gt tables not honoring factors levels in row labels-CodePudding

I have a silly problem in making a table using the otherwise excellent gt package.

I have this table:

currTab <- structure(list(`Age range` = structure(c(5L, 6L, 7L, 8L, 9L, 
10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 1L, 2L, 3L, 4L), .Label = c(" ≤1 year", 
"2 yrs", "3 yrs", "4 yrs", "5 yrs", "6 yrs", "7-8 yrs", "9-10 yrs", 
"11-12 yrs", "13-14 yrs", "15-16 yrs", "19-30 yrs", "31-40 yrs", 
"41-50 yrs", "51-60 yrs", "61-70 yrs", " ≥70 yrs"), class = c("ordered", 
"factor")), minF_Female = c(192.513259215355, 183.831034165788, 
171.923523427238, 158.002976410505, 146.564781760376, 137.789704831087, 
127.370737204799, 128.398075852923, 127.830665246427, 114.61707107954, 
90.3633466641061, 78.010313243078, 78.1870193570691, NA, NA, 
NA, NA), minF_Male = c(207.855719860607, 191.535711870608, 169.079769539432, 
142.555089696259, 120.190679816665, 102.112304160514, 79.4522096443978, 
74.5501293799995, 74.0560562513096, 69.8375905638724, 57.7437980326593, 
49.4092475281028, 48.9416497200912, NA, NA, NA, NA), maxF_Female = c(488.066672846171, 
489.629983633728, 490.630420606523, 489.6953109154, 485.997969341596, 
479.493366060129, 457.131832057242, 386.052841894336, 356.20654778542, 
432.373754791911, 550.984958319451, 599.030148485128, 622.392016651455, 
NA, NA, NA, NA), maxF_Male = c(386.491941716704, 383.013074412721, 
377.262604560802, 368.664103740006, 358.88619036232, 347.858049187743, 
321.425630395873, 258.610024319393, 223.40438098279, 272.562362517114, 
352.663065356397, 389.139726222453, 396.387425129329, NA, NA, 
NA, NA), nominalF1_Female = c(792.606585070623, 774.67333252336, 
748.978655452818, 716.766904166985, 687.067342631714, 659.942877422917, 
613.464127049404, 549.839814945283, 524.453021680478, 524.604252664451, 
511.016250159981, 490.803284150502, 486.151004978768, 870.189435502058, 
849.931906280897, 830.243701660919, 811.132651353652), nominalF1_Male = c(754.927353762102, 
735.91406180303, 708.672474530183, 674.554785316654, 643.185788473706, 
614.682090933963, 565.988043403975, 499.441794119581, 471.850496193325, 
467.279224258147, 461.886047442941, 458.911042417315, 509.566754276534, 
837.039982744214, 815.632443409745, 794.801313106926, 774.561360377223
), nominalF2_Female = c(2316.79654051926, 2274.86292176996, 2214.51473531373, 
2138.33574040433, 2067.34402899125, 2001.61879507854, 1885.76397373785, 
1714.61348292451, 1625.93585114191, 1622.14234117408, 1641.9648727809, 
1707.39999135551, 1820.70094063161, 2497.1503947177, 2450.18163132232, 
2404.46219881265, 2359.99840070589), nominalF2_Male = c(2204.72154293521, 
2158.60270220094, 2092.40242942714, 2009.22489043384, 1932.3313895761, 
1861.92275643787, 1740.32902601832, 1567.84624090872, 1487.1049441955, 
1467.78392743302, 1499.7012515019, 1581.48607357091, 1689.73201386241, 
2403.51904879437, 2351.72182188825, 2301.30633827736, 2252.29783346018
), nominalF3_Female = c(3716.13980758452, 3629.61667155808, 3506.02757238294, 
3351.95172828646, 3211.26448866239, 3084.53931579307, 2871.44540359288, 
2591.76336829096, 2553.30039539724, 2581.55257096308, 2593.29167872634, 
2617.84457067156, 2692.78060751014, 3695.7825841822, 3626.26881435704, 
3558.60405424272, 3805.66484270251), nominalF3_Male = c(3398.97976277625, 
3327.2795690819, 3224.61918529811, 3096.22641948377, 2978.49201056792, 
2871.90468878882, 2690.5686257907, 2445.67764464339, 2369.21560078373, 
2361.71802712342, 2414.55734269414, 2497.82856943456, 2539.1115058239, 
3557.20819221567, 3480.54829639461, 3405.93338065049, 3473.04043452418
)), class = c("tbl_df", "tbl", "data.frame"), row.names = c(NA, 
-17L))

in which the Age range column is a factor:

> levels(currTab$`Age range`)
 [1] " ≤1 year"  "2 yrs"     "3 yrs"     "4 yrs"     "5 yrs"     "6 yrs"     "7-8 yrs"   "9-10 yrs"  "11-12 yrs" "13-14 yrs" "15-16 yrs"
[12] "19-30 yrs" "31-40 yrs" "41-50 yrs" "51-60 yrs" "61-70 yrs" " ≥70 yrs"

and apply this formating code:

currTab %>% 
  gt(rowname_col = "Age range")  %>%
  tab_stubhead(label="Age range")  %>%
  tab_spanner(
    label = "Female speakers",
    columns = c(minF_Female,maxF_Female,nominalF1_Female,   nominalF2_Female,nominalF3_Female)
  ) %>%
  tab_spanner(
    label = "Male speakers",
    columns = c(minF_Male,maxF_Male,nominalF1_Male, nominalF2_Male,nominalF3_Male)
  ) %>%
    cols_label(
    minF_Female = "minF",
    maxF_Female = "maxF",
    nominalF1_Female = "nominalF1",
    nominalF2_Female = "nominalF2",
    nominalF3_Female = "nominalF3" ,
    minF_Male = "minF",
    maxF_Male = "maxF",
    nominalF1_Male = "nominalF1",
    nominalF2_Male = "nominalF2",
    nominalF3_Male = "nominalF3"
  ) %>%
  fmt_integer(
    columns = minF_Female:nominalF3_Male,
    use_seps=FALSE
  ) %>%
  fmt_missing(everything(),missing_text="---")

and get this table:

As you can imagine, I would prefer the Age range column to follow the factor levels, and not place the first ones with empty columns at the end like that.

Any ideas?

Fredrik

CodePudding user response：

Order the dataframe beforehand:

base R

currTab[order(currTab$`Age range`),]

dplyr

currTab %>%
  arrange(`Age range`)

output

currTab %>%
  arrange(`Age range`) %>% 
  gt(rowname_col = "Age range")  %>%
  tab_stubhead(label="Age range")  %>%
  tab_spanner(
    label = "Female speakers",
    columns = c(minF_Female,maxF_Female,nominalF1_Female,   nominalF2_Female,nominalF3_Female)
  ) %>%
  tab_spanner(
    label = "Male speakers",
    columns = c(minF_Male,maxF_Male,nominalF1_Male, nominalF2_Male,nominalF3_Male)
  ) %>%
  cols_label(
    minF_Female = "minF",
    maxF_Female = "maxF",
    nominalF1_Female = "nominalF1",
    nominalF2_Female = "nominalF2",
    nominalF3_Female = "nominalF3" ,
    minF_Male = "minF",
    maxF_Male = "maxF",
    nominalF1_Male = "nominalF1",
    nominalF2_Male = "nominalF2",
    nominalF3_Male = "nominalF3"
  ) %>%
  fmt_integer(
    columns = minF_Female:nominalF3_Male,
    use_seps=FALSE
  ) %>%
  fmt_missing(everything(),missing_text="---")