Issue: Plot alpha values scaling with Y-Axis/number of observations in ggplot facets-CodePudding

I haven't found anyone else with this issue. Here is my plot:

Like OP's case, we expect all rectangles to be the same alpha value, but they are not. Also, note the alpha value is ridiculously low (0.01) for the color you see there. What's going on should be more obvious if we check number of observations in mtcars that falls within each facet:

> library(dplyr)
> mtcars %>% group_by(cyl) %>% tally()
# A tibble: 3 x 2
    cyl     n
  <dbl> <int>
1     4    11
2     6     7
3     8    14

There's a lower number of observations where cyl==6 and cyl==4 has lower observations than cyl==8. This corresponds precisely to the alpha values we see for the geoms in the plot, so this is what's going on. For each observation, a rectangle is drawn over the same position and so there are 7 rectangles drawn in the middle facet, 14 on the right facet, and 11 on the left facet.

Fixing the Issue: Summarize the Data

To fix the issue, you should summarize your data and use the summarized dataset for plotting the rectangles.

summary_df <- df %>%
  group_by(cyl) %>%
  summarize(mean_d = mean(disp))

p   geom_rect(
  data = summary_df,
  aes(x=1, y=1, xmin=mean_d-50, xmax=mean_d 50, ymin=-Inf, ymax=Inf),
  alpha=0.2, fill='red')

Since summary_df has only 3 observations (one for each group of cyl), the rectangles are drawn correctly and now alpha=0.2 with fill="red" gives the expected result. One thing to note here is that we still have to define x and y in the aes(). I set them both to 1 because although geom_rect() doesn't use them, ggplot2 still expects to find them in the dataset summary_df because we stated that they are assigned to that plot globally up in ggplot(df, aes(x=..., y=...)). The fix is to either move the aes() declaration into geom_point() or just assign both to be constant values in geom_rect().