Baselight

Video Game Sales Dataset Updated -Extra Feat

Uncover the Gaming Industry Trends with the Most Comprehensive Sales Data

@kaggle.ibriiee_video_games_sales_dataset_2022_updated_extra_feat

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About this Dataset

Video Game Sales Dataset Updated -Extra Feat

Video Games Sales Dataset

About Dataset

This Dataset provides up-to-date information on the sales performance and popularity of various video games worldwide. The data includes the name, platform, year of release, genre, publisher, and sales in North America, Europe, Japan, and other regions. It also features scores and ratings from both critics and users, including average critic score, number of critics reviewed, average user score, number of users reviewed, developer, and rating. This comprehensive and essential dataset offers valuable insights into the global video game market and is a must-have tool for gamers, industry professionals, and market researchers.
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Columns
Column Name Description
Name The name of the video game.
Platform The platform on which the game was released, such as PlayStation, Xbox, Nintendo, etc.
Year of Release The year in which the game was released.
Genre The genre of the video game, such as action, adventure, sports, etc.
Publisher The company responsible for publishing the game.
NA Sales The sales of the game in North America.
EU Sales The sales of the game in Europe.
JP Sales The sales of the game in Japan.
Other Sales The sales of the game in other regions.
Global Sales The total sales of the game across the world.
Critic Score The average score given to the game by professional critics.
Critic Count The number of critics who reviewed the game.
User Score The average score given to the game by users.
User Count The number of users who reviewed the game.
Developer The company responsible for developing the game.
Rating The rating assigned to the game by organizations such as the ESRB or PEGI.

Research Ideas / Data Use
  • Market Analysis: The video game sales data can be used to analyze market trends and identify popular genres, platforms, and publishers. This can be useful for industry professionals to make informed decisions about game development and marketing strategies.
  • Sales Forecasting: The sales data can be used to forecast future trends and predict the success of upcoming games.
  • Consumer Insights: The data can be analyzed to gain insights into consumer preferences and buying habits, which can be used to tailor marketing strategies and improve customer satisfaction.
  • Comparison of Competitors: The data can be used to compare the sales performance of competing video games and identify market leaders.
  • Gaming Industry Performance: The data can be used to evaluate the overall performance of the gaming industry and track its growth over time.
  • Gaming Popularity by Region: The data can be analyzed to determine which regions are the largest markets for video games and which genres are most popular in each region.
  • Impact of Reviews: The data can be used to study the impact of critic and user reviews on sales and the relationship between scores and sales performance.
  • Gaming Trends over Time: The data can be used to identify trends in the gaming industry over time and to track the evolution of the market.
  • Gaming Demographics: The data can be used to analyze the demographic makeup of the gaming audience, including age, gender, and income.
  • Impact of Gaming Industry on the Economy: The data can be used to evaluate the impact of the gaming industry on the economy and to assess its contribution to job creation and economic growth.

Acknowledgements

if this dataset was used in your work or studies, please credit the original source
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Tables

Video Games

@kaggle.ibriiee_video_games_sales_dataset_2022_updated_extra_feat.video_games
  • 478.15 KB
  • 16719 rows
  • 16 columns
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CREATE TABLE video_games (
  "name" VARCHAR,
  "platform" VARCHAR,
  "year_of_release" DOUBLE,
  "genre" VARCHAR,
  "publisher" VARCHAR,
  "na_sales" DOUBLE,
  "eu_sales" DOUBLE,
  "jp_sales" DOUBLE,
  "other_sales" DOUBLE,
  "global_sales" DOUBLE,
  "critic_score" DOUBLE,
  "critic_count" DOUBLE,
  "user_score" VARCHAR,
  "user_count" DOUBLE,
  "developer" VARCHAR,
  "rating" VARCHAR
);

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