Analyze Starcraft II replays with Jupyter Notebooks
Create data visualizations for Starcraft II replays with the Data Science Experience
With this code pattern for the Starcraft II enthusiast, you can actually improve your game. This pattern helps you achieve your goals, whether you’re a developer wanting to find interesting insights by using replay analytics, or you’re a professional player looking to ramp up your gaming skills. Learn how to create data visualizations with Jupyter Notebooks, including the capability to analyze Starcraft II data.
Starcraft II is a real-time strategy video game that has more than 240,000 active players worldwide and numerous competitions to showcase the best in gamer strategy. This code pattern uses Jupyter Notebooks to analyze StarCraft II replays, create data visualizations that are based on player activity, and extract interesting insights about the winners and losers.
With this pattern, you master how to:
- Create and run a Jupyter Notebook in IBM Watson™ Studio.
- Use IBM Watson Studio Object Storage to access a replay file.
- Use sc2reader to load a replay into a Python object.
- Examine some of the basic replay information in the result.
- Parse the contest details into a usable object.
- Visualize the contest with Bokeh graphics.
- Store the processed replay in Cloudant®.
- The developer loads the provided notebook on IBM Watson Studio platform.
- Starcraft II replays are loaded into the IBM Cloud Object Storage.
- The notebook analyzes the replays, pulling them from the IBM Cloud Object Storage.
- The notebook uses a Cloudant NoSQL database to store the results and analysis.
Ready to put this code pattern to use? Complete details on how to get started running and using this application are in the README.md file.