Companion code to webinar: Fanning the Flames: An Unfair Comparison Between Python and R in Data Science
There is a very popular, evergreen, debate on which is the more appropriate general-purpose tool for Data Science tasks: Python or R?
This is a side-by-side comparison of the two frameworks, applied to a typical Data Science workflow:
There's this cool massive-multiplayer game called sPyThon ("Space Python").
Players pilot gigantic metallic spaceships and compete to devour planets, which give them resources to upgrade their spaceships, making them even larger. All the time, you have to avoid crashing into yourself or other players trying to do the same as you. Think an updated 'Snake Game,' but in 3D, with thousands of other people --- and in space!
Sounds weird, but apparently fun once you get into it. Players get in-game credits, depending on the planet, and can also perform upgrades and customization via in-game purchases (which is how the game makes money).
The games company behind sPyThon needs a Data Scientist to answer one question: did their recent promotion increase in-game purchases?
Follow along with the Python and the R versions of this analysis!
You can also download the respective code as standalone scripts, right here from this repo.