當我們獲得多因素的原始數據的時候，就會根據不同的因素來繪制多組一樣的圖片。一個一個畫當然也行，不過很累，這里，我來使用ggplot2批量生成一個類型的圖片，并將他們拼接在一起。
這是某次血常規的數據（經過了修改），將數據整理成下面這種形式：
分組情況如下：
library(rio)
library(ggplot2)
library(patchwork)
rawdata <- import(file = "exp.xlsx",sheet = 1,col_names = T,na = "0",col_type = "numeric")? ?#從excel讀取數據，并將空單元格和單元格值為0的數字變為NA
group <- import(file = "exp.xlsx",sheet = 2,col_names = T,na = "0")
rawdata <- merge(group,rawdata,by = "order")? ? #按照order列合并，加入分組信息
rawdata
這里我們是想要每一列都做一個柱形圖，因此可以寫一個for循環，基本思路就是先把要做圖的那一列變量和group列提取出來，然后對每一個變量計算各組的均值和標準差（均值就是柱子的高度，標準差是為了畫出誤差棒）。
需要先畫一個圖（本例就是先畫出WBC，然后給出布局，例如這里要畫14個圖，我打算畫四行，每行4個圖，最后一行兩個圖）：
data <- rawdata[,c(2,3)]
data <- na.omit(data)? #刪除NA值
frame <- data.frame()? #使用循環計算出mean和sd
? for (j in c(1:7)){
? ? variable <- data[which(data$group == group[j,2]),]
? ? mean <- mean(variable[,2])
? ? sd <- sd(variable[,2])
? ? frame <- rbind(frame,cbind(mean = mean,sd = sd,order = j,group = group[j,2]))}
? frame$mean <- as.numeric(frame$mean)
? frame$sd <- as.numeric(frame$sd)
? p <- ggplot(frame,aes(x = reorder(group,order),y = mean))+
? ? geom_errorbar(aes(ymin = mean-sd ,ymax = mean + sd),size = 1.2,width = 0.2,color = "gray")+
? ? geom_bar(size = 1.2,color = "black",stat = "identity",width = 0.7,fill = rainbow(7),alpha = 0.6)+
? ? geom_point(shape = 18,size = 6,color = rainbow(7),alpha = 0.6)+
? ? labs(x = colnames(data)[2],y = paste("The organ coefficient of",colnames(data)[2]))+
? ? coord_cartesian(xlim = c(0.5,7.5),ylim = c(0,max(frame$mean+frame$sd)*1.2),expand = F)+
? ? geom_text(x = 4,y = max(frame$mean+frame$sd)*1.15,label = "One-way ANOVA: P > 0.05",size = 6)+
? ? theme(panel.background = element_blank(),
? ? ? ? ? panel.grid.major.y = element_line(colour = "grey",linetype = 2),
? ? ? ? ? axis.line = element_line(colour = "black",size = rel(2),arrow = arrow(angle = 30,length = unit(0.1,"inches"))),
? ? ? ? ? axis.title.y = element_text(size = rel(2),hjust = 0.5),
? ? ? ? ? axis.title.x = element_text(size = rel(2),hjust = 0.5),
? ? ? ? ? axis.text.x = element_text(size = rel(2),hjust = 1,angle = 45),
? ? ? ? ? axis.text.y = element_text(hjust = 1,size = rel(2)),
? ? ? ? ? axis.ticks = element_line(size = rel(1.3)),
? ? ? ? ? plot.title = element_text(size = rel(1.8)),
? ? ? ? ? plot.margin = margin(15,9,9,30))
? graph_one <- p + plot_layout(nrow = 4,ncol = 4,tag_level = "new")+plot_annotation(tag_levels = "A")+theme(plot.tag = element_text(size = rel(2)))? ? ? ? ?#這個函數就是給出整個圖片的布局
下面用for循環，將剩下的變量（WBC后面的變量）按照和上面一樣的操作進行繪圖，并將他們拼在一起。
for (i in c(4:dim(rawdata)[2])){
? data <- rawdata[,c(2,i)]
? data <- na.omit(data)
? frame <- data.frame()
? for (j in c(1:7)){
? ? variable <- data[which(data$group == group[j,2]),]
? ? mean <- mean(variable[,2])
? ? sd <- sd(variable[,2])
? ? frame <- rbind(frame,cbind(mean = mean,sd = sd,order = j,group = group[j,2]))}
? ? frame$mean <- as.numeric(frame$mean)
? ? frame$sd <- as.numeric(frame$sd)
? ? p <- ggplot(frame,aes(x = reorder(group,order),y = mean))+
? ? ? geom_errorbar(aes(ymin = mean-sd ,ymax = mean + sd),size = 1.2,width = 0.2,color = "gray")+
? ? ? geom_bar(size = 1.2,color = "black",stat = "identity",width = 0.7,fill = rainbow(7),alpha = 0.6)+
? ? ? geom_point(shape = 18,size = 6,color = rainbow(7),alpha = 0.6)+
? ? ? labs(x = colnames(data)[2],y = paste("The organ coefficient of",colnames(data)[2]))+
? ? ? coord_cartesian(xlim = c(0.5,7.5),ylim = c(0,max(frame$mean+frame$sd)*1.2),expand = F)+
? ? ? geom_text(x = 4,y = max(frame$mean+frame$sd)*1.15,label = "One-way ANOVA: P > 0.05",size = 6)+
? ? ? theme(panel.background = element_blank(),
? ? ? ? ? ? panel.grid.major.y = element_line(colour = "grey",linetype = 2),
? ? ? ? ? ? axis.line = element_line(colour = "black",size = rel(2),arrow = arrow(angle = 30,length = unit(0.1,"inches"))),
? ? ? ? ? ? axis.title.y = element_text(size = rel(2),hjust = 0.5),
? ? ? ? ? ? axis.title.x = element_text(size = rel(2),hjust = 0.5),
? ? ? ? ? ? axis.text.x = element_text(size = rel(2),hjust = 1,angle = 45),
? ? ? ? ? ? axis.text.y = element_text(hjust = 1,size = rel(2)),
? ? ? ? ? ? axis.ticks = element_line(size = rel(1.3)),
? ? ? ? ? ? plot.title = element_text(size = rel(1.8)),
? ? ? ? ? ? plot.margin = margin(15,9,9,30))
? ? graph_one <- graph_one + p + plot_layout(nrow = 4,ncol = 4,tag_level = "new")+plot_annotation(tag_levels = "A")+theme(plot.tag = element_text(size = rel(2))) ?#和上面的寫法有一點不一樣
? }
ggsave(graph_one,filename = "graph_one.tiff",width = 30,height = 22,dpi = 300,compression = "lzw")? #將圖片保存
最終圖片：
