SQL Integration with Python

A beginner-friendly project showing how to use SQLite with Python for querying, updating, and visualizing data in Jupyter Notebook.

Key Features

1. Database Setup

   • Created a sales table with sample product data.
   • Created a customers table with customer details.

2. Data Insertion & Updates

   • Inserted sample data into both tables.
   • Updated sales table with customer_id using ALTER TABLE and UPDATE queries.

3. SQL Queries with Pandas

   • Queried data using SQL commands via pd.read_sql().
   • Demonstrated joins and aggregations.

4. Data Visualization

   • Used matplotlib and seaborn to visualize revenue by product and by country.

Key Learnings

• How to manage SQLite database in-memory via Python.
• Practice with SELECT, JOIN, GROUP BY, and aggregation.
• Quick data analysis pipeline inside Jupyter with clean output.

Tools Used

• Python (Jupyter Notebook)
• SQLite
• pandas
• matplotlib
• seaborn