A hands-on project where I dive into a retail dataset to uncover patterns and insights using Python, SQL, and data visualization. It covers everything from cleaning raw data to answering real business questions.
notebooks/: My Jupyter notebooks for data cleaning, analysis, and visualizations.sql/: SQL scripts for creating and managing the database.data/: Raw dataset (excluded here — see below)..env: Secure storage for API keys and DB credentials (not shared).
- Data wrangling and transformation in pandas
- SQL queries for insights like top-performing cities, best-selling products, and profit margins
- Visualizations: histograms, bar charts, and more to bring the numbers to life
- Clone the repo.
- Set up your Python environment.
- Install the required packages:
pip install -r requirements.txt. - Open the notebook and follow along!
⚠️ The dataset isn’t included in the repo — you can grab it directly from Kaggle and place it in thedata/folder.
Tiffany Karanja