fix: typo yuo -> you in tibbles & isolating primers

transform-data/01-tibbles/01-tibbles.Rmd

@@ -28,7 +28,7 @@ In this primer, you will explore the popularity of different names over time. To
 
 * tibbles and `View()`, which let you inspect raw data
 * `select()` and `filter()`, which let you extract rows and columns from a data frame
-* `arrange()`, which lets yuo reorder the rows in your data
+* `arrange()`, which lets you reorder the rows in your data
 * `%>%`, which organizes your code into reader-friendly "pipes"
 * `mutate()`, `group_by()`, and `summarize()`, which help you use your data to compute new variables and summary statistics
 

transform-data/02-isolating/02-isolating.Rmd

@@ -28,7 +28,7 @@ knitr::opts_chunk$set(echo = FALSE)
 In this case study, you will explore the popularity of your own name over time. Along the way, you will master some of the most useful functions for isolating variables, cases, and values within a data frame:
 
 * `select()` and `filter()`, which let you extract rows and columns from a data frame
-* `arrange()`, which lets yuo reorder the rows in your data
+* `arrange()`, which lets you reorder the rows in your data
 * `%>%`, which organizes your code into reader-friendly "pipes"
 
 This tutorial uses the [core tidyverse packages](http://tidyverse.org/), including ggplot2, tibble, and dplyr, as well as the `babynames` package. All of these packages have been pre-installed and pre-loaded for your convenience.