ggokabeito provides ggplot2 and ggraph scales to easily use the discrete, colorblind-friendly ‘Okabe-Ito’ palette in your data visualizations. Currently, ggokabeito provides the following scales:
scale_color_okabe_ito()/scale_colour_okabe_ito()scale_fill_okabe_ito()scale_edge_color_okabe_ito()/scale_edge_colour_okabe_ito()You can install ggokabeito from CRAN with:
install.packages("ggokabeito")You can alternatively install the development version of ggokabeito from GitHub with:
# install.packages("devtools")
devtools::install_github("malcolmbarrett/ggokabeito")library(ggokabeito)
library(ggplot2)
ggplot(mpg, aes(cty, hwy, color = class)) +
geom_point() +
scale_color_okabe_ito()
ggplot(mpg, aes(cty, hwy, color = factor(cyl))) +
geom_point(alpha = 0.7) +
scale_color_okabe_ito(name = "Cylinders", alpha = .9)
ggplot(mpg, aes(hwy, color = class, fill = class)) +
geom_density() +
scale_fill_okabe_ito(name = "Class", alpha = .9) +
scale_color_okabe_ito(name = "Class")
ggokabeito also works with ggraph
# example from https://www.data-imaginist.com/2017/ggraph-introduction-edges/
library(ggraph, warn.conflicts = FALSE)
library(igraph, warn.conflicts = FALSE)
graph <- graph_from_data_frame(highschool)
pop1957 <- degree(
delete_edges(graph, which(E(graph)$year == 1957)),
mode = "in"
)
pop1958 <- degree(
delete_edges(graph, which(E(graph)$year == 1958)),
mode = "in"
)
V(graph)$pop_devel <- ifelse(
pop1957 < pop1958,
"increased",
ifelse(pop1957 > pop1958, "decreased",
"unchanged"
)
)
V(graph)$popularity <- pmax(pop1957, pop1958)
E(graph)$year <- as.character(E(graph)$year)
ggraph(graph, layout = "kk") +
geom_edge_link(aes(colour = as.character(year))) +
scale_edge_color_okabe_ito()
ggokabeito is heavily inspired by the excellent colorblindr package. However, colorblindr is not currently on CRAN and includes some complex features for analyzing colorblind safeness that are not necessary for using the Okabe-Ito palette. Additionally, colorblindr was developed prior to R 4.0.0, which set Okabe-Ito as the default discrete color palette. ggokabeito thus has fewer overall dependencies but a strong one on R 4.0.0 or greater.
Please note that the ggokabeito project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.