geom_bin_2d: warning message when using weight without group

[szimmer]

I found a problem with geom_bin_2d

I expected to be able to use a weight variable without a group variable but get a warning when I do this. The weight does seem to be used appropriately as the result is different when not using the weight.

Here is the code to reproduce the bug:

library(survey)
#> Loading required package: grid
#> Loading required package: Matrix
#> Loading required package: survival
#> 
#> Attaching package: 'survey'
#> The following object is masked from 'package:graphics':
#> 
#>     dotchart
library(ggplot2)

data(api)

ggplot(aes(x=api99, y=api00, weight=pw), data=apiclus2) +
  geom_bin_2d() 
#> Warning: The following aesthetics were dropped during statistical transformation: weight
#> ℹ This can happen when ggplot fails to infer the correct grouping structure in
#>   the data.
#> ℹ Did you forget to specify a `group` aesthetic or to convert a numerical
#>   variable into a factor?

ggplot(aes(x=api99, y=api00), data=apiclus2) +
  geom_bin_2d() 

^{Created on 2023-03-05 with reprex v2.0.2}

Standard output and standard error

-- nothing to show --

Session info

sessioninfo::session_info()
#> ─ Session info ───────────────────────────────────────────────────────────────
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#>  language (EN)
#>  collate  English_United States.utf8
#>  ctype    English_United States.utf8
#>  tz       America/New_York
#>  date     2023-03-05
#>  pandoc   2.19.2 @ C:/Program Files/RStudio/resources/app/bin/quarto/bin/tools/ (via rmarkdown)
#> 
#> ─ Packages ───────────────────────────────────────────────────────────────────
#>  package     * version date (UTC) lib source
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#> ──────────────────────────────────────────────────────────────────────────────

[teunbrand]

Thanks for the report! Is this conceptually similar to #5053, where also an inappropriate warning was emitted?

[szimmer]

Yes, I believe it is the same. Sorry I didn't see that when searching for issues before writing this one.

[teunbrand]

Reviewing when this occurs, I found that many more stats mention dropping weights. I think the weights are being dropped by design, so we don't need these warnings.

library(ggplot2)

ggplot(data.frame(x = 1:2)) +
  aes(x, y = x, weight = x) +
  geom_bin_2d()
#> Warning: The following aesthetics were dropped during statistical transformation: weight
#> ℹ This can happen when ggplot fails to infer the correct grouping structure in
#>   the data.
#> ℹ Did you forget to specify a `group` aesthetic or to convert a numerical
#>   variable into a factor?

ggplot(data.frame(x = c("A", "A", "B", "B"), y = 1:4)) +
  aes(x, y, weight = seq_along(y)) +
  geom_boxplot()
#> Warning: The following aesthetics were dropped during statistical transformation: weight
#> ℹ This can happen when ggplot fails to infer the correct grouping structure in
#>   the data.
#> ℹ Did you forget to specify a `group` aesthetic or to convert a numerical
#>   variable into a factor?

ggplot(faithfuld, aes(waiting, eruptions, z = density)) +
  geom_contour(aes(weight = seq_along(density)))
#> Warning: The following aesthetics were dropped during statistical transformation: weight
#> ℹ This can happen when ggplot fails to infer the correct grouping structure in
#>   the data.
#> ℹ Did you forget to specify a `group` aesthetic or to convert a numerical
#>   variable into a factor?

ggplot(data.frame(x = 1:2)) +
  aes(x, y = x, weight = x) +
  geom_hex()
#> Warning: The following aesthetics were dropped during statistical transformation: weight
#> ℹ This can happen when ggplot fails to infer the correct grouping structure in
#>   the data.
#> ℹ Did you forget to specify a `group` aesthetic or to convert a numerical
#>   variable into a factor?

ggplot(data.frame(x = 1:2)) +
  aes(x, x, weight = x) +
  stat_quantile()
#> Smoothing formula not specified. Using: y ~ x
#> Warning: The following aesthetics were dropped during statistical transformation: weight
#> ℹ This can happen when ggplot fails to infer the correct grouping structure in
#>   the data.
#> ℹ Did you forget to specify a `group` aesthetic or to convert a numerical
#>   variable into a factor?

^{Created on 2023-03-06 with reprex v2.0.2}