In this project we delve into the captivating world of video games! For further details, please refer to the GitHub repository linked here.

The Golden Age of Video Games

Introduction

Welcome to my latest data analysis project, where we delve into the captivating world of video games! In this project, we explore the concept of the “golden age” of video games by analyzing critic and user scores, as well as sales data for the top 400 video games released between 1977 and 2020. Our goal is to uncover insights into the years that stood out in terms of critical acclaim, user satisfaction, and commercial success.

Dataset

The project utilizes two main tables:

• game_sales: Contains information about the top-selling video games, including the game title, platform, publisher, developer, number of copies sold, and release year.
• game_reviews: Includes critic and user scores for the games.

Tasks and Queries

Task 1: Top 10 Best-Selling Video Games

• Query:

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SELECT *
FROM game_sales
ORDER BY games_sold DESC
LIMIT 10;

• Summary: The top 10 best-selling video games include titles such as “Wii Sports,” “Super Mario Bros.,” and “Minecraft.”

Task 2: Missing Review Scores

• Query:

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SELECT COUNT(*)
FROM game_sales gs
LEFT JOIN reviews r ON gs.game = r.game
WHERE r.critic_score IS NULL AND r.user_score IS NULL;

• Result: 31 games are missing both critic and user review scores.

Task 3: Years with Highest Average Critic Scores

• Query:

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SELECT year AS release_year,
       ROUND(AVG(critic_score), 2) AS avg_critic_score
FROM game_sales gs
JOIN reviews r ON gs.game = r.game
GROUP BY year
ORDER BY avg_critic_score DESC
LIMIT 10;

• Summary: Years like 1990, 1992, and 1998 have the highest average critic scores, indicating potential golden ages.

Task 4: Years with More than Four Reviewed Games

• Query:

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SELECT year, 
       AVG(critic_score) AS avg_critic_score, 
       COUNT(*) AS num_games
FROM game_sales gs
JOIN reviews r ON gs.game = r.game
GROUP BY year
HAVING COUNT(*) > 4
ORDER BY avg_critic_score DESC
LIMIT 10;

• Summary: These years have a significant number of reviewed games, providing more robust data for analysis.

Task 5: Years with Highest Average User Scores

• Query:

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SELECT year AS release_year,
       ROUND(AVG(user_score), 2) AS avg_user_score,
       COUNT(*) AS num_games
FROM game_sales gs
JOIN reviews r ON gs.game = r.game
GROUP BY year
HAVING COUNT(*) > 4
ORDER BY avg_user_score DESC
LIMIT 10;

• Summary: Years such as 1997, 1998, and 2010 have the highest average user scores, indicating strong player satisfaction.

Task 6: Overlapping Years Loved by Critics and Users

• Query:

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SELECT year
FROM top_critic_years_more_than_four_games
INTERSECT
SELECT year
FROM top_user_years_more_than_four_games;

• Summary: Several years, including 1998, 2008, and 2002, are loved by both critics and users.

Task 7: Sales in the Best Video Game Years

• Query:

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SELECT gs.year,
       SUM(gs.games_sold) AS total_games_sold
FROM game_sales gs
WHERE gs.year IN (
    SELECT year
    FROM top_critic_years_more_than_four_games
    INTERSECT
    SELECT year
    FROM top_user_years_more_than_four_games
)
GROUP BY gs.year
ORDER BY total_games_sold DESC;

• Summary: Years like 2008, 1998, and 2002 saw significant sales, aligning with critical and user acclaim.

Task 8: Sales in the Best Video Game Years

• Query:

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SELECT gs.year,
       SUM(gs.games_sold) AS total_games_sold
FROM game_sales gs
WHERE gs.year IN (
    SELECT year
    FROM top_critic_years_more_than_four_games
    INTERSECT
    SELECT year
    FROM top_user_years_more_than_four_games
)
GROUP BY gs.year
ORDER BY total_games_sold DESC;

• Summary: The years 2008, 1998, and 2002 stand out with the highest total games sold, indicating strong commercial success during these periods.

Conclusion

Based on our analysis, the early 1990s and the years 1998, 2008, and 2002 appear to be potential “golden ages” of video games, as they received high praise from both critics and users and had significant sales figures.

Stay tuned for more exciting data analysis projects on various topics!

Game-Scope Streamlit App

Welcome to the Game-Scope Streamlit app! This app allows you to explore and analyze data related to video games, including top-selling games, critic scores, user scores, and sales analysis.

How to Use

1. Navigation: Use the sidebar on the left to navigate between different pages:

• Top Selling Games: View the top-selling games based on total shipments.
• Critic Scores: Explore critic scores for video games.
• User Scores: Discover user scores for video games.
• Sales Analysis: Analyze sales trends and insights.

2. Interactive Visualizations: Each page includes interactive visualizations to help you explore the data more effectively.

3. Data Analysis: Gain insights into top publishers, top developers, and average sales per year through the Sales Analysis page.

Access the App

You can access the Game-Scope Streamlit app here.

GitHub Repository

Explore the code and contribute to the development of the Game-Scope app on GitHub: Game-Scope GitHub Repository.

Author

• Name: Mohammed Mebarek Mecheter
• Email: mohammedmecheter@gmail.com
• GitHub: Mohammed Mebarek Mecheter

Feedback and Contributions

We welcome any feedback or contributions to improve the functionality and user experience of the app. Feel free to open issues or pull requests on the GitHub repository.