Skip to content
Project: When Was the Golden Era of Video Games?
  • AI Chat
  • Code
  • Report

    • Video games are big business: the global gaming market is projected to be worth more than $300 billion by 2027 according to Mordor Intelligence. With so much money at stake, the major game publishers are hugely incentivized to create the next big hit. But are games getting better, or has the golden age of video games already passed?

    In this project, you'll analyze video game critic and user scores as well as sales data for the top 400 video games released since 1977. You'll search for a golden age of video games by identifying release years that users and critics liked best, and you'll explore the business side of gaming by looking at game sales data.

    Your search will involve joining datasets and comparing results with set theory. You'll also filter, group, and order data. Make sure you brush up on these skills before trying this project! The database contains two tables. Each table has been limited to 400 rows for this project, but you can find the complete dataset with over 13,000 games on Kaggle.

    game_sales table

    ColumnDefinitionData Type
    nameName of the video gamevarchar
    platformGaming platformvarchar
    publisherGame publishervarchar
    developerGame developervarchar
    games_soldNumber of copies sold (millions)float
    yearRelease yearint

    reviews table

    ColumnDefinitionData Type
    nameName of the video gamevarchar
    critic_scoreCritic score according to Metacriticfloat
    user_scoreUser score according to Metacriticfloat

    users_avg_year_rating table

    ColumnDefinitionData Type
    yearRelease year of the games reviewedint
    num_gamesNumber of games released that yearint
    avg_user_scoreAverage score of all the games ratings for the yearfloat

    critics_avg_year_rating table

    ColumnDefinitionData Type
    yearRelease year of the games reviewedint
    num_gamesNumber of games released that yearint
    avg_critic_scoreAverage score of all the games ratings for the yearfloat
    Unknown integration
    DataFrameavailable as
    df
    variable
    select * from game_sales 
limit 2 ;
    Unknown integration
    DataFrameavailable as
    df1
    variable
     select * from critics_avg_year_rating 
 limit 2;
    Unknown integration
    DataFrameavailable as
    df2
    variable
     select * from  users_avg_year_rating
 limit 2;
    Unknown integration
    DataFrameavailable as
    df3
    variable
      select * from   reviews
  limit 2;
    Unknown integration
    DataFrameavailable as
    best_selling_games
    variable
    -- best_selling_games
select * from game_sales 
order by games_sold desc 
limit 10;
    Unknown integration
    DataFrameavailable as
    critics_top_ten_years
    variable
    SELECT g.year, COUNT(g.name) AS num_games, ROUND(AVG(r.critic_score),2) AS avg_critic_score
FROM game_sales g
INNER JOIN reviews r
ON g.name = r.name
GROUP BY g.year
HAVING COUNT(g.name) > 4
ORDER BY avg_critic_score DESC
LIMIT 10;
    Unknown integration
    DataFrameavailable as
    golden_years
    variable
    -- golden_years
SELECT u.year, u.num_games, c.avg_critic_score, u.avg_user_score, GREATEST(c.avg_critic_score, u.avg_user_score) - LEAST(c.avg_critic_score, u.avg_user_score) AS diff
FROM critics_avg_year_rating c
INNER JOIN users_avg_year_rating u
ON c.year = u.year
WHERE c.avg_critic_score > 9 OR u.avg_user_score > 9
ORDER BY diff ASC