第98期 R语言教程科研绘图配色常用R包

第98期 R语言教程科研绘图配色常用R包

在r语言，ggplot2绘图过程中最重要的一部分就是配色的选择。优秀的配色要充分考虑到颜色的区分度，期刊要求，冷暖特点等

本期介绍如何调整r语言中的配色，使整个图片美观优雅

基础工作

加载数据

为了方便效果展示我们先载入数据库进行基础绘图

library(bruceR)

data(iris)
head(iris, 10)

01 数据

基础可视化

# ggplot2建立柱状图可视化

ggplot(iris, aes(x = Species, y = Sepal.Length, fill = Species)) +
  geom_bar(stat = "identity") +
  labs(title = "Sepal Length by Species", x = "Species", y = "Sepal Length") +
  theme_minimal()

ggplot2手动调整配色

使用函数 scale_*__manualma,一般适用于网上已知的优秀配色,使用吸管工具吸取配色方案并使用

例如指定新的深色调使用r

ggplot(iris, aes(x = Species, y = Sepal.Length, fill = Species)) +
  geom_bar(stat = "identity") +
  labs(title = "Sepal Length by Species", x = "Species", y = "Sepal Length") +
  theme_minimal()+
  scale_fill_manual(values = c("black", "grey", "brown"))

Rcolorbrew调整配色

Rcolorbrew介绍

CRAN库:CRAN: Package RColorBrewer (r-project.org)

调用网站https://colorbrewer2.org/上的配色方案,使用人数众多,整体比较中规中矩

R包调用

先display配色,查看目标色数和色型
选择合适的调色盘,在ggplot中使用 scale_*_brewer调用

# 使用RColorBrewer包设置颜色
library(RColorBrewer)

# 查看配色盘，选择3颜色，区分色
display.brewer.all(3, type = 'div')

调用SpectralRdG方案

ggplot(iris, aes(x = Species, y = Sepal.Length, fill = Species)) +
  geom_bar(stat = "identity") +
  labs(title = "Sepal Length by Species", x = "Species", y = "Sepal Length") +
  theme_minimal()+
  scale_fill_brewer(palette = "Spectral")

ggsci调整配色

R包介绍

ggsci包含期刊或软件的经典配色,投稿时调用快,效果好,顺手就用上了我用该包配色最多

CRAN库:CRAN: Package ggsci (r-project.org)

教程:Scientific Journal and Sci-Fi Themed Color Palettes for ggplot2 (r-project.org)

配色方案

Name	Scales	Palette Types	Palette Generator
NPG	`scale_color_npg()` `scale_fill_npg()`	`"nrc"`	`pal_npg()`
AAAS	`scale_color_aaas()` `scale_fill_aaas()`	`"default"`	`pal_aaas()`
NEJM	`scale_color_nejm()` `scale_fill_nejm()`	`"default"`	`pal_nejm()`
Lancet	`scale_color_lancet()` `scale_fill_lancet()`	`"lanonc"`	`pal_lancet()`
JAMA	`scale_color_jama()` `scale_fill_jama()`	`"default"`	`pal_jama()`
BMJ	`scale_color_bmj()` `scale_fill_bmj()`	`"default"`	`pal_bmj()`
JCO	`scale_color_jco()` `scale_fill_jco()`	`"default"`	`pal_jco()`
UCSCGB	`scale_color_ucscgb()` `scale_fill_ucscgb()`	`"default"`	`pal_ucscgb()`
D3	scale_color_d3()``scale_fill_d3()	`"category10"` `"category20"` `"category20b"` `"category20c"`	`pal_d3()`
Observable	`scale_color_observable()` `scale_fill_observable()`	`"observable10"`	`pal_observable()`
LocusZoom	`scale_color_locuszoom()` `scale_fill_locuszoom()`	`"default"`	`pal_locuszoom()`
IGV	`scale_color_igv()` `scale_fill_igv()`	"default"``"alternating"	`pal_igv()`
COSMIC	`scale_color_cosmic()` `scale_fill_cosmic()`	"hallmarks_light"``"hallmarks_dark"``"signature_substitutions"	`pal_cosmic()`
UChicago	`scale_color_uchicago()` `scale_fill_uchicago()`	"default"``"light"``"dark"	`pal_uchicago()`
Star Trek	`scale_color_startrek()` `scale_fill_startrek()`	`"uniform"`	`pal_startrek()`
Tron Legacy	`scale_color_tron()` `scale_fill_tron()`	`"legacy"`	`pal_tron()`
Futurama	`scale_color_futurama()` `scale_fill_futurama()`	`"planetexpress"`	`pal_futurama()`
Rick and Morty	`scale_color_rickandmorty()` `scale_fill_rickandmorty()`	`"schwifty"`	`pal_rickandmorty()`
The Simpsons	`scale_color_simpsons()` `scale_fill_simpsons()`	`"springfield"`	`pal_simpsons()`
Flat UI	`scale_color_flatui()` `scale_fill_flatui()`	`"default"` `"flattastic"` `"aussie"`	`pal_flatui()`
Frontiers	`scale_color_frontiers()` `scale_fill_frontiers()`	`"default"`	`pal_frontiers()`
GSEA	`scale_color_gsea()` `scale_fill_gsea()`	`"default"`	`pal_gsea()`
Bootstrap 5	`scale_color_bs5()` `scale_fill_bs5()`	`"blue"` "indigo"``"purple" "pink"``"red" "orange"``"yellow" "green"``"teal" "cyan"``"gray"	`pal_bs5()`
Material Design	`scale_color_material()` `scale_fill_material()`	`"red"` "pink"``"purple" "deep-purple"``"indigo" "blue"``"light-blue" "cyan"``"teal" "green"``"light-green" "lime"``"yellow" "amber"``"orange" "deep-orange"``"brown" "grey"``"blue-grey"	`pal_material()`
Tailwind CSS	`scale_color_tw3()` `scale_fill_tw3()`	`"slate"` "gray"``"zinc" "neutral"``"stone" "red"``"orange" "amber"``"yellow" "lime"``"green" "emerald"``"teal" "cyan"``"sky" "blue"``"indigo" "violet"``"purple" "fuchsia"``"pink" `"rose"`	`pal_tw3()`

R包调用

使用柳叶刀配色,其它配色方案自行选择,如实际需要的颜色数n少于调色盘,则会按前n个切片使用

# 使用RColorBrewer包设置颜色
library(ggsci)

# 柳叶刀配色
ggplot(iris, aes(x = Species, y = Sepal.Length, fill = Species)) +
  geom_bar(stat = "identity") +
  labs(title = "Sepal Length by Species", x = "Species", y = "Sepal Length") +
  theme_minimal()+
  scale_fill_lancet()

其它配色

viridis: Colorblind-Friendly Color Maps for R

介绍

官方仓库:CRAN: Package viridis (r-project.org)

教程:Introduction to the viridis color maps (r-project.org)

多用于连续渐变色

使用效果

色盘

使用方案参考

MetBrewer: 博物馆配色

r包介绍

官方CRAN库:CRAN: Package MetBrewer (r-project.org)

配色方案参考纽约大都会艺术博物馆,艺术感爆表一起来看看

使用方案

library(MetBrewer)

ggplot(iris, aes(x = Species, y = Sepal.Length, fill = Species)) +
  geom_bar(stat = "identity") +
  labs(title = "Sepal Length by Species", x = "Species", y = "Sepal Length") +
  theme_minimal()+
  scale_fill_manual(values = met.brewer("Austria"))

ggplot(iris, aes(x = Species, y = Sepal.Length, fill = Species)) +
  geom_bar(stat = "identity") +
  labs(title = "Sepal Length by Species", x = "Species", y = "Sepal Length") +
  theme_minimal()+
  scale_fill_manual(values = met.brewer("Degas"))