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Tweak package install advice

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Hadley Wickham 2023-01-23 08:27:51 -06:00
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intro.qmd
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@ -213,15 +213,26 @@ This doesn't make them better or worse, just different.
In other words, the complement to the tidyverse is not the messyverse but many other universes of interrelated packages.
As you tackle more data science projects with R, you'll learn new packages and new ways of thinking about data.
In this book, we'll use five data packages from outside the tidyverse:
We'll use many packages from outside the tidyverse in this book.
For example, we use the following four data packages to provide interesting applications:
```{r}
#| eval: false
install.packages(c("gapminder", "Lahman", "nycflights13", "palmerpenguins"))
install.packages(c("babynames", "gapminder", "nycflights13", "palmerpenguins"))
```
These packages provide data on world development, baseball, airline flights, and body measurements of penguins that we'll use to illustrate key data science ideas, while the final one helps generate random data sets.
We'll also use a selection of other packages for one off examples.
You don't need to install them now, just remember that whenever you see an error like this:
```{r}
#| eval: false
library(ggrepel)
#> Error in library(ggrepel) : there is no package called ‘ggrepel’
```
You need to run `install.packages("ggrepel")` to install the package.
## Running R code