stat_count gives cryptic error when used on a column of doubles

[arencambre]

Run this trivial code (csv is attached):

library(tidyverse)

data <- read_csv("data.csv")

data %>%
  ggplot(aes(x=Tenure)) +
  geom_bar()

You get this warning:

Warning message:
Computation failed in `stat_count()`:
Elements must equal the number of rows or 1 

This is the resulting plot:

The data:
data.csv

Expected behavior: it should "just work". All the data in this tibble is just doubles. I reviewed the geom_bar documentation, and I see no contraindications for this working.

If I have done something wrong here, then this becomes a feature request for a useful error message or improved documentation.

[hadley]

Minimal reprex:

library(ggplot2)

df <- data.frame(x = rep(c(1, 2), 5) + rep(c(0, -2.220446e-16), c(4, 1)))
df
#>    x
#> 1  1
#> 2  2
#> 3  1
#> 4  2
#> 5  1
#> 6  2
#> 7  1
#> 8  2
#> 9  1
#> 10 2
ggplot(df, aes(x)) + geom_bar()
#> Warning: Computation failed in `stat_count()`:
#> Elements must equal the number of rows or 1

^{Created on 2022-03-15 by the reprex package (v2.0.1)}

Since this seems like a FP buglet I think it's worth taking a bit of a look to see what's going wrong.

[yutannihilation]

It seems the problem is that the criteria of the "same" value differ between vctrs::vec_unique() (which is used in unique0()) and as.factor() (in tapply()).

ggplot2/R/stat-count.r

Lines 79 to 89 in a979ffd

	count <- as.numeric(tapply(weight, x, sum, na.rm = TRUE))
	count[is.na(count)] <- 0
	bars <- data_frame0(
	count = count,
	prop = count / sum(abs(count)),
	x = sort(unique0(x)),
	width = width,
	flipped_aes = flipped_aes,
	.size = length(count)
	)

df <- data.frame(x = rep(c(1, 2), 5) + rep(c(0, -2.220446e-16), c(4, 1)))
ggplot2:::unique0(df$x)
#> [1] 1 2 1 2

tapply(rep(1, times = nrow(df)), df$x, sum, na.rm = TRUE)
#> 1 2 
#> 5 5
as.factor(df$x)
#>  [1] 1 2 1 2 1 2 1 2 1 2
#> Levels: 1 2

^{Created on 2022-07-23 by the reprex package (v2.0.1)}

[teunbrand]

In such case, should we add a tolerance or treat them as unequal? If treated as unequal, we could replace the tapply() by rowsum().

[hadley]

I'd say we follow whatever vec_unique does.