What and Why Tidy Data?

Data scientists like to work with tidy data because it makes the data easier to work with. Visualizations, data manipulation, and modeling are made much easier when working with tidy data. Common coding environments for data science, including R Studio, Pandas in Python, and related packages have been designed to work well with tidy data. The first critical step in investigating a dataset is tidying. We will take a look at each rule from R for Data Science and see how you can format a data frame for each donut that you, as a data scientist/baker can use to visualize, explore, or model your data.