# tidyverse

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The tidyverse collection of packages is a suite of packages that simplifies a huge number of the commonest tasks I do in R. It’s become indispensable for me, and I’ll make heavy use of it.

I draw your attention to dplyr, one of the tidyverse packages. It provides a set of functions that makes manipulating data frames a lot neater. You can filter, select, sort, and create new columns in a much neater way than using R’s… esoteric… native syntax.

I strongly recommend visiting — and bookmarking — their website.

Here’s one example of how the clarity of a piece of code can improve. Suppose you want to subset the (inbuilt) `iris`

data frame according to the width of the sepals and the length of the petals. In the traditional R way, you might write

`iris[iris$Sepal.Width < 3.25 & iris$Petal.Length < 5, ]`

But using dplyr, it’s

```
iris %>%
filter(Sepal.Width < 3.25) %>%
filter(Petal.Length < 5)
```

I will use `filter`

, `select`

, `arrange`

, `mutate`

from the dplyr package, `crossing`

from the tidyr package, and many functions from the stringr package frequently.

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