Robin Langlois [DAFT JAN 2020]
[Data Analytics DAF JAN 2020, BCN]
My project is a short story of videogame consoles from 2000 onwards, focusing on the 4 major brands (Sony, Microsoft, Nintendo & Sega). I created a methodology to measure, through several indicators & metrics, which consoles have the best games and how they perform versus one another. (check out my paper VideoGame_Consoles_Market_Study for mor in-depth infos)
My asumption was that Sony PlayStations are performing very well, when comparing to others. Aside from the sales records, which are publically known good to PlayStation, I wanted to measure whether critics scores are good when measuring games quality. My datasets & analysis confirmed that asumption, while giving more precise insights on that topic.
What dataset (or datasets) did you use? What are the different sources you used (e.g. APIs, web scrapping, etc.)? Provide links to the data if available and describe the data briefly.
- I scraped data through API calls from RAWG, a popular videogame API centralising info over 360K games
- web scraping from VG Charts
- CSVs from Kaggle MetaCritics from 2000
Outline the workflow you used in your project. What are the steps you went through?
- Several days of Data scavengering, looking for possible
- Establishing hypothesis
- Several Notebooks to test out codes, chart creation
- Tableau dashboard creation to centralise key findings
How did you organize your work? I created a Trello to display & distribute tasks divided into 3 categories : 1 - Pre-work (research & Data) 2 - Coding 3 - Tableau 3 - Presentation
What does your repository look like? Quite straightforward :
- One folder for the Notebooks, the Python Scripts & the Tableau Dashboards
- One folder for the database
- One folder for the charts
Include links to your repository, slides and kanban board. Feel free to include any other links associated with your project.