Data Science Take-Home Challenge
Dataset: Video Game Sales (https://www.kaggle.com/datasets/siddharth0935/video-game-sales)
Instructions: This take-home exam assesses your skills in data exploration, analysis, modeling, and
communication. Please submit a well-documented Jupyter notebook and a short summary report (PDF or
Word). Include visualizations and commentary wherever applicable.
Section 1: Exploratory Data Analysis (Easy)
1. Identify the top 10 video games by global sales. Provide their names, platforms, and total global sales.
2. Calculate total global sales for each genre. Which genre has the highest total sales?
3. Determine total sales in North America, Europe, and Japan. Which region has the highest sales overall?
4. Plot total global sales per year. Identify any noticeable trends.
Section 2: Insights and Aggregations (Medium)
5. For each platform, calculate the average global sales per game. Which has the highest?
6. Identify the top 5 publishers by total global sales. For each, list their top-selling game.
7. Analyze genre popularity over the years. Which genres are gaining or losing traction?
8. Compare top 3 genres in North America, Europe, and Japan. How do preferences differ?
Section 3: Modeling and Business Strategy (Hard)
9. Build a machine learning model to predict global sales based on platform, genre, publisher, and regional
sales.
10. Recommend a market entry strategy for a new game. Suggest genre, platform, and region for maximizing
Data Science Take-Home Challenge
sales.
11. Analyze successful publishers. What strategic choices (e.g., genre/platform focus) contribute to higher
sales?
12. Identify anomalous games (unusually high or low sales compared to similar titles). What might explain
them?