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", diverging "div"", cyclic "cyc", and bivariate (seq x seq "bivs", seq x cat "bivc", seq x div "bivd", seq x desaturated "bivg") 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).
Usage
c4a_palettes(
type = c("all", "cat", "seq", "div", "cyc", "bivs", "bivc", "bivd", "bivg"),
series = NULL,
full.names = TRUE
)
c4a_series(type = c("all", "cat", "seq", "div", "cyc"), as.data.frame = TRUE)
c4a_types(series = NULL, as.data.frame = TRUE)
c4a_overview(return.matrix = FALSE, zero.count.as.NA = FALSE)
.PArguments
- type
type of color palette: one of
"all"(all palettes),"cat","seq","div","cyc","bivs","bivc","bivd", or"bivg". Seec4a_typesfor descriptions.- 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?- return.matrix
should only a matrix be returned with numbers per palette and type? If
FALSEa data.frame is returned with addional information- zero.count.as.NA
should zeros counted in the table be returned as 0 (
FALSE, default) or asNA(TRUE)?
See also
References of the palettes: cols4all-package.
Examples
c4a_series()
#> series description
#> 1 bivario Palettes from the Python library bivario
#> 2 brewer ColorBrewer palettes
#> 3 carto Palettes designed by CARTO
#> 4 cols4all cols4all palettes (in development)
#> 5 gmt Palettes from General Mapping Tools
#> 6 hcl Palettes from the Hue Chroma Luminance color space
#> 7 kovesi Palettes designed by Peter Kovesi
#> 8 matplotlib Palettes from the Python library matplotlib
#> 9 met Palettes inspired by The Metropolitan Museum of Art
#> 10 meteo Palettes by Oliver Fuhrer from MeteoSwiss
#> 11 misc Miscellaneous palettes
#> 12 ocean Colormaps for Oceanography by Thyng et al.
#> 13 parks Palettes inspired by National Parks
#> 14 pinkfloyd Palettes extracted from Pink Floyd album covers
#> 15 poly Qualitative palettes with many colors
#> 16 powerbi Palettes from Microsoft Power BI
#> 17 scico Scientific colour maps by Fabio Crameri
#> 18 seaborn Palettes from the Python library Seaborn
#> 19 stevens Bivariate palettes by Joshua Stevens
#> 20 tableau Palettes designed by Tableau
#> 21 tol Palettes designed by Paul Tol
#> 22 wes Palettes from Wes Anderson movies
c4a_types()
#> type description
#> 1 cat categorical
#> 2 seq sequential
#> 3 div diverging
#> 4 cyc cyclic
#> 5 bivs bivariate (sequential x sequential)
#> 6 bivc bivariate (sequential x categorical)
#> 7 bivd bivariate (sequential x diverging)
#> 8 bivg bivariate (sequential x desaturated)
c4a_overview()
#> series description cat seq div
#> 1 bivario Palettes from the Python library bivario 0 0 0
#> 2 brewer ColorBrewer palettes 9 18 9
#> 3 carto Palettes designed by CARTO 6 21 7
#> 4 cols4all cols4all palettes (in development) 14 0 2
#> 5 gmt Palettes from General Mapping Tools 0 19 4
#> 6 hcl Palettes from the Hue Chroma Luminance color space 9 23 11
#> 7 kovesi Palettes designed by Peter Kovesi 0 28 14
#> 8 matplotlib Palettes from the Python library matplotlib 0 51 12
#> 9 met Palettes inspired by The Metropolitan Museum of Art 33 8 14
#> 10 meteo Palettes by Oliver Fuhrer from MeteoSwiss 2 14 7
#> 11 misc Miscellaneous palettes 5 0 0
#> 12 ocean Colormaps for Oceanography by Thyng et al. 0 15 3
#> 13 parks Palettes inspired by National Parks 22 5 3
#> 14 pinkfloyd Palettes extracted from Pink Floyd album covers 16 0 0
#> 15 poly Qualitative palettes with many colors 9 0 0
#> 16 powerbi Palettes from Microsoft Power BI 19 1 4
#> 17 scico Scientific colour maps by Fabio Crameri 21 21 10
#> 18 seaborn Palettes from the Python library Seaborn 6 4 2
#> 19 stevens Bivariate palettes by Joshua Stevens 0 5 0
#> 20 tableau Palettes designed by Tableau 29 23 28
#> 21 tol Palettes designed by Paul Tol 8 8 4
#> 22 wes Palettes from Wes Anderson movies 23 0 1
#> cyc bivs bivc bivd bivg
#> 1 0 25 0 0 0
#> 2 0 2 2 1 0
#> 3 0 0 0 0 0
#> 4 0 2 0 2 5
#> 5 0 0 0 0 0
#> 6 6 0 0 0 0
#> 7 8 0 0 0 0
#> 8 3 0 0 0 0
#> 9 0 0 1 0 0
#> 10 0 0 0 0 0
#> 11 0 0 3 0 0
#> 12 0 0 0 0 0
#> 13 0 0 0 0 0
#> 14 0 0 0 0 0
#> 15 0 0 0 0 0
#> 16 0 0 0 0 0
#> 17 5 0 2 0 1
#> 18 0 0 0 0 0
#> 19 0 5 0 0 0
#> 20 0 0 3 0 0
#> 21 0 0 0 0 0
#> 22 0 0 0 0 0
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.cy_or" "kovesi.isoluminant_cgo_80_c38"
#> [3] "kovesi.isoluminant_cm_70_c39" "kovesi.bu_gn_yl_wh"
#> [5] "kovesi.bu_gn_yl" "kovesi.linear_bgyw_15_100_c68"
#> [7] "kovesi.blue_cyan" "kovesi.blue"
#> [9] "kovesi.bu_wh_mg" "kovesi.linear_bmw_5_95_c89"
#> [11] "kovesi.bu_yl_mg" "kovesi.linear_bmy_10_95_c78"
#> [13] "kovesi.linear_gow_60_85_c27" "kovesi.linear_gow_65_90_c35"
#> [15] "kovesi.green" "kovesi.linear_grey_0_100_c0"
#> [17] "kovesi.grey" "kovesi.bk_rd_yl"
#> [19] "kovesi.linear_kry_5_98_c75" "kovesi.bk_rd_wh"
#> [21] "kovesi.linear_kryw_5_100_c67" "kovesi.ternary_blue"
#> [23] "kovesi.ternary_green" "kovesi.ternary_red"
#> [25] "kovesi.rainbow_bu_gn_yl_rd" "kovesi.rainbow_bgyr_35_85_c73"
#> [27] "kovesi.rainbow_bu_gn_yl_rd_mg" "kovesi.rainbow_bgyrm_35_85_c71"
# handy when auto-completion is available:
.P$kovesi$seq$linear_terrain
#> NULL