[pull] main from swcarpentry:main

episodes/05-data-structures-part2.Rmd

@@ -347,7 +347,7 @@ script to use the function of that script without writing everything again.
 Check out `?source` to find out more.
 
 ```{r, eval=FALSE}
-download.file("https://raw.githubusercontent.com/swcarpentry/r-novice-gapminder/gh-pages/_episodes_rmd/data/gapminder_data.csv", destfile = "data/gapminder_data.csv")
+download.file("https://raw.githubusercontent.com/swcarpentry/r-novice-gapminder/main/episodes/data/gapminder_data.csv", destfile = "data/gapminder_data.csv")
 gapminder <- read.csv(file = "data/gapminder_data.csv")
 ```
 

episodes/13-dplyr.Rmd

@@ -470,10 +470,10 @@ lifeExp_2countries_bycontinents <- gapminder %>%
 
 ## Other great resources
 
-- [R for Data Science](https://r4ds.had.co.nz/)
-- [Data Wrangling Cheat sheet](https://www.rstudio.com/wp-content/uploads/2015/02/data-wrangling-cheatsheet.pdf)
-- [Introduction to dplyr](https://dplyr.tidyverse.org/)
-- [Data wrangling with R and RStudio](https://www.rstudio.com/resources/webinars/data-wrangling-with-r-and-rstudio/)
+- [R for Data Science](https://r4ds.hadley.nz/) (online book)
+- [Data Wrangling Cheat sheet](https://www.rstudio.com/wp-content/uploads/2015/02/data-wrangling-cheatsheet.pdf) (pdf file)
+- [Introduction to dplyr](https://dplyr.tidyverse.org/) (online documentation)
+- [Data wrangling with R and RStudio](https://www.rstudio.com/resources/webinars/data-wrangling-with-r-and-rstudio/) (online video)
 
 :::::::::::::::::::::::::::::::::::::::: keypoints
 

episodes/14-tidyr.Rmd

@@ -307,10 +307,10 @@ There and back again!
 
 ## Other great resources
 
-- [R for Data Science](https://r4ds.had.co.nz/index.html)
-- [Data Wrangling Cheat sheet](https://www.rstudio.com/wp-content/uploads/2015/02/data-wrangling-cheatsheet.pdf)
-- [Introduction to tidyr](https://cran.r-project.org/web/packages/tidyr/vignettes/tidy-data.html)
-- [Data wrangling with R and RStudio](https://www.rstudio.com/resources/webinars/data-wrangling-with-r-and-rstudio/)
+- [R for Data Science](https://r4ds.hadley.nz/) (online book)
+- [Data Wrangling Cheat sheet](https://www.rstudio.com/wp-content/uploads/2015/02/data-wrangling-cheatsheet.pdf) (pdf file)
+- [Introduction to tidyr](https://cran.r-project.org/web/packages/tidyr/vignettes/tidy-data.html) (online documentation)
+- [Data wrangling with R and RStudio](https://www.rstudio.com/resources/webinars/data-wrangling-with-r-and-rstudio/) (online video)
 
 :::::::::::::::::::::::::::::::::::::::: keypoints
 

instructors/instructor-notes.md

@@ -69,6 +69,21 @@ To prevent the learners from having to re-enter their password each time they pu
 $ git config --global credential.helper 'cache --timeout=10000000'
 ```
 
+## RStudio Color Preview
+
+RStudio has a feature to preview the color for certain named colors and hexadecimal colors. This may confuse or distract learners (and instructors) who are not expecting it.
+
+Mainly, this is likely to come up during the episode on "Data Structures" with the following code block:
+
+```r
+cats <- data.frame(coat = c("calico", "black", "tabby"),
+                    weight = c(2.1, 5.0, 3.2),
+                    likes_string = c(1, 0, 1))
+```
+
+This option can be turned off and on in the following menu setting:
+Tools -> Global Options -> Code -> Display -> Enable preview of named and hexadecimal colors (under "Syntax") 
+
 ## Pulling in Data
 
 The easiest way to get the data used in this lesson during a workshop is to have