Color a numeric gt column and add a matching quantile legend — gtscale_data_color

This is the primary interface for quantile scales in gtscales.

Usage

gtscale_data_color_quantiles(
  data,
  column,
  palette,
  quantiles = 4,
  oob = NULL,
  right = FALSE,
  labels = NULL,
  title = NULL,
  width = "180px",
  height = "14px",
  apply_to = c("fill", "text"),
  na_color = NULL,
  alpha = NULL,
  reverse = FALSE,
  autocolor_text = TRUE,
  contrast_algo = c("apca", "wcag"),
  autocolor_light = "#FFFFFF",
  autocolor_dark = "#000000"
)

Arguments

data: A gt_tbl created by gt::gt().
column: A numeric, Date, POSIXt, or difftime column to color and legendize.
palette: A vector of colors, palette endpoints, a single named palette, or a palette function used for the quantile groups.
quantiles: The number of quantile groups.
oob: Out-of-bounds handling function or shortcut. Use a function like scales::oob_squish() or a shortcut such as "censor" or "squish".
right: Whether intervals should be closed on the right. The default of FALSE yields intervals like [a, b).
labels: An optional labeling function or a character vector for the quantile ranges. When a function is supplied, it is applied to the quantile boundaries before interval labels are constructed.
title: Optional legend title.
width: Width of the legend.
height: Height of the swatches.
apply_to: Whether colors should be applied to cell fill or text.
na_color: Color used for missing values.
alpha: Alpha applied by gt::data_color().
reverse: Whether to reverse the color mapping.
autocolor_text: Whether to automatically adjust text color.
contrast_algo: Contrast algorithm passed to gt::data_color().
autocolor_light: Light text color used by gt::data_color().
autocolor_dark: Dark text color used by gt::data_color().

Value

A modified gt::gt table.

Examples

library(gt)

exibble |>
  gt() |>
  gtscale_data_color_quantiles(
    column = num,
    palette = c('#fdd49e', '#fdbb84', '#ef6548', '#990000'),
    quantiles = 4,
    title = 'Quantile bins'
  )


  num
      char
      fctr
      date
      time
      datetime
      currency
      row
      group
    
1.111e-01
apricot
one
2015-01-15
13:35
2018-01-01 02:22
49.950
row_1
grp_a
2.222e+00
banana
two
2015-02-15
14:40
2018-02-02 14:33
17.950
row_2
grp_a
3.333e+01
coconut
three
2015-03-15
15:45
2018-03-03 03:44
1.390
row_3
grp_a
4.444e+02
durian
four
2015-04-15
16:50
2018-04-04 15:55
65100.000
row_4
grp_a
5.550e+03
NA
five
2015-05-15
17:55
2018-05-05 04:00
1325.810
row_5
grp_b
NA
fig
six
2015-06-15
NA
2018-06-06 16:11
13.255
row_6
grp_b
7.770e+05
grapefruit
seven
NA
19:10
2018-07-07 05:22
NA
row_7
grp_b
8.880e+06
honeydew
eight
2015-08-15
20:20
NA
0.440
row_8
grp_b
Quantile bins
0 - 1818 - 444444 - 391,275391,275 - 8,880,000

num	char	fctr	date	time	datetime	currency	row	group
1.111e-01	apricot	one	2015-01-15	13:35	2018-01-01 02:22	49.950	row_1	grp_a
2.222e+00	banana	two	2015-02-15	14:40	2018-02-02 14:33	17.950	row_2	grp_a
3.333e+01	coconut	three	2015-03-15	15:45	2018-03-03 03:44	1.390	row_3	grp_a
4.444e+02	durian	four	2015-04-15	16:50	2018-04-04 15:55	65100.000	row_4	grp_a
5.550e+03	NA	five	2015-05-15	17:55	2018-05-05 04:00	1325.810	row_5	grp_b
NA	fig	six	2015-06-15	NA	2018-06-06 16:11	13.255	row_6	grp_b
7.770e+05	grapefruit	seven	NA	19:10	2018-07-07 05:22	NA	row_7	grp_b
8.880e+06	honeydew	eight	2015-08-15	20:20	NA	0.440	row_8	grp_b
Quantile bins 0 - 1818 - 444444 - 391,275391,275 - 8,880,000