1.Error bars
1.1 误差图分类
geom_errorbar()
geom_linerange()
geom_pointrange()
geom_crossbar()
geom_errorbarh()
1.2 数据准备
# geom_errorbar()
# geom_linerange()
# geom_pointrange()
# geom_crossbar()
# geom_errorbarh()
# 向条形图和折线图添加误差线
library(ggplot2)
df <- ToothGrowth
df$dose <- as.factor(df$dose)
head(df)
# 函数计算每组的平均值和标准偏差
# data：数据框
# varname：包含要汇总的变量的列的名称
# groupnames：用作分组变量的列名称的向量
data_summary <- function(data, varname, groupnames){
require(plyr)
summary_func <- function(x, col){
c(mean = mean(x[[col]], na.rm=TRUE),
sd = sd(x[[col]], na.rm=TRUE))
}
data_sum<-ddply(data, groupnames, .fun=summary_func,
varname)
data_sum <- rename(data_sum, c("mean" = varname))
return(data_sum)
}
df2 <- data_summary(ToothGrowth, varname="len",
groupnames=c("supp", "dose"))
# Convert dose to a factor variable
df2$dose=as.factor(df2$dose)
head(df2)
1.3 带误差条的条形图
library(ggplot2)
# 默认条形图
p1 <- ggplot(df2, aes(x=dose, y=len, fill=supp)) +
geom_bar(stat="identity", color="black",
position=position_dodge()) +
geom_errorbar(aes(ymin=len-sd, ymax=len+sd), width=.2,
position=position_dodge(.9))
# 成品条形图
p2 <- p1 +labs(title="Tooth length per dose", x="Dose (mg)", y = "Length")+
theme_classic() +
scale_fill_manual(values=c('#999999','#E69F00'))
# 仅保留较高的误差线
p3 <- ggplot(df2, aes(x=dose, y=len, fill=supp)) +
geom_bar(stat="identity", color="black", position=position_dodge()) +
geom_errorbar(aes(ymin=len, ymax=len+sd), width=.2,
position=position_dodge(.9))
ggarrange(p1,p2,p3)
image.png
1.4 带误差线的线图
# 默认线图
p4 <- ggplot(df2, aes(x=dose, y=len, group=supp, color=supp)) +
geom_line() +
geom_point()+
geom_errorbar(aes(ymin=len-sd, ymax=len+sd), width=.2,
position=position_dodge(0.05))
# 成品线图
p5 <- p4 + labs(title="Tooth length per dose", x="Dose (mg)", y = "Length")+
theme_classic() +
scale_color_manual(values=c('#999999','#E69F00'))
# Use geom_pointrange
p6 <- ggplot(df2, aes(x=dose, y=len, group=supp, color=supp)) +
geom_pointrange(aes(ymin=len-sd, ymax=len+sd))
# Use geom_line()+geom_pointrange()
p7 <- ggplot(df2, aes(x=dose, y=len, group=supp, color=supp)) +
geom_line()+
geom_pointrange(aes(ymin=len-sd, ymax=len+sd))
ggarrange(p4,p5,p6,p7)
image.png
1.5 带有均值点和误差线的点图
# 使用了geom_dotplot()和stat_summary()函数：
# 平均值+/- SD可以添加为纵横线，误差线或点范围：
p8 <- ggplot(df, aes(x=dose, y=len)) +
geom_dotplot(binaxis='y', stackdir='center')
# use geom_crossbar()
p9 <- p8 + stat_summary(fun.data="mean_sdl", fun.args = list(mult=1),
geom="crossbar", width=0.5)
# Use geom_errorbar()
p10 <- p8 + stat_summary(fun.data=mean_sdl, fun.args = list(mult=1),
geom="errorbar", color="red", width=0.2) +
stat_summary(fun.y=mean, geom="point", color="red")
# Use geom_pointrange()
p11 <- p8 + stat_summary(fun.data=mean_sdl, fun.args = list(mult=1),
geom="pointrange", color="red")
ggarrange(p8,p9,p10,p11)
image.png
2.Pie chart
df <- data.frame(
group = c("Male", "Female", "Child"),
value = c(25, 25, 50)
)
head(df)
library(ggplot2)
# Barplot
bp<- ggplot(df, aes(x="", y=value, fill=group))+
geom_bar(width = 1, stat = "identity")
bp
pie <- bp + coord_polar("y", start=0)
pie
ggarrange(bp,pie)
image.png
# 更改饼图填充颜色
# 自定义调色板
p1 <- pie + scale_fill_manual(values=c("#999999", "#E69F00", "#56B4E9"))
# brewer调色板
p2 <- pie + scale_fill_brewer(palette="Dark2")
p3 <- pie + scale_fill_brewer(palette="Blues")+
theme_minimal()
# 灰度
p4 <- pie + scale_fill_grey() + theme_minimal()
ggarrange(p1,p2,p3,p4)
image.png
# 从因子变量创建饼图
head(PlantGrowth)
p5 <- ggplot(PlantGrowth, aes(x=factor(1), fill=group))+
geom_bar(width = 1)+
coord_polar("y")
p5
image.png
# 自定义饼图
blank_theme <- theme_minimal()+
theme(
axis.title.x = element_blank(),
axis.title.y = element_blank(),
panel.border = element_blank(),
panel.grid=element_blank(),
axis.ticks = element_blank(),
plot.title=element_text(size=14, face="bold")
)
# 套用空白主题
library(scales)
p6 <- pie + scale_fill_grey() + blank_theme +
theme(axis.text.x=element_blank()) +
geom_text(aes(y = value/3 + c(0, cumsum(value)[-length(value)]),
label = percent(value/100)), size=5)
# brewer调色板
p7 <- pie + scale_fill_brewer("Blues") + blank_theme +
theme(axis.text.x=element_blank())+
geom_text(aes(y = value/3 + c(0, cumsum(value)[-length(value)]),
label = percent(value/100)), size=5)
ggarrange(p6,p7)
image.png
Reference
1.ggplot2 error bars : Quick start guide - R software and data visualization
2.ggplot2 pie chart : Quick start guide - R software and data visualization
3.ggplot2 pie chart : Quick start guide - R software and data visualization