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Assignment 5: E-Commerce Customer Analytics with pandas

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Assignment Requirements

Apply pandas data cleaning and analysis techniques to e-commerce customer data through 8 progressive problems

Problem 1: Loading and Inspecting Customer Data (10 points)
Problem 2: Detecting Data Quality Issues (10 points)
Problem 3: Strategic Missing Data Handling (15 points)
Problem 4: Duplicate Record Resolution (15 points)
Problem 5: Data Type Conversion and Validation (20 points)
Problem 6: Customer Segmentation with Computed Columns (20 points)
Problem 7: Sales Analysis with GroupBy Aggregation (20 points)
Problem 8: Complete Customer Data Pipeline System (30 points)

Jupyter Notebook * .ipynb file

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.ipynb file • Max 10MB

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E-Commerce Customer Analytics with pandas (100 points total)

Submission Requirements:

Submit your completed Jupyter notebook (.ipynb file)
Ensure all code cells have been executed and show output
Import only pandas and numpy; no other libraries permitted
File size limit: 10MB maximum
You can resubmit multiple times (latest submission counts)
Use concepts from Lectures 18-19