c4a_palettes lists all available cols4all color palettes. Palettes are organized by series. The available series are listed with c4a_series. Palettes are also organized per functional type, where we currently support: categorical "cat", sequential "seq", and diverging "div"" palette types. The function c4a_types lists all available types. The function c4a_overview gives an overview table of the number of palette per series and type. In an IDE with auto-completion (such as RStudio) it is possible to browse through the palette names with .P (using $ like in lists).
Arguments
- type
type of color palette: one of
"all"(all palettes),"cat"(categorical/qualitative palettes),"seq"(sequential palettes) and"div"(diverging palettes).- series
series to list the palettes from. Run
c4a_seriesto see the options.- full.names
should full names, i.e. with the prefix "series."? By default
TRUE.- as.data.frame
should
c4a_seriesandc4a_typesreturn the result as a data.frame, with description included as a column?
See also
References of the palettes: cols4all-package.
Examples
c4a_series()
#> series description
#> 1 brewer ColorBrewer palettes
#> 2 c4a cols4all palettes (in development)
#> 3 carto Palettes designed by CARTO
#> 4 hcl Palettes from the Hue Chroma Luminance color space
#> 5 kovesi Palettes designed by Peter Kovesi
#> 6 met Palettes inspired by The Metropolitan Museum of Art
#> 7 misc Miscellaneous palettes
#> 8 miscs <NA>
#> 9 parks Palettes inspired by National Parks
#> 10 pinkfloyd Palettes extracted from Pink Floyd album covers
#> 11 poly Qualitative palettes with many colors
#> 12 scico Scientific colour map palettes by Fabio Crameri
#> 13 seaborn Palettes from the Python library Seaborn
#> 14 stevens Bivariate palettes by Joshua Stevens
#> 15 tableau Palettes designed by Tableau
#> 16 tol Palettes designed by Paul Tol
#> 17 viridis Palettes fom the Python library matplotlib
#> 18 wes Palettes from Wes Anderson movies
c4a_types()
#> type description
#> 1 cat categorical
#> 2 seq sequential
#> 3 div diverging
#> 4 bivs bivariate (sequential x sequential)
#> 5 bivc bivariate (sequential x categorical)
#> 6 bivd bivariate (sequential x diverging)
#> 7 bivg bivariate (sequential x desaturated)
c4a_overview()
#> cat seq div bivs bivc bivd bivg
#> brewer 9 18 9 2 1 1 NA
#> c4a NA NA 2 2 NA 2 5
#> carto 6 21 7 NA NA NA NA
#> hcl 9 23 11 NA NA NA NA
#> kovesi NA 17 13 NA NA NA NA
#> met 33 8 14 NA 1 NA NA
#> misc 1 NA NA NA 3 NA NA
#> miscs 4 NA NA NA NA NA NA
#> parks 22 5 3 NA NA NA NA
#> pinkfloyd 16 NA NA NA NA NA NA
#> poly 9 NA NA NA NA NA NA
#> scico 21 21 10 NA 2 NA 1
#> seaborn 6 4 2 NA NA NA NA
#> stevens NA NA NA 5 NA NA NA
#> tableau 29 23 28 NA NA NA NA
#> tol 8 8 4 NA NA NA NA
#> viridis NA 7 1 NA NA NA NA
#> wes 23 NA 1 NA NA NA NA
c4a_palettes(type = "cat", series = "tol")
#> [1] "tol.bright" "tol.contrast" "tol.vibrant" "tol.muted" "tol.medium"
#> [6] "tol.light" "tol.dark" "tol.rainbow"
c4a_palettes(type = "seq", series = "kovesi")
#> [1] "kovesi.linear_grey" "kovesi.rainbow_bu_rd"
#> [3] "kovesi.rainbow_bu_pk" "kovesi.linear_ternary_blue"
#> [5] "kovesi.linear_ternary_green" "kovesi.linear_ternary_red"
#> [7] "kovesi.linear_yl_rd_bk" "kovesi.linear_wh_rd_bk"
#> [9] "kovesi.linear_green" "kovesi.linear_yl_mg_bu"
#> [11] "kovesi.linear_wh_mg_bu" "kovesi.linear_blue"
#> [13] "kovesi.linear_tq_bu" "kovesi.linear_wh_yl_gn_bu"
#> [15] "kovesi.linear_yl_gn_bu" "kovesi.isoluminant_tq_or"
#> [17] "kovesi.linear_terrain"
# handy when auto-completion is available:
.P$kovesi$seq$linear_terrain
#> [1] "kovesi.linear_terrain"