📊 Branch Sales Analysis This project performs advanced analysis of sales data across different company branches. It includes data cleaning, calculation of revenue and profit metrics, and visual comparison between branches.

📁 Project Contents sales_branches.csv – Sample dataset containing product sales across branches.

revenue_branche.png – Bar chart comparing revenue and profit per branch.

LICENSE – MIT open-source license.

analysis.ipynb (optional) – Jupyter Notebook with full code and analysis steps (available upon request).

✅ Key Features Handles missing values per product group.

Computes:

Revenue = Unit Price × Quantity

Cost = Cost per Unit × Quantity

Profit = Revenue − Cost

Margin (%) = (Profit ÷ Revenue) × 100

Identifies the branch with the highest total revenue.

Visualizes branch performance using bar charts.

Aggregates average daily revenue and profit.

📊 Output Example 🛠️ Tools & Libraries Python

pandas

NumPy

Matplotlib

📄 License This project is licensed under the MIT License – see the LICENSE file for details.