Assignment.txt

Retail Sales Data Cleaning & Exploratory Analysis

Goal:
    Use Pandas, NumPy, and Matplotlib to clean and analyze retail sales trends.

Tasks:
1. Handle missing values, duplicates, and incorrect data types.

2. Convert columns (e.g., dates, numerics) appropriately.

3. Compute KPIs such as:
        Monthly Revenue
        Region-wise Sales
        Profit Margin (%)
        Average Order Value
        (Come up with 2–3 more KPIs of your choice)

4. Visualize sales trends and outliers using Matplotlib or Seaborn.

5. Apply OOP concepts — create a SalesAnalyzer class encapsulating all logic.

Tech: Python, Pandas, NumPy, Matplotlib

Deliverables: Cleaned CSV + .py script or Jupyter Notebook + output screenshots (cleaned data preview, trend charts, code execution)

Dataset: https://wgcp-my.sharepoint.com/:f:/g/personal/ritish_jogi_blend360_com/EmxzwFjNkaxPuCw2mQ0abr0BGg6XzIPlj22VogFVtQniyg?e=aglSyr