Term_deposit_I.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import csv\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "\n",
    "plt.style.use('fivethirtyeight')\n",
    "%config InlineBackend.figure_format = 'retina'\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import scipy.stats as stats\n",
    "import probscale"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Reading csv file and converting into DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open('C:\\\\data set.csv', 'r') as f:\n",
    "    reader = csv.reader(f)\n",
    "    data = list(reader)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[['age;\"job\";\"marital\";\"education\";\"default\";\"housing\";\"loan\";\"contact\";\"month\";\"day_of_week\";\"duration\";\"campaign\";\"pdays\";\"previous\";\"poutcome\";\"emp.var.rate\";\"cons.price.idx\";\"cons.conf.idx\";\"euribor3m\";\"nr.employed\";\"y\"'],\n",
       " ['56;\"housemaid\";\"married\";\"basic.4y\";\"no\";\"no\";\"no\";\"telephone\";\"may\";\"mon\";261;1;999;0;\"nonexistent\";1.1;93.994;-36.4;4.857;5191;\"no\"'],\n",
       " ['57;\"services\";\"married\";\"high.school\";\"unknown\";\"no\";\"no\";\"telephone\";\"may\";\"mon\";149;1;999;0;\"nonexistent\";1.1;93.994;-36.4;4.857;5191;\"no\"'],\n",
       " ['37;\"services\";\"married\";\"high.school\";\"no\";\"yes\";\"no\";\"telephone\";\"may\";\"mon\";226;1;999;0;\"nonexistent\";1.1;93.994;-36.4;4.857;5191;\"no\"'],\n",
       " ['40;\"admin.\";\"married\";\"basic.6y\";\"no\";\"no\";\"no\";\"telephone\";\"may\";\"mon\";151;1;999;0;\"nonexistent\";1.1;93.994;-36.4;4.857;5191;\"no\"']]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Each row is a list containing a single string\n",
    "data[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Transform the list of lists into a single list of strings to facilitate data wrangling\n",
    "data2 = [row[0] for row in data]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['age;\"job\";\"marital\";\"education\";\"default\";\"housing\";\"loan\";\"contact\";\"month\";\"day_of_week\";\"duration\";\"campaign\";\"pdays\";\"previous\";\"poutcome\";\"emp.var.rate\";\"cons.price.idx\";\"cons.conf.idx\";\"euribor3m\";\"nr.employed\";\"y\"',\n",
       " '56;\"housemaid\";\"married\";\"basic.4y\";\"no\";\"no\";\"no\";\"telephone\";\"may\";\"mon\";261;1;999;0;\"nonexistent\";1.1;93.994;-36.4;4.857;5191;\"no\"',\n",
       " '57;\"services\";\"married\";\"high.school\";\"unknown\";\"no\";\"no\";\"telephone\";\"may\";\"mon\";149;1;999;0;\"nonexistent\";1.1;93.994;-36.4;4.857;5191;\"no\"',\n",
       " '37;\"services\";\"married\";\"high.school\";\"no\";\"yes\";\"no\";\"telephone\";\"may\";\"mon\";226;1;999;0;\"nonexistent\";1.1;93.994;-36.4;4.857;5191;\"no\"',\n",
       " '40;\"admin.\";\"married\";\"basic.6y\";\"no\";\"no\";\"no\";\"telephone\";\"may\";\"mon\";151;1;999;0;\"nonexistent\";1.1;93.994;-36.4;4.857;5191;\"no\"']"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data2[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[['age',\n",
       "  '\"job\"',\n",
       "  '\"marital\"',\n",
       "  '\"education\"',\n",
       "  '\"default\"',\n",
       "  '\"housing\"',\n",
       "  '\"loan\"',\n",
       "  '\"contact\"',\n",
       "  '\"month\"',\n",
       "  '\"day_of_week\"',\n",
       "  '\"duration\"',\n",
       "  '\"campaign\"',\n",
       "  '\"pdays\"',\n",
       "  '\"previous\"',\n",
       "  '\"poutcome\"',\n",
       "  '\"emp.var.rate\"',\n",
       "  '\"cons.price.idx\"',\n",
       "  '\"cons.conf.idx\"',\n",
       "  '\"euribor3m\"',\n",
       "  '\"nr.employed\"',\n",
       "  '\"y\"'],\n",
       " ['56',\n",
       "  '\"housemaid\"',\n",
       "  '\"married\"',\n",
       "  '\"basic.4y\"',\n",
       "  '\"no\"',\n",
       "  '\"no\"',\n",
       "  '\"no\"',\n",
       "  '\"telephone\"',\n",
       "  '\"may\"',\n",
       "  '\"mon\"',\n",
       "  '261',\n",
       "  '1',\n",
       "  '999',\n",
       "  '0',\n",
       "  '\"nonexistent\"',\n",
       "  '1.1',\n",
       "  '93.994',\n",
       "  '-36.4',\n",
       "  '4.857',\n",
       "  '5191',\n",
       "  '\"no\"'],\n",
       " ['57',\n",
       "  '\"services\"',\n",
       "  '\"married\"',\n",
       "  '\"high.school\"',\n",
       "  '\"unknown\"',\n",
       "  '\"no\"',\n",
       "  '\"no\"',\n",
       "  '\"telephone\"',\n",
       "  '\"may\"',\n",
       "  '\"mon\"',\n",
       "  '149',\n",
       "  '1',\n",
       "  '999',\n",
       "  '0',\n",
       "  '\"nonexistent\"',\n",
       "  '1.1',\n",
       "  '93.994',\n",
       "  '-36.4',\n",
       "  '4.857',\n",
       "  '5191',\n",
       "  '\"no\"']]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Split each string into the various columns\n",
    "data3 = [i.split(\";\") for i in data2]\n",
    "data3[0:3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Place the lists into a DataFrame with the first list as the headings\n",
    "df = pd.DataFrame(data3[1:], columns=data3[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "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>age</th>\n",
       "      <th>\"job\"</th>\n",
       "      <th>\"marital\"</th>\n",
       "      <th>\"education\"</th>\n",
       "      <th>\"default\"</th>\n",
       "      <th>\"housing\"</th>\n",
       "      <th>\"loan\"</th>\n",
       "      <th>\"contact\"</th>\n",
       "      <th>\"month\"</th>\n",
       "      <th>\"day_of_week\"</th>\n",
       "      <th>...</th>\n",
       "      <th>\"campaign\"</th>\n",
       "      <th>\"pdays\"</th>\n",
       "      <th>\"previous\"</th>\n",
       "      <th>\"poutcome\"</th>\n",
       "      <th>\"emp.var.rate\"</th>\n",
       "      <th>\"cons.price.idx\"</th>\n",
       "      <th>\"cons.conf.idx\"</th>\n",
       "      <th>\"euribor3m\"</th>\n",
       "      <th>\"nr.employed\"</th>\n",
       "      <th>\"y\"</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>56</td>\n",
       "      <td>\"housemaid\"</td>\n",
       "      <td>\"married\"</td>\n",
       "      <td>\"basic.4y\"</td>\n",
       "      <td>\"no\"</td>\n",
       "      <td>\"no\"</td>\n",
       "      <td>\"no\"</td>\n",
       "      <td>\"telephone\"</td>\n",
       "      <td>\"may\"</td>\n",
       "      <td>\"mon\"</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>999</td>\n",
       "      <td>0</td>\n",
       "      <td>\"nonexistent\"</td>\n",
       "      <td>1.1</td>\n",
       "      <td>93.994</td>\n",
       "      <td>-36.4</td>\n",
       "      <td>4.857</td>\n",
       "      <td>5191</td>\n",
       "      <td>\"no\"</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>57</td>\n",
       "      <td>\"services\"</td>\n",
       "      <td>\"married\"</td>\n",
       "      <td>\"high.school\"</td>\n",
       "      <td>\"unknown\"</td>\n",
       "      <td>\"no\"</td>\n",
       "      <td>\"no\"</td>\n",
       "      <td>\"telephone\"</td>\n",
       "      <td>\"may\"</td>\n",
       "      <td>\"mon\"</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>999</td>\n",
       "      <td>0</td>\n",
       "      <td>\"nonexistent\"</td>\n",
       "      <td>1.1</td>\n",
       "      <td>93.994</td>\n",
       "      <td>-36.4</td>\n",
       "      <td>4.857</td>\n",
       "      <td>5191</td>\n",
       "      <td>\"no\"</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>37</td>\n",
       "      <td>\"services\"</td>\n",
       "      <td>\"married\"</td>\n",
       "      <td>\"high.school\"</td>\n",
       "      <td>\"no\"</td>\n",
       "      <td>\"yes\"</td>\n",
       "      <td>\"no\"</td>\n",
       "      <td>\"telephone\"</td>\n",
       "      <td>\"may\"</td>\n",
       "      <td>\"mon\"</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>999</td>\n",
       "      <td>0</td>\n",
       "      <td>\"nonexistent\"</td>\n",
       "      <td>1.1</td>\n",
       "      <td>93.994</td>\n",
       "      <td>-36.4</td>\n",
       "      <td>4.857</td>\n",
       "      <td>5191</td>\n",
       "      <td>\"no\"</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>40</td>\n",
       "      <td>\"admin.\"</td>\n",
       "      <td>\"married\"</td>\n",
       "      <td>\"basic.6y\"</td>\n",
       "      <td>\"no\"</td>\n",
       "      <td>\"no\"</td>\n",
       "      <td>\"no\"</td>\n",
       "      <td>\"telephone\"</td>\n",
       "      <td>\"may\"</td>\n",
       "      <td>\"mon\"</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>999</td>\n",
       "      <td>0</td>\n",
       "      <td>\"nonexistent\"</td>\n",
       "      <td>1.1</td>\n",
       "      <td>93.994</td>\n",
       "      <td>-36.4</td>\n",
       "      <td>4.857</td>\n",
       "      <td>5191</td>\n",
       "      <td>\"no\"</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>56</td>\n",
       "      <td>\"services\"</td>\n",
       "      <td>\"married\"</td>\n",
       "      <td>\"high.school\"</td>\n",
       "      <td>\"no\"</td>\n",
       "      <td>\"no\"</td>\n",
       "      <td>\"yes\"</td>\n",
       "      <td>\"telephone\"</td>\n",
       "      <td>\"may\"</td>\n",
       "      <td>\"mon\"</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>999</td>\n",
       "      <td>0</td>\n",
       "      <td>\"nonexistent\"</td>\n",
       "      <td>1.1</td>\n",
       "      <td>93.994</td>\n",
       "      <td>-36.4</td>\n",
       "      <td>4.857</td>\n",
       "      <td>5191</td>\n",
       "      <td>\"no\"</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  age        \"job\"  \"marital\"    \"education\"  \"default\" \"housing\" \"loan\"  \\\n",
       "0  56  \"housemaid\"  \"married\"     \"basic.4y\"       \"no\"      \"no\"   \"no\"   \n",
       "1  57   \"services\"  \"married\"  \"high.school\"  \"unknown\"      \"no\"   \"no\"   \n",
       "2  37   \"services\"  \"married\"  \"high.school\"       \"no\"     \"yes\"   \"no\"   \n",
       "3  40     \"admin.\"  \"married\"     \"basic.6y\"       \"no\"      \"no\"   \"no\"   \n",
       "4  56   \"services\"  \"married\"  \"high.school\"       \"no\"      \"no\"  \"yes\"   \n",
       "\n",
       "     \"contact\" \"month\" \"day_of_week\"  ... \"campaign\" \"pdays\" \"previous\"  \\\n",
       "0  \"telephone\"   \"may\"         \"mon\"  ...          1     999          0   \n",
       "1  \"telephone\"   \"may\"         \"mon\"  ...          1     999          0   \n",
       "2  \"telephone\"   \"may\"         \"mon\"  ...          1     999          0   \n",
       "3  \"telephone\"   \"may\"         \"mon\"  ...          1     999          0   \n",
       "4  \"telephone\"   \"may\"         \"mon\"  ...          1     999          0   \n",
       "\n",
       "      \"poutcome\" \"emp.var.rate\" \"cons.price.idx\" \"cons.conf.idx\" \"euribor3m\"  \\\n",
       "0  \"nonexistent\"            1.1           93.994           -36.4       4.857   \n",
       "1  \"nonexistent\"            1.1           93.994           -36.4       4.857   \n",
       "2  \"nonexistent\"            1.1           93.994           -36.4       4.857   \n",
       "3  \"nonexistent\"            1.1           93.994           -36.4       4.857   \n",
       "4  \"nonexistent\"            1.1           93.994           -36.4       4.857   \n",
       "\n",
       "  \"nr.employed\"   \"y\"  \n",
       "0          5191  \"no\"  \n",
       "1          5191  \"no\"  \n",
       "2          5191  \"no\"  \n",
       "3          5191  \"no\"  \n",
       "4          5191  \"no\"  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Cleaning up DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.columns = df.columns.str.strip('\"\"')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.apply(lambda x: x.str.strip('\"\"'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .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>age</th>\n",
       "      <th>job</th>\n",
       "      <th>marital</th>\n",
       "      <th>education</th>\n",
       "      <th>default</th>\n",
       "      <th>housing</th>\n",
       "      <th>loan</th>\n",
       "      <th>contact</th>\n",
       "      <th>month</th>\n",
       "      <th>day_of_week</th>\n",
       "      <th>...</th>\n",
       "      <th>campaign</th>\n",
       "      <th>pdays</th>\n",
       "      <th>previous</th>\n",
       "      <th>poutcome</th>\n",
       "      <th>emp.var.rate</th>\n",
       "      <th>cons.price.idx</th>\n",
       "      <th>cons.conf.idx</th>\n",
       "      <th>euribor3m</th>\n",
       "      <th>nr.employed</th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>56</td>\n",
       "      <td>housemaid</td>\n",
       "      <td>married</td>\n",
       "      <td>basic.4y</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>telephone</td>\n",
       "      <td>may</td>\n",
       "      <td>mon</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>999</td>\n",
       "      <td>0</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>1.1</td>\n",
       "      <td>93.994</td>\n",
       "      <td>-36.4</td>\n",
       "      <td>4.857</td>\n",
       "      <td>5191</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>57</td>\n",
       "      <td>services</td>\n",
       "      <td>married</td>\n",
       "      <td>high.school</td>\n",
       "      <td>unknown</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>telephone</td>\n",
       "      <td>may</td>\n",
       "      <td>mon</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>999</td>\n",
       "      <td>0</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>1.1</td>\n",
       "      <td>93.994</td>\n",
       "      <td>-36.4</td>\n",
       "      <td>4.857</td>\n",
       "      <td>5191</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>37</td>\n",
       "      <td>services</td>\n",
       "      <td>married</td>\n",
       "      <td>high.school</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>telephone</td>\n",
       "      <td>may</td>\n",
       "      <td>mon</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>999</td>\n",
       "      <td>0</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>1.1</td>\n",
       "      <td>93.994</td>\n",
       "      <td>-36.4</td>\n",
       "      <td>4.857</td>\n",
       "      <td>5191</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>40</td>\n",
       "      <td>admin.</td>\n",
       "      <td>married</td>\n",
       "      <td>basic.6y</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>telephone</td>\n",
       "      <td>may</td>\n",
       "      <td>mon</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>999</td>\n",
       "      <td>0</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>1.1</td>\n",
       "      <td>93.994</td>\n",
       "      <td>-36.4</td>\n",
       "      <td>4.857</td>\n",
       "      <td>5191</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>56</td>\n",
       "      <td>services</td>\n",
       "      <td>married</td>\n",
       "      <td>high.school</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>telephone</td>\n",
       "      <td>may</td>\n",
       "      <td>mon</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>999</td>\n",
       "      <td>0</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>1.1</td>\n",
       "      <td>93.994</td>\n",
       "      <td>-36.4</td>\n",
       "      <td>4.857</td>\n",
       "      <td>5191</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  age        job  marital    education  default housing loan    contact month  \\\n",
       "0  56  housemaid  married     basic.4y       no      no   no  telephone   may   \n",
       "1  57   services  married  high.school  unknown      no   no  telephone   may   \n",
       "2  37   services  married  high.school       no     yes   no  telephone   may   \n",
       "3  40     admin.  married     basic.6y       no      no   no  telephone   may   \n",
       "4  56   services  married  high.school       no      no  yes  telephone   may   \n",
       "\n",
       "  day_of_week  ... campaign pdays previous     poutcome emp.var.rate  \\\n",
       "0         mon  ...        1   999        0  nonexistent          1.1   \n",
       "1         mon  ...        1   999        0  nonexistent          1.1   \n",
       "2         mon  ...        1   999        0  nonexistent          1.1   \n",
       "3         mon  ...        1   999        0  nonexistent          1.1   \n",
       "4         mon  ...        1   999        0  nonexistent          1.1   \n",
       "\n",
       "  cons.price.idx cons.conf.idx euribor3m nr.employed   y  \n",
       "0         93.994         -36.4     4.857        5191  no  \n",
       "1         93.994         -36.4     4.857        5191  no  \n",
       "2         93.994         -36.4     4.857        5191  no  \n",
       "3         93.994         -36.4     4.857        5191  no  \n",
       "4         93.994         -36.4     4.857        5191  no  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(41188, 21)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>age</th>\n",
       "      <th>job</th>\n",
       "      <th>marital</th>\n",
       "      <th>education</th>\n",
       "      <th>default</th>\n",
       "      <th>housing</th>\n",
       "      <th>loan</th>\n",
       "      <th>contact</th>\n",
       "      <th>month</th>\n",
       "      <th>day_of_week</th>\n",
       "      <th>...</th>\n",
       "      <th>campaign</th>\n",
       "      <th>pdays</th>\n",
       "      <th>previous</th>\n",
       "      <th>poutcome</th>\n",
       "      <th>emp.var.rate</th>\n",
       "      <th>cons.price.idx</th>\n",
       "      <th>cons.conf.idx</th>\n",
       "      <th>euribor3m</th>\n",
       "      <th>nr.employed</th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1266</th>\n",
       "      <td>39</td>\n",
       "      <td>blue-collar</td>\n",
       "      <td>married</td>\n",
       "      <td>basic.6y</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>telephone</td>\n",
       "      <td>may</td>\n",
       "      <td>thu</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>999</td>\n",
       "      <td>0</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>1.1</td>\n",
       "      <td>93.994</td>\n",
       "      <td>-36.4</td>\n",
       "      <td>4.855</td>\n",
       "      <td>5191</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12261</th>\n",
       "      <td>36</td>\n",
       "      <td>retired</td>\n",
       "      <td>married</td>\n",
       "      <td>unknown</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>telephone</td>\n",
       "      <td>jul</td>\n",
       "      <td>thu</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>999</td>\n",
       "      <td>0</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>1.4</td>\n",
       "      <td>93.918</td>\n",
       "      <td>-42.7</td>\n",
       "      <td>4.966</td>\n",
       "      <td>5228.1</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14234</th>\n",
       "      <td>27</td>\n",
       "      <td>technician</td>\n",
       "      <td>single</td>\n",
       "      <td>professional.course</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>cellular</td>\n",
       "      <td>jul</td>\n",
       "      <td>mon</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>999</td>\n",
       "      <td>0</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>1.4</td>\n",
       "      <td>93.918</td>\n",
       "      <td>-42.7</td>\n",
       "      <td>4.962</td>\n",
       "      <td>5228.1</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16956</th>\n",
       "      <td>47</td>\n",
       "      <td>technician</td>\n",
       "      <td>divorced</td>\n",
       "      <td>high.school</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>cellular</td>\n",
       "      <td>jul</td>\n",
       "      <td>thu</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>999</td>\n",
       "      <td>0</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>1.4</td>\n",
       "      <td>93.918</td>\n",
       "      <td>-42.7</td>\n",
       "      <td>4.962</td>\n",
       "      <td>5228.1</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18465</th>\n",
       "      <td>32</td>\n",
       "      <td>technician</td>\n",
       "      <td>single</td>\n",
       "      <td>professional.course</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>cellular</td>\n",
       "      <td>jul</td>\n",
       "      <td>thu</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>999</td>\n",
       "      <td>0</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>1.4</td>\n",
       "      <td>93.918</td>\n",
       "      <td>-42.7</td>\n",
       "      <td>4.968</td>\n",
       "      <td>5228.1</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20216</th>\n",
       "      <td>55</td>\n",
       "      <td>services</td>\n",
       "      <td>married</td>\n",
       "      <td>high.school</td>\n",
       "      <td>unknown</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>cellular</td>\n",
       "      <td>aug</td>\n",
       "      <td>mon</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>999</td>\n",
       "      <td>0</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>1.4</td>\n",
       "      <td>93.444</td>\n",
       "      <td>-36.1</td>\n",
       "      <td>4.965</td>\n",
       "      <td>5228.1</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20534</th>\n",
       "      <td>41</td>\n",
       "      <td>technician</td>\n",
       "      <td>married</td>\n",
       "      <td>professional.course</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>cellular</td>\n",
       "      <td>aug</td>\n",
       "      <td>tue</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>999</td>\n",
       "      <td>0</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>1.4</td>\n",
       "      <td>93.444</td>\n",
       "      <td>-36.1</td>\n",
       "      <td>4.966</td>\n",
       "      <td>5228.1</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25217</th>\n",
       "      <td>39</td>\n",
       "      <td>admin.</td>\n",
       "      <td>married</td>\n",
       "      <td>university.degree</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>cellular</td>\n",
       "      <td>nov</td>\n",
       "      <td>tue</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>999</td>\n",
       "      <td>0</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>-0.1</td>\n",
       "      <td>93.2</td>\n",
       "      <td>-42</td>\n",
       "      <td>4.153</td>\n",
       "      <td>5195.8</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28477</th>\n",
       "      <td>24</td>\n",
       "      <td>services</td>\n",
       "      <td>single</td>\n",
       "      <td>high.school</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>cellular</td>\n",
       "      <td>apr</td>\n",
       "      <td>tue</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>999</td>\n",
       "      <td>0</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>-1.8</td>\n",
       "      <td>93.075</td>\n",
       "      <td>-47.1</td>\n",
       "      <td>1.423</td>\n",
       "      <td>5099.1</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32516</th>\n",
       "      <td>35</td>\n",
       "      <td>admin.</td>\n",
       "      <td>married</td>\n",
       "      <td>university.degree</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>cellular</td>\n",
       "      <td>may</td>\n",
       "      <td>fri</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>999</td>\n",
       "      <td>0</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>-1.8</td>\n",
       "      <td>92.893</td>\n",
       "      <td>-46.2</td>\n",
       "      <td>1.313</td>\n",
       "      <td>5099.1</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36951</th>\n",
       "      <td>45</td>\n",
       "      <td>admin.</td>\n",
       "      <td>married</td>\n",
       "      <td>university.degree</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>cellular</td>\n",
       "      <td>jul</td>\n",
       "      <td>thu</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>999</td>\n",
       "      <td>0</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>-2.9</td>\n",
       "      <td>92.469</td>\n",
       "      <td>-33.6</td>\n",
       "      <td>1.072</td>\n",
       "      <td>5076.2</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38281</th>\n",
       "      <td>71</td>\n",
       "      <td>retired</td>\n",
       "      <td>single</td>\n",
       "      <td>university.degree</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>telephone</td>\n",
       "      <td>oct</td>\n",
       "      <td>tue</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>999</td>\n",
       "      <td>0</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>-3.4</td>\n",
       "      <td>92.431</td>\n",
       "      <td>-26.9</td>\n",
       "      <td>0.742</td>\n",
       "      <td>5017.5</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>12 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      age          job   marital            education  default housing loan  \\\n",
       "1266   39  blue-collar   married             basic.6y       no      no   no   \n",
       "12261  36      retired   married              unknown       no      no   no   \n",
       "14234  27   technician    single  professional.course       no      no   no   \n",
       "16956  47   technician  divorced          high.school       no     yes   no   \n",
       "18465  32   technician    single  professional.course       no     yes   no   \n",
       "20216  55     services   married          high.school  unknown      no   no   \n",
       "20534  41   technician   married  professional.course       no     yes   no   \n",
       "25217  39       admin.   married    university.degree       no      no   no   \n",
       "28477  24     services    single          high.school       no     yes   no   \n",
       "32516  35       admin.   married    university.degree       no     yes   no   \n",
       "36951  45       admin.   married    university.degree       no      no   no   \n",
       "38281  71      retired    single    university.degree       no      no   no   \n",
       "\n",
       "         contact month day_of_week  ... campaign pdays previous     poutcome  \\\n",
       "1266   telephone   may         thu  ...        1   999        0  nonexistent   \n",
       "12261  telephone   jul         thu  ...        1   999        0  nonexistent   \n",
       "14234   cellular   jul         mon  ...        2   999        0  nonexistent   \n",
       "16956   cellular   jul         thu  ...        3   999        0  nonexistent   \n",
       "18465   cellular   jul         thu  ...        1   999        0  nonexistent   \n",
       "20216   cellular   aug         mon  ...        1   999        0  nonexistent   \n",
       "20534   cellular   aug         tue  ...        1   999        0  nonexistent   \n",
       "25217   cellular   nov         tue  ...        2   999        0  nonexistent   \n",
       "28477   cellular   apr         tue  ...        1   999        0  nonexistent   \n",
       "32516   cellular   may         fri  ...        4   999        0  nonexistent   \n",
       "36951   cellular   jul         thu  ...        1   999        0  nonexistent   \n",
       "38281  telephone   oct         tue  ...        1   999        0  nonexistent   \n",
       "\n",
       "      emp.var.rate cons.price.idx cons.conf.idx euribor3m nr.employed    y  \n",
       "1266           1.1         93.994         -36.4     4.855        5191   no  \n",
       "12261          1.4         93.918         -42.7     4.966      5228.1   no  \n",
       "14234          1.4         93.918         -42.7     4.962      5228.1   no  \n",
       "16956          1.4         93.918         -42.7     4.962      5228.1   no  \n",
       "18465          1.4         93.918         -42.7     4.968      5228.1   no  \n",
       "20216          1.4         93.444         -36.1     4.965      5228.1   no  \n",
       "20534          1.4         93.444         -36.1     4.966      5228.1   no  \n",
       "25217         -0.1           93.2           -42     4.153      5195.8   no  \n",
       "28477         -1.8         93.075         -47.1     1.423      5099.1   no  \n",
       "32516         -1.8         92.893         -46.2     1.313      5099.1   no  \n",
       "36951         -2.9         92.469         -33.6     1.072      5076.2  yes  \n",
       "38281         -3.4         92.431         -26.9     0.742      5017.5   no  \n",
       "\n",
       "[12 rows x 21 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 12 duplicate observations in the dataset, which I will delete\n",
    "duplicates = df[df.duplicated()]\n",
    "duplicates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop_duplicates(inplace = True) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 41176 entries, 0 to 41187\n",
      "Data columns (total 21 columns):\n",
      " #   Column          Non-Null Count  Dtype \n",
      "---  ------          --------------  ----- \n",
      " 0   age             41176 non-null  object\n",
      " 1   job             41176 non-null  object\n",
      " 2   marital         41176 non-null  object\n",
      " 3   education       41176 non-null  object\n",
      " 4   default         41176 non-null  object\n",
      " 5   housing         41176 non-null  object\n",
      " 6   loan            41176 non-null  object\n",
      " 7   contact         41176 non-null  object\n",
      " 8   month           41176 non-null  object\n",
      " 9   day_of_week     41176 non-null  object\n",
      " 10  duration        41176 non-null  object\n",
      " 11  campaign        41176 non-null  object\n",
      " 12  pdays           41176 non-null  object\n",
      " 13  previous        41176 non-null  object\n",
      " 14  poutcome        41176 non-null  object\n",
      " 15  emp.var.rate    41176 non-null  object\n",
      " 16  cons.price.idx  41176 non-null  object\n",
      " 17  cons.conf.idx   41176 non-null  object\n",
      " 18  euribor3m       41176 non-null  object\n",
      " 19  nr.employed     41176 non-null  object\n",
      " 20  y               41176 non-null  object\n",
      "dtypes: object(21)\n",
      "memory usage: 6.9+ MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Numeric data analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Converting the numeric data\n",
    "cols = ['age', 'duration', 'campaign', 'pdays', 'previous', 'emp.var.rate', 'cons.price.idx',\n",
    "        'cons.conf.idx', 'euribor3m', 'nr.employed']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "df[cols] = df[cols].astype('float')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 41176 entries, 0 to 41187\n",
      "Data columns (total 21 columns):\n",
      " #   Column          Non-Null Count  Dtype  \n",
      "---  ------          --------------  -----  \n",
      " 0   age             41176 non-null  float64\n",
      " 1   job             41176 non-null  object \n",
      " 2   marital         41176 non-null  object \n",
      " 3   education       41176 non-null  object \n",
      " 4   default         41176 non-null  object \n",
      " 5   housing         41176 non-null  object \n",
      " 6   loan            41176 non-null  object \n",
      " 7   contact         41176 non-null  object \n",
      " 8   month           41176 non-null  object \n",
      " 9   day_of_week     41176 non-null  object \n",
      " 10  duration        41176 non-null  float64\n",
      " 11  campaign        41176 non-null  float64\n",
      " 12  pdays           41176 non-null  float64\n",
      " 13  previous        41176 non-null  float64\n",
      " 14  poutcome        41176 non-null  object \n",
      " 15  emp.var.rate    41176 non-null  float64\n",
      " 16  cons.price.idx  41176 non-null  float64\n",
      " 17  cons.conf.idx   41176 non-null  float64\n",
      " 18  euribor3m       41176 non-null  float64\n",
      " 19  nr.employed     41176 non-null  float64\n",
      " 20  y               41176 non-null  object \n",
      "dtypes: float64(10), object(11)\n",
      "memory usage: 6.9+ MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "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>age</th>\n",
       "      <th>duration</th>\n",
       "      <th>campaign</th>\n",
       "      <th>pdays</th>\n",
       "      <th>previous</th>\n",
       "      <th>emp.var.rate</th>\n",
       "      <th>cons.price.idx</th>\n",
       "      <th>cons.conf.idx</th>\n",
       "      <th>euribor3m</th>\n",
       "      <th>nr.employed</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>41176.00000</td>\n",
       "      <td>41176.000000</td>\n",
       "      <td>41176.000000</td>\n",
       "      <td>41176.000000</td>\n",
       "      <td>41176.000000</td>\n",
       "      <td>41176.000000</td>\n",
       "      <td>41176.000000</td>\n",
       "      <td>41176.000000</td>\n",
       "      <td>41176.000000</td>\n",
       "      <td>41176.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>40.02380</td>\n",
       "      <td>258.315815</td>\n",
       "      <td>2.567879</td>\n",
       "      <td>962.464810</td>\n",
       "      <td>0.173013</td>\n",
       "      <td>0.081922</td>\n",
       "      <td>93.575720</td>\n",
       "      <td>-40.502863</td>\n",
       "      <td>3.621293</td>\n",
       "      <td>5167.034870</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>10.42068</td>\n",
       "      <td>259.305321</td>\n",
       "      <td>2.770318</td>\n",
       "      <td>186.937102</td>\n",
       "      <td>0.494964</td>\n",
       "      <td>1.570883</td>\n",
       "      <td>0.578839</td>\n",
       "      <td>4.627860</td>\n",
       "      <td>1.734437</td>\n",
       "      <td>72.251364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>17.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-3.400000</td>\n",
       "      <td>92.201000</td>\n",
       "      <td>-50.800000</td>\n",
       "      <td>0.634000</td>\n",
       "      <td>4963.600000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>32.00000</td>\n",
       "      <td>102.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>999.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-1.800000</td>\n",
       "      <td>93.075000</td>\n",
       "      <td>-42.700000</td>\n",
       "      <td>1.344000</td>\n",
       "      <td>5099.100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>38.00000</td>\n",
       "      <td>180.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>999.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.100000</td>\n",
       "      <td>93.749000</td>\n",
       "      <td>-41.800000</td>\n",
       "      <td>4.857000</td>\n",
       "      <td>5191.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>47.00000</td>\n",
       "      <td>319.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>999.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.400000</td>\n",
       "      <td>93.994000</td>\n",
       "      <td>-36.400000</td>\n",
       "      <td>4.961000</td>\n",
       "      <td>5228.100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>98.00000</td>\n",
       "      <td>4918.000000</td>\n",
       "      <td>56.000000</td>\n",
       "      <td>999.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>1.400000</td>\n",
       "      <td>94.767000</td>\n",
       "      <td>-26.900000</td>\n",
       "      <td>5.045000</td>\n",
       "      <td>5228.100000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               age      duration      campaign         pdays      previous  \\\n",
       "count  41176.00000  41176.000000  41176.000000  41176.000000  41176.000000   \n",
       "mean      40.02380    258.315815      2.567879    962.464810      0.173013   \n",
       "std       10.42068    259.305321      2.770318    186.937102      0.494964   \n",
       "min       17.00000      0.000000      1.000000      0.000000      0.000000   \n",
       "25%       32.00000    102.000000      1.000000    999.000000      0.000000   \n",
       "50%       38.00000    180.000000      2.000000    999.000000      0.000000   \n",
       "75%       47.00000    319.000000      3.000000    999.000000      0.000000   \n",
       "max       98.00000   4918.000000     56.000000    999.000000      7.000000   \n",
       "\n",
       "       emp.var.rate  cons.price.idx  cons.conf.idx     euribor3m   nr.employed  \n",
       "count  41176.000000    41176.000000   41176.000000  41176.000000  41176.000000  \n",
       "mean       0.081922       93.575720     -40.502863      3.621293   5167.034870  \n",
       "std        1.570883        0.578839       4.627860      1.734437     72.251364  \n",
       "min       -3.400000       92.201000     -50.800000      0.634000   4963.600000  \n",
       "25%       -1.800000       93.075000     -42.700000      1.344000   5099.100000  \n",
       "50%        1.100000       93.749000     -41.800000      4.857000   5191.000000  \n",
       "75%        1.400000       93.994000     -36.400000      4.961000   5228.100000  \n",
       "max        1.400000       94.767000     -26.900000      5.045000   5228.100000  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "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>age</th>\n",
       "      <th>job</th>\n",
       "      <th>education</th>\n",
       "      <th>duration</th>\n",
       "      <th>campaign</th>\n",
       "      <th>marital</th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>7727</th>\n",
       "      <td>37.0</td>\n",
       "      <td>unemployed</td>\n",
       "      <td>professional.course</td>\n",
       "      <td>3631.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>married</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13820</th>\n",
       "      <td>31.0</td>\n",
       "      <td>technician</td>\n",
       "      <td>professional.course</td>\n",
       "      <td>3643.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>married</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22192</th>\n",
       "      <td>52.0</td>\n",
       "      <td>blue-collar</td>\n",
       "      <td>basic.4y</td>\n",
       "      <td>4199.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>married</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24091</th>\n",
       "      <td>33.0</td>\n",
       "      <td>technician</td>\n",
       "      <td>professional.course</td>\n",
       "      <td>4918.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>single</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40537</th>\n",
       "      <td>27.0</td>\n",
       "      <td>admin.</td>\n",
       "      <td>high.school</td>\n",
       "      <td>3785.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>single</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        age          job            education  duration  campaign  marital  \\\n",
       "7727   37.0   unemployed  professional.course    3631.0       2.0  married   \n",
       "13820  31.0   technician  professional.course    3643.0       1.0  married   \n",
       "22192  52.0  blue-collar             basic.4y    4199.0       3.0  married   \n",
       "24091  33.0   technician  professional.course    4918.0       1.0   single   \n",
       "40537  27.0       admin.          high.school    3785.0       1.0   single   \n",
       "\n",
       "         y  \n",
       "7727   yes  \n",
       "13820  yes  \n",
       "22192  yes  \n",
       "24091   no  \n",
       "40537   no  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# The max 'duration' value seems incredible. Let's see how many people spoke for more than 1 hour to check if... \n",
    "# there are possible errors in the dataset.\n",
    "# Well, the other variables' values seem fine, so it looks legit.\n",
    "df[['age', 'job', 'education', 'duration', 'campaign', 'marital', 'y']][df.duration > 3600]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### All the numeric variables look fine, except for 'pdays' with the max reading of 999"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([999.,   6.,   4.,   3.,   5.,   1.,   0.,  10.,   7.,   8.,   9.,\n",
       "        11.,   2.,  12.,  13.,  14.,  15.,  16.,  21.,  17.,  18.,  22.,\n",
       "        25.,  26.,  19.,  27.,  20.])"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 999 should perhaps be encoded as 0 instead\n",
    "df.pdays.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "999.0    39661\n",
       "3.0        439\n",
       "6.0        412\n",
       "4.0        118\n",
       "9.0         64\n",
       "2.0         61\n",
       "7.0         60\n",
       "12.0        58\n",
       "10.0        52\n",
       "5.0         46\n",
       "13.0        36\n",
       "11.0        28\n",
       "1.0         26\n",
       "15.0        24\n",
       "14.0        20\n",
       "8.0         18\n",
       "0.0         15\n",
       "16.0        11\n",
       "17.0         8\n",
       "18.0         7\n",
       "19.0         3\n",
       "22.0         3\n",
       "21.0         2\n",
       "27.0         1\n",
       "25.0         1\n",
       "20.0         1\n",
       "26.0         1\n",
       "Name: pdays, dtype: int64"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Overwhelming majority of clients in dataset have never been contacted before\n",
    "df.pdays.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Transforming the 'pdays' variable's 999 values\n",
    "df['pdays'] = df.pdays.map(lambda x: 0 if x == 999 else x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    41176.000000\n",
       "mean         0.221294\n",
       "std          1.349065\n",
       "min          0.000000\n",
       "25%          0.000000\n",
       "50%          0.000000\n",
       "75%          0.000000\n",
       "max         27.000000\n",
       "Name: pdays, dtype: float64"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.pdays.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0    35551\n",
       "1.0     4561\n",
       "2.0      754\n",
       "3.0      216\n",
       "4.0       70\n",
       "5.0       18\n",
       "6.0        5\n",
       "7.0        1\n",
       "Name: previous, dtype: int64"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Somewhat more contact history in 'previous' than in 'pdays'\n",
    "df.previous.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Target variable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "no     36537\n",
       "yes     4639\n",
       "Name: y, dtype: int64"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Binary target variable\n",
    "df.y.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Changing the target variable into numeric\n",
    "df['target'] = df.y.map(lambda x: 1 if x == 'yes' else 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.11266271614532737"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.target[df.target == 1].count()/df.target.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 360,
       "width": 365
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Pie chart of the target variable\n",
    "\n",
    "target_labels = 'No', 'Yes'\n",
    "target_counts = [df.target[df.target==0].count(), df.target[df.target==1].count()]\n",
    "\n",
    "explode = (0, 0.25)\n",
    "\n",
    "plt.figure(figsize=(6,6))\n",
    "cmap = plt.get_cmap('tab20')\n",
    "colors = [cmap(i) for i in np.linspace(0, 1, 8)]\n",
    "\n",
    "target_pie = plt.pie(target_counts, labels=target_labels, explode=explode, autopct='%1.2f%%', \n",
    "                     textprops={'fontsize': 14}, shadow=True, colors=colors)\n",
    "plt.title('Pie Chart of Target Variable', fontsize=18)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Marketing success rate is **11.27%**. So this is an **imbalanced** dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop(['y'], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Correlations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1008x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 631,
       "width": 814
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Take a look at the correlation matrix for the numeric variables\n",
    "M = df[['target', 'emp.var.rate', 'cons.price.idx', 'cons.conf.idx', 'euribor3m', 'nr.employed',\n",
    "       'age', 'duration', 'campaign', 'pdays', 'previous']]\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(14, 10))\n",
    "\n",
    "mask = np.zeros_like(M.corr(), dtype=np.bool)\n",
    "mask[np.triu_indices_from(mask)] = True\n",
    "\n",
    "sns.heatmap(M.corr(), mask=mask, annot=True, ax=ax)\n",
    "ax.set_yticks(np.arange(0, df.shape[1])+0.1)\n",
    "ax.set_ylim([M.shape[1], 0])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Very high positive correlation** (at over 0.90) between many of the **macroeconomic variables**, especially **'emp.var.rate', 'nr.employed' &  'euribor3m'**. Using just one of them is advisable to minimise multicollinearity. Best to use **'euribor3m'** as the level of the risk-free interest rate is likely to affect people's propensity to take up bank term deposits. The level of the inflation index, **'cons.price.idx'**, is also highly correlated to **'euribor3m'**, which is expected. But **'cons.conf.idx'** is not as well correlated with the others. So let's pick **'euribor3m' and 'cons.conf.idx'** as potential **explanatory variables** from among the **macroeconomic variables**.\n",
    "\n",
    "**'pdays'** has moderate positive correlation with **'target'**, meaning if the client had been contacted in a previous campaign, the more days that has passed since until the latest (current) campaign contact raise the probability of a successful subscription. **'previous'** also has a moderate positive correlation, so the more contacts with the client before the latest campaign raises the probability of a subscription. There is a relatively high correlation between **'pdays' and 'previous'** (at +0.49), and I will therefore just use the **'previous'** variable because it has more observations of client contact. Interestingly, **'campaign'**, which is the number of contacts during the current campaign, had little correlation to the subscription success rate.\n",
    "\n",
    "**'duration'** of the phone conversation in the current campaign has the highest correlation to **'target'**, and is positive, meaning that the longer the phone conversation with the client in this current campaign, the higher the probability of a successful subscription. Naturally, an interested client will be more willing to discuss taking up term deposits, and such a client will also be more likely to actually subscribe ultimately. A commercial-minded predictive model should probably **not include 'duration'** because it is a variable whose outcome cannot be estimated **independently of the target variable beforehand**. \n",
    "\n",
    "The alternative argument is that **'duration'** might reflect the caller's ability to engage the client, which would then lead to a higher probability of a subscription. But if this view is valid, then it is better to use a variable that measures a caller's ability directly, perhaps the caller's success rate in previous campaigns. I think that a realistic predictive model should **exclude the 'duration' variable**."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "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>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>target</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>220.868079</td>\n",
       "      <td>207.116178</td>\n",
       "      <td>36537</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>553.256090</td>\n",
       "      <td>401.190736</td>\n",
       "      <td>4639</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              mean         std  count\n",
       "target                               \n",
       "0       220.868079  207.116178  36537\n",
       "1       553.256090  401.190736   4639"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Let's look at some summary statistics for 'duration'\n",
    "# The two distributions between target=1 and target=0 are different\n",
    "df.groupby('target')['duration'].agg(['mean', 'std', 'count'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 260,
       "width": 979
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,4))\n",
    "sns.boxplot(x='duration', y='target', data=df, orient='h');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Ttest_indResult(statistic=-89.96034866049264, pvalue=0.0)"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# t-test shows that the two distributions of 'duration' are statistically distinct from each other\n",
    "stats.ttest_ind(df.duration[df.target == 0], df.duration[df.target == 1])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Non-numeric variables"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## _job_ variable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['housemaid', 'services', 'admin.', 'blue-collar', 'technician',\n",
       "       'retired', 'management', 'unemployed', 'self-employed', 'unknown',\n",
       "       'entrepreneur', 'student'], dtype=object)"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.job.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "job_proportion = ((df.target[df.target == 1].groupby(df.job).count())/\n",
    "                  (df.target.groupby(df.job).count()))*100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "job\n",
       "admin.           12.966695\n",
       "blue-collar       6.895061\n",
       "entrepreneur      8.516484\n",
       "housemaid        10.000000\n",
       "management       11.217510\n",
       "retired          25.261932\n",
       "self-employed    10.485574\n",
       "services          8.142173\n",
       "student          31.428571\n",
       "technician       10.832468\n",
       "unemployed       14.201183\n",
       "unknown          11.212121\n",
       "Name: target, dtype: float64"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Subscription success rates by job category\n",
    "job_proportion"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**'blue-collar'** has notably the lowest success rate, while **'student' and 'retired'** have notably higher sucess rates, along with **'unemployed'** as a distant third. Probably useful to use these four job categories as **dummies** in the model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 260,
       "width": 979
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# There appears to be a greater success rate among older clients\n",
    "plt.figure(figsize=(15,4))\n",
    "sns.boxplot(x='age', y='target', data=df, orient='h');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.030380536219875947"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# There is little correlation between the success rate and age for the overall dataset\n",
    "df.age.corr(df.target)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.3450014260768637"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# But there is a good positive correlation between age and the success rate among retirees\n",
    "df['age'][df.job == 'retired'].corr(df.target)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-0.14858666506737792"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Also a decent negative correlation between age and the success rate among student\n",
    "df['age'][df.job == 'student'].corr(df.target)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-0.02948258934812092"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# No such pattern among the unemployed...\n",
    "df['age'][df.job == 'unemployed'].corr(df.target)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-0.010950005078692829"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# nor among blue-collar workers\n",
    "df['age'][df.job == 'blue-collar'].corr(df.target)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The use of **interaction variables** between job dummies for **'retired' and 'student' and 'age'** could prove fruitful for predicting success."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## _education_ variable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['basic.4y', 'high.school', 'basic.6y', 'basic.9y',\n",
       "       'professional.course', 'unknown', 'university.degree',\n",
       "       'illiterate'], dtype=object)"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.education.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "edu_proportion = ((df.target[df.target == 1].groupby(df.education).count())/\n",
    "                  (df.target.groupby(df.education).count()))*100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "education\n",
       "basic.4y               10.249042\n",
       "basic.6y                8.206024\n",
       "basic.9y                7.824648\n",
       "high.school            10.838940\n",
       "illiterate             22.222222\n",
       "professional.course    11.354962\n",
       "university.degree      13.720816\n",
       "unknown                14.508671\n",
       "Name: target, dtype: float64"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Subscription success rates by education category\n",
    "edu_proportion"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**'basic.9y' and 'basic.4y'** have notably the lowest success rates, while **'illiterate'** have notably the highest success rate. **'university' and 'unknown'** also have high sucess rates. Probably useful to use these four job categories as **dummies** in the model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "edu_student = ((df.job[df.job == 'student'].groupby(df.education).count())/\n",
    "               (df.job.groupby(df.education).count()))*100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "education\n",
       "basic.4y               0.622605\n",
       "basic.6y               0.567438\n",
       "basic.9y               1.637717\n",
       "high.school            3.753154\n",
       "illiterate                  NaN\n",
       "professional.course    0.820611\n",
       "university.degree      1.397567\n",
       "unknown                9.653179\n",
       "Name: job, dtype: float64"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Although job==student is well-represented among the education=unknown group, it’s still less than 10%, \n",
    "# so 'unknown' is not synonymous with 'student'\n",
    "edu_student"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "edu_retired = ((df.job[df.job == 'retired'].groupby(df.education).count())/\n",
    "               (df.job.groupby(df.education).count()))*100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "education\n",
       "basic.4y               14.295977\n",
       "basic.6y                3.273680\n",
       "basic.9y                2.398677\n",
       "high.school             2.901598\n",
       "illiterate             16.666667\n",
       "professional.course     4.599237\n",
       "university.degree       2.334758\n",
       "unknown                 5.606936\n",
       "Name: job, dtype: float64"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# job==retired is well-represented among education==illiterate\n",
    "edu_retired"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "edu_blue = ((df.job[df.job == 'blue-collar'].groupby(df.education).count())/\n",
    "            (df.job.groupby(df.education).count()))*100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "education\n",
       "basic.4y               55.507663\n",
       "basic.6y               62.199913\n",
       "basic.9y               59.933830\n",
       "high.school             9.230446\n",
       "illiterate             44.444444\n",
       "professional.course     8.645038\n",
       "university.degree       0.772772\n",
       "unknown                26.242775\n",
       "Name: job, dtype: float64"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# job==blue-collar is heavily represented among 'basic' education categories, which help explain their low rates\n",
    "# but interesting that blue-collar is also a large proportion of education==illiterate, but it has high rates\n",
    "edu_blue"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.2961483449480948"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['age'][df.education == 'basic.4y'].corr(df.target)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.16332150908843854"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['age'][df.education == 'illiterate'].corr(df.target)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's set **dummy variables** for\n",
    "+ 'illiterate', \n",
    "+ 'unknown', \n",
    "+ 'university.degree', and \n",
    "+ a combined 'basic.6y' with 'basic.9y'**\n",
    "\n",
    "Then **interactive dummies** between **'age' and 'basic.4y' & 'age' and 'illiterate'**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## _poutcome_ & _marital_ variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "nonexistent    35551\n",
       "failure         4252\n",
       "success         1373\n",
       "Name: poutcome, dtype: int64"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.poutcome.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "poutcome_proportion = ((df.target[df.target == 1].groupby(df.poutcome).count())/\n",
    "                      (df.target.groupby(df.poutcome).count()))*100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "poutcome\n",
       "failure        14.228598\n",
       "nonexistent     8.832382\n",
       "success        65.112891\n",
       "Name: target, dtype: float64"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Previous success in marketing campaign is linked powerfully to subsequent success, and\n",
    "# even previous contact but failure has an above-sample success rate\n",
    "poutcome_proportion"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.07478009748710428"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['age'][df.poutcome == 'success'].corr(df.target)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "married     24921\n",
       "single      11564\n",
       "divorced     4611\n",
       "unknown        80\n",
       "Name: marital, dtype: int64"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.marital.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "marital_proportion = ((df.target[df.target == 1].groupby(df.marital).count())/\n",
    "                      (df.target.groupby(df.marital).count()))*100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "marital\n",
       "divorced    10.323140\n",
       "married     10.156093\n",
       "single      14.008993\n",
       "unknown     15.000000\n",
       "Name: target, dtype: float64"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 'single' category has notably higher subscription rate, so let's have a dummy for that\n",
    "marital_proportion"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## miscellaneous variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "no         32577\n",
       "unknown     8596\n",
       "yes            3\n",
       "Name: default, dtype: int64"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Extremely few cases of defaults\n",
    "df.default.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "default_proportion = ((df.target[df.target == 1].groupby(df.default).count())/\n",
    "                      (df.target.groupby(df.default).count()))*100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "default\n",
       "no         12.880253\n",
       "unknown     5.153560\n",
       "yes              NaN\n",
       "Name: target, dtype: float64"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Let's have a dummy variable for no defaults\n",
    "default_proportion"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "yes        21571\n",
       "no         18615\n",
       "unknown      990\n",
       "Name: housing, dtype: int64"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.housing.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [],
   "source": [
    "housing_proportion = ((df.target[df.target == 1].groupby(df.housing).count())/\n",
    "                      (df.target.groupby(df.housing).count()))*100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "housing\n",
       "no         10.878324\n",
       "unknown    10.808081\n",
       "yes        11.622085\n",
       "Name: target, dtype: float64"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing_proportion"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 260,
       "width": 1019
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Using 'duration' as a continuous proxy for the target variable, we see little discernible difference in the... \n",
    "# housing loan distributions\n",
    "plt.figure(figsize=(15,4))\n",
    "sns.boxplot(x='duration', y='housing', data=df, orient='h');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "no         33938\n",
       "yes         6248\n",
       "unknown      990\n",
       "Name: loan, dtype: int64"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Extremely few cases of defaults\n",
    "df.loan.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [],
   "source": [
    "loan_proportion = ((df.target[df.target == 1].groupby(df.loan).count())/\n",
    "                   (df.target.groupby(df.loan).count()))*100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "loan\n",
       "no         11.341269\n",
       "unknown    10.808081\n",
       "yes        10.931498\n",
       "Name: target, dtype: float64"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# No discernible effect from 'loan' variable\n",
    "loan_proportion"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "So we've identified the following potential **explanatory variables**: \n",
    "+ 'euribor3m', \n",
    "+'cons.conf.idx', \n",
    "+'age', \n",
    "+blue-collar (age) dummy, \n",
    "+student (job) dummy, \n",
    "+retired (job) dummy, \n",
    "+unemployed (job) dummy, \n",
    "+illiterate (education) dummy,\n",
    "+unknown (education) dummy,\n",
    "+university (education) dummy,\n",
    "+basic.4y (education) dummy,\n",
    "+combined basic.6y & basic.9y (education) dummy,\n",
    "+retired-age interaction variable, \n",
    "+student-age interaction variable,\n",
    "+basic.4y-age interaction variable,\n",
    "+illiterate-age interaction variable,\n",
    "+marital single dummy, \n",
    "+no credit default dummy."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Feature engineering"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Creating new variables, mostly dummy variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Creating a dummy variable for blue-collar workers\n",
    "df['blue_collar'] = df.job.apply(lambda x: 1 if x=='blue-collar' else 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Creating a dummy variable for students\n",
    "df['student'] = df.job.apply(lambda x: 1 if x=='student' else 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Creating a dummy variable for retirees\n",
    "df['retiree'] = df.job.apply(lambda x: 1 if x=='retired' else 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Creating a dummy variable for unemployed\n",
    "df['unemployed'] = df.job.apply(lambda x: 1 if x=='unemployed' else 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Creating a dummy variable for illiterate\n",
    "df['illiterate'] = df.education.apply(lambda x: 1 if x=='illiterate' else 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Creating a dummy variable for unknown\n",
    "df['unknown_edu'] = df.education.apply(lambda x: 1 if x=='unknown' else 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Creating a dummy variable for university degree\n",
    "df['university'] = df.education.apply(lambda x: 1 if x=='university.degree' else 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Creating a dummy variable for basic.4y\n",
    "df['basic4'] = df.education.apply(lambda x: 1 if x=='basic.4y' else 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Creating a dummy variable for basic.6y & basic.9y together\n",
    "df['basic_other'] = df.education.apply(lambda x: 1 if x=='basic.6y' or x=='basic.9y' else 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Creating a dummy variable for singles\n",
    "df['single'] = df.marital.apply(lambda x: 1 if x=='single' else 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Creating a dummy variable for no credit default\n",
    "df['no_default'] = df.default.apply(lambda x: 1 if x=='no' else 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['age_retiree'] = df.age*df.retiree"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['age_student'] = df.age*df.student"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['age_basic4'] = df.age*df.basic4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['age_illiterate'] = df.age*df.illiterate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "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>blue_collar</th>\n",
       "      <th>student</th>\n",
       "      <th>retiree</th>\n",
       "      <th>unemployed</th>\n",
       "      <th>illiterate</th>\n",
       "      <th>unknown_edu</th>\n",
       "      <th>university</th>\n",
       "      <th>basic4</th>\n",
       "      <th>basic_other</th>\n",
       "      <th>single</th>\n",
       "      <th>no_default</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>41176.000000</td>\n",
       "      <td>41176.000000</td>\n",
       "      <td>41176.000000</td>\n",
       "      <td>41176.000000</td>\n",
       "      <td>41176.000000</td>\n",
       "      <td>41176.000000</td>\n",
       "      <td>41176.000000</td>\n",
       "      <td>41176.000000</td>\n",
       "      <td>41176.000000</td>\n",
       "      <td>41176.000000</td>\n",
       "      <td>41176.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.224718</td>\n",
       "      <td>0.021250</td>\n",
       "      <td>0.041723</td>\n",
       "      <td>0.024626</td>\n",
       "      <td>0.000437</td>\n",
       "      <td>0.042015</td>\n",
       "      <td>0.295415</td>\n",
       "      <td>0.101418</td>\n",
       "      <td>0.202448</td>\n",
       "      <td>0.280843</td>\n",
       "      <td>0.791165</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.417402</td>\n",
       "      <td>0.144219</td>\n",
       "      <td>0.199959</td>\n",
       "      <td>0.154984</td>\n",
       "      <td>0.020904</td>\n",
       "      <td>0.200625</td>\n",
       "      <td>0.456235</td>\n",
       "      <td>0.301885</td>\n",
       "      <td>0.401829</td>\n",
       "      <td>0.449417</td>\n",
       "      <td>0.406481</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        blue_collar       student       retiree    unemployed    illiterate  \\\n",
       "count  41176.000000  41176.000000  41176.000000  41176.000000  41176.000000   \n",
       "mean       0.224718      0.021250      0.041723      0.024626      0.000437   \n",
       "std        0.417402      0.144219      0.199959      0.154984      0.020904   \n",
       "min        0.000000      0.000000      0.000000      0.000000      0.000000   \n",
       "25%        0.000000      0.000000      0.000000      0.000000      0.000000   \n",
       "50%        0.000000      0.000000      0.000000      0.000000      0.000000   \n",
       "75%        0.000000      0.000000      0.000000      0.000000      0.000000   \n",
       "max        1.000000      1.000000      1.000000      1.000000      1.000000   \n",
       "\n",
       "        unknown_edu    university        basic4   basic_other        single  \\\n",
       "count  41176.000000  41176.000000  41176.000000  41176.000000  41176.000000   \n",
       "mean       0.042015      0.295415      0.101418      0.202448      0.280843   \n",
       "std        0.200625      0.456235      0.301885      0.401829      0.449417   \n",
       "min        0.000000      0.000000      0.000000      0.000000      0.000000   \n",
       "25%        0.000000      0.000000      0.000000      0.000000      0.000000   \n",
       "50%        0.000000      0.000000      0.000000      0.000000      0.000000   \n",
       "75%        0.000000      1.000000      0.000000      0.000000      1.000000   \n",
       "max        1.000000      1.000000      1.000000      1.000000      1.000000   \n",
       "\n",
       "         no_default  \n",
       "count  41176.000000  \n",
       "mean       0.791165  \n",
       "std        0.406481  \n",
       "min        0.000000  \n",
       "25%        1.000000  \n",
       "50%        1.000000  \n",
       "75%        1.000000  \n",
       "max        1.000000  "
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[['blue_collar', 'student', 'retiree', 'unemployed', 'illiterate', 'unknown_edu', 'university', 'basic4', \n",
    "    'basic_other', 'single', 'no_default']].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "admin.           10419\n",
       "blue-collar       9253\n",
       "technician        6739\n",
       "services          3967\n",
       "management        2924\n",
       "retired           1718\n",
       "entrepreneur      1456\n",
       "self-employed     1421\n",
       "housemaid         1060\n",
       "unemployed        1014\n",
       "student            875\n",
       "unknown            330\n",
       "Name: job, dtype: int64"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Numbers above for the job dummies align, so the dummification was correct\n",
    "df.job.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1296x864 with 2 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 739,
       "width": 1033
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Take a look at the correlation matrix for the new variables\n",
    "W = df[['target', 'blue_collar', 'student', 'retiree', 'unemployed', 'illiterate', 'unknown_edu', \n",
    "        'university', 'basic4', 'basic_other', 'single', 'no_default', 'age_student', 'age_retiree', 'age_basic4',\n",
    "        'age_illiterate']]\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(18, 12))\n",
    "\n",
    "mask = np.zeros_like(W.corr(), dtype=np.bool)\n",
    "mask[np.triu_indices_from(mask)] = True\n",
    "\n",
    "sns.heatmap(W.corr(), mask=mask, annot=True, ax=ax)\n",
    "ax.set_yticks(np.arange(0, df.shape[1])+0.1)\n",
    "ax.set_ylim([W.shape[1], 0])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### The correlations tend to be low for these new set of mostly dummy variables, apart from the four interaction variables, which would be expected. The highest correlation is between 'basic_other and 'blue_collar' at +0.46, which we have already seen previously. After that it's a couple of correlations in the low 0.30s."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Dropping continuous variables from the DF\n",
    "df.drop(['emp.var.rate', 'nr.employed', 'cons.price.idx', 'pdays'], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Dropping the categorial variables from the DF after engineering above\n",
    "df.drop(['job', 'education', 'marital', 'default', 'housing', 'loan'], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Dummifying the rest of the variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.get_dummies(df, columns=['poutcome'], drop_first=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.get_dummies(df, columns=['contact'], drop_first=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.get_dummies(df, columns=['month'], drop_first=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.get_dummies(df, columns=['day_of_week'], drop_first=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['age', 'duration', 'campaign', 'previous', 'cons.conf.idx', 'euribor3m',\n",
       "       'target', 'blue_collar', 'student', 'retiree', 'unemployed',\n",
       "       'illiterate', 'unknown_edu', 'university', 'basic4', 'basic_other',\n",
       "       'single', 'no_default', 'age_retiree', 'age_student', 'age_basic4',\n",
       "       'age_illiterate', 'poutcome_nonexistent', 'poutcome_success',\n",
       "       'contact_telephone', 'month_aug', 'month_dec', 'month_jul', 'month_jun',\n",
       "       'month_mar', 'month_may', 'month_nov', 'month_oct', 'month_sep',\n",
       "       'day_of_week_mon', 'day_of_week_thu', 'day_of_week_tue',\n",
       "       'day_of_week_wed'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1296x864 with 2 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 784,
       "width": 1033
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Take a look at the correlation matrix for the new variables\n",
    "Q = df[['target', 'duration', 'poutcome_nonexistent', 'poutcome_success', 'contact_telephone', 'month_aug', \n",
    "        'month_dec', 'month_jul', 'month_jun', 'month_mar', 'month_may', 'month_nov', 'month_oct', \n",
    "        'month_sep', 'day_of_week_mon', 'day_of_week_thu', 'day_of_week_tue', 'day_of_week_wed']]\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(18, 12))\n",
    "\n",
    "mask = np.zeros_like(Q.corr(), dtype=np.bool)\n",
    "mask[np.triu_indices_from(mask)] = True\n",
    "\n",
    "sns.heatmap(Q.corr(), mask=mask, annot=True, ax=ax)\n",
    "ax.set_yticks(np.arange(0, df.shape[1])+0.1)\n",
    "ax.set_ylim([Q.shape[1], 0])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The correlations tend to be **low** for these remaining set of variables. The **highest correlation** is again between the **two 'poutcome' dummies**, which would be expected, then between 'target' and 'duration'. After that it's a handful of correlations in the 0.30s, largely between the 'contact_telephone' dummy and a couple of months."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop(['duration'], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['age', 'campaign', 'previous', 'cons.conf.idx', 'euribor3m', 'target',\n",
       "       'blue_collar', 'student', 'retiree', 'unemployed', 'illiterate',\n",
       "       'unknown_edu', 'university', 'basic4', 'basic_other', 'single',\n",
       "       'no_default', 'age_retiree', 'age_student', 'age_basic4',\n",
       "       'age_illiterate', 'poutcome_nonexistent', 'poutcome_success',\n",
       "       'contact_telephone', 'month_aug', 'month_dec', 'month_jul', 'month_jun',\n",
       "       'month_mar', 'month_may', 'month_nov', 'month_oct', 'month_sep',\n",
       "       'day_of_week_mon', 'day_of_week_thu', 'day_of_week_tue',\n",
       "       'day_of_week_wed'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [],
   "source": [
    "#df.to_csv(r'C:\\\\df_data.csv', index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### The analysis is continued in the second file of the series"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}