This project analyzes sales data using Python and pandas to extract meaningful business insights such as revenue trends, product performance, and regional sales distribution.
- Calculate total sales revenue
- Identify best-selling products
- Analyze regional performance
- Produce a clean, readable report
- Python 3
- pandas library
The dataset contains:
- Date of sale
- Product name
- Quantity sold
- Price per unit
- Customer ID
- Sales region
- Total sales amount
- Checked and handled missing values
- Removed duplicate records
- Verified data types for accuracy
- Total Revenue: Calculated by summing
Total_Sales - Best-Selling Product: Highest revenue generator
- Top Region: Region contributing the most revenue
- Total Orders: Number of transactions
- Average Order Value: Mean revenue per order
The analysis shows strong performance in specific products and regions, helping businesses optimize inventory and sales strategy.
- Manual validation of revenue calculations
- Group-by aggregation verified using pandas
This project demonstrates effective use of pandas for real-world sales analysis and data-driven decision-making.