Change `data set` to `dataset` (#1282)

- It changes `data set(s)` to `dataset(s)` for consistency, throughout the book.
- It adds `# Left` and `# Right` comments for similar side-by-side plots.

communication.qmd

@@ -774,11 +774,13 @@ Compare the following two plots:
 #| fig-height: 3
 #| message: false
 
+# Left
 ggplot(mpg, aes(x = displ, y = hwy)) +
   geom_point(aes(color = class)) +
   geom_smooth() +
   coord_cartesian(xlim = c(5, 7), ylim = c(10, 30))
 
+# Right
 mpg |>
   filter(displ >= 5, displ <= 7, hwy >= 10, hwy <= 30) |>
   ggplot(aes(x = displ, y = hwy)) +
@@ -799,9 +801,11 @@ For example, if we extract two classes of cars and plot them separately, it's di
 suv <- mpg |> filter(class == "suv")
 compact <- mpg |> filter(class == "compact")
 
+# Left
 ggplot(suv, aes(x = displ, y = hwy, color = drv)) +
   geom_point()
 
+# Right
 ggplot(compact, aes(x = displ, y = hwy, color = drv)) +
   geom_point()
 ```
@@ -817,12 +821,14 @@ x_scale <- scale_x_continuous(limits = range(mpg$displ))
 y_scale <- scale_y_continuous(limits = range(mpg$hwy))
 col_scale <- scale_color_discrete(limits = unique(mpg$drv))
 
+# Left
 ggplot(suv, aes(x = displ, y = hwy, color = drv)) +
   geom_point() +
   x_scale +
   y_scale +
   col_scale
 
+# Right
 ggplot(compact, aes(x = displ, y = hwy, color = drv)) +
   geom_point() +
   x_scale +

intro.qmd

@@ -57,7 +57,7 @@ Visualizations can surprise you, and they don't scale particularly well because
 **Models** are complementary tools to visualization.
 Once you have made your questions sufficiently precise, you can use a model to answer them.
 Models are a fundamentally mathematical or computational tool, so they generally scale well.
-Even when they don\'t, it\'s usually cheaper to buy more computers than it is to buy more brains!
+Even when they don't, it's usually cheaper to buy more computers than it is to buy more brains!
 But every model makes assumptions, and by its very nature a model cannot question its own assumptions.
 That means a model cannot fundamentally surprise you.
 

numbers.qmd

@@ -224,7 +224,7 @@ In R, `%/%` does integer division and `%%` computes the remainder:
 1:10 %% 3
 ```
 
-Modular arithmetic is handy for the flights dataset, because we can use it to unpack the `sched_dep_time` variable into `hour` and `minute`:
+Modular arithmetic is handy for the `flights` dataset, because we can use it to unpack the `sched_dep_time` variable into `hour` and `minute`:
 
 ```{r}
 flights |>