https://github.com/mikaremi/bank-s-customers-analysis

https://github.com/mikaremi/bank-s-customers-analysis

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• Host: GitHub
• URL: https://github.com/mikaremi/bank-s-customers-analysis
• Owner: Mikaremi
• Created: 2024-04-25T18:01:12.000Z (10 months ago)
• Default Branch: main
• Last Pushed: 2024-04-25T18:07:59.000Z (10 months ago)
• Last Synced: 2024-04-25T19:27:02.029Z (10 months ago)
• Language: Jupyter Notebook
• Size: 569 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Bank-Customers-Analysis

## Introduction

* Banks are constantly analysing data to understand their ideal customers

* Customer personalty tests help banks to have a clear visual of who their customers are as well as their behaviors

* This project will analyse a bank dataset to showcase their customers and whether they are likely to deposit with them.

## Insights

* Married people account for the highest number of cutomers while divorced people are the least.

* The bank's highest customers have attained secondary education while the least have no education

* Majority of the customers have neither housing loans nor personal loans

* Non-bank defaulters make up the largest proportion of the bank's customers

* The people in management are more likely to accept to deposit with the bank as compared to housemaids. Also, people in blue-collar jobs had the highest number of people refusing to deposit with the bank.

* People with secondary education make up the largest group of loan non-defaulters.

* Customers with tertiary education are more likely to deposit with the company as compared to those with secondary and primary education.

* Majority of the bank's customers are between 30-40 years old while the oldest range between 60-95 years old.

## Tool used

Python

* Pandas

* Numpy

* Seaborn

* Matplotlib