We have dataset given from an online store - Ice, which sells video games all over the world. User and expert reviews, genres, platforms (e.g. Xbox or PlayStation), and historical data on game sales are available from open sources. We need to identify patterns that determine whether a game succeeds or not. This will allow us to spot potential big winners and plan advertising campaigns.
We've been given data in file datasets/games.csv
. The given csv data file has 11 columns and comma as field separator. The description of the columns are as follows:
Column Names | Description |
---|---|
Name | Name of the game |
Platform | Platform of the games release (i.e. PC,PS4, etc.) |
Year_of_Release | The year when the game was released |
Genre | Genre of the game |
NA_sales | North American sales in USD million |
EU_sales | Sales in Europe in USD million |
JP_sales | Sales in Japan in USD million |
Other_sales | Sales in other countries in USD million |
Critic_Score | Professional critic score given for a game. Maximum of 100. |
User_Score | Score given by users for a game. Maximum of 10. |
Rating | Rating given by ESRB. The Entertainment Software Rating Board evaluates a game's content and assigns an age rating such as Teen or Mature. |
The project goals are as follows:
🔹 Identify patterns that determine the success of video games: By analyzing the available data, we aim to uncover factors that contribute to a game's success, such as user and expert reviews, genres, platforms, and ESRB ratings.
🔹 Spot potential big winners: Through data analysis, we want to identify games that have the potential to be highly successful in terms of sales. By understanding the factors that contribute to success, we can pinpoint games that are likely to perform well and generate significant revenue.
🔹 Plan advertising campaigns: The insights gained from analyzing the data will enable us to plan effective advertising campaigns. By understanding the factors that influence game sales, we can target the right audience and promote games through appropriate channels, maximizing the reach and impact of our campaigns.
🔹 Forecast sales for 2017: Using the data available up until December 2016, we aim to forecast game sales for the upcoming year, 2017. This will allow us to make informed decisions and allocate resources effectively based on projected sales figures.
Overall, the project aims to leverage data analysis techniques to gain a deep understanding of the video game market, identify successful game attributes, and make data-driven decisions to maximize sales and revenue for Ice, the online store.