堆叠条形图将ggplot2 R中不相关变量的变量转换为基于存在与否的百分比

下面是一个示例数据帧

df <- data.frame(SampleID = c(1, 2, 3, 4, 5, 6, 7, 8),
                 Var1 = c(0.1 , 0.5,    0.7,    0,  0,  0,  0.5,    0.2), 
                 Var1PA = c("Present", "Present", "Present", "Absent", "Absent", "Absent",  "Present", "Present"), 
                 Var2 = c(0, 0, 0, 0, 0.1, 0.5, 0.7, 0.2), 
                 Var2PA = c("Absent", "Absent", "Absent", "Absent", "Present", "Present", "Present", "Present"))

df <- data.frame(SampleID = c(1, 2, 3, 4, 5, 6, 7, 8),
             Var1 = c(0.1 , 0.5,    0.7,    0,  0,  0,  0.5,    0.2), 
             Var1PA = c("Present", "Present", "Present", "Absent", "Absent", "Absent",  "Present", "Present"), 
             Var2 = c(0, 0, 0, 0, 0.1, 0.5, 0.7, 0.2), 
             Var2PA = c("Absent", "Absent", "Absent", "Absent", "Present", "Present", "Present", "Present"),
             Disease = c("Case", "Control", "Case", "Control", "Case", "Control", "Case", "Control"))

但在绘图时如何将其转换为百分比？ 我查看了许多熔体选项，但对于这些变量，没有统一的标准来创建公共X轴

最后，如果我想从1000个这样的列变量组成的数据框架中绘制5个变量，那么如何回答上述问题

编辑：谢谢你迄今为止的答案！我对这个问题略作修改 我刚刚在数据框中添加了一个变量

df <- data.frame(SampleID = c(1, 2, 3, 4, 5, 6, 7, 8),
                 Var1 = c(0.1 , 0.5,    0.7,    0,  0,  0,  0.5,    0.2), 
                 Var1PA = c("Present", "Present", "Present", "Absent", "Absent", "Absent",  "Present", "Present"), 
                 Var2 = c(0, 0, 0, 0, 0.1, 0.5, 0.7, 0.2), 
                 Var2PA = c("Absent", "Absent", "Absent", "Absent", "Present", "Present", "Present", "Present"))

df <- data.frame(SampleID = c(1, 2, 3, 4, 5, 6, 7, 8),
             Var1 = c(0.1 , 0.5,    0.7,    0,  0,  0,  0.5,    0.2), 
             Var1PA = c("Present", "Present", "Present", "Absent", "Absent", "Absent",  "Present", "Present"), 
             Var2 = c(0, 0, 0, 0, 0.1, 0.5, 0.7, 0.2), 
             Var2PA = c("Absent", "Absent", "Absent", "Absent", "Present", "Present", "Present", "Present"),
             Disease = c("Case", "Control", "Case", "Control", "Case", "Control", "Case", "Control"))

---

df这应该可以很好地概括。当然，你可以对你选择的变量更具选择性

library(dplyr)
library(tidyr)
mdf = df %>% select(SampleID, ends_with("PA")) %>%
    gather(key = Var, value = PA, -SampleID) %>%
    mutate(PA = factor(PA, levels = c("Present", "Absent")))

ggplot(mdf, aes(x = Var, fill = PA)) +
    geom_bar(position = "fill") +
    scale_y_continuous(labels = scales::percent)


您可以将百分比列添加到长数据框中：

mdf %>% group_by(Var) %>%
    mutate(p_present = mean(PA == "Present"),
           p_absent = mean(PA == "Absent"))
# Source: local data frame [16 x 5]
# Groups: Var [2]
# 
#    SampleID    Var      PA p_present p_absent
#       <dbl>  <chr>  <fctr>     <dbl>    <dbl>
# 1         1 Var1PA Present     0.625    0.375
# 2         2 Var1PA Present     0.625    0.375
# 3         3 Var1PA Present     0.625    0.375
# 4         4 Var1PA  Absent     0.625    0.375
# 5         5 Var1PA  Absent     0.625    0.375
# 6         6 Var1PA  Absent     0.625    0.375
# 7         7 Var1PA Present     0.625    0.375
# 8         8 Var1PA Present     0.625    0.375
# 9         1 Var2PA  Absent     0.500    0.500
# 10        2 Var2PA  Absent     0.500    0.500

应以百分比的形式列出出席/缺席情况，谢谢！抱歉，不能测试
vars一种温和的黑客方式：
library（tidyverse）；df%%>%gather（var，pa，以（'pa'）结尾）%%>%groupby（var）%%>%do（pa=names（table（.pa）），pct=prop.table（table（.pa））*100）%%>%unnest（）%%>%ggplot（aes（var，pct，fill=pa））+geom_-bar（stat='identity'）
@rawr很抱歉回复太晚了，谢谢你的回答，这对我帮助很大！如果我将另一个可变疾病添加到df中，使用prop.table是否可以轻松地分别获取每个变量中的病例（存在和不存在）和对照组（存在和不存在）的百分比？嗨，非常感谢您的回答，非常抱歉回复太晚。生活接管了我尝试了你的解决方案，但是我有点难以理解，因为聚集和变异都是我以前从未使用过的新函数。另外，我想在我绘制的最后一个表格（mdf）中实际查看频率计数，以供您回答。我已经编辑了一点问题，请让我知道，如果你有任何相同的建议。我对你的答案投了赞成票，谢谢！
mutate
所做的就是创建新列，
gather
或多或少地等同于
melt
。（
gather
的功能稍少，但语法更简单。）我将添加几行，将百分比放入数据中。我在这里发布了一个新问题：。谢谢你的时间！