From 0a5be3a0227b7698828208d53c35ecf66121de20 Mon Sep 17 00:00:00 2001 From: Peter Baumgartner Date: Sun, 16 Apr 2023 16:06:53 +0200 Subject: [PATCH] Fixing typo in numbers chapter (#1425) --- numbers.qmd | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/numbers.qmd b/numbers.qmd index 3c2684a..7091c3c 100644 --- a/numbers.qmd +++ b/numbers.qmd @@ -14,7 +14,7 @@ Numeric vectors are the backbone of data science, and you've already used them a Now it's time to systematically survey what you can do with them in R, ensuring that you're well situated to tackle any future problem involving numeric vectors. We'll start by giving you a couple of tools to make numbers if you have strings, and then going into a little more detail of `count()`. -Then we'll dive into various numeric transformations that pair well with `mutate()`, including more general transformations that can be applied to other types of vector, but are often used with numeric vectors. +Then we'll dive into various numeric transformations that pair well with `mutate()`, including more general transformations that can be applied to other types of vectors, but are often used with numeric vectors. We'll finish off by covering the summary functions that pair well with `summarize()` and show you how they can also be used with `mutate()`. ### Prerequisites