更改堆叠条形图的颜色,但保持每个类的堆叠顺序递增

问题描述

我一直在尝试创建一个堆积的条形图,该图的颜色与地图中的颜色有关。基本上,我具有给定多边形覆盖的面积比例。我已经预先对 df 进行了排序,因此每个Proportion的堆栈Class的降序排列。如果将fill的值设置为一个连续变量,即Cluster(但是我不能更改堆栈的特定颜色),并且将它们转换为因子Clu,则堆栈的顺序丢失了,或者我可以设法对它们进行排序,但是对于整个图形,不是每个类...相同的Cluster可以出现在不同的类中,即集群 Two

          Num    Class Cluster Proportion   Clu Order consec
1    9  Class_9       2      0.859   Two     1      1
2    9  Class_9       5      0.141  Five     2      2
3   10 Class_10       2      0.622   Two     1      3
4   10 Class_10       1      0.179   One     2      4
5   10 Class_10       7      0.165 Seven     3      5
6   10 Class_10       6      0.034   Six     4      6
7   11 Class_11       7      1.000 Seven     1      7
8   12 Class_12       2      0.571   Two     1      8
9   12 Class_12       8      0.289 Eight     2      9
10  12 Class_12       1      0.140   One     3     10
11  13 Class_13       8      0.581 Eight     1     11
12  13 Class_13       4      0.210  Four     2     12
13  13 Class_13       2      0.112   Two     3     13
14  13 Class_13       3      0.079 Three     4     14
15  13 Class_13       5      0.018  Five     5     15

我已经设法在代码上走了这么远。

cols<-c(One='Blue',Two='Red',Three='Yellow',Four='lightblue',Five='darkgrey',Six='Black',Seven='cyan',Eight='Green')
  

ggplot(Tx,aes(x=Class,y=Proportion,fill= Clu)) + 
  geom_col(width = .7,colour="black",lwd=0.1) +
  geom_text(aes(label=ifelse(Proportion >= 0.05,sprintf("%.2f",Proportion),"")),position=position_stack(vjust=0.5),colour="white") +
  coord_flip() +
  scale_y_continuous(labels = function(y) paste0(y))+
  scale_fill_manual(values = cols)+ 
  labs(y="",x="")

总而言之,我想为每个类创建一个图,其中比例按升序排列,但要为每个聚类指定颜色

enter image description here

解决方法

一种选择(与您的想法有所不同)是使用position.dodgetidytext::reorder_within

library(tidyverse)
library(tidytext)

cols<-c('Blue','Red','Yellow','lightblue','darkgrey','Black','cyan','Green')

Tx %>%
  mutate(Cluster2 = reorder_within(Cluster,Proportion,Class)) %>%
  ggplot(aes(Cluster2,fill = as.factor(Cluster))) +
  geom_col(position = position_dodge2(preserve = "single")) +
  scale_x_reordered() +
  scale_fill_manual(values = cols) +
  coord_flip() +
  facet_grid(Class~.,scales = 'free_y',space = 'free')

enter image description here


如果您确实需要具有不同顺序的堆叠条形图,则另一个选择是分别为每个类生成图(这允许正确的顺序),然​​后将它们重新堆叠在一起。可以使用cowplot::plot_gridcowplot::get_legend来完成。

以正确的顺序生成地块列表,并将其堆叠到一个地块中。

library(tidyverse)
library(cowplot)

Tx2 <- Tx %>%
  mutate(Cluster = factor(Cluster))

cols<-c(One='Blue',Two='Red',Three='Yellow',Four='lightblue',Five='darkgrey',Six='Black',Seven='cyan',Eight='Green')


p_list <- lapply(unique(Tx2$Class),function(x){
  p <-  Tx2 %>%
    filter(Class == x) %>%
    ggplot(aes(Class,fill = reorder(Clu,-Proportion))) +
    geom_col(color = 'black') +
    geom_text(aes(label=ifelse(Proportion >= 0.05,sprintf("%.2f",Proportion),"")),position=position_stack(vjust=0.5),color = 'white') +
    coord_flip() +
    scale_fill_manual(values = cols) +
    labs(x = NULL,y = NULL) +
    theme_minimal() +
    theme(legend.position = 'none') 
  
 if (x != 'Class_13') p <- p + theme(axis.text.x = element_blank()) 
  
 p
})



p_col <- plot_grid(plotlist = p_list,ncol = 1,align = 'v',rel_heights = c(rep(1,4),1.2))

生成要使用的图例。

p <- ggplot(Tx2,aes(Class,as.numeric(Cluster)))) +  
  geom_col(color = 'black') +
  scale_fill_manual(values = cols,labels= 1:8,name = 'Cluster')
l <- cowplot::get_legend(p)

将堆积的图和图例放在一起。

plot_grid(p_col,l,rel_widths = c(3,.4))

!enter image description here


数据

Tx <- read.table(text = 
'  Num    Class Cluster Proportion   Clu Order consec
1    9  Class_9       2      0.859   Two     1      1
2    9  Class_9       5      0.141  Five     2      2
3   10 Class_10       2      0.622   Two     1      3
4   10 Class_10       1      0.179   One     2      4
5   10 Class_10       7      0.165 Seven     3      5
6   10 Class_10       6      0.034   Six     4      6
7   11 Class_11       7      1.000 Seven     1      7
8   12 Class_12       2      0.571   Two     1      8
9   12 Class_12       8      0.289 Eight     2      9
10  12 Class_12       1      0.140   One     3     10
11  13 Class_13       8      0.581 Eight     1     11
12  13 Class_13       4      0.210  Four     2     12
13  13 Class_13       2      0.112   Two     3     13
14  13 Class_13       3      0.079 Three     4     14
15  13 Class_13       5      0.018  Five     5     15')