Not all Pokémon are created equal. Some are consigned to mediocrity, useless in battle until they reach their more evolved states. Others – like Zapdos, Articuno and Moltres – are so unique and powerful that they have officially been classified as legendary. But what exactly makes a Pokémon the stuff of legend? In this project, we will answer that question with the help of a dataset that includes the base stats, height, weight and type of 801 Pokémon from all seven generations. Using the random forest algorithm, we will predict Pokemon status based on these characteristics and rank their importance in determining whether a Pokemon is classified as legendary. Students should be familiar with the tidyverse suite of packages, particularly ggplot2 for data visualization and dplyr for data manipulation. They should also have experience with classification problems and tree-based methods, as taught through Supervised Learning in R: Classification and Machine Learning with Tree-Based Models in R. This project uses a subset of The Complete Pokemon Dataset published on Kaggle.

In 1847, the Hungarian physician Ignaz Semmelweis makes a breakthough discovery: He discovers handwashing. Contaminated hands was a major cause of childbed fever and by enforcing handwashing at his hospital he saved hundreds of lives. In this R project we will reanalyze the medical data Semmelweis collected. This project assumes you can manipulate data frames using dplyr and make simple plots using ggplot2. You can learn these skills in the course Introduction to the Tidyverse.

This article was written by Leap Kasten. The visualization and code featured in this article were created by Jennifer Smith.