>\n",
       "      <td>-0.085238</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.103611</td>\n",
       "      <td>0.102370</td>\n",
       "      <td>-0.028880</td>\n",
       "      <td>0.005608</td>\n",
       "      <td>0.158290</td>\n",
       "      <td>-0.065682</td>\n",
       "      <td>-0.124270</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.058395</td>\n",
       "      <td>-0.008392</td>\n",
       "      <td>-0.103875</td>\n",
       "      <td>-0.006649</td>\n",
       "      <td>-0.083128</td>\n",
       "      <td>-0.056012</td>\n",
       "      <td>0.062789</td>\n",
       "      <td>0.154415</td>\n",
       "      <td>-0.206499</td>\n",
       "      <td>-0.032318</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>age_of_respondent</th>\n",
       "      <td>-0.019330</td>\n",
       "      <td>-0.047373</td>\n",
       "      <td>-0.103611</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.012745</td>\n",
       "      <td>-0.120030</td>\n",
       "      <td>0.005242</td>\n",
       "      <td>0.053767</td>\n",
       "      <td>-0.296633</td>\n",
       "      <td>0.462524</td>\n",
       "      <td>...</td>\n",
       "      <td>0.171390</td>\n",
       "      <td>-0.089447</td>\n",
       "      <td>-0.061105</td>\n",
       "      <td>-0.014614</td>\n",
       "      <td>-0.057238</td>\n",
       "      <td>0.000097</td>\n",
       "      <td>0.028948</td>\n",
       "      <td>0.022690</td>\n",
       "      <td>-0.012334</td>\n",
       "      <td>-0.063400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gender_of_respondent</th>\n",
       "      <td>0.000317</td>\n",
       "      <td>0.012924</td>\n",
       "      <td>0.102370</td>\n",
       "      <td>0.012745</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.004768</td>\n",
       "      <td>0.017434</td>\n",
       "      <td>0.056201</td>\n",
       "      <td>0.086199</td>\n",
       "      <td>-0.220843</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.023990</td>\n",
       "      <td>0.052309</td>\n",
       "      <td>-0.073582</td>\n",
       "      <td>-0.011521</td>\n",
       "      <td>-0.120942</td>\n",
       "      <td>0.037074</td>\n",
       "      <td>0.019273</td>\n",
       "      <td>-0.009150</td>\n",
       "      <td>0.019064</td>\n",
       "      <td>-0.044125</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>marital_status_Divorced/Seperated</th>\n",
       "      <td>0.017146</td>\n",
       "      <td>0.023893</td>\n",
       "      <td>-0.028880</td>\n",
       "      <td>-0.120030</td>\n",
       "      <td>0.004768</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.005738</td>\n",
       "      <td>-0.285380</td>\n",
       "      <td>-0.222979</td>\n",
       "      <td>-0.112214</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.015876</td>\n",
       "      <td>0.035217</td>\n",
       "      <td>0.092733</td>\n",
       "      <td>-0.013111</td>\n",
       "      <td>-0.008232</td>\n",
       "      <td>0.014432</td>\n",
       "      <td>-0.062172</td>\n",
       "      <td>-0.092080</td>\n",
       "      <td>0.165557</td>\n",
       "      <td>-0.009676</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>marital_status_Dont know</th>\n",
       "      <td>0.022291</td>\n",
       "      <td>0.008875</td>\n",
       "      <td>0.005608</td>\n",
       "      <td>0.005242</td>\n",
       "      <td>0.017434</td>\n",
       "      <td>-0.005738</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.016919</td>\n",
       "      <td>-0.013219</td>\n",
       "      <td>-0.006653</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.001900</td>\n",
       "      <td>0.005937</td>\n",
       "      <td>-0.003052</td>\n",
       "      <td>-0.004046</td>\n",
       "      <td>0.001047</td>\n",
       "      <td>-0.000978</td>\n",
       "      <td>0.031283</td>\n",
       "      <td>-0.014175</td>\n",
       "      <td>-0.011542</td>\n",
       "      <td>-0.005776</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>marital_status_Married/Living together</th>\n",
       "      <td>-0.005174</td>\n",
       "      <td>-0.236190</td>\n",
       "      <td>0.158290</td>\n",
       "      <td>0.053767</td>\n",
       "      <td>0.056201</td>\n",
       "      <td>-0.285380</td>\n",
       "      <td>-0.016919</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.657426</td>\n",
       "      <td>-0.330849</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.056816</td>\n",
       "      <td>0.034374</td>\n",
       "      <td>-0.076028</td>\n",
       "      <td>0.033234</td>\n",
       "      <td>-0.123928</td>\n",
       "      <td>-0.137685</td>\n",
       "      <td>0.146348</td>\n",
       "      <td>0.212768</td>\n",
       "      <td>-0.447459</td>\n",
       "      <td>0.120579</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>marital_status_Single/Never Married</th>\n",
       "      <td>0.022470</td>\n",
       "      <td>0.268959</td>\n",
       "      <td>-0.065682</td>\n",
       "      <td>-0.296633</td>\n",
       "      <td>0.086199</td>\n",
       "      <td>-0.222979</td>\n",
       "      <td>-0.013219</td>\n",
       "      <td>-0.657426</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.258505</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.020981</td>\n",
       "      <td>-0.029386</td>\n",
       "      <td>0.026880</td>\n",
       "      <td>-0.032389</td>\n",
       "      <td>0.106828</td>\n",
       "      <td>0.177932</td>\n",
       "      <td>-0.113112</td>\n",
       "      <td>-0.203893</td>\n",
       "      <td>0.395795</td>\n",
       "      <td>-0.105139</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>marital_status_Widowed</th>\n",
       "      <td>-0.041787</td>\n",
       "      <td>-0.052119</td>\n",
       "      <td>-0.124270</td>\n",
       "      <td>0.462524</td>\n",
       "      <td>-0.220843</td>\n",
       "      <td>-0.112214</td>\n",
       "      <td>-0.006653</td>\n",
       "      <td>-0.330849</td>\n",
       "      <td>-0.258505</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.134023</td>\n",
       "      <td>-0.041697</td>\n",
       "      <td>-0.003455</td>\n",
       "      <td>0.008066</td>\n",
       "      <td>0.042197</td>\n",
       "      <td>-0.061843</td>\n",
       "      <td>-0.007162</td>\n",
       "      <td>0.053055</td>\n",
       "      <td>-0.035267</td>\n",
       "      <td>-0.023285</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>education_level_No formal education</th>\n",
       "      <td>-0.095970</td>\n",
       "      <td>-0.090530</td>\n",
       "      <td>-0.204751</td>\n",
       "      <td>0.360651</td>\n",
       "      <td>-0.114902</td>\n",
       "      <td>-0.031375</td>\n",
       "      <td>-0.003135</td>\n",
       "      <td>-0.008467</td>\n",
       "      <td>-0.159623</td>\n",
       "      <td>0.278089</td>\n",
       "      <td>...</td>\n",
       "      <td>0.088524</td>\n",
       "      <td>0.014135</td>\n",
       "      <td>-0.002909</td>\n",
       "      <td>-0.012010</td>\n",
       "      <td>0.003133</td>\n",
       "      <td>-0.057010</td>\n",
       "      <td>-0.055177</td>\n",
       "      <td>0.099524</td>\n",
       "      <td>-0.033026</td>\n",
       "      <td>-0.031887</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>education_level_Other/Dont know/RTA</th>\n",
       "      <td>-0.004110</td>\n",
       "      <td>0.005291</td>\n",
       "      <td>-0.007483</td>\n",
       "      <td>0.025557</td>\n",
       "      <td>-0.003034</td>\n",
       "      <td>-0.004233</td>\n",
       "      <td>-0.000712</td>\n",
       "      <td>0.011086</td>\n",
       "      <td>-0.013690</td>\n",
       "      <td>0.006811</td>\n",
       "      <td>...</td>\n",
       "      <td>0.006844</td>\n",
       "      <td>0.019873</td>\n",
       "      <td>0.014154</td>\n",
       "      <td>0.007341</td>\n",
       "      <td>-0.006268</td>\n",
       "      <td>-0.008849</td>\n",
       "      <td>-0.002592</td>\n",
       "      <td>0.011422</td>\n",
       "      <td>-0.016799</td>\n",
       "      <td>0.011114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>education_level_Primary education</th>\n",
       "      <td>-0.080300</td>\n",
       "      <td>-0.017513</td>\n",
       "      <td>-0.009652</td>\n",
       "      <td>-0.071953</td>\n",
       "      <td>0.019350</td>\n",
       "      <td>-0.019500</td>\n",
       "      <td>0.007638</td>\n",
       "      <td>0.038260</td>\n",
       "      <td>0.028174</td>\n",
       "      <td>-0.084623</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.035422</td>\n",
       "      <td>0.072892</td>\n",
       "      <td>-0.014798</td>\n",
       "      <td>-0.029052</td>\n",
       "      <td>-0.114946</td>\n",
       "      <td>0.106425</td>\n",
       "      <td>-0.136442</td>\n",
       "      <td>0.015264</td>\n",
       "      <td>0.118510</td>\n",
       "      <td>-0.003412</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>education_level_Secondary education</th>\n",
       "      <td>0.118902</td>\n",
       "      <td>0.043332</td>\n",
       "      <td>0.120163</td>\n",
       "      <td>-0.210338</td>\n",
       "      <td>0.057692</td>\n",
       "      <td>-0.002609</td>\n",
       "      <td>-0.002620</td>\n",
       "      <td>0.005193</td>\n",
       "      <td>0.077408</td>\n",
       "      <td>-0.120473</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.038404</td>\n",
       "      <td>-0.055866</td>\n",
       "      <td>0.019559</td>\n",
       "      <td>0.048224</td>\n",
       "      <td>0.124968</td>\n",
       "      <td>-0.066475</td>\n",
       "      <td>0.176127</td>\n",
       "      <td>-0.017674</td>\n",
       "      <td>-0.186068</td>\n",
       "      <td>0.053143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>education_level_Tertiary education</th>\n",
       "      <td>0.040560</td>\n",
       "      <td>0.084803</td>\n",
       "      <td>0.099981</td>\n",
       "      <td>-0.091143</td>\n",
       "      <td>0.041775</td>\n",
       "      <td>0.100412</td>\n",
       "      <td>-0.004195</td>\n",
       "      <td>-0.092213</td>\n",
       "      <td>0.079033</td>\n",
       "      <td>-0.062324</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.008000</td>\n",
       "      <td>-0.045833</td>\n",
       "      <td>0.019724</td>\n",
       "      <td>-0.005747</td>\n",
       "      <td>0.031559</td>\n",
       "      <td>-0.005113</td>\n",
       "      <td>-0.002897</td>\n",
       "      <td>-0.102780</td>\n",
       "      <td>0.144431</td>\n",
       "      <td>-0.049169</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>education_level_Vocational/Specialised training</th>\n",
       "      <td>0.129668</td>\n",
       "      <td>0.050682</td>\n",
       "      <td>0.099093</td>\n",
       "      <td>-0.037137</td>\n",
       "      <td>0.025083</td>\n",
       "      <td>0.008365</td>\n",
       "      <td>-0.003467</td>\n",
       "      <td>0.009907</td>\n",
       "      <td>0.014090</td>\n",
       "      <td>-0.043600</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.005585</td>\n",
       "      <td>-0.062158</td>\n",
       "      <td>-0.020935</td>\n",
       "      <td>0.009099</td>\n",
       "      <td>0.008120</td>\n",
       "      <td>-0.019813</td>\n",
       "      <td>0.125680</td>\n",
       "      <td>-0.100385</td>\n",
       "      <td>-0.028621</td>\n",
       "      <td>0.022395</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>job_type_Dont Know/Refuse to answer</th>\n",
       "      <td>0.011706</td>\n",
       "      <td>-0.022894</td>\n",
       "      <td>0.002013</td>\n",
       "      <td>-0.002836</td>\n",
       "      <td>-0.006716</td>\n",
       "      <td>-0.010511</td>\n",
       "      <td>-0.001354</td>\n",
       "      <td>0.020374</td>\n",
       "      <td>-0.019384</td>\n",
       "      <td>0.006378</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.007559</td>\n",
       "      <td>-0.041003</td>\n",
       "      <td>-0.012143</td>\n",
       "      <td>-0.016097</td>\n",
       "      <td>-0.025458</td>\n",
       "      <td>-0.045041</td>\n",
       "      <td>-0.039272</td>\n",
       "      <td>0.011106</td>\n",
       "      <td>-0.045923</td>\n",
       "      <td>0.113842</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>job_type_Farming and Fishing</th>\n",
       "      <td>-0.248909</td>\n",
       "      <td>-0.347103</td>\n",
       "      <td>0.111969</td>\n",
       "      <td>0.154106</td>\n",
       "      <td>-0.001908</td>\n",
       "      <td>-0.081449</td>\n",
       "      <td>-0.004650</td>\n",
       "      <td>0.214283</td>\n",
       "      <td>-0.229832</td>\n",
       "      <td>0.079174</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.056505</td>\n",
       "      <td>-0.306498</td>\n",
       "      <td>-0.090771</td>\n",
       "      <td>-0.120328</td>\n",
       "      <td>-0.190295</td>\n",
       "      <td>-0.336677</td>\n",
       "      <td>0.047353</td>\n",
       "      <td>0.378012</td>\n",
       "      <td>-0.343272</td>\n",
       "      <td>-0.171782</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>job_type_Formally employed Government</th>\n",
       "      <td>0.056126</td>\n",
       "      <td>0.047243</td>\n",
       "      <td>0.071687</td>\n",
       "      <td>-0.005859</td>\n",
       "      <td>0.029416</td>\n",
       "      <td>-0.021387</td>\n",
       "      <td>-0.002385</td>\n",
       "      <td>0.069210</td>\n",
       "      <td>-0.037641</td>\n",
       "      <td>-0.033035</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.013323</td>\n",
       "      <td>-0.072265</td>\n",
       "      <td>-0.021402</td>\n",
       "      <td>-0.028370</td>\n",
       "      <td>-0.044867</td>\n",
       "      <td>-0.079380</td>\n",
       "      <td>0.122348</td>\n",
       "      <td>-0.011552</td>\n",
       "      <td>-0.080935</td>\n",
       "      <td>-0.040502</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>job_type_Formally employed Private</th>\n",
       "      <td>0.094141</td>\n",
       "      <td>0.067894</td>\n",
       "      <td>0.105723</td>\n",
       "      <td>-0.061983</td>\n",
       "      <td>0.062368</td>\n",
       "      <td>0.040473</td>\n",
       "      <td>0.007143</td>\n",
       "      <td>-0.021469</td>\n",
       "      <td>0.037730</td>\n",
       "      <td>-0.058850</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.022321</td>\n",
       "      <td>-0.121076</td>\n",
       "      <td>-0.035857</td>\n",
       "      <td>-0.047533</td>\n",
       "      <td>-0.075172</td>\n",
       "      <td>-0.132997</td>\n",
       "      <td>0.067538</td>\n",
       "      <td>-0.098090</td>\n",
       "      <td>0.033391</td>\n",
       "      <td>0.009920</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>job_type_Government Dependent</th>\n",
       "      <td>-0.006426</td>\n",
       "      <td>-0.002052</td>\n",
       "      <td>-0.058395</td>\n",
       "      <td>0.171390</td>\n",
       "      <td>-0.023990</td>\n",
       "      <td>-0.015876</td>\n",
       "      <td>-0.001900</td>\n",
       "      <td>-0.056816</td>\n",
       "      <td>-0.020981</td>\n",
       "      <td>0.134023</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.057558</td>\n",
       "      <td>-0.017046</td>\n",
       "      <td>-0.022597</td>\n",
       "      <td>-0.035736</td>\n",
       "      <td>-0.063226</td>\n",
       "      <td>0.001226</td>\n",
       "      <td>-0.000619</td>\n",
       "      <td>0.013439</td>\n",
       "      <td>-0.022023</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>job_type_Informally employed</th>\n",
       "      <td>-0.156028</td>\n",
       "      <td>-0.071098</td>\n",
       "      <td>-0.008392</td>\n",
       "      <td>-0.089447</td>\n",
       "      <td>0.052309</td>\n",
       "      <td>0.035217</td>\n",
       "      <td>0.005937</td>\n",
       "      <td>0.034374</td>\n",
       "      <td>-0.029386</td>\n",
       "      <td>-0.041697</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.057558</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.092463</td>\n",
       "      <td>-0.122570</td>\n",
       "      <td>-0.193842</td>\n",
       "      <td>-0.342951</td>\n",
       "      <td>-0.005646</td>\n",
       "      <td>0.165238</td>\n",
       "      <td>-0.061068</td>\n",
       "      <td>-0.174983</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>job_type_No Income</th>\n",
       "      <td>0.081631</td>\n",
       "      <td>0.045064</td>\n",
       "      <td>-0.103875</td>\n",
       "      <td>-0.061105</td>\n",
       "      <td>-0.073582</td>\n",
       "      <td>0.092733</td>\n",
       "      <td>-0.003052</td>\n",
       "      <td>-0.076028</td>\n",
       "      <td>0.026880</td>\n",
       "      <td>-0.003455</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.017046</td>\n",
       "      <td>-0.092463</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.036300</td>\n",
       "      <td>-0.057407</td>\n",
       "      <td>-0.101567</td>\n",
       "      <td>-0.097565</td>\n",
       "      <td>-0.127176</td>\n",
       "      <td>0.119465</td>\n",
       "      <td>0.176754</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>job_type_Other Income</th>\n",
       "      <td>0.101870</td>\n",
       "      <td>0.011032</td>\n",
       "      <td>-0.006649</td>\n",
       "      <td>-0.014614</td>\n",
       "      <td>-0.011521</td>\n",
       "      <td>-0.013111</td>\n",
       "      <td>-0.004046</td>\n",
       "      <td>0.033234</td>\n",
       "      <td>-0.032389</td>\n",
       "      <td>0.008066</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.022597</td>\n",
       "      <td>-0.122570</td>\n",
       "      <td>-0.036300</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.076100</td>\n",
       "      <td>-0.134639</td>\n",
       "      <td>-0.057839</td>\n",
       "      <td>-0.032802</td>\n",
       "      <td>-0.121468</td>\n",
       "      <td>0.335828</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>job_type_Remittance Dependent</th>\n",
       "      <td>0.095070</td>\n",
       "      <td>0.054247</td>\n",
       "      <td>-0.083128</td>\n",
       "      <td>-0.057238</td>\n",
       "      <td>-0.120942</td>\n",
       "      <td>-0.008232</td>\n",
       "      <td>0.001047</td>\n",
       "      <td>-0.123928</td>\n",
       "      <td>0.106828</td>\n",
       "      <td>0.042197</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.035736</td>\n",
       "      <td>-0.193842</td>\n",
       "      <td>-0.057407</td>\n",
       "      <td>-0.076100</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.212928</td>\n",
       "      <td>0.168241</td>\n",
       "      <td>-0.078517</td>\n",
       "      <td>-0.010421</td>\n",
       "      <td>-0.108642</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>job_type_Self employed</th>\n",
       "      <td>0.180932</td>\n",
       "      <td>0.296278</td>\n",
       "      <td>-0.056012</td>\n",
       "      <td>0.000097</td>\n",
       "      <td>0.037074</td>\n",
       "      <td>0.014432</td>\n",
       "      <td>-0.000978</td>\n",
       "      <td>-0.137685</td>\n",
       "      <td>0.177932</td>\n",
       "      <td>-0.061843</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.063226</td>\n",
       "      <td>-0.342951</td>\n",
       "      <td>-0.101567</td>\n",
       "      <td>-0.134639</td>\n",
       "      <td>-0.212928</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.153959</td>\n",
       "      <td>-0.352309</td>\n",
       "      <td>0.416131</td>\n",
       "      <td>0.176895</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country_Kenya</th>\n",
       "      <td>0.712544</td>\n",
       "      <td>0.031225</td>\n",
       "      <td>0.062789</td>\n",
       "      <td>0.028948</td>\n",
       "      <td>0.019273</td>\n",
       "      <td>-0.062172</td>\n",
       "      <td>0.031283</td>\n",
       "      <td>0.146348</td>\n",
       "      <td>-0.113112</td>\n",
       "      <td>-0.007162</td>\n",
       "      <td>...</td>\n",
       "      <td>0.001226</td>\n",
       "      <td>-0.005646</td>\n",
       "      <td>-0.097565</td>\n",
       "      <td>-0.057839</td>\n",
       "      <td>0.168241</td>\n",
       "      <td>-0.153959</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.453119</td>\n",
       "      <td>-0.368965</td>\n",
       "      <td>-0.184639</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country_Rwanda</th>\n",
       "      <td>-0.885158</td>\n",
       "      <td>-0.389062</td>\n",
       "      <td>0.154415</td>\n",
       "      <td>0.022690</td>\n",
       "      <td>-0.009150</td>\n",
       "      <td>-0.092080</td>\n",
       "      <td>-0.014175</td>\n",
       "      <td>0.212768</td>\n",
       "      <td>-0.203893</td>\n",
       "      <td>0.053055</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.000619</td>\n",
       "      <td>0.165238</td>\n",
       "      <td>-0.127176</td>\n",
       "      <td>-0.032802</td>\n",
       "      <td>-0.078517</td>\n",
       "      <td>-0.352309</td>\n",
       "      <td>-0.453119</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.480946</td>\n",
       "      <td>-0.240677</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country_Tanzania</th>\n",
       "      <td>0.017770</td>\n",
       "      <td>0.431626</td>\n",
       "      <td>-0.206499</td>\n",
       "      <td>-0.012334</td>\n",
       "      <td>0.019064</td>\n",
       "      <td>0.165557</td>\n",
       "      <td>-0.011542</td>\n",
       "      <td>-0.447459</td>\n",
       "      <td>0.395795</td>\n",
       "      <td>-0.035267</td>\n",
       "      <td>...</td>\n",
       "      <td>0.013439</td>\n",
       "      <td>-0.061068</td>\n",
       "      <td>0.119465</td>\n",
       "      <td>-0.121468</td>\n",
       "      <td>-0.010421</td>\n",
       "      <td>0.416131</td>\n",
       "      <td>-0.368965</td>\n",
       "      <td>-0.480946</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.195978</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country_Uganda</th>\n",
       "      <td>0.378473</td>\n",
       "      <td>-0.069356</td>\n",
       "      <td>-0.032318</td>\n",
       "      <td>-0.063400</td>\n",
       "      <td>-0.044125</td>\n",
       "      <td>-0.009676</td>\n",
       "      <td>-0.005776</td>\n",
       "      <td>0.120579</td>\n",
       "      <td>-0.105139</td>\n",
       "      <td>-0.023285</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.022023</td>\n",
       "      <td>-0.174983</td>\n",
       "      <td>0.176754</td>\n",
       "      <td>0.335828</td>\n",
       "      <td>-0.108642</td>\n",
       "      <td>0.176895</td>\n",
       "      <td>-0.184639</td>\n",
       "      <td>-0.240677</td>\n",
       "      <td>-0.195978</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>30 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                     year  location_type  \\\n",
       "year                                             1.000000       0.214621   \n",
       "location_type                                    0.214621       1.000000   \n",
       "cellphone_access                                -0.066505      -0.085238   \n",
       "age_of_respondent                               -0.019330      -0.047373   \n",
       "gender_of_respondent                             0.000317       0.012924   \n",
       "marital_status_Divorced/Seperated                0.017146       0.023893   \n",
       "marital_status_Dont know                         0.022291       0.008875   \n",
       "marital_status_Married/Living together          -0.005174      -0.236190   \n",
       "marital_status_Single/Never Married              0.022470       0.268959   \n",
       "marital_status_Widowed                          -0.041787      -0.052119   \n",
       "education_level_No formal education             -0.095970      -0.090530   \n",
       "education_level_Other/Dont know/RTA             -0.004110       0.005291   \n",
       "education_level_Primary education               -0.080300      -0.017513   \n",
       "education_level_Secondary education              0.118902       0.043332   \n",
       "education_level_Tertiary education               0.040560       0.084803   \n",
       "education_level_Vocational/Specialised training  0.129668       0.050682   \n",
       "job_type_Dont Know/Refuse to answer              0.011706      -0.022894   \n",
       "job_type_Farming and Fishing                    -0.248909      -0.347103   \n",
       "job_type_Formally employed Government            0.056126       0.047243   \n",
       "job_type_Formally employed Private               0.094141       0.067894   \n",
       "job_type_Government Dependent                   -0.006426      -0.002052   \n",
       "job_type_Informally employed                    -0.156028      -0.071098   \n",
       "job_type_No Income                               0.081631       0.045064   \n",
       "job_type_Other Income                            0.101870       0.011032   \n",
       "job_type_Remittance Dependent                    0.095070       0.054247   \n",
       "job_type_Self employed                           0.180932       0.296278   \n",
       "country_Kenya                                    0.712544       0.031225   \n",
       "country_Rwanda                                  -0.885158      -0.389062   \n",
       "country_Tanzania                                 0.017770       0.431626   \n",
       "country_Uganda                                   0.378473      -0.069356   \n",
       "\n",
       "                                                 cellphone_access  \\\n",
       "year                                                    -0.066505   \n",
       "location_type                                           -0.085238   \n",
       "cellphone_access                                         1.000000   \n",
       "age_of_respondent                                       -0.103611   \n",
       "gender_of_respondent                                     0.102370   \n",
       "marital_status_Divorced/Seperated                       -0.028880   \n",
       "marital_status_Dont know                                 0.005608   \n",
       "marital_status_Married/Living together                   0.158290   \n",
       "marital_status_Single/Never Married                     -0.065682   \n",
       "marital_status_Widowed                                  -0.124270   \n",
       "education_level_No formal education                     -0.204751   \n",
       "education_level_Other/Dont know/RTA                     -0.007483   \n",
       "education_level_Primary education                       -0.009652   \n",
       "education_level_Secondary education                      0.120163   \n",
       "education_level_Tertiary education                       0.099981   \n",
       "education_level_Vocational/Specialised training          0.099093   \n",
       "job_type_Dont Know/Refuse to answer                      0.002013   \n",
       "job_type_Farming and Fishing                             0.111969   \n",
       "job_type_Formally employed Government                    0.071687   \n",
       "job_type_Formally employed Private                       0.105723   \n",
       "job_type_Government Dependent                           -0.058395   \n",
       "job_type_Informally employed                            -0.008392   \n",
       "job_type_No Income                                      -0.103875   \n",
       "job_type_Other Income                                   -0.006649   \n",
       "job_type_Remittance Dependent                           -0.083128   \n",
       "job_type_Self employed                                  -0.056012   \n",
       "country_Kenya                                            0.062789   \n",
       "country_Rwanda                                           0.154415   \n",
       "country_Tanzania                                        -0.206499   \n",
       "country_Uganda                                          -0.032318   \n",
       "\n",
       "                                                 age_of_respondent  \\\n",
       "year                                                     -0.019330   \n",
       "location_type                                            -0.047373   \n",
       "cellphone_access                                         -0.103611   \n",
       "age_of_respondent                                         1.000000   \n",
       "gender_of_respondent                                      0.012745   \n",
       "marital_status_Divorced/Seperated                        -0.120030   \n",
       "marital_status_Dont know                                  0.005242   \n",
       "marital_status_Married/Living together                    0.053767   \n",
       "marital_status_Single/Never Married                      -0.296633   \n",
       "marital_status_Widowed                                    0.462524   \n",
       "education_level_No formal education                       0.360651   \n",
       "education_level_Other/Dont know/RTA                       0.025557   \n",
       "education_level_Primary education                        -0.071953   \n",
       "education_level_Secondary education                      -0.210338   \n",
       "education_level_Tertiary education                       -0.091143   \n",
       "education_level_Vocational/Specialised training          -0.037137   \n",
       "job_type_Dont Know/Refuse to answer                      -0.002836   \n",
       "job_type_Farming and Fishing                              0.154106   \n",
       "job_type_Formally employed Government                    -0.005859   \n",
       "job_type_Formally employed Private                       -0.061983   \n",
       "job_type_Government Dependent                             0.171390   \n",
       "job_type_Informally employed                             -0.089447   \n",
       "job_type_No Income                                       -0.061105   \n",
       "job_type_Other Income                                    -0.014614   \n",
       "job_type_Remittance Dependent                            -0.057238   \n",
       "job_type_Self employed                                    0.000097   \n",
       "country_Kenya                                             0.028948   \n",
       "country_Rwanda                                            0.022690   \n",
       "country_Tanzania                                         -0.012334   \n",
       "country_Uganda                                           -0.063400   \n",
       "\n",
       "                                                 gender_of_respondent  \\\n",
       "year                                                         0.000317   \n",
       "location_type                                                0.012924   \n",
       "cellphone_access                                             0.102370   \n",
       "age_of_respondent                                            0.012745   \n",
       "gender_of_respondent                                         1.000000   \n",
       "marital_status_Divorced/Seperated                            0.004768   \n",
       "marital_status_Dont know                                     0.017434   \n",
       "marital_status_Married/Living together                       0.056201   \n",
       "marital_status_Single/Never Married                          0.086199   \n",
       "marital_status_Widowed                                      -0.220843   \n",
       "education_level_No formal education                         -0.114902   \n",
       "education_level_Other/Dont know/RTA                         -0.003034   \n",
       "education_level_Primary education                            0.019350   \n",
       "education_level_Secondary education                          0.057692   \n",
       "education_level_Tertiary education                           0.041775   \n",
       "education_level_Vocational/Specialised training              0.025083   \n",
       "job_type_Dont Know/Refuse to answer                         -0.006716   \n",
       "job_type_Farming and Fishing                                -0.001908   \n",
       "job_type_Formally employed Government                        0.029416   \n",
       "job_type_Formally employed Private                           0.062368   \n",
       "job_type_Government Dependent                               -0.023990   \n",
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       "job_type_No Income                                          -0.073582   \n",
       "job_type_Other Income                                       -0.011521   \n",
       "job_type_Remittance Dependent                               -0.120942   \n",
       "job_type_Self employed                                       0.037074   \n",
       "country_Kenya                                                0.019273   \n",
       "country_Rwanda                                              -0.009150   \n",
       "country_Tanzania                                             0.019064   \n",
       "country_Uganda                                              -0.044125   \n",
       "\n",
       "                                                 marital_status_Divorced/Seperated  \\\n",
       "year                                                                      0.017146   \n",
       "location_type                                                             0.023893   \n",
       "cellphone_access                                                         -0.028880   \n",
       "age_of_respondent                                                        -0.120030   \n",
       "gender_of_respondent                                                      0.004768   \n",
       "marital_status_Divorced/Seperated                                         1.000000   \n",
       "marital_status_Dont know                                                 -0.005738   \n",
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       "marital_status_Widowed                                                   -0.112214   \n",
       "education_level_No formal education                                      -0.031375   \n",
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       "education_level_Primary education                                        -0.019500   \n",
       "education_level_Secondary education                                      -0.002609   \n",
       "education_level_Tertiary education                                        0.100412   \n",
       "education_level_Vocational/Specialised training                           0.008365   \n",
       "job_type_Dont Know/Refuse to answer                                      -0.010511   \n",
       "job_type_Farming and Fishing                                             -0.081449   \n",
       "job_type_Formally employed Government                                    -0.021387   \n",
       "job_type_Formally employed Private                                        0.040473   \n",
       "job_type_Government Dependent                                            -0.015876   \n",
       "job_type_Informally employed                                              0.035217   \n",
       "job_type_No Income                                                        0.092733   \n",
       "job_type_Other Income                                                    -0.013111   \n",
       "job_type_Remittance Dependent                                            -0.008232   \n",
       "job_type_Self employed                                                    0.014432   \n",
       "country_Kenya                                                            -0.062172   \n",
       "country_Rwanda                                                           -0.092080   \n",
       "country_Tanzania                                                          0.165557   \n",
       "country_Uganda                                                           -0.009676   \n",
       "\n",
       "                                                 marital_status_Dont know  \\\n",
       "year                                                             0.022291   \n",
       "location_type                                                    0.008875   \n",
       "cellphone_access                                                 0.005608   \n",
       "age_of_respondent                                                0.005242   \n",
       "gender_of_respondent                                             0.017434   \n",
       "marital_status_Divorced/Seperated                               -0.005738   \n",
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       "job_type_Farming and Fishing                                    -0.004650   \n",
       "job_type_Formally employed Government                           -0.002385   \n",
       "job_type_Formally employed Private                               0.007143   \n",
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       "job_type_Self employed                                          -0.000978   \n",
       "country_Kenya                                                    0.031283   \n",
       "country_Rwanda                                                  -0.014175   \n",
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       "country_Uganda                                                  -0.005776   \n",
       "\n",
       "                                                 marital_status_Married/Living together  \\\n",
       "year                                                                          -0.005174   \n",
       "location_type                                                                 -0.236190   \n",
       "cellphone_access                                                               0.158290   \n",
       "age_of_respondent                                                              0.053767   \n",
       "gender_of_respondent                                                           0.056201   \n",
       "marital_status_Divorced/Seperated                                             -0.285380   \n",
       "marital_status_Dont know                                                      -0.016919   \n",
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       "job_type_Formally employed Government                                          0.069210   \n",
       "job_type_Formally employed Private                                            -0.021469   \n",
       "job_type_Government Dependent                                                 -0.056816   \n",
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       "job_type_No Income                                                            -0.076028   \n",
       "job_type_Other Income                                                          0.033234   \n",
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       "job_type_Self employed                                                        -0.137685   \n",
       "country_Kenya                                                                  0.146348   \n",
       "country_Rwanda                                                                 0.212768   \n",
       "country_Tanzania                                                              -0.447459   \n",
       "country_Uganda                                                                 0.120579   \n",
       "\n",
       "                                                 marital_status_Single/Never Married  \\\n",
       "year                                                                        0.022470   \n",
       "location_type                                                               0.268959   \n",
       "cellphone_access                                                           -0.065682   \n",
       "age_of_respondent                                                          -0.296633   \n",
       "gender_of_respondent                                                        0.086199   \n",
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       "marital_status_Dont know                                                   -0.013219   \n",
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       "job_type_Self employed                                                      0.177932   \n",
       "country_Kenya                                                              -0.113112   \n",
       "country_Rwanda                                                             -0.203893   \n",
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       "country_Uganda                                                             -0.105139   \n",
       "\n",
       "                                                 marital_status_Widowed  ...  \\\n",
       "year                                                          -0.041787  ...   \n",
       "location_type                                                 -0.052119  ...   \n",
       "cellphone_access                                              -0.124270  ...   \n",
       "age_of_respondent                                              0.462524  ...   \n",
       "gender_of_respondent                                          -0.220843  ...   \n",
       "marital_status_Divorced/Seperated                             -0.112214  ...   \n",
       "marital_status_Dont know                                      -0.006653  ...   \n",
       "marital_status_Married/Living together                        -0.330849  ...   \n",
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       "job_type_Formally employed Private                            -0.058850  ...   \n",
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       "job_type_No Income                                            -0.003455  ...   \n",
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       "job_type_Self employed                                        -0.061843  ...   \n",
       "country_Kenya                                                 -0.007162  ...   \n",
       "country_Rwanda                                                 0.053055  ...   \n",
       "country_Tanzania                                              -0.035267  ...   \n",
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       "\n",
       "                                                 job_type_Government Dependent  \\\n",
       "year                                                                 -0.006426   \n",
       "location_type                                                        -0.002052   \n",
       "cellphone_access                                                     -0.058395   \n",
       "age_of_respondent                                                     0.171390   \n",
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       "job_type_Formally employed Private                                   -0.022321   \n",
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       "country_Kenya                                                         0.001226   \n",
       "country_Rwanda                                                       -0.000619   \n",
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       "\n",
       "                                                 job_type_Informally employed  \\\n",
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       "cellphone_access                                                    -0.008392   \n",
       "age_of_respondent                                                   -0.089447   \n",
       "gender_of_respondent                                                 0.052309   \n",
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       "country_Tanzania                                                    -0.061068   \n",
       "country_Uganda                                                      -0.174983   \n",
       "\n",
       "                                                 job_type_No Income  \\\n",
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       "\n",
       "                                                 job_type_Other Income  \\\n",
       "year                                                          0.101870   \n",
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       "country_Tanzania                                             -0.121468   \n",
       "country_Uganda                                                0.335828   \n",
       "\n",
       "                                                 job_type_Remittance Dependent  \\\n",
       "year                                                                  0.095070   \n",
       "location_type                                                         0.054247   \n",
       "cellphone_access                                                     -0.083128   \n",
       "age_of_respondent                                                    -0.057238   \n",
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       "job_type_No Income                                                   -0.057407   \n",
       "job_type_Other Income                                                -0.076100   \n",
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       "job_type_Self employed                                               -0.212928   \n",
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       "country_Rwanda                                                       -0.078517   \n",
       "country_Tanzania                                                     -0.010421   \n",
       "country_Uganda                                                       -0.108642   \n",
       "\n",
       "                                                 job_type_Self employed  \\\n",
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       "job_type_Farming and Fishing                                  -0.336677   \n",
       "job_type_Formally employed Government                         -0.079380   \n",
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       "job_type_Self employed                                         1.000000   \n",
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       "country_Uganda                                                 0.176895   \n",
       "\n",
       "                                                 country_Kenya  \\\n",
       "year                                                  0.712544   \n",
       "location_type                                         0.031225   \n",
       "cellphone_access                                      0.062789   \n",
       "age_of_respondent                                     0.028948   \n",
       "gender_of_respondent                                  0.019273   \n",
       "marital_status_Divorced/Seperated                    -0.062172   \n",
       "marital_status_Dont know                              0.031283   \n",
       "marital_status_Married/Living together                0.146348   \n",
       "marital_status_Single/Never Married                  -0.113112   \n",
       "marital_status_Widowed                               -0.007162   \n",
       "education_level_No formal education                  -0.055177   \n",
       "education_level_Other/Dont know/RTA                  -0.002592   \n",
       "education_level_Primary education                    -0.136442   \n",
       "education_level_Secondary education                   0.176127   \n",
       "education_level_Tertiary education                   -0.002897   \n",
       "education_level_Vocational/Specialised training       0.125680   \n",
       "job_type_Dont Know/Refuse to answer                  -0.039272   \n",
       "job_type_Farming and Fishing                          0.047353   \n",
       "job_type_Formally employed Government                 0.122348   \n",
       "job_type_Formally employed Private                    0.067538   \n",
       "job_type_Government Dependent                         0.001226   \n",
       "job_type_Informally employed                         -0.005646   \n",
       "job_type_No Income                                   -0.097565   \n",
       "job_type_Other Income                                -0.057839   \n",
       "job_type_Remittance Dependent                         0.168241   \n",
       "job_type_Self employed                               -0.153959   \n",
       "country_Kenya                                         1.000000   \n",
       "country_Rwanda                                       -0.453119   \n",
       "country_Tanzania                                     -0.368965   \n",
       "country_Uganda                                       -0.184639   \n",
       "\n",
       "                                                 country_Rwanda  \\\n",
       "year                                                  -0.885158   \n",
       "location_type                                         -0.389062   \n",
       "cellphone_access                                       0.154415   \n",
       "age_of_respondent                                      0.022690   \n",
       "gender_of_respondent                                  -0.009150   \n",
       "marital_status_Divorced/Seperated                     -0.092080   \n",
       "marital_status_Dont know                              -0.014175   \n",
       "marital_status_Married/Living together                 0.212768   \n",
       "marital_status_Single/Never Married                   -0.203893   \n",
       "marital_status_Widowed                                 0.053055   \n",
       "education_level_No formal education                    0.099524   \n",
       "education_level_Other/Dont know/RTA                    0.011422   \n",
       "education_level_Primary education                      0.015264   \n",
       "education_level_Secondary education                   -0.017674   \n",
       "education_level_Tertiary education                    -0.102780   \n",
       "education_level_Vocational/Specialised training       -0.100385   \n",
       "job_type_Dont Know/Refuse to answer                    0.011106   \n",
       "job_type_Farming and Fishing                           0.378012   \n",
       "job_type_Formally employed Government                 -0.011552   \n",
       "job_type_Formally employed Private                    -0.098090   \n",
       "job_type_Government Dependent                         -0.000619   \n",
       "job_type_Informally employed                           0.165238   \n",
       "job_type_No Income                                    -0.127176   \n",
       "job_type_Other Income                                 -0.032802   \n",
       "job_type_Remittance Dependent                         -0.078517   \n",
       "job_type_Self employed                                -0.352309   \n",
       "country_Kenya                                         -0.453119   \n",
       "country_Rwanda                                         1.000000   \n",
       "country_Tanzania                                      -0.480946   \n",
       "country_Uganda                                        -0.240677   \n",
       "\n",
       "                                                 country_Tanzania  \\\n",
       "year                                                     0.017770   \n",
       "location_type                                            0.431626   \n",
       "cellphone_access                                        -0.206499   \n",
       "age_of_respondent                                       -0.012334   \n",
       "gender_of_respondent                                     0.019064   \n",
       "marital_status_Divorced/Seperated                        0.165557   \n",
       "marital_status_Dont know                                -0.011542   \n",
       "marital_status_Married/Living together                  -0.447459   \n",
       "marital_status_Single/Never Married                      0.395795   \n",
       "marital_status_Widowed                                  -0.035267   \n",
       "education_level_No formal education                     -0.033026   \n",
       "education_level_Other/Dont know/RTA                     -0.016799   \n",
       "education_level_Primary education                        0.118510   \n",
       "education_level_Secondary education                     -0.186068   \n",
       "education_level_Tertiary education                       0.144431   \n",
       "education_level_Vocational/Specialised training         -0.028621   \n",
       "job_type_Dont Know/Refuse to answer                     -0.045923   \n",
       "job_type_Farming and Fishing                            -0.343272   \n",
       "job_type_Formally employed Government                   -0.080935   \n",
       "job_type_Formally employed Private                       0.033391   \n",
       "job_type_Government Dependent                            0.013439   \n",
       "job_type_Informally employed                            -0.061068   \n",
       "job_type_No Income                                       0.119465   \n",
       "job_type_Other Income                                   -0.121468   \n",
       "job_type_Remittance Dependent                           -0.010421   \n",
       "job_type_Self employed                                   0.416131   \n",
       "country_Kenya                                           -0.368965   \n",
       "country_Rwanda                                          -0.480946   \n",
       "country_Tanzania                                         1.000000   \n",
       "country_Uganda                                          -0.195978   \n",
       "\n",
       "                                                 country_Uganda  \n",
       "year                                                   0.378473  \n",
       "location_type                                         -0.069356  \n",
       "cellphone_access                                      -0.032318  \n",
       "age_of_respondent                                     -0.063400  \n",
       "gender_of_respondent                                  -0.044125  \n",
       "marital_status_Divorced/Seperated                     -0.009676  \n",
       "marital_status_Dont know                              -0.005776  \n",
       "marital_status_Married/Living together                 0.120579  \n",
       "marital_status_Single/Never Married                   -0.105139  \n",
       "marital_status_Widowed                                -0.023285  \n",
       "education_level_No formal education                   -0.031887  \n",
       "education_level_Other/Dont know/RTA                    0.011114  \n",
       "education_level_Primary education                     -0.003412  \n",
       "education_level_Secondary education                    0.053143  \n",
       "education_level_Tertiary education                    -0.049169  \n",
       "education_level_Vocational/Specialised training        0.022395  \n",
       "job_type_Dont Know/Refuse to answer                    0.113842  \n",
       "job_type_Farming and Fishing                          -0.171782  \n",
       "job_type_Formally employed Government                 -0.040502  \n",
       "job_type_Formally employed Private                     0.009920  \n",
       "job_type_Government Dependent                         -0.022023  \n",
       "job_type_Informally employed                          -0.174983  \n",
       "job_type_No Income                                     0.176754  \n",
       "job_type_Other Income                                  0.335828  \n",
       "job_type_Remittance Dependent                         -0.108642  \n",
       "job_type_Self employed                                 0.176895  \n",
       "country_Kenya                                         -0.184639  \n",
       "country_Rwanda                                        -0.240677  \n",
       "country_Tanzania                                      -0.195978  \n",
       "country_Uganda                                         1.000000  \n",
       "\n",
       "[30 rows x 30 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "6216c9a5",
   "metadata": {},
   "outputs": [],
   "source": [
    "# scale our data into range of 0 and 1\n",
    "scaler = MinMaxScaler(feature_range=(0, 1))\n",
    "X_train = scaler.fit_transform(X_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "60e79642",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1., 0., 1., ..., 0., 0., 0.],\n",
       "       [1., 0., 0., ..., 0., 0., 0.],\n",
       "       [1., 1., 1., ..., 0., 0., 0.],\n",
       "       ...,\n",
       "       [1., 0., 1., ..., 0., 0., 1.],\n",
       "       [1., 1., 1., ..., 0., 0., 1.],\n",
       "       [1., 0., 1., ..., 0., 0., 1.]])"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "5649f0e6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(23524, 30)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "a74ef500",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0        1\n",
       "1        0\n",
       "2        1\n",
       "3        0\n",
       "4        0\n",
       "        ..\n",
       "23519    0\n",
       "23520    0\n",
       "23521    0\n",
       "23522    0\n",
       "23523    0\n",
       "Name: bank_account, Length: 23524, dtype: int32"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_train"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "0fae04be",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(23524,)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_train.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "b336af1d",
   "metadata": {},
   "outputs": [],
   "source": [
    "import sklearn.model_selection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "22a4841d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Split train_data\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "X_Train, X_Val, y_Train, y_val = train_test_split(X_train, y_train, stratify = y_train, \n",
    "                                                  test_size = 0.3, random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "3cf58e0c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "fd91cc5ede164892bb9f4bdfd442daee",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "MetricVisualizer(layout=Layout(align_self='stretch', height='500px'))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Learning rate set to 0.069131\n",
      "0:\ttest: 0.7889223\tbest: 0.7889223 (0)\ttotal: 200ms\tremaining: 3m 20s\n",
      "999:\ttest: 0.9240820\tbest: 0.9240825 (998)\ttotal: 12.6s\tremaining: 0us\n",
      "\n",
      "bestTest = 0.9240825063\n",
      "bestIteration = 998\n",
      "\n",
      "Shrink model to first 999 iterations.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<catboost.core.CatBoostClassifier at 0x20d9ac5a6a0>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from catboost import CatBoostClassifier\n",
    "#creating CatBoost classifier\n",
    "cbr = CatBoostClassifier(loss_function = 'Logloss', eval_metric ='AUC', verbose = 1000, random_seed = 1000)\n",
    "\n",
    "# Train the classifier\n",
    "cbr.fit(X_train,y_train, eval_set = (X_Val, y_val), use_best_model = True, plot =True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "d4809854",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 1, 0, ..., 0, 0, 0], dtype=int64)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_pred = cbr.predict(X_Val)\n",
    "y_pred"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "aea27d71",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.92      0.98      0.95      6064\n",
      "           1       0.84      0.51      0.63       994\n",
      "\n",
      "    accuracy                           0.92      7058\n",
      "   macro avg       0.88      0.75      0.79      7058\n",
      "weighted avg       0.91      0.92      0.91      7058\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import classification_report\n",
    "print(classification_report(y_val, y_pred))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "2574c7fa",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<sklearn.metrics._plot.confusion_matrix.ConfusionMatrixDisplay at 0x20d9ac5a190>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.metrics import plot_confusion_matrix\n",
    "\n",
    "# Get confusion matrix for Gradient Boosting Classifier\n",
    "plot_confusion_matrix(cbr,X_Val, y_val,normalize='true')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "e04dbfa5",
   "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>country</th>\n",
       "      <th>year</th>\n",
       "      <th>uniqueid</th>\n",
       "      <th>location_type</th>\n",
       "      <th>cellphone_access</th>\n",
       "      <th>household_size</th>\n",
       "      <th>age_of_respondent</th>\n",
       "      <th>gender_of_respondent</th>\n",
       "      <th>relationship_with_head</th>\n",
       "      <th>marital_status</th>\n",
       "      <th>education_level</th>\n",
       "      <th>job_type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Kenya</td>\n",
       "      <td>2018</td>\n",
       "      <td>uniqueid_6056</td>\n",
       "      <td>Urban</td>\n",
       "      <td>Yes</td>\n",
       "      <td>3</td>\n",
       "      <td>30</td>\n",
       "      <td>Male</td>\n",
       "      <td>Head of Household</td>\n",
       "      <td>Married/Living together</td>\n",
       "      <td>Secondary education</td>\n",
       "      <td>Formally employed Government</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Kenya</td>\n",
       "      <td>2018</td>\n",
       "      <td>uniqueid_6060</td>\n",
       "      <td>Urban</td>\n",
       "      <td>Yes</td>\n",
       "      <td>7</td>\n",
       "      <td>51</td>\n",
       "      <td>Male</td>\n",
       "      <td>Head of Household</td>\n",
       "      <td>Married/Living together</td>\n",
       "      <td>Vocational/Specialised training</td>\n",
       "      <td>Formally employed Private</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Kenya</td>\n",
       "      <td>2018</td>\n",
       "      <td>uniqueid_6065</td>\n",
       "      <td>Rural</td>\n",
       "      <td>No</td>\n",
       "      <td>3</td>\n",
       "      <td>77</td>\n",
       "      <td>Female</td>\n",
       "      <td>Parent</td>\n",
       "      <td>Married/Living together</td>\n",
       "      <td>No formal education</td>\n",
       "      <td>Remittance Dependent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Kenya</td>\n",
       "      <td>2018</td>\n",
       "      <td>uniqueid_6072</td>\n",
       "      <td>Rural</td>\n",
       "      <td>No</td>\n",
       "      <td>6</td>\n",
       "      <td>39</td>\n",
       "      <td>Female</td>\n",
       "      <td>Head of Household</td>\n",
       "      <td>Married/Living together</td>\n",
       "      <td>Primary education</td>\n",
       "      <td>Remittance Dependent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Kenya</td>\n",
       "      <td>2018</td>\n",
       "      <td>uniqueid_6073</td>\n",
       "      <td>Urban</td>\n",
       "      <td>No</td>\n",
       "      <td>3</td>\n",
       "      <td>16</td>\n",
       "      <td>Male</td>\n",
       "      <td>Child</td>\n",
       "      <td>Single/Never Married</td>\n",
       "      <td>Secondary education</td>\n",
       "      <td>Remittance Dependent</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  country  year       uniqueid location_type cellphone_access  household_size  \\\n",
       "0   Kenya  2018  uniqueid_6056         Urban              Yes               3   \n",
       "1   Kenya  2018  uniqueid_6060         Urban              Yes               7   \n",
       "2   Kenya  2018  uniqueid_6065         Rural               No               3   \n",
       "3   Kenya  2018  uniqueid_6072         Rural               No               6   \n",
       "4   Kenya  2018  uniqueid_6073         Urban               No               3   \n",
       "\n",
       "   age_of_respondent gender_of_respondent relationship_with_head  \\\n",
       "0                 30                 Male      Head of Household   \n",
       "1                 51                 Male      Head of Household   \n",
       "2                 77               Female                 Parent   \n",
       "3                 39               Female      Head of Household   \n",
       "4                 16                 Male                  Child   \n",
       "\n",
       "            marital_status                  education_level  \\\n",
       "0  Married/Living together              Secondary education   \n",
       "1  Married/Living together  Vocational/Specialised training   \n",
       "2  Married/Living together              No formal education   \n",
       "3  Married/Living together                Primary education   \n",
       "4     Single/Never Married              Secondary education   \n",
       "\n",
       "                       job_type  \n",
       "0  Formally employed Government  \n",
       "1     Formally employed Private  \n",
       "2          Remittance Dependent  \n",
       "3          Remittance Dependent  \n",
       "4          Remittance Dependent  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "7d67fadb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>location_type</th>\n",
       "      <th>cellphone_access</th>\n",
       "      <th>age_of_respondent</th>\n",
       "      <th>gender_of_respondent</th>\n",
       "      <th>marital_status_Divorced/Seperated</th>\n",
       "      <th>marital_status_Dont know</th>\n",
       "      <th>marital_status_Married/Living together</th>\n",
       "      <th>marital_status_Single/Never Married</th>\n",
       "      <th>marital_status_Widowed</th>\n",
       "      <th>...</th>\n",
       "      <th>job_type_Government Dependent</th>\n",
       "      <th>job_type_Informally employed</th>\n",
       "      <th>job_type_No Income</th>\n",
       "      <th>job_type_Other Income</th>\n",
       "      <th>job_type_Remittance Dependent</th>\n",
       "      <th>job_type_Self employed</th>\n",
       "      <th>country_Kenya</th>\n",
       "      <th>country_Rwanda</th>\n",
       "      <th>country_Tanzania</th>\n",
       "      <th>country_Uganda</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>30</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2018</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>51</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2018</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>77</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>1</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2018</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>39</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2018</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>16</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   year  location_type  cellphone_access  age_of_respondent  \\\n",
       "0  2018              1                 1                 30   \n",
       "1  2018              1                 1                 51   \n",
       "2  2018              0                 0                 77   \n",
       "3  2018              0                 0                 39   \n",
       "4  2018              1                 0                 16   \n",
       "\n",
       "   gender_of_respondent  marital_status_Divorced/Seperated  \\\n",
       "0                     1                                  0   \n",
       "1                     1                                  0   \n",
       "2                     0                                  0   \n",
       "3                     0                                  0   \n",
       "4                     1                                  0   \n",
       "\n",
       "   marital_status_Dont know  marital_status_Married/Living together  \\\n",
       "0                         0                                       1   \n",
       "1                         0                                       1   \n",
       "2                         0                                       1   \n",
       "3                         0                                       1   \n",
       "4                         0                                       0   \n",
       "\n",
       "   marital_status_Single/Never Married  marital_status_Widowed  ...  \\\n",
       "0                                    0                       0  ...   \n",
       "1                                    0                       0  ...   \n",
       "2                                    0                       0  ...   \n",
       "3                                    0                       0  ...   \n",
       "4                                    1                       0  ...   \n",
       "\n",
       "   job_type_Government Dependent  job_type_Informally employed  \\\n",
       "0                              0                             0   \n",
       "1                              0                             0   \n",
       "2                              0                             0   \n",
       "3                              0                             0   \n",
       "4                              0                             0   \n",
       "\n",
       "   job_type_No Income  job_type_Other Income  job_type_Remittance Dependent  \\\n",
       "0                   0                      0                              0   \n",
       "1                   0                      0                              0   \n",
       "2                   0                      0                              1   \n",
       "3                   0                      0                              1   \n",
       "4                   0                      0                              1   \n",
       "\n",
       "   job_type_Self employed  country_Kenya  country_Rwanda  country_Tanzania  \\\n",
       "0                       0              1               0                 0   \n",
       "1                       0              1               0                 0   \n",
       "2                       0              1               0                 0   \n",
       "3                       0              1               0                 0   \n",
       "4                       0              1               0                 0   \n",
       "\n",
       "   country_Uganda  \n",
       "0               0  \n",
       "1               0  \n",
       "2               0  \n",
       "3               0  \n",
       "4               0  \n",
       "\n",
       "[5 rows x 30 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    " # Convert the following numerical labels from interger to float\n",
    "float_array = test[[\"age_of_respondent\", \"year\"]].values.astype(float)\n",
    "    \n",
    "# categorical features to be onverted to One Hot Encoding\n",
    "categ = [\"marital_status\",\n",
    "             \"education_level\",\n",
    "             \"job_type\",\n",
    "             \"country\"]\n",
    "    \n",
    "# One Hot Encoding conversion\n",
    "test = pd.get_dummies(test, prefix_sep=\"_\", columns=categ)\n",
    "    \n",
    "# Label Encoder conversion\n",
    "test[\"location_type\"] = le.fit_transform(test[\"location_type\"])\n",
    "test[\"cellphone_access\"] = le.fit_transform(test[\"cellphone_access\"])\n",
    "test[\"gender_of_respondent\"] = le.fit_transform(test[\"gender_of_respondent\"])\n",
    "    \n",
    "# drop uniquid column\n",
    "test = test.drop([\"uniqueid\", \"household_size\",\"relationship_with_head\"], axis=1)\n",
    "    \n",
    "test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "6aecfe7a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# scale our data into range of 0 and 1\n",
    "scaler = MinMaxScaler(feature_range=(0, 1))\n",
    "test = scaler.fit_transform(test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "10244f56",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get the predicted result for the test Data\n",
    "predictions = cbr.predict(test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "c5cb4555",
   "metadata": {},
   "outputs": [],
   "source": [
    "test2 = pd.read_csv('test.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "01a8e36e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create submission DataFrame\n",
    "submission = pd.DataFrame({\"uniqueid\": test2[\"uniqueid\"] + \" x \" + test2[\"country\"],\n",
    "                           \"bank_account\": predictions})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "4c521d98",
   "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>uniqueid</th>\n",
       "      <th>bank_account</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>uniqueid_6056 x Kenya</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>uniqueid_6060 x Kenya</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>uniqueid_6065 x Kenya</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>uniqueid_6072 x Kenya</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>uniqueid_6073 x Kenya</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                uniqueid  bank_account\n",
       "0  uniqueid_6056 x Kenya             1\n",
       "1  uniqueid_6060 x Kenya             1\n",
       "2  uniqueid_6065 x Kenya             0\n",
       "3  uniqueid_6072 x Kenya             0\n",
       "4  uniqueid_6073 x Kenya             0"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "submission.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "548c0b30",
   "metadata": {},
   "outputs": [],
   "source": [
    "submission.to_csv('seventh_submission.csv', index = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "f331ce13",
   "metadata": {},
   "outputs": [],
   "source": [
    "# # Example of calculating Euclidean distance\n",
    "# from math import sqrt\n",
    "\n",
    "# # calculate the Euclidean distance between two vectors\n",
    "# def euclidean_distance(row1, row2):\n",
    "# \tdistance = 0.0\n",
    "# \tfor i in range(len(row1)-1):\n",
    "# \t\tdistance += (row1[i] - row2[i])**2\n",
    "# \treturn sqrt(distance)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "0314d08c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# # Test distance function\n",
    "# dataset = train\n",
    "# row0 = dataset[5]\n",
    "# for row in dataset:\n",
    "# \tdistance = euclidean_distance(row0, row)\n",
    "# \tprint(distance)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "293e1fe7",
   "metadata": {},
   "outputs": [],
   "source": [
    "# # Locate the most similar neighbors\n",
    "# def get_neighbors(train, test_row, num_neighbors):\n",
    "# \tdistances = list()\n",
    "# \tfor train_row in train:\n",
    "# \t\tdist = euclidean_distance(test_row, train_row)\n",
    "# \t\tdistances.append((train_row, dist))\n",
    "# \tdistances.sort(key=lambda tup: tup[1])\n",
    "# \tneighbors = list()\n",
    "# \tfor i in range(num_neighbors):\n",
    "# \t\tneighbors.append(distances[i][0])\n",
    "# \treturn neighbors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "67fc01e9",
   "metadata": {},
   "outputs": [],
   "source": [
    "# # Example of getting neighbors for an instance\n",
    "# from math import sqrt\n",
    "\n",
    "# # calculate the Euclidean distance between two vectors\n",
    "# def euclidean_distance(row1, row2):\n",
    "# \tdistance = 0.0\n",
    "# \tfor i in range(len(row1)-1):\n",
    "# \t\tdistance += (row1[i] - row2[i])**2\n",
    "# \treturn sqrt(distance)\n",
    "\n",
    "# # Locate the most similar neighbors\n",
    "# def get_neighbors(train, test_row, num_neighbors):\n",
    "# \tdistances = list()\n",
    "    \n",
    "# \tfor train_row in train:\n",
    "# \t\tdist = euclidean_distance(test_row, train_row)\n",
    "# \t\tdistances.append((train_row, dist))\n",
    "    \n",
    "# \tdistances.sort(key=lambda tup: tup[1])\n",
    "# \tneighbors = list()\n",
    "# \tfor i in range(num_neighbors):\n",
    "# \t\tneighbors.append(distances[i][0])\n",
    "# \treturn neighbors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "acc1616a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# # Test distance function\n",
    "# dataset = train\n",
    "# neighbors = get_neighbors(dataset, dataset[0], 3)\n",
    "# # print(\"These are my distance: \" distances)\n",
    "# for neighbor in neighbors:\n",
    "# \tprint(\"These are my neighbors: {}\".format(neighbors))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "b1589b57",
   "metadata": {},
   "outputs": [],
   "source": [
    "# # Make a classification prediction with neighbors\n",
    "# def predict_classification(train, test_row, num_neighbors):\n",
    "# \tneighbors = get_neighbors(train, test_row, num_neighbors)\n",
    "# \toutput_values = [row[-1] for row in neighbors]\n",
    "# \tprediction = max(set(output_values), key=output_values.count)\n",
    "# \treturn prediction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "d86b5421",
   "metadata": {},
   "outputs": [],
   "source": [
    "# # Test distance function\n",
    "# dataset = train\n",
    "# prediction = predict_classification(dataset, dataset[0], 3)\n",
    "# print('Expected %d, Got %d.' % (dataset[0][-1], prediction))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "33f69108",
   "metadata": {},
   "outputs": [],
   "source": [
    "# train"
   ]
  }
 ],
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