facet_wrap 中的条带标签自定义

Question

我想将第2列中的分面图的条带标签移至右侧。 正如我在图中标记的那样，

我正在使用此代码

library(reshape2)
library(tidyverse)
library(ggh4x)
library(scales)
library(ggplot2)
#step 1: mutate the data
df <- melt(df, id=c("Specie","Treatment"))
head(df)
#plotting
left  <- scale_y_continuous(labels = number_format(accuracy = 0.01))
right <- scale_y_continuous(labels = number_format(accuracy = 0.01),position = "right")

ggplot(df1, aes(x = Specie, y = mean, fill = Treatment, colour=Treatment)) +
  geom_col(position = position_dodge(), width = 0.8)+
  facet_wrap(~ variable, scales = "free_y", ncol = 2, 
             labeller = label_parsed, strip.position = "left")+
  geom_errorbar(aes(ymin = mean, ymax = mean + sd), width = 0.2,
                position = position_dodge(0.9)) +theme_bw()+
  geom_text(aes(y = mean+sd,label = label),position = position_dodge(0.9),
            size = 3.5, vjust=-0.2, family="serif", colour="black")+
  geom_text(aes(y = Q1/2,label = letter),size = 3.5, family="serif", colour="#000000")+
  scale_fill_manual(values=c('#DEB887','#CD853F'))+
  scale_color_manual(values=c('#DEB887','#CD853F'))+
  facetted_pos_scales(y = list(left, right, left, right, left, right))+
  #coord_flip()+
  theme(axis.text.x = element_text(face = "italic"),
        strip.placement = "outside",
        strip.background = element_blank())

这是示例数据集

治疗	硬币	Pn	Gs	E	WUE
CT	S。科默森	4.8100	0.0736	1.1100	4.3333
CT	S。科默森	11.5000	0.4660	5.4400	2.1140
CT	S。马铃薯 2x	16.4000	0.4930	5.5200	2.9710
CT	S。马铃薯 2x	4.2400	0.0862	1.8100	2.3425
CT	S。查科恩斯	3.9200	0.0426	0.7160	5.4749
CT	S。查科恩斯	7.9000	0.1500	1.9400	4.0722
HS	S。科默森	10.1000	0.3520	6.0300	1.6750
HS	S。科默森	6.8500	0.3700	5.4600	1.2546
HS	S。马铃薯 2x	4.7100	0.0205	0.8400	5.6071
HS	S。马铃薯 2x	4.3400	0.0314	1.2450	3.4859
HS	S。查科恩斯	13.8000	0.2450	6.4800	2.1296
HS	S。查科恩斯	14.4000	0.1700	5.5100	2.6134

Answer 1

您可以使用

patchwork

包并将两个图拼凑在一起，使标签成为单独的，然后用共享轴/图例修补在一起。这不包括图中的所有规格（例如，误差线、颜色、文本），但总体思路是：

library(patchwork)


#Creating dataset and adding grouping variable
mod_iris <- iris %>% 
    group_by(Species) %>% 
    mutate(average_petal_length = mean(Petal.Length)) %>% 
    mutate(species_length_group = case_when(Petal.Length <= average_petal_length ~ "Short",
                                            TRUE ~ "Long")) %>% 
    select(-average_petal_length) %>% 
    ungroup() %>% 
    pivot_longer(cols = "Sepal.Length":"Petal.Width")  

#Create two datasets

#One for length

iris_lengths_data <- mod_iris %>% 
    filter(!str_detect(name,"Width"))

#This will be plot that has information on the left
length_plot <- iris_lengths_data %>% 
    ggplot(aes(x = Species, y = value, fill = species_length_group, color = species_length_group)) +
    geom_bar(stat = "identity", position = "dodge") +
    facet_wrap(.~name, scales = "free_y", ncol = 1, strip.position = "left") +
    theme(strip.placement = "outside")



#One for width

iris_widths_data <- mod_iris %>% 
    filter(str_detect(name,"Width"))
    
#This will be plot that has information on the right
width_plot <- iris_widths_data %>% 
    ggplot(aes(x = Species, y = value, fill = species_length_group, color = species_length_group)) +
    geom_bar(stat = "identity", position = "dodge") +
    facet_wrap(.~name, scales = "free_y", ncol = 1, strip.position = "right") +
    scale_y_continuous(position = "right") +
    labs(y = NULL)+ #Removed to have just one y axis
    theme(strip.placement = "outside",
          strip.text.y.right = element_text(angle = 90))  #adjusted to have text in same direction as length plot

    

#Patch together 
iris_patch <- length_plot + width_plot + plot_layout(guides = "collect") & xlab(NULL) & theme(legend.position = "right")


#Add common x-axis and position
wrap_elements(panel = iris_patch) +
    labs(tag = "Species") +
    theme(plot.tag = element_text(size = rel(1)),
          plot.tag.position = c(.415, 0))