game_success_analysis

Pattern identification that determine success of the game

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This project shows:

• ability of writing solid,structured Python code
• ability of using existing utilities(libraries) for processing and analyzing data.
• statistical analysis application
• exploratory analysis application
• analytical and data pre-processing skills

Project involves:

1. Data pre-processing
2. Exploratory Analysis
3. Statistical Analysis

Data description

Data is from open sources 2016 - historical game sales data: user and expert ratings, country sales, genres and platforms, ESRB ratings

• Name - the name of the game
• Platform - platform
• Year_of_Release - release year
• Genre - game genre
• NA_sales - sales in North America (millions of copies sold)
• EU_sales - sales in Europe (millions of copies sold)
• JP_sales - sales in Japan (millions of copies sold)
• Other_sales - sales in other countries (millions of copies sold)
• Critic_Score - critic scores (maximum 100)
• User_Score - user rating (maximum 10)
• Rating - rating by the ESRB (Entertainment Software Rating Board), which determines the rating of the game and the appropriate age category

Task

We have open-source data on game sales, user and expert ratings, genres ,and platforms. We need to help the global online game store to find a potentially popular product, which will allow them to plan advertising campaigns. We need to identify patterns that determine the success of the game.

Libraries used

pandas numpy matplotlib seaborn scipy