This project conducts analysis on video game data, emphasizing user scores, developers, geners and release years. The dataset used in this analysis contains information about various video games, including user ratings, developers, release years, and other relevant details.
The objective of this project is to gain insights into the video game industry by performing SQL-based analyses on user scores, developers, and release years. By querying the dataset, we aim to identify trends, patterns, and correlations that can provide valuable information for game developers, publishers, and enthusiasts.
Imputing Null Values: Code for handling null values in key columns such as Product_Rating, User_Score, and User_Ratings_Count.
Creating Product Rating Code: Introduces a new column, Product_Rating_Code, based on a mapping of Product_Rating values.
Games with Highest User Score in Every Year with Genre: Identifies the highest-rated game in each year along with its genre.
Highest Rating Games from Each Developer: Lists games from each developer with a user score of 8 or higher.
Number of Games Each Developer has with User Score of 8 or Higher: Provides a count of games with a user score of 8 or higher for each developer.
Highest-Rated Game by Each Developer Each Year: Presents the highest-rated game by each developer in each year.
Number of Titles in Each Genre with User Score of 8 or Higher: Counts titles in each genre with a user score of 8 or higher.
User-Defined Function (UDF) for Top 10 Games by Genre: Demonstrates the creation of a UDF to fetch the top 10 games for a specified genre.
Average User Score by Genre: Calculates the average user score and the number of games for each combination of genre and product rating.
The dataset used in this project is sourced from (https://www.kaggle.com/datasets/beridzeg45/video-games )