火狐截图_2020-02-11T08-36-22.554Z.png
ggplot2 colors : How to change colors automatically and manually?
ggplot2 ：如何自动和手动更改颜色？
本教程的目的是描述如何更改使用R和ggplot2包生成的图的颜色。
（一）：数据准备
rm(list = ls())
#convert dose and cyl columns from a numeric to a factor variables
ToothGrowth$dose <- as.factor(ToothGrowth$dose)
mtcars$cyl <- as.factor(mtcars$cyl)
head(ToothGrowth)
head(mtcars)
（二）：单色绘图
library(ggplot2)
library(ggpubr)
# Box plot
a <- ggplot(ToothGrowth, aes(x=dose, y=len)) +geom_boxplot()
# scatter plot
b <- ggplot(mtcars, aes(x=wt, y=mpg)) + geom_point()
# box plot
c <- ggplot(ToothGrowth, aes(x=dose, y=len)) +
geom_boxplot(fill='#A4A4A4', color="darkred")
# scatter plot
d <- ggplot(mtcars, aes(x=wt, y=mpg)) +
geom_point(color='darkblue')
ggarrange(a,b,c, d,
labels = c("A","B","C","D"),
nrow = 2, ncol = 2)
Rplot01.png
（三）：按组更改颜色
3.1. 默认配色
#Change colors by groups
# Box plot
bp <- ggplot(ToothGrowth, aes(x=dose, y=len, fill=dose)) +
geom_boxplot()
# Scatter plot
sp <- ggplot(mtcars, aes(x=wt, y=mpg, color=cyl)) + geom_point()
# Box plot
bp1 <- bp + scale_fill_hue(l=40, c=35)
# Scatter plot
sp1 <- sp + scale_color_hue(l=40, c=35)
ggarrange(bp, sp,bp1, sp1,
labels = c("A","B","C","D"),
nrow = 2, ncol = 2)
scale_color_gradient()：用于两种颜色之间的顺序渐变
scale_color_gradient2()：用于分散梯度
scale_color_gradientn()：用于n种颜色之间的渐变
Rplot02.png
3.2. 手动更改配色
#Change colors manually
# Box plot
m <- bp + scale_fill_manual(values=c("#999999", "#E69F00", "#56B4E9"))
# Scatter plot
n <- sp + scale_color_manual(values=c("#999999", "#E69F00", "#56B4E9"))
# Box plot
o <- bp + scale_fill_manual(breaks = c("2", "1", "0.5"),
values=c("red", "blue", "green"))
# Scatter plot
p <- sp + scale_color_manual(breaks = c("8", "6", "4"),
values=c("red", "blue", "green"))
ggarrange(m, n, o, p,
labels = c("A","B","C","D"),
nrow = 2, ncol = 2)
Rplot03.png
3.3. RColorBrewer设置颜色
#Use RColorBrewer palettes
# Box plot
x <- bp + scale_fill_brewer(palette="Dark2")
# Scatter plot
y <- sp + scale_color_brewer(palette="Dark2")
ggarrange(x, y,
labels = c("A","B"),
nrow = 1)
Rplot04.png
3.4. Wes Anderson设置颜色
#Use Wes Anderson color palettes
library(wesanderson)
# Box plot
x1 <- bp+scale_fill_manual(values=wes_palette(n=3, name="GrandBudapest1"))
# Scatter plot
x2 <- sp+scale_color_manual(values=wes_palette(name="GrandBudapest1"))
ggarrange(x1, x2,
labels = c("A","B"),
nrow = 1)
Rplot05.png
（四）： 设置灰色
#Use gray colors
# Box plot
g1 <- bp + scale_fill_grey() + theme_classic()
# Scatter plot
g2 <- sp + scale_color_grey() + theme_classic()
# Box plot
g3 <- bp + scale_fill_grey(start=0.8, end=0.2) + theme_classic()
# Scatter plot
g4 <- sp + scale_color_grey(start=0.8, end=0.2) + theme_classic()
ggarrange(g1,g2,g3,g4,
labels = c("A","B","C","D"),
nrow = 2, ncol = 2)
Rplot06.png
（五）： 设置连续色
5.1. 散点图的渐变颜色
#Continuous colors
# Color by qsec values
sp2<-ggplot(mtcars, aes(x=wt, y=mpg, color=qsec)) + geom_point()
# Change the low and high colors
# Sequential color scheme
sp3 <- sp2+scale_color_gradient(low="blue", high="red")
# Diverging color scheme 不同的配色方案
mid<-mean(mtcars$qsec)
sp4 <- sp2+scale_color_gradient2(midpoint=mid, low="blue", mid="white",
high="red", space ="Lab" )
ggarrange(sp2,sp3,sp4,
labels = c("A","B","C"),
nrow = 1, ncol = 3)
Rplot07.png
5.2. 直方图的渐变颜色
#Gradient colors for histogram plots
set.seed(1234)
x <- rnorm(200)
# Histogram
hp <- qplot(x =x, fill=..count.., geom="histogram")
# Sequential color scheme
hp1 <- hp+scale_fill_gradient(low="blue", high="red")
#Gradient between n colors
# Scatter plot
# Color points by the mpg variable
sp3 <- ggplot(mtcars, aes(x=wt, y=mpg, color=mpg)) + geom_point()
# Gradient between n colors
sp4 <- sp3+scale_color_gradientn(colours = rainbow(5))
ggarrange(hp,hp1,sp3,sp4,
labels = c("A","B","C","D"),
nrow = 2, ncol = 2)
Rplot08.png
