E-commerce Sales Analytics Dashboard (Python & Streamlit)

This repository contains an interactive E-commerce Sales Analytics dashboard implemented in Python (Streamlit).

Features

• Sales over time analysis (weekly aggregation).
• Top products and category breakdowns.
• Basic customer segmentation (RFM-like segmentation by monetary value).
• Geography-based revenue charts (country, city).
• Revenue distribution and price vs quantity scatter plot.
• Download filtered data as CSV.

Quickstart

1. Clone or extract the repo.
2. Put your sales CSV in the data/ folder. The sample CSV included is named sample_ecom_sales.csv. Expected columns (case-insensitive): order_id, order_date, customer_id, product_id, product_category, country, city, quantity, price
3. Create a virtual env and install dependencies:

python -m venv venv
source venv/bin/activate  # or venv\Scripts\activate on Windows
pip install -r requirements.txt

4. Run the app:

streamlit run app.py

Notes

• The app computes revenue = quantity * price if revenue is not provided.
• If your file has different column names, rename them or modify app.py mapping accordingly.

License

MIT