Fix double legend in grouped_ggbarstats and grouped_ggpiestats

[Copilot]

When groups have different observed levels of x, grouped_ggbarstats/grouped_ggpiestats produce duplicate legends because patchwork::guides("collect") can't merge non-identical fill scales.

Root cause: descriptive_data() reconstructs the factor via factor(x, unique(x)), discarding unobserved levels after .cat_counter() filters zero-count rows. Each subplot ends up with a different set of factor levels → different legends.

Changes:

• R/ggpiestats-ggbarstats-helpers.R: Capture original factor levels before counting/filtering, then use union(unique(x), all_lvls) when reconstructing the factor to retain unobserved levels
• R/ggbarstats.R, R/ggpiestats.R: Add drop = FALSE to scale_fill_paletteer_d() so the fill scale includes all factor levels even when absent from the subplot's data
• Removed stale snapshot SVGs for regeneration in CI

# Previously produced two separate legends (4 vs 5 levels)
grouped_ggbarstats(
  data          = dt,
  x             = GenderIdentity,
  y             = subject,
  grouping.var  = school,
)

Original prompt

---

This section details on the original issue you should resolve

<issue_title>double legend in grouped_ggbarstats</issue_title>
<issue_description>I am potting some data that you can find below:

structure(list(school = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), levels = c("School 1", 
"School 2", "School 3", "School 4", "School 5", "School 6"), class = "factor"), 
    subject = structure(c(2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L), levels = c("Biology", "Chemistry", 
    "Physics"), class = "factor"), GenderIdentity = structure(c(1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 3L, 3L, 4L, 4L, NA, NA, NA, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 5L, 5L, 5L, 5L, 
    5L, 5L, 5L, 5L, 5L, 5L, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 
    5L, 5L, 5L, 5L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), levels = c("Man", 
    "Woman", "Non-binary", "Not listed", "Prefer not to answer"
    ), class = "factor")), class = c("grouped_df", "tbl_df", 
"tbl", "data.frame"), row.names = c(NA, -180L), groups = structure(list(
    school = structure(c(1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), levels = c("School 1", 
    "School 2", "School 3", "School 4", "School 5", "School 6"
    ), class = "factor"), subject = structure(c(2L, 2L, 2L, 2L, 
    2L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 
    3L, 3L), levels = c("Biology", "Chemistry", "Physics"), class = "factor"), 
    GenderIdentity = structure(c(1L, 2L, 3L, 4L, NA, 1L, 2L, 
    3L, 5L, NA, 1L, 2L, 3L, 5L, NA, 1L, 2L, 3L, 4L, 5L, NA), levels = c("Man", 
    "Woman", "Non-binary", "Not listed", "Prefer not to answer"
    ), class = "factor"), .rows = structure(list(1:10, 11:20, 
        21:22, 23:24, 25:27, 28:37, 38:47, 48:57, 58:67, 68:77, 
        78:87, 88:97, 98:107, 108:117, 118:127, 128:137, 138:147, 
        148:157, 158:160, 161:170, 171:180), ptype = integer(0), class = c("vctrs_list_of", 
    "vctrs_vctr", "list"))), row.names = c(NA, -21L), .drop = TRUE, class = c("tbl_df", 
"tbl", "data. Frame")))

When i plot, the legend is somehow messed up, and i cant figure out why there are two legends

grouped_ggbarstats(
  data          = dt,
  x             = GenderIdentity,
  y             = subject,
  grouping.var  = school,
  plotgrid.args = list(nrow = 2)
)

• I tried converting everything to characters- did not work
  </issue_description>

Comments on the Issue (you are @copilot in this section)

• Fixes double legend in grouped_ggbarstats #868

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[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 100.00%. Comparing base (7979ee2) to head (fe97bf5).
⚠️ Report is 2 commits behind head on main.

Additional details and impacted files

@@             Coverage Diff             @@
##             main     #1040      +/-   ##
===========================================
+ Coverage   99.86%   100.00%   +0.13%     
===========================================
  Files          17        17              
  Lines         767       770       +3     
===========================================
+ Hits          766       770       +4     
+ Misses          1         0       -1     

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