R语言：箱线图绘制（添加平均值趋势线）
箱线图绘制
- 1. 写在前面
- 2.箱线图绘制
-
- 2.1 相关R包导入
- 2.2 数据导入及格式转换
- 2.3 ggplot绘图
1. 写在前面
今天有时间把之前使用过的一些代码和大家分享，其中箱线图绘制我认为是非常有用的一个部分。之前我是比较喜欢使用origin进行绘图，但是绘制的图不太好看，并且需要进行不断调整，不太方便，所以开始使用R语言进行绘制。
2.箱线图绘制
2.1 相关R包导入
library(openxlsx)
library(tidyverse)
library(ggsignif)
library(ggpubr)
library(RColorBrewer)
library(ggplot2)
2.2 数据导入及格式转换
由于使用ggplot2进行绘图需要将原本的表格数据进行转换，一下为数据导入和转换方法：
数据格式：
setwd("C:/Users/Desktop/Practice/")
dataT1 <- read.xlsx("T1.xlsx", sheet = 1) # 文件名+sheet的序号
dataS1 <- read.xlsx("S1.xlsx", sheet = 1) # 文件名+sheet的序号
summary(dataT1)
head(dataT1)
summary(dataS1)
head(dataS1)
#使用tidyverse包对数据进行处理
dataT1 <- dataT1 %>%
gather(key = 'group',value = 'values') %>% #gather()函数可以把多列数据合并成一列数据
filter(!is.na(values))
head(dataT1)
summary(dataT1)
dataS1 <- dataS1 %>%
gather(key = 'group',value = 'values') %>% #gather()函数可以把多列数据合并成一列数据
filter(!is.na(values))
head(dataS1)
summary(dataS1)
dataT1$group<-factor(dataT1$group,levels = c("2dm","4dm","6dm","8dm","10dm"))
dataS1$group<-factor(dataS1$group,levels = c("2dm","4dm","6dm","8dm","10dm"))
数据转换格式：
> head(dataT1)
group values
1 2dm 0.8640
2 2dm 0.8500
3 2dm 0.8680
4 2dm 0.8850
5 2dm 0.8870
6 2dm 0.8951
> head(dataS1)
group values
1 2dm 0.619
2 2dm 0.610
3 2dm 0.632
4 2dm 0.700
5 2dm 0.679
6 2dm 0.711
2.3 ggplot绘图
(p1 <- ggplot(data = dataT1, aes(x = group, y = values)) +
stat_boxplot(geom = "errorbar", width = 0.3, size = 0.8, aes(color = group)) +
geom_boxplot(aes(x = group, y = values, colour = group), size = 1.0, width = 0.6) +
geom_jitter(mapping = aes(x = group, y = values, colour = group), size = 1.5, alpha = 0.3) +
stat_summary(fun = "mean", geom = "point", color = "black", size = 2) +
stat_summary(fun = "mean", geom = "line", aes(group = 1), color = "black", size = 1) +
scale_color_manual(limits = c("2dm","4dm","6dm","8dm","10dm"),
values = c("#8dd3c7", "#fdb462", "#bebada", "#fb8072", "#80b1d3")) +
theme_classic(base_line_size = 1) +
labs(x = "空间分割等级", y = "Kappa") +
theme(
text = element_text(size = 16, family = "serif"),
axis.ticks.length = unit(0.2, "cm"), # 设置刻度线的长度
axis.ticks = element_line(size = 1), # 设置刻度线的粗细
legend.position = "none",
plot.title = element_text(size = 16, colour = "black", hjust = 0.5),
axis.title.y = element_text(size = 16, color = "black", vjust = 1.9, hjust = 0.5, angle = 90),
legend.title = element_text(color = "black", size = 16),
legend.text = element_text(color = "black", size = 16),
axis.text.x = element_text(size = 16, color = "black", vjust = 0.5, hjust = 0.5, angle = 0),
axis.text.y = element_text(size = 16, color = "black", vjust = 0.5, hjust = 0.5, angle = 0),
panel.border = element_rect(color = "black", size = 1, fill = NA),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
axis.line = element_line(colour = "black", size = 2),
axis.line.x = element_line(colour = "black", size = 0),
axis.line.y = element_line(colour = "black", size = 0)
)
)
(p2 <- ggplot(data = dataS1, aes(x = group, y = values)) +
stat_boxplot(geom = "errorbar", width = 0.3, size = 0.8, aes(color = group)) +
geom_boxplot(aes(x = group, y = values, colour = group), size = 1.0, width = 0.6) +
geom_jitter(mapping = aes(x = group, y = values, colour = group), size = 1.5, alpha = 0.3) +
stat_summary(fun = "mean", geom = "point", color = "black", size = 2) +
stat_summary(fun = "mean", geom = "line", aes(group = 1), color = "black", size = 1) +
scale_color_manual(limits = c("2dm","4dm","6dm","8dm","10dm"),
values = c("#8dd3c7", "#fdb462", "#bebada", "#fb8072", "#80b1d3")) +
theme_classic(base_line_size = 1) +
labs(x = "空间分割等级", y = "Kappa") +
theme(
text = element_text(size = 16, family = "serif"),
axis.ticks.length = unit(0.2, "cm"), # 设置刻度线的长度
axis.ticks = element_line(size = 1), # 设置刻度线的粗细
legend.position = "none",
plot.title = element_text(size = 16, colour = "black", hjust = 0.5),
axis.title.y = element_text(size = 16, color = "black", vjust = 1.9, hjust = 0.5, angle = 90),
legend.title = element_text(color = "black", size = 16),
legend.text = element_text(color = "black", size = 16),
axis.text.x = element_text(size = 16, color = "black", vjust = 0.5, hjust = 0.5, angle = 0),
axis.text.y = element_text(size = 16, color = "black", vjust = 0.5, hjust = 0.5, angle = 0),
panel.border = element_rect(color = "black", size = 1, fill = NA),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
axis.line = element_line(colour = "black", size = 2),
axis.line.x = element_line(colour = "black", size = 0),
axis.line.y = element_line(colour = "black", size = 0)
)
)
最后将两张图进行拼接并保存：
p1_cowplot <- ggdraw(p1)
p2_cowplot <- ggdraw(p2)
combined_plot <- plot_grid(p1_cowplot, p2_cowplot, ncol = 2, labels = "AUTO") #, labels = "AUTO"
combined_plot
ggsave("combined_plot.jpg", width = 28, height = 10, units = "cm", dpi= 600)
结果展示：
欢迎大家交流指正！