Danirex001/Africa-loans-Analysis

# Loan Dataset Analysis ## Project Overview This project analyzes loan dataset espercially Africa loans and has details such as loan guarantee numbers, transaction report IDs, guarantee country names, loan amounts, currencies, disbursement dates, end dates, business sectors, and more. The goal is to extract insights, identify trends, and visualize key findings. ## Objectives of the Analysis Identify the total loan amount per business sector. Determine the country with the highest loan amount. Analyze the gender gap in loan disbursement. Identify first-time borrowers. Calculate days between disbursement and repayment. Examine the relationship between business sector and loan duration. Provide visualizations to support insights. Dataset Description The dataset includes the following key columns: Guarantee Number – Unique identifier for each loan. Transaction Report ID – ID for loan transaction. Guarantee Country Name – The country where the loan is guaranteed. Amount – Loan amount disbursed. Currency Name – The currency in which the loan was given. Disbursement Date – Date when the loan was disbursed. End Date – Date when the loan is due for repayment. Business Sector – The sector in which the loan was invested. and more . ## Analysis & Findings 1. Loan Distribution Across Business Sectors A bar chart visualizing the total amount of loans given to each business sector. Identified which sectors received the highest funding. 2. Country with the Highest Loan Amount A ranking of countries based on the total loan amount received. A heatmap showing loan distribution across countries. 3. Gender Gap in Loan Disbursement Comparison of loans received by male vs. female borrowers. Insights into gender disparities in loan approvals. 4. First-Time Borrowers Analysis Identification of borrowers receiving a loan for the first time. Percentage of first-time borrowers compared to repeat borrowers. 5. Days Between Disbursement and Repayment Calculated the average loan duration per …