Pandas Data Analysis Challenge

Background

Embark on a data analysis journey using Python's Pandas library. This challenge simulates real-world data analysis tasks within an e-commerce context, focusing on customer insights, product trends, and profitability.

Files

• Module 4 Challenge files.

Setup

• Repository: pandas-challenge-1
• Clone and push changes to GitHub or GitLab.

Challenge Instructions

Part 1: Explore the Data

• Import CSV data.
• Examine column names and statistics.
• Investigate data to answer key questions about item categories, subcategories, and client activity.

Part 2: Transform the Data

• Calculate subtotals, shipping prices, total prices, costs, and profits.
• Apply transformations to enhance data analysis capabilities.

Part 3: Confirm Your Work

• Verify transformed data against actual order receipts.

Part 4: Summarize and Analyze

• Analyze spending for top clients.
• Summarize findings in a presentation-ready format.
• Write a concise summary of insights gained from the data.

Hints and Considerations

• Utilize Pandas documentation for advanced functions.
• Implement well-named functions to streamline operations and improve code readability.
• Follow the analytical process, defining questions and exploring data thoroughly.

Requirements

Data Exploration

• Display column names and descriptive statistics.
• Identify top item categories and subcategories.
• Determine clients with the most data entries.
• Reveal the quantity ordered by the top client.

Data Transformation

• Create columns for subtotals, shipping prices, total prices, costs, and profits.
• Ensure accurate calculation of financial metrics.

Data Confirmation

• Match calculated total prices with provided order receipts.

Data Summary and Analysis

• Calculate total revenue for top clients.
• Construct a summary DataFrame for top clients with key financial metrics.
• Develop a function to convert currency to millions and format data for presentation.
• Provide a brief summary of analytical findings.

Submission

Submit your GitHub repository URL containing the challenge work for evaluation.