🛍️ Retail Orders Analysis

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.

📁 Project Structure

• 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).

📊 What’s Inside

• 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

🚀 How to Run This

1. Clone the repo.
2. Set up your Python environment.
3. Install the required packages: pip install -r requirements.txt.
4. 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 the data/ folder.

👩🏽‍💻 Created by

Tiffany Karanja