Jemtai-Stacy/mpesa-transaction-analyzer

Python data analysis tool for M-PESA-style mobile money transactions # 📱 Mobile Money Transaction Analyzer A Python data analysis tool that processes M-PESA-style mobile money transaction data to uncover personal finance patterns, visualise spending behaviour, and flag anomalous transactions. Built as a portfolio project to demonstrate practical data analysis skills using Python — with a focus on financial data relevant to the East African fintech context. --- ## 🎯 What This Project Does | Feature | Description | |---|---| | **Data Cleaning** | Loads and validates raw transaction CSVs, handles missing values and duplicates | | **Financial Summary** | Computes total income, expenses, and net balance across a date range | | **Spending Breakdown** | Categorises outgoing transactions and visualises them with horizontal bar charts | | **Monthly Cash Flow** | Compares income vs. expenses month-over-month with trend line | | **Anomaly Detection** | Flags statistically unusual transactions using Z-score analysis | | **Top Recipients** | Identifies the counterparties receiving the most money | --- ## 🛠️ Tech Stack - **Python 3.10+** - **pandas** — data loading, cleaning, grouping, and aggregation - **matplotlib** — data visualisation and chart export --- ## 🚀 Getting Started ### 1. Clone the repository ```bash git clone github.com cd mpesa-transaction-analyzer ``` ### 2. Install dependencies ```bash pip install -r requirements.txt ``` ### 3. Add your transaction data Replace `transactions.csv` with your own M-PESA export, or use the included sample dataset. Your CSV should have these columns: ``` transaction_id, date, type, amount_kes, category, counterparty, status ``` ### 4. Run the analysis ```bash python analyze.py ``` Charts are saved automatically to the `/outputs` folder. --- ## 📊 Sample Output ``` 🔍 Mobile Money Transaction Analyzer ✅ Loaded 60 valid transactions from transactions.csv ================================================== FINANCIAL SUMMARY (KES) === …