Add bin_prop computed variable to stat_bin

[kieran-mace]

Summary

Adds after_stat(bin_prop) functionality to stat_bin, bringing feature parity with stat_count. The new bin_prop computed variable shows the proportion of each group within each bin.

Closes #6478

Motivation

stat_count provides after_stat(prop) for proportion-based visualizations, but stat_bin lacked equivalent functionality. This made it difficult to create proportion-based histograms for continuous data.

Implementation

• Added compute_panel method to StatBin that calculates bin_prop = count_in_group / total_count_in_bin
• Handles multiple groups, weights, and empty bins correctly
• Maintains backwards compatibility (single groups have bin_prop = 1)
• Updated documentation to include the new computed variable

Usage Example

# Show proportion of each group within weight bins
ggplot(data, aes(x = weight, y = after_stat(bin_prop), fill = sex)) +
  stat_bin(geom = "col", bins = 8, position = "dodge") +
  scale_y_continuous(labels = scales::percent)

This addresses the feature gap where users could use after_stat(prop) with stat_count for discrete data but had no equivalent for continuous data with stat_bin.

Test plan

• All existing stat_bin tests pass (no regressions)
• Added comprehensive tests for bin_prop functionality
• Tested with single groups, multiple groups, and weighted data
• Verified after_stat(bin_prop) works correctly in plots
• Confirmed proportions sum to 1 within each bin

Some example output:

library(ggplot2)
# Create sample data with two groups
df <- data.frame(
  mass_kg = c(rnorm(1000, mean = 70, sd = 10), rnorm(500, mean = 85, sd = 12)),
  sex = c(rep("Female", 1000), rep("Male", 500))
)

ggplot(df, aes(x = mass_kg, fill = sex, color = sex)) +
  stat_bin(binwidth = 5, 
           mapping = aes(y = after_stat(bin_prop))) +
  labs(
    title = "Proportion in Each Mass bin",
    x = "Mass",
    y = "Proportion",
    color = "Sex"
  )

ggplot(df, aes(x = mass_kg, fill = sex, color = sex)) +
  stat_bin(binwidth = 5, 
           mapping = aes(y = after_stat(bin_prop)),
           geom = 'line',
           position = 'dodge') +
  labs(
    title = "Proportion in Each Mass bin",
    x = "Mass",
    y = "Proportion",
    color = "Sex"
  )

^{Created on 2025-05-22 with reprex v2.1.1}

🤖 Generated with Claude Code

[teunbrand]

Hi there, thanks for the PR! There are a few concerns that I hope can be alleviated, see related comments.

[teunbrand]

This all seems more complicated than it needs to be. Can't this be computed more directly?

[teunbrand]

Can you regenerate the .Rd files as well?

[teunbrand]

Breaks can be set directly if predictability is an issue

[teunbrand]

Isn't it more simple to test that the sum over bins is 1, regardless of how many groups?

[teunbrand]

Suggested change

	bin1_data <- data[data$x == min(data$x), ]
	bin2_data <- data[data$x == max(data$x), ]
	bin1_data <- data[data$x == 1, ]
	bin2_data <- data[data$x == 2, ]

We know from the test data what these values should be