okcolors is a collection of aesthetically appealing color palettes inspired by OK Go music videos for data visualization with 'ggplot2'. All palettes support both discrete and continuous data.
install.packages("okcolors")
library(okcolors)
# dev version:
install.packages('remotes') # if not already installed
# wait for the installation to complete
remotes::install_github('nelsonquesado/okcolors@main')
library(okcolors)The okcolors package provides three simple functions:
okcolors()– returns annumber of color hex codes from a namedpalette.scale_color_okcolors()– adds a custom color scale to aggplot2plot.scale_fill_okcolors()– adds a custom fill scale to aggplot2plot.valid_palettes()- lists available palettes in the okcolors Package.
library(ggplot2)
library(okcolors)
ggplot(mpg, aes(displ, hwy, color = class)) +
geom_point(size = 3) +
scale_color_okcolors() # Just add it like any ggplot scale
library(ggplot2)
library(okcolors)
ggplot(mpg, aes(class, fill = class)) +
geom_bar() +
scale_fill_okcolors("skyscrapers") # Again, just add it like any ggplot scale
There are 5 different collor palettes, which are descibed in the next section.
valid_palettes()
[1] "it" "stone" "skyscrapers" "obsession" "moment"
Although the palettes are made of 5 basic colors, the package interpolates any number of colors to match the palette.
okcolors('obsession', 12)
[1] "#45924C" "#83A744" "#C1BC3C" "#EFC344" "#ECA07C" "#EA7DB5"
[7] "#EB66B9" "#EF5C87" "#F35155" "#C4536D" "#845A9E" "#4561CF"
library(tidyverse); library(okcolors); library(aopdata); library(sf)
read_landuse('fortaleza', geometry = T) %>%
group_by(id_hex, geometry) %>%
reframe(`Low-income individuals` = P001 * (R003 <= 4) %>% if_else(is.na(.), 0, .),
`Low-complexity job psitions` = T002) %>%
pivot_longer(cols = 3:4) %>%
mutate(value = value/sum(value)) %>%
st_as_sf() %>%
ggplot() +
geom_sf(aes(fill = value), color = NA) +
facet_grid(.~name) +
scale_fill_okcolors('it',
discrete = F,
transform = 'log',
na.value = okcolors('it', n = 1, direction = 1),
breaks = c(.000001, .0001, .005),
labels = c('0.0001%', '0.01%', '0.5%'),
name = 'Proportion\n',
direction = 1) +
theme_linedraw() +
labs(title = 'Spatial misatch between low-complexity job positions\nand low-income individuals in Fortaleza, Brazil.') +
theme(legend.position = 'bottom')
Source: Pereira, Rafael H. M. et al. (2022) Distribuição espacial de características sociodemográficas e localização de empregos e serviços públicos das vinte maiores cidades do Brasil. Texto para Discussão 2772. Ipea - Instituto de Pesquisa Econômica Aplicada. http://dx.doi.org/10.38116/td2772
library(tidyverse); library(okcolors)
library(GTFSwizard); library(hrbrthemes)
for_bus_gtfs %>%
get_fleet('by.hour') %>%
ggplot +
geom_line(aes(x = hour, y = fleet, color = service_pattern, group = service_pattern), linewidth = 2) +
scale_color_okcolors('stone',
discrete = T,
direction = -1,
name = 'Service Pattern',
labels = c('Business days', 'Sundays', 'Saturdays')) +
theme_linedraw() +
scale_y_comma(big.mark = '.') +
labs(title = 'Bus fleet variation during the day in Fortaleza, Brazil.',
x = 'Time of the day', y = 'Fleet (veh)') +
theme(legend.position = 'bottom')
Source: Quesado Filho, N. de O., Guimarães, C. G. C. (2024). GTFSwizard: Exploring and Manipulating 'GTFS' Files. R package version 1.1.0, https://github.com/OPATP/GTFSwizard.
library(tidyverse); library(okcolors); library(aopdata); library(hrbrthemes)
read_population('all') %>%
mutate(`Proportion of white individuals` = (P002/P001) %>% round(1)) %>%
group_by(`Proportion of white individuals`, name_muni) %>%
reframe(`Average per capita household income` = mean(R001, na.rm = T)) %>%
ggplot +
geom_line(aes(`Proportion of white individuals`,
`Average per capita household income`,
color = `Average per capita household income`)) +
geom_point(aes(`Proportion of white individuals`,
`Average per capita household income`,
color = `Average per capita household income`),
size = 4) +
facet_wrap(name_muni~.) +
scale_color_okcolors('skyscrapers', guide = 'none', discrete = F) +
scale_x_percent(breaks = c(0, 0.2, .4, .6, .8)) +
scale_y_comma(big.mark = '.', prefix = 'R$ ', breaks = c(1000, 3000, 5000)) +
labs(title = 'Average income for different racial contexts') +
theme_linedraw()
Source: Pereira, Rafael H. M. et al. (2022) Distribuição espacial de características sociodemográficas e localização de empregos e serviços públicos das vinte maiores cidades do Brasil. Texto para Discussão 2772. Ipea - Instituto de Pesquisa Econômica Aplicada. http://dx.doi.org/10.38116/td2772
library(tidyverse); library(okcolors)
mpg %>%
ggplot() +
geom_boxplot(aes(x = class, y = hwy, fill = class)) +
labs(title = "Highway MPG by Car Class",
x = "Car Class",
y = "Highway MPG") +
theme_linedraw() +
theme(legend.position = "none") +
scale_fill_okcolors()
Wickham H, Averick M, Bryan J, Chang W, McGowan LD, François R, Grolemund G, Hayes A, Henry L, Hester J, Kuhn M, Pedersen TL, Miller E, Bache SM, Müller K, Ooms J, Robinson D, Seidel DP, Spinu V, Takahashi K, Vaughan D, Wilke C, Woo K, Yutani H (2019). “Welcome to the tidyverse.” Journal of Open Source Software, 4(43), 1686. doi:10.21105/joss.01686 https://doi.org/10.21105/joss.01686.
library(okcolors); library(tidyverse)
diamonds %>%
ggplot(aes(x = cut, fill = clarity)) +
geom_bar(position = "fill") +
labs(title = "Proportion of Clarity Within Diamond Cuts",
x = "Cut",
y = "Proportion",
fill = "Clarity") +
theme_linedraw() +
scale_fill_okcolors('moment', direction = -1)
H. Wickham. ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York, 2016.
Contributions are welcome! To report a bug, suggest a feature, or contribute code, please use the repository’s Issues.
okcolors mainly relies on ggplot2.
To cite package ‘okcolors’ in publications use:
- Quesado Filho, N. O. de, & Silveira, A. F. T. (2025). okcolors: A Set of Color Palettes Inspired by OK Go Music Videos for 'ggplot2' in R. R package version 0.1.0. DOI: 10.32614/CRAN.package.okcolors.
A BibTeX entry for LaTeX users is
@Manual{quesado.silveira.2025,
title = {okcolors: A Set of Color Palettes Inspired by OK Go Music Videos for ggplot2 in R.},
author = {Nelson de O. {Quesado Filho} and Ana Flávia T. {Silveira},
year = {2025},
note = {R package version 0.1.0},
url = {https://cran.r-project.org/package=okcolors},
doi = {10.32614/CRAN.package.okcolors}}okcolors is developed by Nelson Quesado and Ana Flávia Teles.