Start with R for data science (book by Hadley, available online for free) Tidy verse assumes tidy data. If you are not working with tidy data, it is unlikely t

Start with R for data science (book by Hadley, available online for free) Tidy verse assumes tidy data. If you are not working with tidy data, it is unlikely to be a big help. Most data can probably be thought of as tidy. Remember that any and every operation on a data frame returns a data frame, so unlike chaining in Pandas, you never have to worry if a method you want to use belongs to a series or a data frame, or if your method is returning a series or a data frame. Select() selects columns, filter() selects rows. This never changes unlike the [] which means different thing depending on if it is used on a data frame (which you are not guaranteed to be served after calling a method on data frame in pandas!) on a series or using the .loc or .iloc methods. There is no index, instead you just filter on rows. Pandas comes with a ton of build in utilities which the tidyverse doesn’t, mostly because R is already full of functions you can easily apply across columns. But particularly pandas date handling functions are really cool