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R ggplot2堆叠条形图,按百分比包含几个类别变量

[英]R ggplot2 stacked barplot by percentage with several categorical variables

这是一个简单的问题,但是我很难理解ggplot2所需的格式:

我在R中有以下data.table

print(dt)
    ID       category      A    B   C     totalABC                                                                                                                                                                                                                                         
1:  10      group1        1    3   0      4                                                                                                                                                                                                                                         
2:  11      group1        1   11   1      13                                                                                                                                                                                                                                         
3:  12      group2        15  20   2      37                                                                                                                                                                                                                                         
4:  13      group2        6   12   2      20                                                                                                                                                                                                                                         
5:  14      group2        17  83   6      106   
...

我的目标是创建一个比例堆叠的条形图,如以下示例所示: https : //rpubs.com/escott8908/RGC_Ch3_Gar_Graphs

其中X / totalABC的百分比,其中X是A,B或C的category_type 。我也想按类别执行此操作,例如x轴值应为group1group2等。

作为具体的例子,在的情况下group1 ,有4 + 13 = 17总的元件。

百分比将为percent_A = 11.7%, percent_B = 82.3%, percent_C = 5.9%

正确的ggplot2解决方案似乎是:

library(ggplot2)
pp = ggplot(dt, aes(x=category, y=percentage, fill=category_type)) +                                                                                                                                                                                                                               
          geom_bar(position="dodge", stat="identity")  

我的困惑:如何创建与三个分类值相对应的单个percentage列?

如果以上内容不正确,我该如何格式化data.table以创建堆叠的条形图?

您可以使用以下代码:

melt(data.frame( #melt to get each variable (i.e. A, B, C) in a single row
     dt[,-1] %>% #get rid of ID
            group_by(category) %>% #group by category
                  summarise_each(funs(sum))), #get the summation for each variable
                  id.vars=c("category", "totalABC")) %>% 
ggplot(aes(x=category,y=value/totalABC,fill=variable))+ #define the x and y 
       geom_bar(stat = "identity",position="fill") + #make the stacked bars
                scale_y_continuous(labels = scales::percent) #change y axis to % format

它将绘制:

在此处输入图片说明

数据:

dt <- structure(list(ID = 10:14, category = structure(c(1L, 1L, 2L, 
    2L, 2L), .Label = c("group1", "group2"), class = "factor"), A = c(1L, 
    1L, 15L, 6L, 17L), B = c(3L, 11L, 20L, 12L, 83L), C = c(0L, 1L, 
    2L, 2L, 6L), totalABC = c(4L, 13L, 37L, 20L, 106L)), .Names = c("ID", 
    "category", "A", "B", "C", "totalABC"), row.names = c(NA, -5L
    ), class = c("data.table", "data.frame"), .internal.selfref = <pointer: 0x0000000000100788>)

如果要坚持绘图所用的代码怎么办?

在这种情况下,您可以使用此方法获取百分比:

df <- melt(data.frame( #melt to get each variable (i.e. A, B, C) in a single row
        dt[,-1] %>% #get rid of ID
          group_by(category) %>% #group by category
            summarise_each(funs(sum))), #get the summation for each variable
              id.vars=c("category", "totalABC")) %>% 
                mutate(percentage = dtf$value*100/dtf$totalABC)

但是需要修改您的ggplot才能正确获取堆积的条形:

#variable is the column carrying category_type
#position dodge make the bars to be plotted next to each other 
#while fill makes the stacked bars
ggplot(df, aes(x=category, y=percentage, fill=variable)) +           
       geom_bar(position="fill", stat="identity") 

这是一个解决方案:

require(data.table)
require(ggplot2)
require(dplyr)

melt(dt,measure.vars = c("A","B","C"),
     variable.name = "groups",value.name = "nobs") %>%
 ggplot(aes(x=category,y=nobs,fill=groups)) + 
  geom_bar(stat = "identity",position="fill")

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