In the classic Pokémon games, you have a team of 6 Pokémon that you use to battle against other trainers. In battles, type match-ups are very important, as some types of moves are “super effective” against other types. For example, fire moves are super effective against grass Pokémon, which means they do double the damage they normally would. If you can set your team up so that you’re always optimally matched, you’re going to have a much easier time.
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I knew there was a chart out there that matches up every attacking type against every defending and tells you whether they’re super effective, normal, not very effective, or doesn’t have any effect. So I decided to use my R skills to answer this question (many thanks to my brother David Robinson for his guidance at various points). Along the way, we’ll do a quick exploratory analysis, learn about combinatorials, and leave the tidyverse to use matrices and some base functions.
In What Types Should You Have on Your Pokémon Team? Efficient Simulation with Matrices in R the excellent Emily Robinson makes the case that the best way to learn data science is to solve problems that you are interested in. There are of a course some fantastic further lines of enquiry for those interested - support for the national dex, support for other games in the series (like Pokémon Go), consideration for weather effects (water pokémon are more powerful in the rain, for instance), second order teams that are optimized to defeat the otherwise "efficient" teams, and support for personal preference (I will always have a Snorlax in my team, even though it may be suboptimal as a combatant).
Via Flowing Data.
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