This project includes an analysis conducted on a dataset of video game sales. Below, you'll find information about the project steps and analysis results.
The dataset used in the project contains sales data for video games. The dataset includes the following features:
- Rank: Overall sales ranking
- Name: Name of the game
- Platform: Platform of the game's release (PC, PS4, etc.)
- Year: Year of the game's release
- Genre: Genre of the game
- Publisher: Publisher of the game
- NA_Sales: Sales in North America (in millions)
- EU_Sales: Sales in Europe (in millions)
- JP_Sales: Sales in Japan (in millions)
- Other_Sales: Sales in the rest of the world (in millions)
- Global_Sales: Total worldwide sales
Missing data in the dataset has been checked, and appropriate methods have been used to fill in missing values.
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Descriptive Analysis of Numeric Variables: Statistical analyses and box plots have been created for Rank, Year, NA_Sales, EU_Sales, JP_Sales, Other_Sales, and Global_Sales.
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Analysis of Categorical Variables: Analyses with various charts have been conducted for Genre, Platform, and Publisher categorical variables.
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Top Game Publishers: The top 20 publishers with the highest number of games have been identified, and the counts of their games are visualized.
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Regional Correlation of Game Sales: The correlation of sales between North America, Europe, Japan, and other regions is visualized with a heatmap.
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Total Sales Over the Years: Line graphs show the total sales in North America, Europe, Japan, and other regions over the years.
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Top-selling Genres and Platforms: The top-selling genres and platforms are identified and visualized based on Genre and Platform.
If you want to contribute to the project, please fork it and send your changes in a pull request.
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Facebook
Microsoft
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Alibaba
D3
Tencent