The tidyverse

The tidyverse is a set of packages which attempts to make R more consistent. R was written by statisticians and it is a bit quirky. The tidyverse makes it look more like other programming languages which were developed by computer scientists. It is a different style of writing R code and it is by no means necessary.

A glimpse at the tidyverse

The best introduction to the tidyverse is probably the book R for Data Science by Hadley Wickham and Garrett Grolemund.

Posit (the company formerly known as RStudio Inc. behind the tidyverse) developed a series of useful cheatsheets. Below are links to the ones you are the most likely to use as you get started with R.

Data import

The first thing you often need to do is to import your data into R. This is done with readr.

from Posit Cheatsheets

Data transformation

You then often need to transformation your data into the right format. This is done with the packages dplyr and tidyr.

from Posit Cheatsheets

from Posit Cheatsheets

Visualization

Visualization in the tidyverse is done with the ggplot2 package which we will explore in the next section.

from Posit Cheatsheets

Working with factors

The package forcats offers the tidyverse approach to working with factors.

from Posit Cheatsheets

Working with strings

stringr is for strings.

from Posit Cheatsheets

Working with dates

lubridate will help you deal with dates.

from Posit Cheatsheets

Functional programming

Finally, purrr is the tidyverse equivalent to the apply functions in base R: a way to run functions on functions.

from Posit Cheatsheets

Base R or tidyverse?

“Base R” refers to the use of the standard R library. The expression is often used in contrast to the tidyverse.

There are a many things that you can do with either base R or the tidyverse. Because the syntaxes are quite different, it almost feels like using two different languages and people tend to favour one or the other.

Which one you should use is really up to you.

Base R	Tidyverse
Preferred by old-schoolers	Increasingly becoming the norm with newer R users
More stable	More consistent syntax and behaviour
Doesn’t require installing and loading packages	More and more resources and documentation available

In truth, even though the tidyverse has many detractors amongst old R users, it is increasingly becoming the norm.