在分类变量图表中显示百分比而不是计数 [英] Show percent % instead of counts in charts of categorical variables

问题描述

我正在绘制一个分类变量，而不是显示每个类别值的计数.

我正在寻找一种方法来让 ggplot 显示该类别中值的百分比.当然，可以使用计算出的百分比创建另一个变量并绘制该变量，但我必须这样做几十次，我希望在一个命令中实现.

我正在尝试类似的东西

qplot(mydataf) +stat_bin(aes(n = nrow(mydataf), y = ..count../n)) +scale_y_continuous(格式化程序=百分比")

但我一定是错误地使用了它，因为我遇到了错误.

为了轻松重现设置，这里有一个简化的例子:

mydata <- c ("aa", "bb", NULL, "bb", "cc", "aa", "aa", "aa", "ee", NULL, "cc");mydataf <- 因子(mydata);qplot (mydataf);#this 显示计数，我希望看到 % 显示.

在实际情况下，我可能会使用 ggplot 而不是 qplot，但是正确的使用方法是

这个问题目前是 google 上ggplot 计数与百分比直方图"的第一个热门问题，因此希望这有助于提炼目前包含在对已接受答案的评论中的所有信息.

备注:如果hp没有设置为一个因子，ggplot返回:

I'm plotting a categorical variable and instead of showing the counts for each category value.

I'm looking for a way to get ggplot to display the percentage of values in that category. Of course, it is possible to create another variable with the calculated percentage and plot that one, but I have to do it several dozens of times and I hope to achieve that in one command.

I was experimenting with something like

qplot(mydataf) +
  stat_bin(aes(n = nrow(mydataf), y = ..count../n)) +
  scale_y_continuous(formatter = "percent")

but I must be using it incorrectly, as I got errors.

To easily reproduce the setup, here's a simplified example:

mydata <- c ("aa", "bb", NULL, "bb", "cc", "aa", "aa", "aa", "ee", NULL, "cc");
mydataf <- factor(mydata);
qplot (mydataf); #this shows the count, I'm looking to see % displayed.

In the real case, I'll probably use ggplot instead of qplot, but the right way to use stat_bin still eludes me.

I've also tried these four approaches:

ggplot(mydataf, aes(y = (..count..)/sum(..count..))) + 
  scale_y_continuous(formatter = 'percent');

ggplot(mydataf, aes(y = (..count..)/sum(..count..))) + 
  scale_y_continuous(formatter = 'percent') + geom_bar();

ggplot(mydataf, aes(x = levels(mydataf), y = (..count..)/sum(..count..))) + 
  scale_y_continuous(formatter = 'percent');

ggplot(mydataf, aes(x = levels(mydataf), y = (..count..)/sum(..count..))) + 
  scale_y_continuous(formatter = 'percent') + geom_bar();

but all 4 give:

Error: ggplot2 doesn't know how to deal with data of class factor

The same error appears for the simple case of

ggplot (data=mydataf, aes(levels(mydataf))) +
  geom_bar()

so it's clearly something about how ggplot interacts with a single vector. I'm scratching my head, googling for that error gives a single result.

解决方案

Since this was answered there have been some meaningful changes to the ggplot syntax. Summing up the discussion in the comments above:

 require(ggplot2)
 require(scales)

 p <- ggplot(mydataf, aes(x = foo)) +  
        geom_bar(aes(y = (..count..)/sum(..count..))) + 
        ## version 3.0.0
        scale_y_continuous(labels=percent)

Here's a reproducible example using mtcars:

 ggplot(mtcars, aes(x = factor(hp))) +  
        geom_bar(aes(y = (..count..)/sum(..count..))) + 
        scale_y_continuous(labels = percent) ## version 3.0.0

This question is currently the #1 hit on google for 'ggplot count vs percentage histogram' so hopefully this helps distill all the information currently housed in comments on the accepted answer.

Remark: If hp is not set as a factor, ggplot returns:

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