Feedback from twitter

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Hadley Wickham 2022-11-04 16:37:53 -05:00
parent 3f68594404
commit eb0b19e641
1 changed files with 3 additions and 1 deletions

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@ -70,9 +70,11 @@ There are five main types of things that you can subset a vector with, i.e. that
x <- c(10, 3, NA, 5, 8, 1, NA)
# All non-missing values of x
!is.na(x)
x[!is.na(x)]
# All even (or missing!) values of x
x %% 2 == 0
x[x %% 2 == 0]
```
@ -123,7 +125,7 @@ We need to use it here because `[` doesn't use tidy evaluation, so you need to b
There's an important difference between tibbles and data frames when it comes to `[`.
In this book we've mostly used tibbles, which *are* data frames, but they tweak some older behaviors to make your life a little easier.
In most places, you can use tibbles and data frame interchangeably, so went we want to draw particular attention to R's built-in data frame, we'll write `data.frame`s.
In most places, you can use tibbles and data frame interchangeably, so when we want to draw particular attention to R's built-in data frame, we'll write `data.frame`s.
So if `df` is a `data.frame`, then `df[, cols]` will return a vector if `col` selects a single column and a data frame if it selects more than one column.
If `df` is a tibble, then `[` will always return a tibble.