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Remove uses of the mpg dataset. See #46
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bensoltoff committed Jan 6, 2022
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18 changes: 10 additions & 8 deletions content/notes/gapminder/index.Rmd
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Expand Up @@ -177,25 +177,27 @@ ggplot(data = gapminder, mapping = aes(x = gdpPercap, y = lifeExp, color = conti

Why use `facet_grid()` here instead of `facet_wrap()`? Good question! Let's reframe it and instead ask, what is the difference between `facet_grid()` and `facet_wrap()`?^[Example drawn from [this StackOverflow thread](https://stackoverflow.com/questions/20457905/whats-the-difference-between-facet-wrap-and-facet-grid-in-ggplot2).]

The answer below refers to the case when you have 2 arguments in `facet_grid()` or `facet_wrap()`. `facet_grid(x ~ y)` will display $x \times y$ plots even if some plots are empty. For example:
The answer below refers to the case when you have 2 arguments in `facet_grid()` or `facet_wrap()`. `facet_grid(rows = vars(x), cols = vars(y))` will display $y \times x$ plots even if some plots are empty. For example:

```{r facet-grid}
ggplot(mpg, aes(displ, hwy)) +
library(palmerpenguins)
ggplot(data = penguins, aes(x = bill_length_mm, y = body_mass_g)) +
geom_point() +
facet_grid(rows = vars(cyl), cols = vars(class))
facet_grid(rows = vars(species), cols = vars(island))
```

There are 4 distinct `cyl` and 7 distinct `class` values. This plot displays $4 \times 7 = 28$ plots, even if some are empty (because some classes do not have corresponding cylinder values, like rows with `class = "midsize"` doesn't have any corresponding `cyl = 5` value ).
There are 3 distinct `species` and `island` values. This plot displays $3 \times 3 = 9$ plots, even if some are empty (for example, Chinstrap penguins were not observed on Biscoe Island).

`facet_wrap(facets = vars(cyl, class))` displays only the plots having actual values.
`facet_wrap(facets = vars(species, island))` displays only the plots having actual values.

```{r facet-wrap}
ggplot(mpg, aes(displ, hwy)) +
ggplot(data = penguins, aes(x = bill_length_mm, y = body_mass_g)) +
geom_point() +
facet_wrap(facets = vars(cyl, class))
facet_wrap(facets = vars(species, island))
```

There are 19 plots displayed now, one for every combination of `cyl` and `class`. So for this exercise, I would use `facet_wrap()` because we are faceting on a single variable. If we faceted on multiple variables, `facet_grid()` may be more appropriate.
There are 5 plots displayed now, one for every combination of `species` and `island`. So for this exercise, I would use `facet_wrap()` because we are faceting on a single variable. If we faceted on multiple variables, `facet_grid()` may be more appropriate.

{{< /spoiler >}}

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194 changes: 105 additions & 89 deletions content/notes/gapminder/index.md
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Original file line number Diff line number Diff line change
Expand Up @@ -240,31 +240,41 @@ ggplot(data = gapminder, mapping = aes(x = gdpPercap, y = lifeExp, color = conti

Why use `facet_grid()` here instead of `facet_wrap()`? Good question! Let's reframe it and instead ask, what is the difference between `facet_grid()` and `facet_wrap()`?^[Example drawn from [this StackOverflow thread](https://stackoverflow.com/questions/20457905/whats-the-difference-between-facet-wrap-and-facet-grid-in-ggplot2).]

The answer below refers to the case when you have 2 arguments in `facet_grid()` or `facet_wrap()`. `facet_grid(x ~ y)` will display $x \times y$ plots even if some plots are empty. For example:
The answer below refers to the case when you have 2 arguments in `facet_grid()` or `facet_wrap()`. `facet_grid(rows = vars(x), cols = vars(y))` will display $y \times x$ plots even if some plots are empty. For example:


```r
ggplot(mpg, aes(displ, hwy)) +
library(palmerpenguins)

ggplot(data = penguins, aes(x = bill_length_mm, y = body_mass_g)) +
geom_point() +
facet_grid(rows = vars(cyl), cols = vars(class))
facet_grid(rows = vars(species), cols = vars(island))
```

```
## Warning: Removed 2 rows containing missing values (geom_point).
```

<img src="{{< blogdown/postref >}}index_files/figure-html/facet-grid-1.png" width="672" />

There are 4 distinct `cyl` and 7 distinct `class` values. This plot displays $4 \times 7 = 28$ plots, even if some are empty (because some classes do not have corresponding cylinder values, like rows with `class = "midsize"` doesn't have any corresponding `cyl = 5` value ).
There are 3 distinct `species` and `island` values. This plot displays $3 \times 3 = 9$ plots, even if some are empty (for example, Chinstrap penguins were not observed on Biscoe Island).

`facet_wrap(facets = vars(cyl, class))` displays only the plots having actual values.
`facet_wrap(facets = vars(species, island))` displays only the plots having actual values.


```r
ggplot(mpg, aes(displ, hwy)) +
ggplot(data = penguins, aes(x = bill_length_mm, y = body_mass_g)) +
geom_point() +
facet_wrap(facets = vars(cyl, class))
facet_wrap(facets = vars(species, island))
```

```
## Warning: Removed 2 rows containing missing values (geom_point).
```

<img src="{{< blogdown/postref >}}index_files/figure-html/facet-wrap-1.png" width="672" />

There are 19 plots displayed now, one for every combination of `cyl` and `class`. So for this exercise, I would use `facet_wrap()` because we are faceting on a single variable. If we faceted on multiple variables, `facet_grid()` may be more appropriate.
There are 5 plots displayed now, one for every combination of `species` and `island`. So for this exercise, I would use `facet_wrap()` because we are faceting on a single variable. If we faceted on multiple variables, `facet_grid()` may be more appropriate.

{{< /spoiler >}}

Expand Down Expand Up @@ -309,89 +319,95 @@ devtools::session_info()
## collate en_US.UTF-8
## ctype en_US.UTF-8
## tz America/Chicago
## date 2021-10-11
## date 2022-01-06
##
## ─ Packages ───────────────────────────────────────────────────────────────────
## package * version date lib source
## assertthat 0.2.1 2019-03-21 [1] CRAN (R 4.1.0)
## backports 1.2.1 2020-12-09 [1] CRAN (R 4.1.0)
## blogdown 1.4 2021-07-23 [1] CRAN (R 4.1.0)
## bookdown 0.23 2021-08-13 [1] CRAN (R 4.1.0)
## broom 0.7.9 2021-07-27 [1] CRAN (R 4.1.0)
## bslib 0.2.5.1 2021-05-18 [1] CRAN (R 4.1.0)
## cachem 1.0.6 2021-08-19 [1] CRAN (R 4.1.0)
## callr 3.7.0 2021-04-20 [1] CRAN (R 4.1.0)
## cellranger 1.1.0 2016-07-27 [1] CRAN (R 4.1.0)
## cli 3.0.1 2021-07-17 [1] CRAN (R 4.1.0)
## colorspace 2.0-2 2021-06-24 [1] CRAN (R 4.1.0)
## crayon 1.4.1 2021-02-08 [1] CRAN (R 4.1.0)
## DBI 1.1.1 2021-01-15 [1] CRAN (R 4.1.0)
## dbplyr 2.1.1 2021-04-06 [1] CRAN (R 4.1.0)
## desc 1.3.0 2021-03-05 [1] CRAN (R 4.1.0)
## devtools 2.4.2 2021-06-07 [1] CRAN (R 4.1.0)
## digest 0.6.27 2020-10-24 [1] CRAN (R 4.1.0)
## dplyr * 1.0.7 2021-06-18 [1] CRAN (R 4.1.0)
## ellipsis 0.3.2 2021-04-29 [1] CRAN (R 4.1.0)
## evaluate 0.14 2019-05-28 [1] CRAN (R 4.1.0)
## fansi 0.5.0 2021-05-25 [1] CRAN (R 4.1.0)
## fastmap 1.1.0 2021-01-25 [1] CRAN (R 4.1.0)
## forcats * 0.5.1 2021-01-27 [1] CRAN (R 4.1.0)
## fs 1.5.0 2020-07-31 [1] CRAN (R 4.1.0)
## generics 0.1.0 2020-10-31 [1] CRAN (R 4.1.0)
## ggplot2 * 3.3.5 2021-06-25 [1] CRAN (R 4.1.0)
## glue 1.4.2 2020-08-27 [1] CRAN (R 4.1.0)
## gtable 0.3.0 2019-03-25 [1] CRAN (R 4.1.0)
## haven 2.4.3 2021-08-04 [1] CRAN (R 4.1.0)
## here 1.0.1 2020-12-13 [1] CRAN (R 4.1.0)
## hms 1.1.0 2021-05-17 [1] CRAN (R 4.1.0)
## htmltools 0.5.1.1 2021-01-22 [1] CRAN (R 4.1.0)
## httr 1.4.2 2020-07-20 [1] CRAN (R 4.1.0)
## jquerylib 0.1.4 2021-04-26 [1] CRAN (R 4.1.0)
## jsonlite 1.7.2 2020-12-09 [1] CRAN (R 4.1.0)
## knitr 1.33 2021-04-24 [1] CRAN (R 4.1.0)
## lifecycle 1.0.0 2021-02-15 [1] CRAN (R 4.1.0)
## lubridate 1.7.10 2021-02-26 [1] CRAN (R 4.1.0)
## magrittr 2.0.1 2020-11-17 [1] CRAN (R 4.1.0)
## memoise 2.0.0 2021-01-26 [1] CRAN (R 4.1.0)
## modelr 0.1.8 2020-05-19 [1] CRAN (R 4.1.0)
## munsell 0.5.0 2018-06-12 [1] CRAN (R 4.1.0)
## pillar 1.6.2 2021-07-29 [1] CRAN (R 4.1.0)
## pkgbuild 1.2.0 2020-12-15 [1] CRAN (R 4.1.0)
## pkgconfig 2.0.3 2019-09-22 [1] CRAN (R 4.1.0)
## pkgload 1.2.1 2021-04-06 [1] CRAN (R 4.1.0)
## prettyunits 1.1.1 2020-01-24 [1] CRAN (R 4.1.0)
## processx 3.5.2 2021-04-30 [1] CRAN (R 4.1.0)
## ps 1.6.0 2021-02-28 [1] CRAN (R 4.1.0)
## purrr * 0.3.4 2020-04-17 [1] CRAN (R 4.1.0)
## R6 2.5.1 2021-08-19 [1] CRAN (R 4.1.0)
## Rcpp 1.0.7 2021-07-07 [1] CRAN (R 4.1.0)
## readr * 2.0.1 2021-08-10 [1] CRAN (R 4.1.0)
## readxl 1.3.1 2019-03-13 [1] CRAN (R 4.1.0)
## remotes 2.4.0 2021-06-02 [1] CRAN (R 4.1.0)
## reprex 2.0.1 2021-08-05 [1] CRAN (R 4.1.0)
## rlang 0.4.11 2021-04-30 [1] CRAN (R 4.1.0)
## rmarkdown 2.10 2021-08-06 [1] CRAN (R 4.1.0)
## rprojroot 2.0.2 2020-11-15 [1] CRAN (R 4.1.0)
## rstudioapi 0.13 2020-11-12 [1] CRAN (R 4.1.0)
## rvest 1.0.1 2021-07-26 [1] CRAN (R 4.1.0)
## sass 0.4.0 2021-05-12 [1] CRAN (R 4.1.0)
## scales 1.1.1 2020-05-11 [1] CRAN (R 4.1.0)
## sessioninfo 1.1.1 2018-11-05 [1] CRAN (R 4.1.0)
## stringi 1.7.3 2021-07-16 [1] CRAN (R 4.1.0)
## stringr * 1.4.0 2019-02-10 [1] CRAN (R 4.1.0)
## testthat 3.0.4 2021-07-01 [1] CRAN (R 4.1.0)
## tibble * 3.1.3 2021-07-23 [1] CRAN (R 4.1.0)
## tidyr * 1.1.3 2021-03-03 [1] CRAN (R 4.1.0)
## tidyselect 1.1.1 2021-04-30 [1] CRAN (R 4.1.0)
## tidyverse * 1.3.1 2021-04-15 [1] CRAN (R 4.1.0)
## tzdb 0.1.2 2021-07-20 [1] CRAN (R 4.1.0)
## usethis 2.0.1 2021-02-10 [1] CRAN (R 4.1.0)
## utf8 1.2.2 2021-07-24 [1] CRAN (R 4.1.0)
## vctrs 0.3.8 2021-04-29 [1] CRAN (R 4.1.0)
## withr 2.4.2 2021-04-18 [1] CRAN (R 4.1.0)
## xfun 0.25 2021-08-06 [1] CRAN (R 4.1.0)
## xml2 1.3.2 2020-04-23 [1] CRAN (R 4.1.0)
## yaml 2.2.1 2020-02-01 [1] CRAN (R 4.1.0)
## package * version date lib source
## assertthat 0.2.1 2019-03-21 [1] CRAN (R 4.1.0)
## backports 1.2.1 2020-12-09 [1] CRAN (R 4.1.0)
## blogdown 1.7 2021-12-19 [1] CRAN (R 4.1.0)
## bookdown 0.23 2021-08-13 [1] CRAN (R 4.1.0)
## broom 0.7.9 2021-07-27 [1] CRAN (R 4.1.0)
## bslib 0.3.1 2021-10-06 [1] CRAN (R 4.1.0)
## cachem 1.0.6 2021-08-19 [1] CRAN (R 4.1.0)
## callr 3.7.0 2021-04-20 [1] CRAN (R 4.1.0)
## cellranger 1.1.0 2016-07-27 [1] CRAN (R 4.1.0)
## cli 3.1.0 2021-10-27 [1] CRAN (R 4.1.0)
## codetools 0.2-18 2020-11-04 [1] CRAN (R 4.1.0)
## colorspace 2.0-2 2021-06-24 [1] CRAN (R 4.1.0)
## crayon 1.4.2 2021-10-29 [1] CRAN (R 4.1.0)
## DBI 1.1.1 2021-01-15 [1] CRAN (R 4.1.0)
## dbplyr 2.1.1 2021-04-06 [1] CRAN (R 4.1.0)
## desc 1.3.0 2021-03-05 [1] CRAN (R 4.1.0)
## devtools 2.4.2 2021-06-07 [1] CRAN (R 4.1.0)
## digest 0.6.28 2021-09-23 [1] CRAN (R 4.1.0)
## dplyr * 1.0.7 2021-06-18 [1] CRAN (R 4.1.0)
## ellipsis 0.3.2 2021-04-29 [1] CRAN (R 4.1.0)
## evaluate 0.14 2019-05-28 [1] CRAN (R 4.1.0)
## fansi 0.5.0 2021-05-25 [1] CRAN (R 4.1.0)
## farver 2.1.0 2021-02-28 [1] CRAN (R 4.1.0)
## fastmap 1.1.0 2021-01-25 [1] CRAN (R 4.1.0)
## forcats * 0.5.1 2021-01-27 [1] CRAN (R 4.1.0)
## fs 1.5.0 2020-07-31 [1] CRAN (R 4.1.0)
## gapminder * 0.3.0 2017-10-31 [1] CRAN (R 4.1.0)
## generics 0.1.1 2021-10-25 [1] CRAN (R 4.1.0)
## ggplot2 * 3.3.5 2021-06-25 [1] CRAN (R 4.1.0)
## glue 1.5.0 2021-11-07 [1] CRAN (R 4.1.0)
## gtable 0.3.0 2019-03-25 [1] CRAN (R 4.1.0)
## haven 2.4.3 2021-08-04 [1] CRAN (R 4.1.0)
## here 1.0.1 2020-12-13 [1] CRAN (R 4.1.0)
## highr 0.9 2021-04-16 [1] CRAN (R 4.1.0)
## hms 1.1.1 2021-09-26 [1] CRAN (R 4.1.0)
## htmltools 0.5.2 2021-08-25 [1] CRAN (R 4.1.0)
## httr 1.4.2 2020-07-20 [1] CRAN (R 4.1.0)
## jquerylib 0.1.4 2021-04-26 [1] CRAN (R 4.1.0)
## jsonlite 1.7.2 2020-12-09 [1] CRAN (R 4.1.0)
## knitr 1.33 2021-04-24 [1] CRAN (R 4.1.0)
## labeling 0.4.2 2020-10-20 [1] CRAN (R 4.1.0)
## lifecycle 1.0.1 2021-09-24 [1] CRAN (R 4.1.0)
## lubridate 1.7.10 2021-02-26 [1] CRAN (R 4.1.0)
## magrittr 2.0.1 2020-11-17 [1] CRAN (R 4.1.0)
## memoise 2.0.0 2021-01-26 [1] CRAN (R 4.1.0)
## modelr 0.1.8 2020-05-19 [1] CRAN (R 4.1.0)
## munsell 0.5.0 2018-06-12 [1] CRAN (R 4.1.0)
## palmerpenguins * 0.1.0 2020-07-23 [1] CRAN (R 4.1.0)
## pillar 1.6.4 2021-10-18 [1] CRAN (R 4.1.0)
## pkgbuild 1.2.0 2020-12-15 [1] CRAN (R 4.1.0)
## pkgconfig 2.0.3 2019-09-22 [1] CRAN (R 4.1.0)
## pkgload 1.2.1 2021-04-06 [1] CRAN (R 4.1.0)
## prettyunits 1.1.1 2020-01-24 [1] CRAN (R 4.1.0)
## processx 3.5.2 2021-04-30 [1] CRAN (R 4.1.0)
## ps 1.6.0 2021-02-28 [1] CRAN (R 4.1.0)
## purrr * 0.3.4 2020-04-17 [1] CRAN (R 4.1.0)
## R6 2.5.1 2021-08-19 [1] CRAN (R 4.1.0)
## Rcpp 1.0.7 2021-07-07 [1] CRAN (R 4.1.0)
## readr * 2.0.2 2021-09-27 [1] CRAN (R 4.1.0)
## readxl 1.3.1 2019-03-13 [1] CRAN (R 4.1.0)
## remotes 2.4.0 2021-06-02 [1] CRAN (R 4.1.0)
## reprex 2.0.1 2021-08-05 [1] CRAN (R 4.1.0)
## rlang 0.4.12 2021-10-18 [1] CRAN (R 4.1.0)
## rmarkdown 2.11 2021-09-14 [1] CRAN (R 4.1.0)
## rprojroot 2.0.2 2020-11-15 [1] CRAN (R 4.1.0)
## rstudioapi 0.13 2020-11-12 [1] CRAN (R 4.1.0)
## rvest 1.0.1 2021-07-26 [1] CRAN (R 4.1.0)
## sass 0.4.0 2021-05-12 [1] CRAN (R 4.1.0)
## scales 1.1.1 2020-05-11 [1] CRAN (R 4.1.0)
## sessioninfo 1.1.1 2018-11-05 [1] CRAN (R 4.1.0)
## stringi 1.7.5 2021-10-04 [1] CRAN (R 4.1.0)
## stringr * 1.4.0 2019-02-10 [1] CRAN (R 4.1.0)
## testthat 3.0.4 2021-07-01 [1] CRAN (R 4.1.0)
## tibble * 3.1.6 2021-11-07 [1] CRAN (R 4.1.0)
## tidyr * 1.1.4 2021-09-27 [1] CRAN (R 4.1.0)
## tidyselect 1.1.1 2021-04-30 [1] CRAN (R 4.1.0)
## tidyverse * 1.3.1 2021-04-15 [1] CRAN (R 4.1.0)
## tzdb 0.1.2 2021-07-20 [1] CRAN (R 4.1.0)
## usethis 2.0.1 2021-02-10 [1] CRAN (R 4.1.0)
## utf8 1.2.2 2021-07-24 [1] CRAN (R 4.1.0)
## vctrs 0.3.8 2021-04-29 [1] CRAN (R 4.1.0)
## withr 2.4.2 2021-04-18 [1] CRAN (R 4.1.0)
## xfun 0.29 2021-12-14 [1] CRAN (R 4.1.0)
## xml2 1.3.2 2020-04-23 [1] CRAN (R 4.1.0)
## yaml 2.2.1 2020-02-01 [1] CRAN (R 4.1.0)
##
## [1] /Library/Frameworks/R.framework/Versions/4.1/Resources/library
```
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