Skip to content

Instantly share code, notes, and snippets.

@aszenz

aszenz/eda_credit_dataset.ipynb

Last active October 27, 2018 12:56
Show Gist options
  • Save aszenz/b5b8877032091bc4ba13e70b351edc70 to your computer and use it in GitHub Desktop.
Save aszenz/b5b8877032091bc4ba13e70b351edc70 to your computer and use it in GitHub Desktop.
Download ZIP
EDA_Credit_Dataset.ipynb
Display the source blob
Display the rendered blob
Raw
eda_credit_dataset.ipynb
{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"name": "EDA_Credit_Dataset.ipynb",
"version": "0.3.2",
"provenance": [],
"include_colab_link": true
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
}
},
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
"<a href=\"https://colab.research.google.com/gist/aszenz/b5b8877032091bc4ba13e70b351edc70/eda_credit_dataset.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
]
},
{
"metadata": {
"id": "tLs2bMbUHkh7",
"colab_type": "text"
},
"cell_type": "markdown",
"source": [
"# Exploratory Data Analysis of Credit Dataset"
]
},
{
"metadata": {
"id": "e3ukMFWgHrhA",
"colab_type": "text"
},
"cell_type": "markdown",
"source": [
""
]
},
{
"metadata": {
"id": "qosGvW0lJU30",
"colab_type": "text"
},
"cell_type": "markdown",
"source": [
"## Import Necessary Libraries"
]
},
{
"metadata": {
"id": "STiphpEnyxKj",
"colab_type": "code",
"colab": {}
},
"cell_type": "code",
"source": [
"import numpy as np\n",
"import pandas as pd\n",
"import matplotlib.pyplot as plt\n",
"import seaborn as sns"
],
"execution_count": 0,
"outputs": []
},
{
"metadata": {
"id": "4iVfmxD1JYRG",
"colab_type": "text"
},
"cell_type": "markdown",
"source": [
"## Read and Understand Data"
]
},
{
"metadata": {
"id": "-Q2I7lpQzSGy",
"colab_type": "code",
"colab": {}
},
"cell_type": "code",
"source": [
"data = pd.read_csv('http://suprath.com/Smart_Diagnostic_Tool/credit.csv')"
],
"execution_count": 0,
"outputs": []
},
{
"metadata": {
"id": "ybwMLKQIzcxr",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 379
},
"outputId": "ff25bd3c-4ad9-46f3-d4b0-58b38440486c"
},
"cell_type": "code",
"source": [
"data.head(10)"
],
"execution_count": 15,
"outputs": [
{
"output_type": "execute_result",
"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>checking_balance</th>\n",
" <th>months_loan_duration</th>\n",
" <th>credit_history</th>\n",
" <th>purpose</th>\n",
" <th>amount</th>\n",
" <th>savings_balance</th>\n",
" <th>employment_duration</th>\n",
" <th>percent_of_income</th>\n",
" <th>years_at_residence</th>\n",
" <th>age</th>\n",
" <th>other_credit</th>\n",
" <th>housing</th>\n",
" <th>existing_loans_count</th>\n",
" <th>job</th>\n",
" <th>dependents</th>\n",
" <th>phone</th>\n",
" <th>default</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>&lt; 0 DM</td>\n",
" <td>6</td>\n",
" <td>critical</td>\n",
" <td>furniture/appliances</td>\n",
" <td>1169</td>\n",
" <td>unknown</td>\n",
" <td>&gt; 7 years</td>\n",
" <td>4</td>\n",
" <td>4</td>\n",
" <td>67</td>\n",
" <td>none</td>\n",
" <td>own</td>\n",
" <td>2</td>\n",
" <td>skilled</td>\n",
" <td>1</td>\n",
" <td>yes</td>\n",
" <td>no</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>1 - 200 DM</td>\n",
" <td>48</td>\n",
" <td>good</td>\n",
" <td>furniture/appliances</td>\n",
" <td>5951</td>\n",
" <td>&lt; 100 DM</td>\n",
" <td>1 - 4 years</td>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" <td>22</td>\n",
" <td>none</td>\n",
" <td>own</td>\n",
" <td>1</td>\n",
" <td>skilled</td>\n",
" <td>1</td>\n",
" <td>no</td>\n",
" <td>yes</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>unknown</td>\n",
" <td>12</td>\n",
" <td>critical</td>\n",
" <td>education</td>\n",
" <td>2096</td>\n",
" <td>&lt; 100 DM</td>\n",
" <td>4 - 7 years</td>\n",
" <td>2</td>\n",
" <td>3</td>\n",
" <td>49</td>\n",
" <td>none</td>\n",
" <td>own</td>\n",
" <td>1</td>\n",
" <td>unskilled</td>\n",
" <td>2</td>\n",
" <td>no</td>\n",
" <td>no</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>&lt; 0 DM</td>\n",
" <td>42</td>\n",
" <td>good</td>\n",
" <td>furniture/appliances</td>\n",
" <td>7882</td>\n",
" <td>&lt; 100 DM</td>\n",
" <td>4 - 7 years</td>\n",
" <td>2</td>\n",
" <td>4</td>\n",
" <td>45</td>\n",
" <td>none</td>\n",
" <td>other</td>\n",
" <td>1</td>\n",
" <td>skilled</td>\n",
" <td>2</td>\n",
" <td>no</td>\n",
" <td>no</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>&lt; 0 DM</td>\n",
" <td>24</td>\n",
" <td>poor</td>\n",
" <td>car</td>\n",
" <td>4870</td>\n",
" <td>&lt; 100 DM</td>\n",
" <td>1 - 4 years</td>\n",
" <td>3</td>\n",
" <td>4</td>\n",
" <td>53</td>\n",
" <td>none</td>\n",
" <td>other</td>\n",
" <td>2</td>\n",
" <td>skilled</td>\n",
" <td>2</td>\n",
" <td>no</td>\n",
" <td>yes</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>unknown</td>\n",
" <td>36</td>\n",
" <td>good</td>\n",
" <td>education</td>\n",
" <td>9055</td>\n",
" <td>unknown</td>\n",
" <td>1 - 4 years</td>\n",
" <td>2</td>\n",
" <td>4</td>\n",
" <td>35</td>\n",
" <td>none</td>\n",
" <td>other</td>\n",
" <td>1</td>\n",
" <td>unskilled</td>\n",
" <td>2</td>\n",
" <td>yes</td>\n",
" <td>no</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>unknown</td>\n",
" <td>24</td>\n",
" <td>good</td>\n",
" <td>furniture/appliances</td>\n",
" <td>2835</td>\n",
" <td>500 - 1000 DM</td>\n",
" <td>&gt; 7 years</td>\n",
" <td>3</td>\n",
" <td>4</td>\n",
" <td>53</td>\n",
" <td>none</td>\n",
" <td>own</td>\n",
" <td>1</td>\n",
" <td>skilled</td>\n",
" <td>1</td>\n",
" <td>no</td>\n",
" <td>no</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>1 - 200 DM</td>\n",
" <td>36</td>\n",
" <td>good</td>\n",
" <td>car</td>\n",
" <td>6948</td>\n",
" <td>&lt; 100 DM</td>\n",
" <td>1 - 4 years</td>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" <td>35</td>\n",
" <td>none</td>\n",
" <td>rent</td>\n",
" <td>1</td>\n",
" <td>management</td>\n",
" <td>1</td>\n",
" <td>yes</td>\n",
" <td>no</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>unknown</td>\n",
" <td>12</td>\n",
" <td>good</td>\n",
" <td>furniture/appliances</td>\n",
" <td>3059</td>\n",
" <td>&gt; 1000 DM</td>\n",
" <td>4 - 7 years</td>\n",
" <td>2</td>\n",
" <td>4</td>\n",
" <td>61</td>\n",
" <td>none</td>\n",
" <td>own</td>\n",
" <td>1</td>\n",
" <td>unskilled</td>\n",
" <td>1</td>\n",
" <td>no</td>\n",
" <td>no</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>1 - 200 DM</td>\n",
" <td>30</td>\n",
" <td>critical</td>\n",
" <td>car</td>\n",
" <td>5234</td>\n",
" <td>&lt; 100 DM</td>\n",
" <td>unemployed</td>\n",
" <td>4</td>\n",
" <td>2</td>\n",
" <td>28</td>\n",
" <td>none</td>\n",
" <td>own</td>\n",
" <td>2</td>\n",
" <td>management</td>\n",
" <td>1</td>\n",
" <td>no</td>\n",
" <td>yes</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" checking_balance months_loan_duration credit_history purpose \\\n",
"0 < 0 DM 6 critical furniture/appliances \n",
"1 1 - 200 DM 48 good furniture/appliances \n",
"2 unknown 12 critical education \n",
"3 < 0 DM 42 good furniture/appliances \n",
"4 < 0 DM 24 poor car \n",
"5 unknown 36 good education \n",
"6 unknown 24 good furniture/appliances \n",
"7 1 - 200 DM 36 good car \n",
"8 unknown 12 good furniture/appliances \n",
"9 1 - 200 DM 30 critical car \n",
"\n",
" amount savings_balance employment_duration percent_of_income \\\n",
"0 1169 unknown > 7 years 4 \n",
"1 5951 < 100 DM 1 - 4 years 2 \n",
"2 2096 < 100 DM 4 - 7 years 2 \n",
"3 7882 < 100 DM 4 - 7 years 2 \n",
"4 4870 < 100 DM 1 - 4 years 3 \n",
"5 9055 unknown 1 - 4 years 2 \n",
"6 2835 500 - 1000 DM > 7 years 3 \n",
"7 6948 < 100 DM 1 - 4 years 2 \n",
"8 3059 > 1000 DM 4 - 7 years 2 \n",
"9 5234 < 100 DM unemployed 4 \n",
"\n",
" years_at_residence age other_credit housing existing_loans_count \\\n",
"0 4 67 none own 2 \n",
"1 2 22 none own 1 \n",
"2 3 49 none own 1 \n",
"3 4 45 none other 1 \n",
"4 4 53 none other 2 \n",
"5 4 35 none other 1 \n",
"6 4 53 none own 1 \n",
"7 2 35 none rent 1 \n",
"8 4 61 none own 1 \n",
"9 2 28 none own 2 \n",
"\n",
" job dependents phone default \n",
"0 skilled 1 yes no \n",
"1 skilled 1 no yes \n",
"2 unskilled 2 no no \n",
"3 skilled 2 no no \n",
"4 skilled 2 no yes \n",
"5 unskilled 2 yes no \n",
"6 skilled 1 no no \n",
"7 management 1 yes no \n",
"8 unskilled 1 no no \n",
"9 management 1 no yes "
]
},
"metadata": {
"tags": []
},
"execution_count": 15
}
]
},
{
"metadata": {
"id": "UEDknbkPzlCx",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 34
},
"outputId": "8d71516e-c217-4267-ab79-7cfe04885fdc"
},
"cell_type": "code",
"source": [
"data.shape"
],
"execution_count": 6,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"(1000, 17)"
]
},
"metadata": {
"tags": []
},
"execution_count": 6
}
]
},
{
"metadata": {
"id": "pKmLMWvYJj1Q",
"colab_type": "text"
},
"cell_type": "markdown",
"source": [
"So its a small dataset with **1000 entries and 17 columns**\n",
"\n",
"The target variable is *'default'* which has only two values *Yes* and *No*"
]
},
{
"metadata": {
"id": "97kMhkxnJtDL",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 323
},
"outputId": "744b3f98-456d-4678-a3fe-7a1330cf7c1c"
},
"cell_type": "code",
"source": [
"# check data types for each column\n",
"data.dtypes"
],
"execution_count": 65,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"checking_balance object\n",
"months_loan_duration int64\n",
"credit_history object\n",
"purpose object\n",
"amount int64\n",
"savings_balance object\n",
"employment_duration object\n",
"percent_of_income int64\n",
"years_at_residence int64\n",
"age int64\n",
"other_credit object\n",
"housing object\n",
"existing_loans_count int64\n",
"job object\n",
"dependents int64\n",
"phone object\n",
"default object\n",
"dtype: object"
]
},
"metadata": {
"tags": []
},
"execution_count": 65
}
]
},
{
"metadata": {
"id": "qOYEd1m8Ka8N",
"colab_type": "text"
},
"cell_type": "markdown",
"source": [
"*Most of the features (columns) are categorical*"
]
},
{
"metadata": {
"id": "SwY13EDz0uF8",
"colab_type": "code",
"colab": {}
},
"cell_type": "code",
"source": [
"# separating the numeric and categorical cols\n",
"data_num = data.select_dtypes(include=[np.number])\n",
"data_cat = data.select_dtypes(include='object')"
],
"execution_count": 0,
"outputs": []
},
{
"metadata": {
"id": "paQQXBmNVjYy",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 204
},
"outputId": "b3a6d147-0cc7-47fd-e5bb-cbc4266fb4b1"
},
"cell_type": "code",
"source": [
"data_num.head()"
],
"execution_count": 69,
"outputs": [
{
"output_type": "execute_result",
"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>months_loan_duration</th>\n",
" <th>amount</th>\n",
" <th>percent_of_income</th>\n",
" <th>years_at_residence</th>\n",
" <th>age</th>\n",
" <th>existing_loans_count</th>\n",
" <th>dependents</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>6</td>\n",
" <td>1169</td>\n",
" <td>4</td>\n",
" <td>4</td>\n",
" <td>67</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>48</td>\n",
" <td>5951</td>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" <td>22</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>12</td>\n",
" <td>2096</td>\n",
" <td>2</td>\n",
" <td>3</td>\n",
" <td>49</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>42</td>\n",
" <td>7882</td>\n",
" <td>2</td>\n",
" <td>4</td>\n",
" <td>45</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>24</td>\n",
" <td>4870</td>\n",
" <td>3</td>\n",
" <td>4</td>\n",
" <td>53</td>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" months_loan_duration amount percent_of_income years_at_residence age \\\n",
"0 6 1169 4 4 67 \n",
"1 48 5951 2 2 22 \n",
"2 12 2096 2 3 49 \n",
"3 42 7882 2 4 45 \n",
"4 24 4870 3 4 53 \n",
"\n",
" existing_loans_count dependents \n",
"0 2 1 \n",
"1 1 1 \n",
"2 1 2 \n",
"3 1 2 \n",
"4 2 2 "
]
},
"metadata": {
"tags": []
},
"execution_count": 69
}
]
},
{
"metadata": {
"id": "YLq7hvfDVmSD",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 204
},
"outputId": "274dd979-ace9-4b9c-afb4-5772ad6196c5"
},
"cell_type": "code",
"source": [
"data_cat.head()"
],
"execution_count": 70,
"outputs": [
{
"output_type": "execute_result",
"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>checking_balance</th>\n",
" <th>credit_history</th>\n",
" <th>purpose</th>\n",
" <th>savings_balance</th>\n",
" <th>employment_duration</th>\n",
" <th>other_credit</th>\n",
" <th>housing</th>\n",
" <th>job</th>\n",
" <th>phone</th>\n",
" <th>default</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>&lt; 0 DM</td>\n",
" <td>critical</td>\n",
" <td>furniture/appliances</td>\n",
" <td>unknown</td>\n",
" <td>&gt; 7 years</td>\n",
" <td>none</td>\n",
" <td>own</td>\n",
" <td>skilled</td>\n",
" <td>yes</td>\n",
" <td>no</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>1 - 200 DM</td>\n",
" <td>good</td>\n",
" <td>furniture/appliances</td>\n",
" <td>&lt; 100 DM</td>\n",
" <td>1 - 4 years</td>\n",
" <td>none</td>\n",
" <td>own</td>\n",
" <td>skilled</td>\n",
" <td>no</td>\n",
" <td>yes</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>unknown</td>\n",
" <td>critical</td>\n",
" <td>education</td>\n",
" <td>&lt; 100 DM</td>\n",
" <td>4 - 7 years</td>\n",
" <td>none</td>\n",
" <td>own</td>\n",
" <td>unskilled</td>\n",
" <td>no</td>\n",
" <td>no</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>&lt; 0 DM</td>\n",
" <td>good</td>\n",
" <td>furniture/appliances</td>\n",
" <td>&lt; 100 DM</td>\n",
" <td>4 - 7 years</td>\n",
" <td>none</td>\n",
" <td>other</td>\n",
" <td>skilled</td>\n",
" <td>no</td>\n",
" <td>no</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>&lt; 0 DM</td>\n",
" <td>poor</td>\n",
" <td>car</td>\n",
" <td>&lt; 100 DM</td>\n",
" <td>1 - 4 years</td>\n",
" <td>none</td>\n",
" <td>other</td>\n",
" <td>skilled</td>\n",
" <td>no</td>\n",
" <td>yes</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" checking_balance credit_history purpose savings_balance \\\n",
"0 < 0 DM critical furniture/appliances unknown \n",
"1 1 - 200 DM good furniture/appliances < 100 DM \n",
"2 unknown critical education < 100 DM \n",
"3 < 0 DM good furniture/appliances < 100 DM \n",
"4 < 0 DM poor car < 100 DM \n",
"\n",
" employment_duration other_credit housing job phone default \n",
"0 > 7 years none own skilled yes no \n",
"1 1 - 4 years none own skilled no yes \n",
"2 4 - 7 years none own unskilled no no \n",
"3 4 - 7 years none other skilled no no \n",
"4 1 - 4 years none other skilled no yes "
]
},
"metadata": {
"tags": []
},
"execution_count": 70
}
]
},
{
"metadata": {
"id": "PJfsRo9qUx7G",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 323
},
"outputId": "96f38cca-cd5c-4f6d-f198-5edd1b67a848"
},
"cell_type": "code",
"source": [
"# check for nulls\n",
"data.isnull().sum()"
],
"execution_count": 76,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"checking_balance 0\n",
"months_loan_duration 0\n",
"credit_history 0\n",
"purpose 0\n",
"amount 0\n",
"savings_balance 0\n",
"employment_duration 0\n",
"percent_of_income 0\n",
"years_at_residence 0\n",
"age 0\n",
"other_credit 0\n",
"housing 0\n",
"existing_loans_count 0\n",
"job 0\n",
"dependents 0\n",
"phone 0\n",
"default 0\n",
"dtype: int64"
]
},
"metadata": {
"tags": []
},
"execution_count": 76
}
]
},
{
"metadata": {
"id": "SAo0GUumKqig",
"colab_type": "text"
},
"cell_type": "markdown",
"source": [
"No explicit null values in the dataset"
]
},
{
"metadata": {
"id": "TzgyDHyfzsRg",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 297
},
"outputId": "10936d16-3df1-4d5a-b803-98547cccd1eb"
},
"cell_type": "code",
"source": [
"# get numeric data statistics\n",
"data_num.describe()"
],
"execution_count": 77,
"outputs": [
{
"output_type": "execute_result",
"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>months_loan_duration</th>\n",
" <th>amount</th>\n",
" <th>percent_of_income</th>\n",
" <th>years_at_residence</th>\n",
" <th>age</th>\n",
" <th>existing_loans_count</th>\n",
" <th>dependents</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>count</th>\n",
" <td>1000.000000</td>\n",
" <td>1000.000000</td>\n",
" <td>1000.000000</td>\n",
" <td>1000.000000</td>\n",
" <td>1000.000000</td>\n",
" <td>1000.000000</td>\n",
" <td>1000.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>mean</th>\n",
" <td>20.903000</td>\n",
" <td>3271.258000</td>\n",
" <td>2.973000</td>\n",
" <td>2.845000</td>\n",
" <td>35.546000</td>\n",
" <td>1.407000</td>\n",
" <td>1.155000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>std</th>\n",
" <td>12.058814</td>\n",
" <td>2822.736876</td>\n",
" <td>1.118715</td>\n",
" <td>1.103718</td>\n",
" <td>11.375469</td>\n",
" <td>0.577654</td>\n",
" <td>0.362086</td>\n",
" </tr>\n",
" <tr>\n",
" <th>min</th>\n",
" <td>4.000000</td>\n",
" <td>250.000000</td>\n",
" <td>1.000000</td>\n",
" <td>1.000000</td>\n",
" <td>19.000000</td>\n",
" <td>1.000000</td>\n",
" <td>1.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25%</th>\n",
" <td>12.000000</td>\n",
" <td>1365.500000</td>\n",
" <td>2.000000</td>\n",
" <td>2.000000</td>\n",
" <td>27.000000</td>\n",
" <td>1.000000</td>\n",
" <td>1.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50%</th>\n",
" <td>18.000000</td>\n",
" <td>2319.500000</td>\n",
" <td>3.000000</td>\n",
" <td>3.000000</td>\n",
" <td>33.000000</td>\n",
" <td>1.000000</td>\n",
" <td>1.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>75%</th>\n",
" <td>24.000000</td>\n",
" <td>3972.250000</td>\n",
" <td>4.000000</td>\n",
" <td>4.000000</td>\n",
" <td>42.000000</td>\n",
" <td>2.000000</td>\n",
" <td>1.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>max</th>\n",
" <td>72.000000</td>\n",
" <td>18424.000000</td>\n",
" <td>4.000000</td>\n",
" <td>4.000000</td>\n",
" <td>75.000000</td>\n",
" <td>4.000000</td>\n",
" <td>2.000000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" months_loan_duration amount percent_of_income \\\n",
"count 1000.000000 1000.000000 1000.000000 \n",
"mean 20.903000 3271.258000 2.973000 \n",
"std 12.058814 2822.736876 1.118715 \n",
"min 4.000000 250.000000 1.000000 \n",
"25% 12.000000 1365.500000 2.000000 \n",
"50% 18.000000 2319.500000 3.000000 \n",
"75% 24.000000 3972.250000 4.000000 \n",
"max 72.000000 18424.000000 4.000000 \n",
"\n",
" years_at_residence age existing_loans_count dependents \n",
"count 1000.000000 1000.000000 1000.000000 1000.000000 \n",
"mean 2.845000 35.546000 1.407000 1.155000 \n",
"std 1.103718 11.375469 0.577654 0.362086 \n",
"min 1.000000 19.000000 1.000000 1.000000 \n",
"25% 2.000000 27.000000 1.000000 1.000000 \n",
"50% 3.000000 33.000000 1.000000 1.000000 \n",
"75% 4.000000 42.000000 2.000000 1.000000 \n",
"max 4.000000 75.000000 4.000000 2.000000 "
]
},
"metadata": {
"tags": []
},
"execution_count": 77
}
]
},
{
"metadata": {
"id": "26-rYhMu0iRk",
"colab_type": "code",
"colab": {}
},
"cell_type": "code",
"source": [
"from matplotlib import cm as cm\n",
"def correlation_matrix(df, labels):\n",
" fig = plt.figure()\n",
" ax1 = fig.add_subplot(111)\n",
" cmap = cm.get_cmap('jet', 30)\n",
" cax = ax1.imshow(df.corr(), interpolation=\"nearest\", cmap=cmap)\n",
" ax1.grid(True)\n",
" plt.title('Feature Correlation')\n",
" ax1.set_xticklabels(labels,fontsize=6)\n",
" ax1.set_yticklabels(labels,fontsize=6)\n",
" fig.colorbar(cax, ticks=[.75,.8,.85,.90,.95,1])\n",
" plt.show()"
],
"execution_count": 0,
"outputs": []
},
{
"metadata": {
"id": "kzePxizJWmLB",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 357
},
"outputId": "adab60c7-a7d3-4da8-c8f6-7d3eb169a69a"
},
"cell_type": "code",
"source": [
"# find correlation between numeric data types\n",
"correlation_matrix(data_num, labels=['', 'Loan Duration','Amount','% Income','Residence Years','Age','Loan Count','Dependents'])"
],
"execution_count": 90,
"outputs": [
{
"output_type": "display_data",
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAa4AAAFUCAYAAAB8/NjlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4yLCBo\ndHRwOi8vbWF0cGxvdGxpYi5vcmcvNQv5yAAAIABJREFUeJzt3XtYlGXeB/DvMxxE5ZCDgCUoBpQo\nZB5WQWNXcWyUXDS1stLoSpfVVrfTJh7qBStJ6/VtV3JbNa/VN4uEPKS+tZ7XTRsQDxiGCeJplAUF\nQRAlGLjfP5CJWWBAeEa45fu5rq6Eee7f83vm4Nf7mWfuUYQQAkRERJLQtHUDREREd4LBRUREUmFw\nERGRVBhcREQkFQYXERFJhcFFRERSsW/rBqjjevjhh9GrVy/Y2dmZf9ezZ0+sXbu2RfUqKirwzTff\nYOLEiWq12OA+Vq5ciZ07d6L2kyRjx47FH/7wBzg6Otpkn6mpqXjrrbewe/duq9udOHECnTp1Qt++\nfbFhwwYUFBTg1VdftUlPRG2JwUVt6rPPPkOPHj1UqZWZmYmtW7faNLjmzZuHW7duISkpCa6urigu\nLkZMTAwWLFiA5cuX22y/zbFp0yYMHjwYffv2xbRp09q0FyJb4qlCapfy8vIwa9Ys6PV66PV6HDhw\nwHxbcnIyxo0bh8cffxzPP/88Ll++jIKCAsyZMwfp6el47rnncOnSJfTr1888pu7Pmzdvxpw5cxAV\nFYUPPvgAALBx40aMHTsW4eHheP3111FeXl6vp+zsbBw4cADLli2Dq6srAOC+++5DfHw8pkyZAgAo\nLi7GK6+8Ar1ej4iICKxevdo8/uGHH8aqVaug1+tRVVWF8PBwfPzxx9Dr9cjNzbV6zLVu3bqFV199\nFXq9HuHh4Vi2bBkAIDExEV9//TU+/PBD/P3vf0dCQgIWLVoEAMjNzcWMGTOg1+sxfvx4bN261Xyf\nPPbYY/jf//1f/Pa3v0VYWBi++eablj9oRHeLIGojDz30kPj3v//d4G0vvPCC+Oijj4QQQpw/f14M\nHTpUXLt2TRQUFIigoCDzuPnz54uFCxcKIYTYtGmTiIqKEkIIYTQaRWBgoLle3Z83bdokHn30UXHu\n3DkhhBBpaWkiNDRU5OXlCSGEePvtt8XSpUvr9bRhwwbx4osvWj2mt99+W7z99ttCCCGKiorEyJEj\nRVpamvl4P/nkE/O2o0aNEm+99VaTx5ySkiJ0Op0QQoi1a9eKmTNniurqalFcXCyGDh1qrj9t2jSx\ndetWIYQQK1asMN8vL730kvjb3/4mhBDi0qVLYvDgwcJoNAqj0Sj69esnPvvsMyGEEN98840YM2aM\n1eMjag8446I2NX36dIwdO9b831tvvYWbN28iNTUVL774IgCgd+/eGDx4MA4cOAB3d3ccPXrUfHpx\nyJAhMBqNd7xfX19f+Pr6AgD27duHiIgIeHl5AQCeffZZ7Nq1q96Y69evw93d3WrdAwcO4LnnngNQ\nMxsbM2YMDh06ZL595MiRFtvX/mztmOt66aWX8Ne//hWKosDNzQ0BAQG4dOlSo/1UVlbi+++/N/fU\ns2dPDBs2DCkpKQAAk8mESZMmAQD69++P3Nxcq8dH1B7wPS5qUw29x5Wfnw8hBKZOnWr+3c2bNxES\nEoKqqiqsWLEC+/btQ1VVFcrKytCnT5873q+bm5v5z6Wlpdi9ezcOHjwIABBCoLKyst6Ybt26IT8/\n32rda9eumU8jAoCrqyuuXLli/vm+++5rsI/S0tJGj/n+++83/+78+fNYunQpzp49C41Gg7y8PHPw\nNKS4uBhCCLi4uFj0dO3aNQCAnZ0dunTpAgDQaDSorq62enxE7QGDi9odd3d32NnZYdOmTejatavF\nbdu3b8e+ffuwYcMGaLVaJCUlYfv27fVq2NnZobq6GkIIKIqCkpKSRvfn6emJJ598EjExMVb7Gjp0\nKN5//33k5+ebZ2cAUFJSgr///e/44x//iO7du6O4uBgPPPAAgJrg6N69e6uOOTU11fznd955B/37\n98fKlSthZ2dnEXQN6datGzQaDa5fv24OyeLi4iZnjkTtGU8VUrtjb2+P3/zmN/jyyy8B1FyQsGDB\nAvz73/9GYWEhevbsCa1Wi6KiInz77bcoKyszj7tx4waEEOjWrRvs7Oxw+vRpADBfkNCQ8PBw7Nq1\nyzwL2bNnj8VFFbX8/PwQERGB119/HQUFBQBqQuD1119HUVERFEXByJEjsXHjRgA1s6/du3fXOz14\np8dcV2FhIQIDA2FnZ4dDhw7hwoULuHnzprlGaWlpvbqPPfaYuaeLFy/iyJEjGD58eJM9EbVXDC5q\nl+Li4pCWloaxY8fiySefhI+PD+6//36MHz8excXFGDNmDN544w28+uqryMvLw9KlSzF48GBcuXIF\nYWFhcHBwwNy5czFz5kxMmjQJgYGBje6rf//+mDVrFqZPn45x48Zh3bp1GD16dIPbvvvuuxg2bBie\nf/55jB07FtOnT8ewYcPwX//1XwCAV199FSUlJRg7diymTZuG6OhoPPLII6065rpmz56NZcuWYfz4\n8Th8+DDmzJmDhIQEHD16FDqdDv/93/+N999/32LM4sWLkZqaav682XvvvVevLpFMFCH4fVxERCQP\nzriIiEgqDC4iIlJNVlYWdDodNmzYUO+277//HlOmTMEzzzyDlStXmn8fHx+PZ555BlOnTsUPP/zQ\n5D54VSEREani5s2bePfddxEaGtrg7e+99x7Wrl0LLy8vTJs2DXq9HteuXcOFCxewceNG5OTkYOHC\nheaLiRrDGRcREanC0dERa9asgaenZ73bjEYj3NzccP/990Oj0eA3v/kNDAYDDAYDdDodgJord69f\nv44bN25Y3Q+Di4iIVGFvbw8nJ6cGb7t69Sq0Wq35Z61Wi6tXr6KgoADdunWr93ur+1GnXXnEKYpN\n6r6ckYG/BgerWjNui6rlaoRnAPvU7VO5YpsLUzOmAMFfqVw0R+V6t2W8BgR/pHLR+qtOtVpGMhD8\nlMpF/VSud1vG/wDBr6tc1FaPvw3uV3Fc3Xq1Frfi78DYu3ARenMudO9wwWUrnkFBbd1C87hK0ieA\nIG3T27QXQep8M4vNBfm3dQfNF9SrrTtoPpnu17bi6elp/uA+ULO0m6enJxwcHCx+f+XKFXh4eFit\nxVOFRERkc97e3rhx4wYuXboEk8mE/fv3Y8SIERgxYgR27twJAPjxxx/h6ekJZ2dnq7U44yIiIlWc\nPHkSy5Ytw+XLl2Fvb4+dO3ciPDwc3t7eGDNmDOLi4vDGG28AACIiItCnTx/06dMH/fv3x9SpU6Eo\nCmJjY5vcD4OLiIhUERQUhM8++6zR23/1q181eKn7n/70pzvaD08VEhGRVBhcREQkFQYXERFJhe9x\nERGRauLj43HixAkoioKFCxdafK3Pnj178Mknn8DR0RFPPPEEpk2bhtTUVLzyyisICAgAADz00EN4\n++23re6DwUVERKo4fPhwo+sOVldX491338WWLVtw33334Xe/+515qaehQ4dixYoVzd4Pg4uIqAN5\n2Ia1G1t30NnZGUVFRXB1dTUv+xQSEoLvv/8ePXv2vOP98D0uIiJShbV1B7VaLcrKynD+/HlUVlYi\nNTXVvGLGmTNnMGvWLDz77LM4dOhQk/vhjIuIiGyi7rqDiqJg6dKlWLhwIVxcXODt7Q0A8PX1xZw5\nczBu3DgYjUa88MIL2LVrFxwdHRutyxkXERGp4j/XI/zPdQeHDh2KL774AqtWrYKLiwt69uwJLy8v\nREREQFEU9OrVC927d0d+fr7V/TC4iIhIFU2tOzhz5kwUFhbi5s2b2L9/P0JDQ7Ft2zasXbsWQM1X\nnxQWFsLLy8vqfniqkIiIVDFo0KB66w5u3rwZLi4uGDNmDJ5++mm89NJLUBQF0dHR0Gq1CA8Px5/+\n9Cfs3bsXlZWViIuLs3qaEGBwERGRiv5z3cG+ffua//z444/j8ccft7jd2dkZf/vb3+5oHzxVSERE\nUmFwERGRVBhcREQklVa9x5WQkICoqCi4urq2aGznzp2hKAo8PDwQGRnZ5JiLFy+ic+fOOHPmDEJD\nQ1vSMhFRh9a36U1a5U7XKmxqTENUuzgjNzcXycnJcHBwgF6vx+7du+Hg4ABfX18YDAaEhIQgLS0N\nCxYsMI95+umn4erqivj4eHh4eKCsrAwuLi4oLS3Ftm3b8Pzzz+P06dNwdHSEoijIz89Hjx49kJ2d\nDWdnZxgMBpSVlUGn0yEpKQl+fn4ICAjAiBEjGu3z5YwMeAYFqXXYFuLqfNiuXZuobp+2PGoRbcPi\nKhPLVC6odr3bxHHb1LUF8VVbd9B8Mt2vttKStQovXrzY6JjGqBZc6enpGDVqFJydnZGWlgYXFxd0\n7doVmZmZUBQFOp0OqampDY6trq6GoigAfvmktaenJ4YNGwaj0QgnJyecOHECgYGBCAwMRHZ2NgwG\nAyZPnozMzExkZmbCz88POp0Oe/futRpcfw0OVuuQLcQJgbjbx6BazS2qlqsxUQBb1e1TuWKb6BLR\ngLJa5aI5Kte7TSwDlBiVi+5SuR5q/nJVBqpc1E/lereJrwBlispFbfX42+B+lTEIW7JWodFobHRM\nY1r9HldSUhI2bNiAAQMGYO/evfj2228xePBgnD17Fo6OjjAajVbHrl69GgMGDMADDzyAY8eO4fjx\nmkerNsh++ukn2NnZoaCgAB4eHjh8+DAAIDQ0FMnJyThy5Aj69etnrilkmfUQEd1jWrJWobUxjWnV\njGvu3LkWP7/22mvmP9d+n0pERIT5d4sWLWp0LADMmzfP/OfaBH7rrbcAAOPGjQMAhIWFmbcJrjN7\nqv3ziy++eGcHQURENtGctQqtjWkMP4BMRESqaO5ahQCwfPly9OzZEz///LPVMQ3h5fBERKSKlqxV\n2NSYhnDGRUREqmjJWoVarbbemKYwuIiISDV3ulZhQ2OawlOFREQkFc64iIg6kL4ubd1B6zG4iIhI\nNdaWb/r888+xbds2aDQaBAUFYdGiRdi8eTP+8pe/oFevXgCA4cOHY/bs2Vb3weAiIiJVWFvy6caN\nG1i7di127doFe3t7vPTSS0hPTwdQ83nfmJjmLz3D97iIiEgVjS35BAAODg5wcHDAzZs3YTKZcOvW\nLbi5ubVoPwwuIiJShbXlmzp16oQ//OEP0Ol0GDVqFAYMGIA+ffoAqJmpzZgxA1FRUcjMzGxyPzxV\nSERENlF3+aYbN25g1apV+Mc//gFnZ2dERUXhp59+woABA6DVajFy5EgcP34cMTEx2L59u9W6nHER\nEZEqrC35lJOTAx8fH2i1Wjg6OmLIkCE4efIk/Pz8MHLkSADAwIEDce3aNVRVVVndD4OLiIhUYW35\npp49eyInJwfl5eUAgJMnT8LX1xdr1qzBjh07AABZWVnQarWws7Ozuh+eKiQiIlU0teTTjBkz8MIL\nL8DOzg4DBw7EkCFD4O3tjTfffBNffvklTCYTlixZ0uR+GFxERKQaa0s+TZ06FVOnTrW4vUePHvjs\ns8/uaB8MLiKiDsTJt607aD2+x0VERFJhcBERkVQ63KnCuC3y1I57Ut16ABAnbFE3Tu2CNaLjgN+r\nXHueyvVsqf63P7TPujkq17MlP0lrS+RO1yqsrKzE/PnzkZubCzs7O7z//vvw8fGxug/OuIiISBV1\n1ypcsmSJxRWCtWsVfv7550hMTEROTg7S09OxY8cOuLq6IjExEbNmzcLy5cub3A+Di4iIVNGStQoN\nBgPGjBkDoGZl+GPHjjW5HwYXERGpoiVrFRYUFECr1QIANBoNFEVBRUWF1f10uPe4iIjo7mjOWoXW\nxjSGMy4iIlJFS9Yq9PT0NM/KKisrIYSAo6Oj1f0wuIiISBUtWatwxIgR+Mc//gEA2L9/P4YNG9bk\nfniqkIioI+lju9ItWauwqqoK33//PZ599lk4Ojpi6dKlTe6HwUVERKq507UKaz+7dSd4qpCIiKTC\n4CIiIqkwuIiISCp8j4uIiFTT2FqF+fn5Fu9/GY1GvPHGG6isrMRf/vIX9OrVC0DN6hmzZ8+2ug8G\nFxERqaLuWoU5OTlYuHAhNm7cCADw8vIyf2GkyWTC9OnTER4ejp07dyIiIgIxMTHN3g9PFRIRkSqs\nrVVY15YtW6DX69G1a9cW7YfBRUREqrC2VmFdycnJmDJlivnnw4cPY8aMGYiKikJmZmaT++GpQiIi\nsomG1h08fvw4HnzwQfOKGgMGDIBWq8XIkSNx/PhxxMTEYPv27VbrMriIiDoSX9uVtrZWYa1//vOf\nCA0NNf/s5+cHP7+ab+EcOHAgrl27hqqqKtjZ2TW6H54qJCIiVVhbq7BWRkaGxWoaa9aswY4dOwAA\nWVlZ0Gq1VkMLaCczrnXr1qGiogLR0dEtrnHy5EkEBASgU6dOKnZGRETN1dRahQBw9epVuLu7m8f8\n9re/xZtvvokvv/wSJpPJ4luTG9PmwVVZWWleLTg2NhZhYWHYu3cvRowYgZKSEjg5OaGqqgq5ubnw\n8fFBYGAgTp06hcDAQKxYsQJ6vR4mkwlpaWmIjIzEiBEj2viIiIg6LmtrFQKo9/5Vjx49zJfJN1eb\nB9fOnTthMpkA1FxKuXjxYhw9ehTjx4/HkiVLYGdnh/nz52P58uWorKwE8Msbft7e3pg4cSLi4+Ph\n7e2N4ODgpncYngG4BtnmYCY2/QVodyJO3XJ16qrcp6rVLAlhy+rqEsvauoPmkaVPABBftXUHzSdT\nr7Jr8+D68ccfzR88u3LlSr3b/f39kZycDHt7e/j5+eHAgQMoKChAv379zNsIIdCjRw+kpqaap6ON\n2teMcGuJiQLYqqhaMu5JVcvV1BQCcYq6fS5GrKr1agkRB0WJU7foPJXr3SaWAUrzPz/ZZmzSZ47K\n9W4TXwHKlKa3aw9s0SuDsHFtHlx1Py39zjvvWPxu0aJF9bYfMmSI+c+1tze0HRER3Zt4VSEREUmF\nwUVERFJhcBERkVTa/D0uIiK6i/q0dQOtxxkXERFJhcFFRERSYXAREZFUGFxERCQVBhcREUmFwUVE\nRFJhcBERkVQYXEREJBUGFxERSYUrZxARdSRcOYOIiOjuYnAREZFUGFxERCQVBhcREUmlw12coVwR\nNqkrbFI7TuV6NRUXI1bVmrFYrGq9X8SpXnuxDe5TksguSWuTBc64iIhIKgwuIiKSCoOLiIikwuAi\nIiKpdLiLM4iIOjTftm6g9TjjIiIiqTC4iIhIKgwuIiKSCoOLiIikwuAiIiKpMLiIiEgqDC4iIpIK\ng4uIiKTC4CIiIqlw5Qwiog7E1KflY9tLYHDGRUREUmFwERGRVBhcREQkFQYXERFJ5a4G144dO/DJ\nJ5+gsrISSUlJKC4uNt+WkJCAkpKSu9kOERFJ6K5eJFJeXg4PDw+kpKSgqKgI+/fvx4QJE6DR/JKf\ns2fPhl6vh8lkgr29PUpLS2Fvb49OnTqhqqoKubm58PHxQVlZGbKzsxESEoJTp05h3LhxOHjwIEpL\nSzFz5ky4ubndzUMjIqK75K4GV58+fZCTk4OzZ8/Cy8sLnTp1woULF9Cnzy/XZ3p7e2PixImIj4+H\nvb095s2bBwBYunQp5s+fj+XLl6OyshJDhgxBbm4uIiIicPz4cRw8eBBdunSBRqNBbm5uo8GVMQUI\n0trm+ES0ygWj41QuWEMIteuqXa9OZSHUradqNUtimQ2Lq0iWPgFAfNXWHTSf4Amju+auBtfgwYNx\n5swZTJ48Gf/617+QnZ2NsLCwBrcVQuDBBx9EYmIifv75Z/j7+yM5ORn29vZwcHCot/3w4cORkpIC\ne3t7+Pj4NNpDsI1eCCIaUFarXPT3cSoXrAktRVG3biwWq1qvVpwQiFMUVWsunqduENYSywAlxial\nVWWTPnNUrneb+ApQpqhcdJfK9W4TJYDiqn5Nathd/zzZM888AwCIiIiw+P3cuXMBAIsWLbL4vzWB\ngYEW2wYFBanWJxERtU/t5YPQRER0F1xy7dHisb7qtdEqvByeiIikwuAiIiKpMLiIiEgqDC4iIpIK\ng4uIiKTC4CIiIqkwuIiISCoMLiIikgqDi4iIpMKVM4iIOhAjvFs81le9NlqFMy4iIpIKg4uIiKTC\n4CIiIqkwuIiISCoMLiIikgqDi4iIpMLgIiIiqXS8z3HlSFR7XpzKBW1TdzHUrVcrDsDieULVmrEf\nKKrWM1smVK/9f+JfqtarEYYhy75TteKR1WGq1rPwuMr1/FSuV9dsG9YmC5xxERGRVDrejIuIqAO7\nBJ+2bqHVOOMiIiKpMLiIiEgqDC4iIpIKg4uIiKTC4CIiIqkwuIiISCoMLiIikgqDi4iIpMLgIiIi\nqXDlDCKiDuQSvNu6hVbjjIuIiKTC4CIiIqkwuIiISCoMLiIikgqDi4iIpMLgIiIiqTC4iIhIKlaD\nKyEhAZ9++inWr1+PNWvWWC1kMBgsxpWUlLS4KYPBgO3bt6OqqgrvvPMOTCZTi2sREdG9RRFCiMZu\nTEhIQFRUFFxdXfHee+9h5syZ2LhxIzQaDSIjI5GYmAh/f388+uij2LhxIwYNGoSioiKkpKRg4cKF\n+Pzzz+Hm5oZBgwYhOTkZOp0OGRkZ0Ol0OHDgAEwmE8aMGYODBw+itLQUM2fOhJubGwDg448/RnV1\nNSIiIlBRUWGxTWJiIhwcHODr6wuDwYDg4GAUFBTA3d0d7u7uCAsLa/SAT+YBQT3UvyOJiGTwIf7Y\n4rFvYoWKnbRckytnbN68GefOnUNYWBiOHTsGjUYDrVYLo9GIwMBA5OXloaKiAgDwww8/ICYmBteu\nXUN+fj7Kysrg6+sLo9EIZ2dnjB49GikpKTh06BCmT58OV1dXrF69Gl26dIFGo0Fubq45uGbMmIH4\n+Hj4+/tbbHPp0iW4uLiga9euyMzMBABMmDABaWlpSE9PR5cuXaweT/BHrb3LGiaWAUqMbWqrSZY+\nAdv0GvuBom7B2+KEQJyibu3/E/9StR4ApCEMv8J3qtY8srrxfyi2hogGlNUqF81Rud5ttniuimXq\n1qtlhI9tCt9FTb7HNWnSJLz88ss4ceIEBg4cCEVRUFVVhYCAAOTn50Or1eLcuXMAgP79+2PDhg3I\nysqCl5cXXFxcUFlZib59+1rUDA0NxRdffIEPP/wQw4cPR3l5Oezt7eHj88sd2rlzZzg5OQGAxTa9\nevXC2bNn4ejoCKPRCOX2XxZGoxHu7u64cOGCancOERG1P1ZPFd6LbDXbkGUmI0ufAGdcnHFxxmUL\nf8SHLR67Am+q2EnL8apCIiKSCoOLiIikwuAiIiKpMLiIiEgqDC4iIpIKg4uIiKTC4CIiIqk0uXIG\nERHdOy7Bu61baDXOuIiISCoMLiIikgqDi4iIpMLgIiIiqTC4iIhIKgwuIiKSCoOLiIikwuAiIiKp\nMLiIiEgqXDmDiKgDMd4DK2d0vODaZaO6y2xQ+3GV6xH+T/zLJnXjbFD7CeXXqtYDAAihet0je4Wq\n9Sz4t/N6deltWJss8FQhERFJhcFFRERSYXAREZFUGFxERCQVBhcREUmFwUVERFJhcBERkVQYXERE\nJJWO9wFkIqIO7BJ82rqFVuOMi4iIpMLgIiIiqTC4iIhIKgwuIiKSCoOLiIikwuAiIiKpMLiIiEgq\nDC4iIpIKg4uIiKQi1coZ69atQ0VFBaKjo9u6FSIiKeVd8G754N7q9dEa0gRXZWUlysvLAQDr16+H\ns7Mz9uzZg9jYWGzcuBEajQaRkZHo3bud3LNERGQTihBCtHUTzbFjxw6cP38eALB582bs27cPS5cu\nxSOPPIKcnBxotVr07t0bjz32mNU6J88AQf53oWEionZIuWBq8VjRu33MddpHF83w448/IiYmBkDN\njGvLli04f/48oqKicPbsWVRVVSEgIKDJOsFP2aY/cRxQBqpc9HGV6wEQywAlRv26tmCLXocs+07d\ngrelIQy/grq1n1B+rWo9AIgTAnGKomrNxXtt829fEQ4o+2xSWnW26FWEq1vvXiJNcNWGFgAkJCTg\n4sWL6N+/P+6//37MmTOnDTsjIqK7SZrgqiskJAQhISFt3QYREbUBXg5PRERSYXAREZFUGFxERCQV\nBhcREUlFyosziIiohXJa8dd+O1nfgTMuIiKSCoOLiIikwuAiIiKpMLiIiEgqDC4iIpIKg4uIiKTC\n4CIiIqkwuIiISCoMLiIikgpXziAi6khyWjG2nXy5JWdcREQkFQYXERFJpeOdKvSTqHZrpvRtUdcW\nVO71yOowdQvWila/9pG9QtV6ABAHYLHKdWNHK6rWMxNC9dqLV6l/nwKoOYV2xgY1qUGccRERkVQY\nXEREJBUGFxERSYXBRUREUmFwERGRVBhcREQklY53OTwRUUcm08dhGsEZFxERSYXBRUREUmFwERGR\nVBhcREQkFQYXERFJhcFFRERSYXAREZFUGFxERCQVBhcREUmFK2cQEXUkXDmDiIjo7mJwERGRVGwW\nXAkJCSgpKWnR2FOnTmHFihVYt24dVq5c2exxRUVFyMm5B+bBRETUqLvyHldubi6Sk5Ph4OAAvV6P\n3bt3w8HBAb6+vjAYDAgJCUFaWhoWLFgAANi0aRMWLlwIjUaDiooKZGRkwGAwoKysDDqdDkePHoVO\np8OePXtw+vRp6HQ6ZGRkwMfHBxcvXsRrr712Nw6LiIjawF0JrvT0dIwaNQrOzs5IS0uDi4sLunbt\niszMTCiKAp1Oh9TUVIsxQggAwM2bN2EwGDB58mRkZmYiMzPT4nZnZ2eMHj0aKSkp8Pb2hpubm9Ve\nMv4HCOplg4MEIL6yTV21ydInIFmv0W3dQfOIcLULCpUL/iJO5dpxqlazJMvjfy+waXAlJSXByckJ\no0aNQlJSEhwdHaHX65GYmIjBgwfDaDQ2GDSTJk3Cn//8Z7i7u6OyshKhoaFITk7GrVu3MHXqVKxa\ntQoGg6HeOK1Wi3/+85/Q6XSN9hT8uqqHaCa+ApQptqmtJln6BGzU6+Mq17tNRAPKapWL+qtcDzWh\npexTt2bsaEXdgrfFCYE4Rd3ai1fZJmRt8fgzCBunCGHDfy61Q7b6S1uWQJClT4DBxeBicNmC8lTL\nx4pk9fpoDV5VSEREUmFwERGLN9wzAAAKlElEQVSRVLhyBhFRR3KmrRtoPc64iIhIKgwuIiKSCoOL\niIikwuAiIiKpMLiIiEgqDC4iIpIKg4uIiKTC4CIiIqnwA8hERB3JPfCVhZxxERGRVBhcREQkFQYX\nERFJhcFFRERSYXAREZFUGFxERCSVjnc5vC0vBVW7tp/K9Wxll0S1bXmfqv34+6tcz0YWrxI2qRtn\ng9qxv1dUrWcWLdSvHW2b+/VewBkXERFJhcFFRERS6XinComIOrLS8lYMdlKtjdbgjIuIiKTC4CIi\nIqkwuIiISCoMLiIikgqDi4iIpMLgIiIiqTC4iIhIKgwuIiKSCoOLiIikwpUziIg6lJ9aMfZR1bpo\nDc64iIhIKgwuIiKSCoOLiIikwuAiIiKpMLiIiEgqDC4iIpKKTS6HT0hIQOfOnaEoCjw8PBAZGdni\nWkuWLMGiRYsavf3kyZMICAhAp06dWrwPIiKShyKEEGoXTUhIQFRUFFxdXbFgwQJ4eXnBzs4OkZGR\n+OCDDxAZGYm8vDz4+vri4sWLyM/Px1NPPYVPP/0Ufn5+CAgIQEZGBnx8fLBnzx787ne/w8GDB1Fa\nWoqZM2di/vz50Ov1MJlMSEtLQ2RkJL777jv4+/vj0Ucfhb+/f6O9nTwDBDV+MxHRPU1R0ls8Voj2\n8Tkum38AOT09HePGjYNWq4XRaISnpyf0ej0++ugjXL58GX379oWTkxMKCwvh5+cHnU6HvXv34vr1\n65g1axZOnDiBgwcPokuXLtBoNMjNzYW3tzcmTpyI+Ph4eHt7Izg4GAUFBcjLy0NFRYXVfoKfss1x\niuOAMlDlon4q1wMgvgKUKSoX3aVyvdtECaC4qlx0tsr1bhPLACVG5aJ6lesBEOGAsk/lomdUrneb\niAaU1erWjP29om7B2+KEQJyibu049ecU9wybBVdSUhKqq6sRHR2Ny5cvo6qqCgEBAUhMTMTXX3+N\nbt26YdCgQbh8+TJcXFzQvXt381ghBJydnbF161YUFhYiMjISKSkpsLe3h4+Pj8V2PXr0QGpqKvLz\n86HVanHu3Dn069fPVodFRCQ5+VfOsElwzZ07t9HbHnjgAUyYMKHB21588UWL/wPAxIkTAQBBQUHm\n39W+52XtvS8iIro33fWrChk2RETUGrwcnoiIpMLgIiIiqTC4iIhIKgwuIiKSCoOLiIikwuAiIiKp\nMLiIiEgqNl/yiYiI2pPTbd1Aq3HGRUREUmFwERGRVBhcREQkFQYXERFJhcFFRERSYXAREZFUGFxE\nRCQVBhcREUmFwUVERFJRhBCirZsgIiJqLs64iIhIKgwuIiKSCoOLiIikwuAiIiKpMLiIiEgqDC4i\nIpJKhw6uhIQElJSUtHjsp59+irVr12Lbtm3NGnPx4kVcvXoVBoOhRftsyrp167B69epW1Th58iR+\n/vlnlTr6xY4dO/DJJ5+gsrISSUlJKC4uNt/WmsfhTtQ+ZuvXr8eaNWusblv3MWptfwaDAdu3b0dV\nVRXeeecdmEymFte6U2o8J1qjNffdqVOnsGLFCqxbtw4rV65s9riioiLk5OTc0b5a8npuzJIlS6ze\nbqvXWEfCb0C+LTc3F8nJyXBwcIBer8fu3bvh4OAAX19fGAwGhISEIC0tDQsWLDCPefrpp+Hq6or4\n+Hh4eHigrKwMLi4uKC0txbZt2/D888/j9OnTcHR0hKIoyM/PR48ePZCdnQ1nZ2cYDAaUlZVBp9Mh\nKSkJfn5+CAgIwIgRI+64/8rKSpSXlwMAYmNjERYWhr1792LEiBEoKSmBk5MTqqqqkJubCx8fHwQG\nBuLUqVMIDAzEihUroNfrYTKZkJaWhsjIyBb1YE15eTk8PDyQkpKCoqIi7N+/HxMmTIBG88u/nWbP\nnm3uw97eHqWlpbC3t0enTp0sei8rK0N2djZCQkJw6tQpjBs3DgcPHkRpaSlmzpwJNze3Rvuofcze\ne+895OXlYePGjdBoNIiMjERiYiL8/f3x6KOPYt++fSguLkZRURGys7Nx8+ZNrFmzBm5ubhg0aBCS\nk5Oh0+mQkZEBnU6HAwcOwGQyYcyYMfV6CQ0Nxccff4yVK1fiueeeQ1ZWlsU2iYmJFs+14OBgFBQU\nwN3dHe7u7ggLC2vRfV73ObF+/Xo4Oztjz549iI2NtTju3r17t6j+nbrT19imTZuwcOFCaDQaVFRU\nICMjw+I1c/ToUeh0OuzZswenT582Px4+Pj64ePEiXnvttTvqr/a5sWDBApw9exZ2dnaIjIzEBx98\ngMjISOTl5cHX1xcXL15Efn4+nnrqKXz66afm123tvgsKCpCZmWnxGM+fP7/ea+y7774zP9/8/f1t\ncZffszr0jKuu9PR0jBo1CmPHjsWRI0fg4uICd3d3ZGZmQlEU6HQ6VFdXNzi2uroaiqIAAGo/z+3p\n6Ylhw4ahS5cucHZ2xpkzZ+Dt7Y3g4GAANf8Knzx5MoYMGYLMzEz4+flBp9PhzJkzLep/586dMJlM\nMJlMMBgM0Ol0uO+++zB+/HicO3cOWVlZeOqpp2AymVBZWWnRq7e3NyZOnIisrCyLHtXUp08fVFdX\n4+zZs/Dy8oKTkxMuXLhgsU3dPrKysjB9+nQ8++yz9XofMmQIunbtioiICJSXl+PgwYPo0qUL3Nzc\nkJuba7WPzZs3IzY2FiEhITh27Bg0Gg20Wi2MRiMCAwNRWFiIiooKAMAPP/yA5557Dg899BDy8/NR\nVlaGbt26wWg0wtnZGaNHj0ZZWRkOHTqE6dOn45VXXmm0lxkzZuDq1avw9/e32ObSpUsWzzUAmDBh\nAh555BFcvXoVt27davF9Xvc5sX79ekyePBm9e/eud9x3S0teY7XP0Zs3b9Z7zdS9ve7j0drncHp6\nusX94+npCb1ej2vXruHQoUPo2rUrnJycUFhYaPG6vX79Op544gl4eHjUex409Br7z+cbNV+HD66k\npCRs2LABAwYMwN69e/Htt99i8ODBOHv2LBwdHa2+sJOSkrB69WoMGDAADzzwAI4dO4bjx48DgDnI\nfvrpJ9jZ2aGgoAAeHh44fPgwACA0NBTJyck4cuQI+vXrZ67Z0oVMfvzxR8yZMwdz5sxBSEhIvdv9\n/f2RnJwMe3t7+Pn54cCBAzh16pTFNkII9OjRA6mpqS3qwZrBgwdDCIHJkyfD0dER2dnZ8PDwaHBb\nIQQefPBBJCYmYt26dRa9Ozg41Nt++PDhKC8vh729PXx8fKz2MWnSJLz88ss4ceIEBg4cCEVRUFVV\nhYCAAOTn50Or1eLcuXMAgP79+2PDhg3IysqCl5cXXFxcUFlZib59+1rUDA0NxRdffIEPP/yw0V46\nd+4MJyenev326tXL4rlW+7wxGo1wd3evF+53ou5zorS0FFu2bMH58+frHbettfQ1NmnSJPz5z3/G\nunXrkJycbPGa+fWvf43z5883eNpdq9Xi6NGjLepz9erViI6OhkajMd8/V65cwddff41u3bphxIgR\nKC8vh4uLC7p3724eK4SAs7Mztm7disLCwkafB3VfY//5fKPm45JPRB1ASkqK+RTX3Llz27odqSxZ\nsgSLFi1q6zaoDgYXERFJpcOfKiQiIrkwuIiISCoMLiIikgqDi4iIpMLgIiIiqTC4iIhIKv8P83UT\n3nxg73IAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7fcfdfb64860>"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"metadata": {
"id": "upVZYp_EWuEt",
"colab_type": "text"
},
"cell_type": "markdown",
"source": [
"No signigicant correlation except bw Amount and Loan Duration which is to be expected"
]
},
{
"metadata": {
"id": "iGaSWUE0Y3IP",
"colab_type": "text"
},
"cell_type": "markdown",
"source": [
"## Analyzing frequency distributions of data features"
]
},
{
"metadata": {
"id": "yZXI1cKz7oVb",
"colab_type": "code",
"colab": {}
},
"cell_type": "code",
"source": [
"def plot_freq_dist(feature):\n",
" default_count = cat_data[feature].value_counts()\n",
" sns.set(style=\"darkgrid\")\n",
" sns.barplot(default_count.index, default_count.values, alpha=0.9)\n",
" plt.title('Frequency Distribution of {}'.format(feature))\n",
" plt.ylabel('Number of Occurrences', fontsize=12)\n",
" plt.xlabel(feature, fontsize=12)\n",
" plt.show()"
],
"execution_count": 0,
"outputs": []
},
{
"metadata": {
"id": "gj1s3sLC9FCc",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 412
},
"outputId": "367bc873-0ec4-449e-a25c-7535abb675e7"
},
"cell_type": "code",
"source": [
"plot_freq_dist('default')"
],
"execution_count": 33,
"outputs": [
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/seaborn/categorical.py:1428: FutureWarning: remove_na is deprecated and is a private function. Do not use.\n",
" stat_data = remove_na(group_data)\n"
],
"name": "stderr"
},
{
"output_type": "display_data",
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAfQAAAFpCAYAAABqLtoXAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nIwAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7fcfdfef2470>"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"metadata": {
"id": "eoZmBiOiaA7N",
"colab_type": "text"
},
"cell_type": "markdown",
"source": [
"**70%** of the loans are paid back (no default)"
]
},
{
"metadata": {
"id": "mgcHHCKW9NXp",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 412
},
"outputId": "0068c627-b282-42ef-aea5-e23bf8eb84e3"
},
"cell_type": "code",
"source": [
"plot_freq_dist('job')"
],
"execution_count": 34,
"outputs": [
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/seaborn/categorical.py:1428: FutureWarning: remove_na is deprecated and is a private function. Do not use.\n",
" stat_data = remove_na(group_data)\n"
],
"name": "stderr"
},
{
"output_type": "display_data",
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAfQAAAFpCAYAAABqLtoXAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAQAwgP8HHnfaf5LVkrgAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7fcfdff8c128>"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"metadata": {
"id": "SWL35Qm_aXDs",
"colab_type": "text"
},
"cell_type": "markdown",
"source": [
"*Most of the people in this dataset have skilled jobs (above **60%**)*"
]
},
{
"metadata": {
"id": "fidMBEd-WtKE",
"colab_type": "code",
"colab": {}
},
"cell_type": "code",
"source": [
"def plot_pie_chart(feature):\n",
" labels = data[feature].astype('category').cat.categories.tolist()\n",
" counts = data[feature].value_counts()\n",
" sizes = [counts[var_cat] for var_cat in labels]\n",
" fig1, ax1 = plt.subplots()\n",
" ax1.pie(sizes, labels=labels, autopct='%1.1f%%', shadow=True) #autopct is show the % on plot\n",
" ax1.axis('equal')\n",
" plt.show()"
],
"execution_count": 0,
"outputs": []
},
{
"metadata": {
"id": "d6yHww3r9D9L",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 335
},
"outputId": "55d2b38a-c8b2-4470-b395-581ba140fd96"
},
"cell_type": "code",
"source": [
"plot_pie_chart('purpose')"
],
"execution_count": 36,
"outputs": [
{
"output_type": "display_data",
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAcwAAAE+CAYAAAAAgSCUAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7fcfe003ce80>"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"metadata": {
"id": "AZG5s4CIZ16v",
"colab_type": "text"
},
"cell_type": "markdown",
"source": [
"*We find that most of the credit (loan) is taken for **furniture and appliances***"
]
},
{
"metadata": {
"id": "b13dopNU8oRi",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 330
},
"outputId": "5c1ac70b-e0ae-4f0a-8ce7-18a3f30ba042"
},
"cell_type": "code",
"source": [
"plot_pie_chart('credit_history')"
],
"execution_count": 38,
"outputs": [
{
"output_type": "display_data",
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAcwAAAE5CAYAAAAdhBAsAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nCUwhhBCiABKYQgghRAEkMIUQQogC/A/SmUGCq2YPagAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7fcfdfbd5c88>"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"metadata": {
"id": "eL3Jbb3Yao5e",
"colab_type": "text"
},
"cell_type": "markdown",
"source": [
"*Most of the people have good credit history*"
]
},
{
"metadata": {
"id": "3UqXPLRP96V5",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 330
},
"outputId": "6533994f-cf9e-4a35-a9bf-caddf3000b31"
},
"cell_type": "code",
"source": [
"plot_pie_chart('savings_balance')"
],
"execution_count": 39,
"outputs": [
{
"output_type": "display_data",
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAcwAAAE5CAYAAAAdhBAsAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nSUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7fcfdfbba198>"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"metadata": {
"id": "wpBpMURa-GQv",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 330
},
"outputId": "0ab6525a-91dc-4c49-af98-e7f01bf72f3c"
},
"cell_type": "code",
"source": [
"plot_pie_chart('employment_duration')"
],
"execution_count": 40,
"outputs": [
{
"output_type": "display_data",
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAcwAAAE5CAYAAAAdhBAsAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\npaOOmWcAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7fcfdfbd54e0>"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"metadata": {
"id": "fWFM1WfH-N4r",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 330
},
"outputId": "c0ed1778-d621-4fc5-df5e-5fc6c88b0309"
},
"cell_type": "code",
"source": [
"plot_pie_chart('housing')"
],
"execution_count": 41,
"outputs": [
{
"output_type": "display_data",
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAcwAAAE5CAYAAAAdhBAsAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\ngIFJREQ0A/8/57DU2ApmO2YAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7fcfdfaf8cf8>"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"metadata": {
"id": "kYk4fRL_a3m2",
"colab_type": "text"
},
"cell_type": "markdown",
"source": [
"## Comparing Features for dependency"
]
},
{
"metadata": {
"id": "z0c8VFIka94E",
"colab_type": "text"
},
"cell_type": "markdown",
"source": [
"First lets compare numeric features with categorical features using box plots."
]
},
{
"metadata": {
"id": "YPfPpcJn5faL",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 408
},
"outputId": "0ef26567-c700-4780-f2f1-f652b9ce1df6"
},
"cell_type": "code",
"source": [
"data.boxplot('age', 'default')"
],
"execution_count": 24,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7fcfdfd07780>"
]
},
"metadata": {
"tags": []
},
"execution_count": 24
},
{
"output_type": "display_data",
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAe0AAAF2CAYAAABDFcB7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4yLCBo\ndHRwOi8vbWF0cGxvdGxpYi5vcmcvNQv5yAAAIABJREFUeJzt3XlcVXX+x/E3skgsxSIaLrRMipZs\nlS0UFmq5QGqZaaRmWkml5sMMzWpsm8ll1MmypHGbybH8SWWaG7mkVoBbGVZqtokmeANUlE3g/P7w\n5/2JomCAly+8nn/BXc75HOz04pxzudfJsixLAACgzmvk6AEAAEDVEG0AAAxBtAEAMATRBgDAEEQb\nAABDEG0AAAxBtIEqSktLU3BwsHJychw9Sp1R2c8kODhYq1atqrX1X8jybTab7r//foWFhWnbtm3V\nXvfAgQP1yiuvVHs5wIVwcfQAQFV16tRJWVlZatTo5O+aHh4eateunYYPH64bb7zRwdOdLS0tTa6u\nrrr++usdPQokrVixQhkZGfryyy/l5eVVo8suKyvT7Nmz9fjjj9focoEzcaQNo4wePVrp6elKT0/X\nmjVr1Lp1az366KMqKChw9GhnmTdvnr7++mtHj4H/k5eXp4CAgBoPtiR9//33euedd2p8ucCZiDaM\n5e3trb59+6qgoECZmZn22z/++GPdc889CgsLU3R0tBITE2VZlgoLC9W1a1fNnDnT/tgVK1aoQ4cO\nysrKsp/q3bBhg7p166bQ0FA9+OCD5ZZ9ukOHDunpp59WZGSkIiIiNGTIEP3000+SpCFDhmj9+vWa\nNm2aYmJiKnx+RkaG+vXrp9DQUPXq1UtffvmlgoODlZ6eLunkmYWZM2eqR48e9iO4861z//795Z4v\nSatWrVJwcLD9++DgYC1evFgDBw5UaGiounTpotTU1HLbNHLkSN12222KiIjQ0KFD9dtvv9nv/+67\n73TfffcpPDxcffv21c8//1zpv1NWVpYGDRqk8PBwxcTE6Msvv5R08vTyhAkTyj127dq1ioiI0PHj\nx89aTm5uruLj43X99derS5cuWrNmTbn7i4uLNWnSJHXu3FlhYWHq1auXNm7cKEmaNGmS3n77be3d\nu1chISHasmWLjh49qjFjxti3tV+/ftqxY4d9eZ06ddKcOXPs3+fk5Cg4OFhpaWnl1rtlyxb169dP\n+fn5CgkJ0aefflrpzwT4s4g2jJWTk6P58+crIiJCV1xxhSRp48aNmjBhghISErRt2zZNnjxZiYmJ\n+uSTT+Tu7q6//e1vmj17tjIyMnTs2DFNnDhRzz33nJo1a2Zf7vvvv68FCxZo48aNcnNzU0JCQoXr\nHzFihEpKSrRixQpt2rRJfn5+euKJJ1RWVqa5c+eqRYsWGj16tJYvX17h85966il5e3vryy+/1PTp\n0zV16tSzHrNkyRJNnz5diYmJla6zqmbPnq1x48Zpy5Yt6t69u5588knl5+dLkp588km5u7tr1apV\n2rRpkwIDAzV8+HBJJ08BjxgxQu3bt1dqaqomTpyohQsXVrq+9957T2PGjFFaWpo6deqkp556SocP\nH1afPn20cuVKFRcX2x+7atUq3X333fL09DxrOa+//rpsNps+++wzJSUladmyZeXunz59ulJSUjR/\n/nxt3bpVAwYM0FNPPaWsrCyNHTtWTzzxhK655hqlp6erQ4cOmjJlivbv369Vq1YpLS1NISEhGjly\nZJV/jqd06NBBr776qjw8PJSenq7Y2NgLXgZQVUQbRpk2bZpCQkIUEhKiW2+9VVu2bNH48ePt17kX\nLVqku+++W1FRUXJxcVGHDh3UtWtXezhvvPFG3X///Xrttdf01ltvqW3btrrvvvvKrWPw4MFq0qSJ\nfHx8NGTIEG3evFlHjx4t95hdu3bpm2++UUJCgnx8fOTl5aXRo0frt99+086dOyvdjqysLO3evVuP\nPfaYvL29dfXVV2vAgAFnPe7mm29WcHCwnJycqr3OU2JiYnTdddepcePGGjZsmAoLC5WSkqLvvvtO\n6enpSkhIkLe3t7y8vDR27Fjt3bvXfkniwIED9rD/5S9/UZ8+faq0vtDQUDVu3Fjx8fEqKSnR5s2b\n1bVrV5WUlGjdunWSTh4pr1u3Tr17965wOatXr9agQYPk7+8vHx8fxcfH2+8rKyvT4sWL9fjjj6tV\nq1ZydXVV37591bp163Me+b744ouaM2eOvL295ebmph49eigzM1M2m63KP0vgYuOFaDDK6NGjNXTo\nUElSQUGBkpOTNXjwYL377ru68cYblZGRoR49epR7zhVXXKHt27eXW0ZsbKy2bdtW4VHwVVddZf+6\nZcuWsizrrP+RZ2RkyNXV1X6EL0nNmzeXq6ur9u3bp9DQ0PNux6FDhyRJrVq1st8WFhZ21uNatmxZ\n5XX6+fmdd50VbZ+Xl5d8fHyUlZWlwsJCSVJ0dHS5xzdq1EgHDhyQk5OTXF1ddfnll9vva926daXr\nu+aaa+xfe3p6ys/PT5mZmbrkkkvUo0cPLVmyRN26ddMXX3yhSy+9VLfccstZy8jNzVVhYaGCgoIq\nXG52drby8vKUkJCgsWPH2m+3LEsREREVzrV//35NnDhRO3bsKHc6vqioqNJtAhyFaMNYl1xyiXr1\n6qW1a9dqwYIFuvHGG8udaj2dk5OT/eujR48qLy9PZWVlOnjwYLlT45LKnWo+14fgnWs9Z67rXE4t\n19XV9bzPO/3+P7POik6bl5aWnjWLk5OTGjdurEaNGumbb76Rs7PzWc9btmzZWT+PqpyWP3UW5PT1\nNW7cWJLUp08fDRgwQDk5OVq1apV69uxZ4bac2vbTZz99Fnd3d0knT/1XFP0zlZWV6fHHH1fbtm21\ndOlSNWvWTDt27NADDzxw3ucAjsbpcdQLp44Sg4KCtGfPnnL3/fjjj7ryyivt30+YMEHdu3fXyJEj\nNX78+LNiuG/fPvvX+/fvV6NGjc4Ke6tWrXTixIlyL8T65ZdfdOLEiXJHwudy6qg4IyPDftu33357\n3udUts5T4Tr1szhzW045fZ3Hjh3TkSNHFBgYqCuvvFJlZWXavXu3/X7LsrR//35JUrNmzVRSUqKs\nrCz7/Wf+rCty+rzHjh1TTk6O/Wg9IiJCQUFB+vTTT7VmzZpznhr38/OTq6urDh48aL/t9Dm9vb3l\n5+enXbt2lXve/v37K/zFKzs7WxkZGRowYID93/bMSwyNGzcu91cJFf0sgYuNaMNYJSUlWr9+vTZs\n2GC/Lt2nTx8lJyfrq6++UklJib766islJyfbr71+8skn2rlzp8aMGaOBAwfK3d1db7zxRrnlzp8/\nXzk5OTp8+LDmzZunyMjIs/5MKCQkRG3atNHUqVOVl5enI0eOaOrUqWrbtq2uu+46SSf/p79v3z4d\nOXLkrNlbtmypoKAgzZkzR8ePH9evv/6qDz744LzbW9k6/fz8dNlll2n16tUqKSnRrl27Kjz9v3z5\ncu3Zs0dFRUVKTEyUh4eHbrnlFl1zzTW66aab9PrrrysrK0tFRUWaOXOm+vfvr6KiIoWFhcnHx0eJ\niYkqLCzUnj179PHHH1f67/Tpp59q9+7dKi4u1rvvvisvL69yR8P33XefZsyYodatW5c7dX86V1dX\n3XbbbXrvvfeUk5OjnJwcvfvuu+WOyh966CHNnj1bO3fuVGlpqdavX6/Y2Fh9//33Zy3P19dXHh4e\n2r59u4qLi7Vp0yatX79ekuy/lFx11VXatGmT/ReN+fPnn3Mb3d3dVVhYqAMHDthf1AfUCgswRHR0\ntHXttdda7du3t9q3b2+Fh4dbvXv3tpYtW1bucf/5z3+s7t27W+Hh4VZsbKy1ZMkSy7Isy2azWTfd\ndJO1fPly+2PT09Ot6667ztqxY4eVmppqtWnTxlq+fLnVtWtXq3379lb//v2tzMxMy7Is+/3Z2dmW\nZVlWRkaGNWzYMOvmm2+2IiMjrVGjRlmHDh2yL3vevHlWaGioddttt1W4PT/88IMVExNjhYaGWv36\n9bM2bNhgtWnTxtq5c6d9e2fPnl3uOZWtc/ny5dadd95phYWFWYMHD7aWL19utWnTxn5/mzZtrLlz\n51oPPfSQFRISYnXu3NnavHmz/f7MzExr+PDhVkREhHXDDTdYDz/8sPXDDz/Y79++fbvVs2dPKzQ0\n1OrTp4/1ySeflPuZnKlNmzbWwoULrQcffNAKDQ21YmJirLS0tHKPOXTokNWuXTtr4cKFFS7j9McN\nGTLECg8Ptzp16mR99tlnVnh4uLVy5UrLsiyrqKjIev31163IyEgrLCzM6tmzp7Vq1Sr782fMmGHF\nxMTYv//000+tqKgoKzw83Bo+fLiVk5NjDRo0yAoPD7d27Nhh7dq1y+rdu7d97i1btlht27a1UlNT\nLcuyrAEDBlgvv/yyZVmWlZOTY8XGxlrXXXed9d577513O4DqcLKsc1y0AxqYtLQ0DRo0SCkpKVV+\nUVd1WJalEydOyM3NTZK0detWPfTQQ/rqq6/k7+9fK+sMDg7WG2+8oW7dutXK8v+MXbt26cEHH9Sm\nTZtq5Y1PgPqEF6IBDvLoo4/K1dVV//jHP+xvgxkWFlZrwa6LsrOzNWHCBA0aNIhgA1XANW3AQV59\n9VVJJ//E6q677pKkCt9gpb5KTExUly5ddPXVV+vJJ5909DiAETg9DgCAITjSBgDAEEQbAABDEG0A\nAAxBtAEAMAR/8gXUU4sXL9bcuXNVWlqqgIAATZ48WU2aNFFCQoK2b9+u1q1b69prr9Uff/yhiRMn\nKjMzUy+99JJ++eUXSdL48eN1xx13OHgrAJyOaAP1UHZ2tl555RV99tlnuvzyy/Xcc8/p7bffVrt2\n7XTo0CGtX79eWVlZ6tu3rzp27ChJGjt2rCIiIjRr1iz99ttveuCBB7Rq1Sr5+vo6eGsAnMLpcaAe\n8vf317Zt2+wfzHHqY0u3bt2qrl27ysXFRS1atLAfSefn5ystLU2DBw+WdPLjTG+44QZt2LDBUZsA\noAIcaQP1UGlpqWbMmKF169aptLRUx48f11VXXaWjR4/Kx8fH/rhmzZopMzNTeXl5sixL/fv3t9+X\nn59fpY+5BHDxEG2gHlqxYoXWrVunBQsWyM/PT//zP/+jZcuWycvLS8ePH7c/zmazSTp5ZO7s7KwP\nP/xQnp6ejhobQCU4PQ7UQ9nZ2WrRooX8/PyUm5urlStX6vjx4woJCVFycrLKysp08OBBbdy4UZLk\n4uKiO+64w/7xoAUFBXruuefKfX41AMcj2kA9FBsbq8OHD+uuu+7SM888o1GjRikzM1M2m02NGzdW\nly5d9PLLLysmJsb+mdQvvfSStmzZom7duunee+9Vq1atFBgY6OAtAXA63nscaGAsy7KHetKkSSot\nLdX48eMdPBWAquBIG2hA1q5dqz59+qi4uFjHjx/Xhg0bFB4e7uixAFQRL0QDGpA777xTGzZsUPfu\n3dWoUSPdeeed6tatm6PHAlBFnB4HAMAQnB4HAMAQRBsAAENclGvaNlvexVgNLhJfXw/l5uY7egwA\np2G/rD8CArzPeR9H2rhgLi7Ojh4BwBnYLxsGog0AgCGINgAAhiDaAAAYgmgDAGAIog0AgCGINgAA\nhiDaAAAYgmgDAGAIog0AgCGINgAAhiDaAAAYgmgDAGAIog0AgCGINgAAhiDaAAAYgmgDAGAIog0A\ngCGINgAAhiDaAAAYgmgDAGAIog0AgCGINgAAhiDaAAAYgmgDAGAIog0AgCGINgAAhiDaAAAYgmgD\nAGAIog0AgCGINgAAhiDaAAAYwqWyByxevFhLly61f79z5069//77eumllyRJwcHBevnll2ttQAAA\ncJKTZVlWVR+8efNmrVy5Unv37tWzzz6r0NBQPfPMM+rZs6fuuOOOcz7PZsurkWFRNwQEePNvCtQx\n7Jf1R0CA9znvu6DT4zNnztRjjz2mAwcOKDQ0VJIUHR2tlJSU6k0IAAAqVeVof/vttwoMDJSzs7Mu\nvfRS++3+/v6y2Wy1MhwAAPh/lV7TPiUpKUn33nvvWbdX5ey6r6+HXFycL2wy1GnnO30DwDHYL+u/\nKkc7LS1NL7zwgpycnHT48GH77VlZWWratOl5n5ubm//nJ0Sdw7UzoO5hv6w/qn1NOysrS56ennJz\nc5Orq6uuvvpqbd26VZKUnJysqKiompkUAACcU5WOtG02m/z8/Ozfjx8/Xn/9619VVlamsLAwRUZG\n1tqAAADgpAv6k68/i1M29Qun4YC6h/2y/qixP/kCAACOQ7QBADAE0QYAwBBEGwAAQxBtAAAMQbQB\nADAE0QYAwBBEGwAAQxBtAAAMQbQBADAE0QYAwBBEGwAAQxBtAAAMQbQBADAE0QYAwBBEGwAAQxBt\nAAAMQbQBADAE0QYAwBBEGwAAQ7g4egDULR073qxdu36o1jLatm2njRvTamgiAMApRBvlVCW2Qyau\n09xxnS7CNACA03F6HAAAQxBtAAAMQbQBADAE0QYAwBBEGwAAQxBtAAAMQbQBADAE0QYAwBBEGwAA\nQxBtAAAMQbQBADAE0QYAwBBEGwAAQxBtAAAMQbQBADAE0QYAwBBEGwAAQ7g4egAAwPl17Hizdu36\nodrLadu2nTZuTKuBieAoVYr20qVLNXv2bLm4uGjkyJEKDg5WQkKCSktLFRAQoClTpsjNza22ZwWA\nBqkqoR0ycZ3mjut0EaaBI1V6ejw3N1czZ87UwoULNWvWLK1du1YzZsxQXFycFi5cqCuuuEJJSUkX\nY1YAABq0SqOdkpKiW2+9VV5eXmratKleffVVpaWlqXPnzpKk6OhopaSk1PqgAAA0dJWeHt+/f78K\nCwsVHx+vo0ePasSIESooKLCfDvf395fNZqv1QQEAaOiqdE378OHDeuutt/T7779r0KBBsizLft/p\nX5+Lr6+HXFyc//yUqHMCArwdPQKAM7Bf1n+VRtvf318RERFycXFRUFCQPD095ezsrMLCQrm7uysr\nK0tNmzY97zJyc/NrbGDUDTZbnqNHAHAG9sv64Xy/fFV6Tfv2229XamqqysrKlJubq/z8fEVGRmr1\n6tWSpOTkZEVFRdXctAAAoEKVHmk3a9ZMXbt21QMPPCBJeuGFFxQSEqKxY8dq0aJFat68uXr37l3r\ngwIA0NBV6Zp2//791b9//3K3zZs3r1YGAgAAFeNtTAEAMATRBgDAEEQbAABDEG0AAAxBtAEAMATR\nBgDAEEQbAABDEG0AAAxBtAEAMATRBgDAEEQbAABDEG0AAAxBtAEAMATRBgDAEEQbAABDEG0AAAxB\ntAEAMATRBgDAEEQbAABDEG0AAAxBtAEAMATRBgDAEEQbAABDEG0AAAxBtAEAMATRBgDAEEQbAABD\nEG0AAAxBtAEAMATRBgDAEEQbAABDEG0AAAxBtAEAMATRBgDAEEQbAABDEG0AAAxBtAEAMATRBgDA\nEEQbAABDuFT2gLS0ND399NNq3bq1JKlNmzZ69NFHlZCQoNLSUgUEBGjKlClyc3Or9WEBAGjIKo22\nJN10002aMWOG/fvnnntOcXFx6t69u6ZNm6akpCTFxcXV2pAAAOBPnh5PS0tT586dJUnR0dFKSUmp\n0aEAAMDZqnSkvXfvXsXHx+vIkSMaPny4CgoK7KfD/f39ZbPZanVIAABQhWhfeeWVGj58uLp3766M\njAwNGjRIpaWl9vsty6p0Jb6+HnJxca7epKhTAgK8HT0CgDOwX9Z/lUa7WbNm6tGjhyQpKChITZo0\nUXp6ugoLC+Xu7q6srCw1bdr0vMvIzc2vmWlRZ9hseY4eAcAZ2C/rh/P98lXpNe2lS5dqzpw5kiSb\nzabs7Gzdd999Wr16tSQpOTlZUVFRNTQqAAA4l0qPtDt16qQxY8Zo7dq1OnHihF566SW1a9dOY8eO\n1aJFi9S8eXP17t37YswKAECDVmm0vby8NGvWrLNunzdvXq0MBAAAKsY7ogEAYAiiDQCAIYg2AACG\nINoAABiCaAMAYAiiDQCAIYg2AACGINoAABiCaAMAYAiiDQCAIYg2AACGINoAABiCaAMAYAiiDQCA\nIYg2AACGINoAABiCaAMAYAiiDQCAIYg2AACGINoAABiCaAMAYAiiDQCAIYg2AACGINoAABiCaAMA\nYAiiDQCAIYg2AACGINoAABiCaAMAYAiiDQCAIYg2AACGINoAABjCxdED4OIZ8c+NOl5YUiPLGjJx\nXbWe7+nuojdHdayRWQCgoSDaDcjxwhLNHdep2ssJCPCWzZZXrWVUN/oA0BBxehwAAEMQbQAADEG0\nAQAwBNEGAMAQRBsAAENUKdqFhYXq0qWLPvroIx08eFADBw5UXFycnn76aRUXF9f2jAAAQFWM9jvv\nvKPLLrtMkjRjxgzFxcVp4cKFuuKKK5SUlFSrAwIAgJMqjfZPP/2kvXv36s4775QkpaWlqXPnzpKk\n6OhopaSk1OqAAADgpEqjPWnSJI0bN87+fUFBgdzc3CRJ/v7+stlstTcdAACwO+87oi1ZskTh4eFq\n1apVhfdbllWllfj6esjFxfnCp0ONCwjwrjPLqalZANM9+MIKHSs4Ue3lVPedBr0ucdX7r/Wo9hyo\nPeeN9ueff66MjAx9/vnnyszMlJubmzw8PFRYWCh3d3dlZWWpadOmla4kNze/xgZG9VT37Uelmnkb\n05qaBagPjhWcqPZbDNfU2wuzXzre+Q5ozhvtf/7zn/av33zzTbVo0UJff/21Vq9erV69eik5OVlR\nUVE1NykAADinC/477REjRmjJkiWKi4vT4cOH1bt379qYCwAAnKHKn/I1YsQI+9fz5s2rlWEAAMC5\n8Y5oAAAYgmgDAGAIog0AgCGINgAAhiDaAAAYgmgDAGAIog0AgCGINgAAhiDaAAAYgmgDAGAIog0A\ngCGINgAAhiDaAAAYgmgDAGAIog0AgCGINgAAhiDaAAAYgmgDAGAIog0AgCGINgAAhiDaAAAYgmgD\nAGAIog0AgCGINgAAhnBx9AC4eIbuW6o9j/6n2svZUxOzuPlI6lQDSwKAhoNoNyBzgnpq7rjqhzIg\nwFs2W161ljFx4jrdVu1JAKBh4fQ4AACGINoAABiCaAMAYAiiDQCAIYg2AACGINoAABiCaAMAYAii\nDQCAIYg2AACGINoAABiCaAMAYAiiDQCAIfjAEABwsJr4BD4+fa9hqDTaBQUFGjdunLKzs1VUVKQn\nn3xSbdu2VUJCgkpLSxUQEKApU6bIzc3tYswLAPVOTXwCH5++1zBUGu3169erffv2euyxx3TgwAEN\nGTJE119/veLi4tS9e3dNmzZNSUlJiouLuxjzAgDQYFV6TbtHjx567LHHJEkHDx5Us2bNlJaWps6d\nO0uSoqOjlZKSUrtTAgCAql/T7t+/vzIzMzVr1iw98sgj9tPh/v7+stlstTYgAAA4qcrR/uCDD/TD\nDz/o2WeflWVZ9ttP//pcfH095OLi/OcmRI0KCPCuM8upqVmA+qCu7FPsl3VbpdHeuXOn/P39FRgY\nqHbt2qm0tFSenp4qLCyUu7u7srKy1LRp0/MuIzc3v8YGRvVU94UqUs284KWmZgHqi+ruD+yX9cf5\nfnGq9Jr21q1bNXfuXEnSH3/8ofz8fEVGRmr16tWSpOTkZEVFRdXQqAAA4FwqPdLu37+/nn/+ecXF\nxamwsFB//etf1b59e40dO1aLFi1S8+bN1bt374sxKwAADVql0XZ3d9fUqVPPun3evHm1MhAAAKgY\nb2MKAIAhiDYAAIYg2gAAGIJoAwBgCKINAIAhiDYAAIYg2gAAGIJoAwBgCKINAIAhiDYAAIao8kdz\non4YMnGdo0eQJHm6858eAFwo/s/ZgMwd16lGljNk4roaWxYAoOo4PQ4AgCGINgAAhiDaAAAYgmgD\nAGAIog0AgCGINgAAhiDaAAAYgr/TBoA6oC688RFvelT38S8EAA5WE29WxJseNQycHgcAwBBEGwAA\nQxBtAAAMQbQBADAE0QYAwBBEGwAAQxBtAAAMQbQBADAE0QYAwBBEGwAAQxBtAAAMQbQBADAE0QYA\nwBBEGwAAQxBtAAAMQbQBADAE0QYAwBBEGwAAQxBtAAAM4VKVB02ePFnbtm1TSUmJhg0bppCQECUk\nJKi0tFQBAQGaMmWK3NzcantWAAAatEqjnZqaqh9//FGLFi1Sbm6u7r33Xt16662Ki4tT9+7dNW3a\nNCUlJSkuLu5izAsAQINV6enxDh066I033pAkXXrppSooKFBaWpo6d+4sSYqOjlZKSkrtTgkAACo/\n0nZ2dpaHh4ckKSkpSR07dtQXX3xhPx3u7+8vm8123mX4+nrIxcW5BsZFXREQ4O3oEQCcgf2y/qvS\nNW1JWrNmjZKSkjR37lzdfffd9tsty6r0ubm5+X9uOtRZNlueo0cAcAb2y/rhfL98VenV45s2bdKs\nWbP0r3/9S97e3vLw8FBhYaEkKSsrS02bNq2ZSQEAwDlVGu28vDxNnjxZiYmJ8vHxkSRFRkZq9erV\nkqTk5GRFRUXV7pQAAKDy0+MrVqxQbm6uRo0aZb9t4sSJeuGFF7Ro0SI1b95cvXv3rtUhAQCA5GRV\n5aJ0NXGdxRwdO96sXbt+qNYy2rZtp40b02poIgA1sV9K7JumON81baKNCxYQ4M2/KVDHsF/WH9V+\nIRoAAHA8og0AgCGINgAAhiDaAAAYgmgDAGAIog0AgCGINgAAhiDaAAAYgmgDAGAIog0AgCGINgAA\nhiDaAAAY4qJ8YAgAAKg+jrQBADAE0QYAwBBEGwAAQxBtAAAMQbQBADAE0QYAwBBEGwAAQxBtAAAM\n4eLoAVC3ffTRR9q2bZtycnL0yy+/aOjQoQoKCtL06dPl4uKiZs2a6fXXX5ebm5ujRwXqtb59+2rq\n1KkKCgpSZmam4uPjde211yojI0MlJSUaOXKkbr31Vi1ZskQLFiyQq6ur2rZtqwkTJjh6dNQgoo1K\n7dmzRx988IF+/fVXjR49WkVFRZo3b54CAwP1yiuvaNmyZerTp4+jxwTqtV69emnFihWKj4/X2rVr\nddddd6m4uFh///vflZOTo4cffljLli3TnDlz9O677yowMFAffvihCgsL5e7u7ujxUUOINioVHh4u\nZ2dnXX755crLy1Pjxo0VGBiUFby7AAAEGklEQVQoSbr55pu1ZcsWB08I1H8xMTEaOnSo4uPj9fnn\nn6tJkyZKT0/X9u3bJUlFRUUqLi5WbGysnnrqKfXs2VOxsbEEu54h2qiUi8v//2dy5MgRBQQE2L8/\nceKEnJycHDEW0KD4+vrq8ssv17fffquysjJ5enoqPj5esbGx5R43bNgw3XPPPVq9erUefvhhLViw\nQL6+vg6aGjWNF6Lhglx22WVycnLS77//LknavHmz2rdv7+CpgIahV69eeuWVV9StWzeFhYVp7dq1\nkqTs7GxNmzZNZWVlmj59ugICAvTII48oPDzcvq+ifuBIGxfs1Vdf1TPPPCMXFxe1atVKMTExjh4J\naBCio6P14osvqmvXrvLw8FBqaqr69++v0tJSDR8+XI0aNZKnp6f69esnb29vtWrVSu3atXP02KhB\nfDQnABgiNTVVH3/8sSZNmuToUeAgHGkDgAFmzJihL774Qm+++aajR4EDcaQNAIAheCEaAACGINoA\nABiCaAMAYAiiDdQjY8aM0UcffXTO+//973+ra9euWr9+/QUve9y4cVq8eLEkadmyZSorK/vTcwL4\nc4g20ICsW7dO48ePV3R0dLWW8+abbxJtwAH4ky/AYGVlZXr++ee1e/dutWjRQvn5+ZKkFStWaMGC\nBbIsS35+fnrttde0fPlyfffdd5o6dapKSkpUVlam2bNny83NTaWlpZo8ebJatmypgQMH6oknnlBk\nZKT279+vuLg4bdy40b7OGTNm6LffftPgwYP11ltvycfHx1GbDzQ4HGkDBvvqq6/0888/68MPP9Tk\nyZO1e/duHTx4ULNmzdL8+fP1/vvv66abblJiYqIGDBigdu3aady4cercubOOHj2q6dOn67333tMd\nd9yh//73v1Va58iRIyVJ8+fPJ9jARcaRNmCwPXv2KCIiQk5OTrrkkksUGhoqNzc32Ww2DR06VJJU\nXFysli1bnvXcJk2aaOzYsbIsSzabTRERERd7fAAXiGgDBrMsq9ynrJWVlcnNzU2hoaFKTEw85/NO\nnDihUaNG6eOPP9aVV16pBQsWaOfOnRU+DkDdwelxwGDXXHONduzYIcuydOzYMe3YsUMFBQX69ttv\nZbPZJEkrV67UmjVryj3v+PHjatSokVq0aKGioiKtXbtWxcXFkiQvLy8dPHhQ0sn3uq6Ik5OTSkpK\nanHLAFSEaAMGu/322xUYGKi+fftq/PjxCg8PV9OmTfX8889r2LBheuihh5SUlKTw8PByz/Px8VFs\nbKzuv/9+jRo1SkOHDlVqaqpWrlypAQMG6J133tEjjzyigoKCCtcbFRWlPn36aN++fRdjMwH8H957\nHAAAQ3CkDQCAIYg2AACGINoAABiCaAMAYAiiDQCAIYg2AACGINoAABiCaAMAYIj/BXcJF5Ixx+vQ\nAAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7fcfdfccd0f0>"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"metadata": {
"id": "sdLE_rdubFj8",
"colab_type": "text"
},
"cell_type": "markdown",
"source": [
"***We observe the mean age for loan defaulters is less, which implies that young people default more on their loans.***"
]
},
{
"metadata": {
"id": "SdhgukLeb60L",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 408
},
"outputId": "465a8591-41da-4bd0-9479-31fba398d7a8"
},
"cell_type": "code",
"source": [
"# months_loan_duration\tamount\tpercent_of_income\tyears_at_residence\tage\texisting_loans_count\tdependents\n",
"data.boxplot('months_loan_duration', 'default')"
],
"execution_count": 92,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7fcfddd630f0>"
]
},
"metadata": {
"tags": []
},
"execution_count": 92
},
{
"output_type": "display_data",
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAe0AAAF2CAYAAABDFcB7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAJYgtAEAsAShDQCAJQhtAAAs8f8AtaAX8fxL7+sAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7fcfdde32a58>"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"metadata": {
"id": "91QmJf5-cL8O",
"colab_type": "text"
},
"cell_type": "markdown",
"source": [
"***Longer duration loans have higher default rate***"
]
},
{
"metadata": {
"id": "P1jkqy7-chVz",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 408
},
"outputId": "a9563895-e755-439e-e67b-c92189f5b646"
},
"cell_type": "code",
"source": [
"data.boxplot('amount', 'default')"
],
"execution_count": 93,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7fcfddd0b240>"
]
},
"metadata": {
"tags": []
},
"execution_count": 93
},
{
"output_type": "display_data",
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAf4AAAF2CAYAAACPjPqQAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nABjk/wHF5FwWzWfETgAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7fcfdddda208>"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"metadata": {
"id": "MtTaCVNYcnfx",
"colab_type": "text"
},
"cell_type": "markdown",
"source": [
"***Higher amounts have a higher default rate***"
]
},
{
"metadata": {
"id": "lJn6VFG1c7rA",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 408
},
"outputId": "938b9adb-6c9b-4d5b-bdd1-f99c9113dbb0"
},
"cell_type": "code",
"source": [
"data.boxplot('percent_of_income', 'default')"
],
"execution_count": 95,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7fcfddea9518>"
]
},
"metadata": {
"tags": []
},
"execution_count": 95
},
{
"output_type": "display_data",
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAfAAAAF2CAYAAACRRcojAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7fcfddeebf60>"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"metadata": {
"id": "Nq-_ia4kc79c",
"colab_type": "text"
},
"cell_type": "markdown",
"source": [
"***The persons defaulting on their loan, have loans which are a higher % of their income ***"
]
},
{
"metadata": {
"id": "PMO7QrCgeVp3",
"colab_type": "text"
},
"cell_type": "markdown",
"source": [
"Now lets compare categorical features"
]
},
{
"metadata": {
"id": "en5pVgwd_amH",
"colab_type": "code",
"colab": {}
},
"cell_type": "code",
"source": [
"job_default_table = pd.crosstab(index=data[\"job\"], columns=data[\"default\"])\n",
"balance_default_table = pd.crosstab(index=data[\"savings_balance\"], columns=data[\"default\"])\n",
"credit_default_table = pd.crosstab(index=data[\"credit_history\"], columns=data[\"default\"])\n",
"purpose_default_table = pd.crosstab(index=data[\"purpose\"], columns=data[\"default\"])\n",
"savings_default_table = pd.crosstab(index=data[\"savings_balance\"], columns=data[\"default\"])\n",
"duration_default_table = pd.crosstab(index=data[\"employment_duration\"], columns=data[\"default\"])\n",
"other_default_table = pd.crosstab(index=data[\"other_credit\"], columns=data[\"default\"])\n",
"housing_default_table = pd.crosstab(index=data[\"housing\"], columns=data[\"default\"])\n",
"phone_default_table = pd.crosstab(index=data[\"phone\"], columns=data[\"default\"])"
],
"execution_count": 0,
"outputs": []
},
{
"metadata": {
"id": "v1zzRNtzElDx",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 562
},
"outputId": "b0b25dfb-1d90-471d-af45-e18a35b627fa"
},
"cell_type": "code",
"source": [
"job_default_table.plot(kind=\"bar\", figsize=(8,8), stacked=True)"
],
"execution_count": 118,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7fcfdd862588>"
]
},
"metadata": {
"tags": []
},
"execution_count": 118
},
{
"output_type": "display_data",
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAeQAAAIQCAYAAABQRR1rAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nA/x/adlhzr1ufa0AAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7fcfdd9bd160>"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"metadata": {
"id": "U5zvIKRvfkB8",
"colab_type": "text"
},
"cell_type": "markdown",
"source": [
"***Most of skilled persons pay back while unskilled have a higher chance of defaulting on their loans***"
]
},
{
"metadata": {
"id": "mOn6K5Rvfkbi",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 571
},
"outputId": "07e9bfa1-5d31-4301-cb9f-b4f03272d15f"
},
"cell_type": "code",
"source": [
"balance_default_table.plot(kind=\"bar\", figsize=(8,8), stacked=True)"
],
"execution_count": 102,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7fcfddf72940>"
]
},
"metadata": {
"tags": []
},
"execution_count": 102
},
{
"output_type": "display_data",
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAeQAAAIZCAYAAAB3SkyjAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nkAEAMACBDACAAQhkAAAMQCADAGCA/wfNseQOGJIsDQAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7fcfddf73908>"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"metadata": {
"id": "5Kk6kLhdfkwB",
"colab_type": "text"
},
"cell_type": "markdown",
"source": [
"***People with higher savings balance default less while those with less default more on their loans***"
]
},
{
"metadata": {
"id": "4MtzdJE7fk_h",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 547
},
"outputId": "e268034d-c19c-456b-b188-f67d86e789c8"
},
"cell_type": "code",
"source": [
"credit_default_table.plot(kind=\"bar\", figsize=(8,8), stacked=True)"
],
"execution_count": 103,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7fcfddf72080>"
]
},
"metadata": {
"tags": []
},
"execution_count": 103
},
{
"output_type": "display_data",
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAeQAAAIBCAYAAACYz8xVAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nIMgAABiAIAMAYACCDACAAf4/TY73UtB+nIEAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7fcfddf7a0b8>"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"metadata": {
"id": "4WX1OpIfkZmB",
"colab_type": "text"
},
"cell_type": "markdown",
"source": [
"## Summary"
]
},
{
"metadata": {
"id": "pqJYpAFmkbHU",
"colab_type": "text"
},
"cell_type": "markdown",
"source": [
"The key features for predicting loan default can be made out easily by this analyis.\n",
"* Age\n",
"* Savings Balace\n",
"* Credit history\n",
"* Job \n",
"* Amount"
]
},
{
"metadata": {
"id": "raE3SiM2kpWG",
"colab_type": "code",
"colab": {}
},
"cell_type": "code",
"source": [
""
],
"execution_count": 0,
"outputs": []
}
]
}
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment