In christyray/crthemes: A Standardized ggplot2 Theme for Visualizations

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.width = 6,
  fig.asp = 2/3,
  out.width = "75%",
  dev = "ragg_png"
)

library(ggplot2)
library(crthemes)

Updated r format(Sys.time(), "%b %d, %Y") \ \ crthemes includes several qualitative, discrete palettes, but does not include any ordered discrete palettes or continuous palettes. The paletteer package collects a large variety of discrete and continuous color palettes and provides wrapper functions to access them.

show_col() from the scales package can be used to preview colors from other packages (and is the basis for the pal_preview() function in this package).

Using `paletteer`

paletteer_c() and paletteer_d() access continuous and discrete palettes in the paletteer package, respectively. The arguments are:

palette: the specific palette to be used, must be provided as a string in the form "packagename::palettename"
n: the number of colors to return; required for continuous palettes, optional for discrete palettes
direction: 1 (default) for the standard direction, -1 for reversed

palettes_c_names and palettes_d_names print the packages and palettes for the included continuous and discrete palettes, respectively. The included palettes are also listed in this repository.

To use more colors than are included in a palette, use the colour_ramp() function from the scales package to interpolate the colors. colour_ramp() returns a function that will take input of a numeric sequence and return a character vector containing the palette colors.

library(scales)
library(paletteer)

pal <- paletteer_d("rcartocolor::DarkMint")
show_col(pal)
# To interpolate between colors in a palette, use colour_ramp()
ramp <- colour_ramp(pal)
# ramp is a function that takes a numeric vector and returns a palette
pal25 <- ramp(seq(0, 1, length.out = 25))
show_col(pal25)
# Paletteer also has continuous palettes
pal <- paletteer_c("pals::ocean.deep", n = 25)
show_col(pal)

Scale Functions

paletteer includes scale_*_paletteer_c() and scale_*_paletteer_d() functions to apply the included palettes to ggplots. Like with the other paletteer functions, the palette needs to be provided as a string in the form packagename::palettename

Continuous

set.seed(503)
x <- rnorm(200)
df <- data.frame(x = x, y = x + rnorm(200, sd = 1.5), 
                 z = x + rnorm(200, mean = 5, sd = 0.5))
p <- ggplot(df, aes(x, y, color = z)) +
  geom_point(alpha = 0.6) +
  labs(x = "X Axis", y = "Y Axis", color = NULL, title = "Continuous") +
  theme_cr()

# Continuous palette
p + scale_color_paletteer_c("pals::ocean.matter", direction = -1)

Discrete

library(dplyr)

df <- df %>% mutate(bin = ntile(.data$z, 7))
p_d <- ggplot(df, aes(x, y, color = as.factor(bin))) +
  geom_point(alpha = 0.6) +
  labs(x = "X Axis", y = "Y Axis", color = NULL, title = "Discrete") +
  theme_cr()

# Discrete palette
p_d + scale_color_paletteer_d("rcartocolor::Sunset")

Interpolating

If the number of colors needed is not the same as the number of colors in the palette, the colour_ramp() function can be used to interpolate the palette.

df <- df %>% mutate(bin = ntile(.data$z, 5))

# Interpolate palette to 5 colors
ramp <- colour_ramp(paletteer_d("rcartocolor::Sunset"))
pal <- ramp(seq(0, 1, length.out = 5))

p_i <- ggplot(df, aes(x, y, color = as.factor(bin))) +
  geom_point(alpha = 0.6) +
  labs(x = "X Axis", y = "Y Axis", color = NULL, title = "Interpolated") +
  theme_cr()

# Interpolated palette; use scale_color_manual because the colors are in a variable
p_i + scale_color_manual(values = pal)

Palette Options

Below are some options for sequential and diverging color palettes from the paletteer, RColorBrewer, and viridis packages.

The RColorBrewer package is included in ggplot2 by default through:

scale_color_brewer() (discrete)
scale_color_distiller() (continuous)
scale_color_fermenter() (binned)

The viridis package is included in ggplot2 by default through:

scale_color_viridis_d() (discrete)
scale_color_viridis_c() (continuous)
scale_color_viridis_b() (binned)

For more colors, see the full list of available palettes.

Sequential

# Discrete, "BurgYl" from "rcartocolor
pal <- paletteer_d("rcartocolor::BurgYl")
show_col(pal, labels = FALSE)
# Discrete, "DarkMint" from "rcartocolor
pal <- paletteer_d("rcartocolor::DarkMint")
show_col(pal, labels = FALSE)
# Discrete, "RdPu" from "RColorBrewer
pal <- paletteer_d("RColorBrewer::RdPu")
show_col(pal, labels = FALSE)
# Discrete, "PuBuGn" from "RColorBrewer
pal <- paletteer_d("RColorBrewer::PuBuGn")
show_col(pal, labels = FALSE)
# Continuous, "magma" from "viridis"
pal <- paletteer_c("viridis::magma",16)
show_col(pal, labels = FALSE)
# Continuous, "viridis" from "viridis"
pal <- paletteer_c("viridis::viridis",16)
show_col(pal, labels = FALSE)
# Continuous, "ocean.matter" from "pals"
pal <- paletteer_c("pals::ocean.matter",16)
show_col(pal, labels = FALSE)
# Continuous, "ocean.tempo" from "pals"
pal <- paletteer_c("pals::ocean.tempo",16)
show_col(pal, labels = FALSE)

Diverging

# Discrete, "TealRose" from "rcartocolor
pal <- paletteer_d("rcartocolor::TealRose")
show_col(pal, labels = FALSE)
# Discrete, "Fall" from "rcartocolor
pal <- paletteer_d("rcartocolor::Fall")
show_col(pal, labels = FALSE)
# Discrete, "RdBu" from "RColorBrewer
pal <- paletteer_d("RColorBrewer::RdBu")
show_col(pal, labels = FALSE)
# Discrete, "BrBG" from "RColorBrewer
pal <- paletteer_d("RColorBrewer::BrBG")
show_col(pal, labels = FALSE)
# Continuous, "vik" from "scico"
pal <- paletteer_c("scico::vik",16)
show_col(pal, labels = FALSE)
# Continuous, "broc" from "scico"
pal <- paletteer_c("scico::broc",16)
show_col(pal, labels = FALSE)
# Continuous, "ocean.balance" from "pals"
pal <- paletteer_c("pals::ocean.balance",16)
show_col(pal, labels = FALSE)
# Continuous, "ocean.curl" from "pals"
pal <- paletteer_c("pals::ocean.curl",16)
show_col(pal, labels = FALSE)