Python: Wrangled and unpivoted gaming datasets. Tableau: created dashboards - Market Beacon and Player’s Shopping Guide.

GameStop

Project timeline: Jan 2021 - April 2021

Project team:

• Zinaida Dvoskina (myself)
• Kirill Ilin
• Zhi Ji
• Zhen Wei

Created two information products for GameStop. Using Python, wrangled and unpivoted datasets, and created Tableau dashboards.

Based on the data of games such as release year, sales in different regions, genres, and platforms built Market Beacon for GameStop internal use. It shows potential opportunities for GameStop to tap into (which games to sell and promote, which platforms are most popular, etc.). The IP can also provide information regarding the sales patterns of different games in each region to help re-allocate resources and lower the inventory costs.

The second IP, the Player’s Shopping Guide provides game comparing services for players who are hesitating about purchasing. More specifically, the IP tells gamers the basic information (genre, publisher, available platforms, etc.) about the game they are looking at, reviews from other players (avg. score), and the keywords in the description and reviews. The IP provides gamers the best “shopping experience” and helps GameStop stay competitive among other video game sellers.

In this repository you can find our code, Tableau dashboards, project report and a presentation. The data files are too big to upload here.