Project: When Was the Golden Era of Video Games?

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

Column	Definition	Data Type
name	Name of the video game	`varchar`
platform	Gaming platform	`varchar`
publisher	Game publisher	`varchar`
developer	Game developer	`varchar`
games_sold	Number of copies sold (millions)	`float`
year	Release year	`int`

`reviews` table

Column	Definition	Data Type
name	Name of the video game	`varchar`
critic_score	Critic score according to Metacritic	`float`
user_score	User score according to Metacritic	`float`

`users_avg_year_rating` table

Column	Definition	Data Type
year	Release year of the games reviewed	`int`
num_games	Number of games released that year	`int`
avg_user_score	Average score of all the games ratings for the year	`float`

`critics_avg_year_rating` table

Column	Definition	Data Type
year	Release year of the games reviewed	`int`
num_games	Number of games released that year	`int`
avg_critic_score	Average score of all the games ratings for the year	`float`

Q1. Find the ten best-selling games.

DataFrameas

best_selling_games

variable

SELECT *
FROM game_sales
ORDER BY games_sold DESC
LIMIT 10;

Q2.Find the ten years with the highest average critic score, where at least four games were released (to ensure a good sample size).

DataFrameas

critics_top_ten_years

variable

SELECT year, COUNT(name) AS num_games, 
			 ROUND(AVG(critic_score),2) AS avg_critic_score
FROM game_sales
INNER JOIN reviews
USING (name)
GROUP BY year
HAVING COUNT(name)>4
ORDER BY avg_critic_score DESC
LIMIT 10;

Q3. Find the years where critics and users broadly agreed that the games released were highly rated. Specifically, return the years where the average critic score was over 9 OR the average user score was over 9.

DataFrameas

golden_years

variable

-- golden_years_
SELECT year, critics_avg_year_rating.num_games, avg_critic_score,
			            avg_user_score, 
						avg_critic_score - avg_user_score AS diff
FROM critics_avg_year_rating
INNER JOIN users_avg_year_rating
USING(year)
WHERE avg_critic_score>9 OR avg_user_score>9
ORDER BY year ASC;

Project: When Was the Golden Era of Video Games?

reviews table

users_avg_year_rating table

critics_avg_year_rating table

Q1. Find the ten best-selling games.

Q2.Find the ten years with the highest average critic score, where at least four games were released (to ensure a good sample size).

Q3. Find the years where critics and users broadly agreed that the games released were highly rated. Specifically, return the years where the average critic score was over 9 OR the average user score was over 9.

`reviews` table

`users_avg_year_rating` table

`critics_avg_year_rating` table