blocks|key|297738|text|修改后的代码应该可以工作|type|unstyled|depth|inlineStyleRanges|entityRanges|data|297739|p+=+ggplot(mydataf,+aes(x+=+foo))+%2B+
++++geom_bar(aes(y+=+(..count..)/sum(..count..)))+%2B+
++++scale_y_continuous(formatter+=+'percent')|code-block|syntax|javascript|297740|如果您的数据包含NAs，并且您不希望将它们包含在绘图中，则将na.omit(mydataf)作为参数传递给ggplot。|297741|希望这能有所帮助。|297742|entityMap^0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|M|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|N|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|O|8|@]|9|@]|A|$]]|$1|I|3|J|5|6|7|P|8|@]|9|@]|A|$]]|$1|K|3|-4|5|6|7|Q|8|@]|9|@]|A|$]]]|L|$]]

this modified code should work

<pre><code>p = ggplot(mydataf, aes(x = foo)) + 
 geom_bar(aes(y = (..count..)/sum(..count..))) + 
 scale_y_continuous(formatter = 'percent')
</code></pre>

if your data has NAs and you dont want them to be included in the plot, pass na.omit(mydataf) as the argument to ggplot.

hope this helps.

blocks|key|294664|text|自从这个问题得到回答以来，ggplot语法已经发生了一些有意义的变化。总结上面评论中的讨论：|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|294665|+require(ggplot2)
+require(scales)

+p+<-+ggplot(mydataf,+aes(x+=+foo))+%2B++
++++++++geom_bar(aes(y+=+(..count..)/sum(..count..)))+%2B+
++++++++##+version+3.0.0
++++++++scale_y_continuous(labels=percent)|code-block|syntax|javascript|294666|下面是一个使用mtcars的可重复使用的示例|294667|+ggplot(mtcars,+aes(x+=+factor(hp)))+%2B++
++++++++geom_bar(aes(y+=+(..count..)/sum(..count..)))+%2B+
++++++++scale_y_continuous(labels+=+percent)+##+version+3.0.0|294668|​|294669|📷|atomic|294670|294671|这个问题目前在google上排名第一，因为“ggplot+count+vs百分比直方图”，所以希望这有助于提取当前在接受答案的评论中包含的所有信息。|294672|备注：如果hp未设置为因子，则ggplot返回：|BOLD|294673|294674|294675|294676|entityMap|0|IMAGE|mutability|IMMUTABLE|imageUrl|https://ask.qcloudimg.com/http-save/yehe-900000/5fb22dcbf5a6f493ca5569e744dad871.png|imageAlt|1|https://ask.qcloudimg.com/http-save/yehe-900000/9974f6e9e69cf21e3e5ae30802dbc6fc.png^0|D|6|0|0|7|6|0|0|0|0|1|0|0|0|0|0|3|5|2|0|0|0|1|1|0|0^^$0|@$1|2|3|4|5|6|7|1D|8|@$9|1E|A|1F|B|C]]|D|@]|E|$]]|$1|F|3|G|5|H|7|1G|8|@]|D|@]|E|$I|J]]|$1|K|3|L|5|6|7|1H|8|@$9|1I|A|1J|B|C]]|D|@]|E|$]]|$1|M|3|N|5|H|7|1K|8|@]|D|@]|E|$I|J]]|$1|O|3|P|5|6|7|1L|8|@]|D|@]|E|$]]|$1|Q|3|R|5|S|7|1M|8|@]|D|@$9|1N|A|1O|1|1P]]|E|$]]|$1|T|3|P|5|6|7|1Q|8|@]|D|@]|E|$]]|$1|U|3|V|5|6|7|1R|8|@]|D|@]|E|$]]|$1|W|3|X|5|6|7|1S|8|@$9|1T|A|1U|B|Y]|$9|1V|A|1W|B|C]]|D|@]|E|$]]|$1|Z|3|P|5|6|7|1X|8|@]|D|@]|E|$]]|$1|10|3|R|5|S|7|1Y|8|@]|D|@$9|1Z|A|20|1|21]]|E|$]]|$1|11|3|P|5|6|7|22|8|@]|D|@]|E|$]]|$1|12|3|-4|5|6|7|23|8|@]|D|@]|E|$]]]|13|$14|$5|15|16|17|E|$18|19|1A|-4]]|1B|$5|15|16|17|E|$18|1C|1A|-4]]]]

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

<pre><code> require(ggplot2)
 require(scales)

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

Here's a reproducible example using <code>mtcars</code>:

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

<a href="https://i.stack.imgur.com/WOiGv.png" rel="noreferrer"><img src="https://i.stack.imgur.com/WOiGv.png" alt="enter image description here"></a>

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 <code>hp</code> is not set as a factor, ggplot returns:

<a href="https://i.stack.imgur.com/coDzn.png" rel="noreferrer"><img src="https://i.stack.imgur.com/coDzn.png" alt="enter image description here"></a>

blocks|key|294678|text|如果您希望百分比标签但实际Ns在y轴上，请尝试以下操作：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|294679|++++library(scales)
perbar=function(xx){
++++++q=ggplot(data=data.frame(xx),aes(x=xx))%2B
++++++geom_bar(aes(y+=+(..count..)),fill="orange")
+++++++q=q%2B++++geom_text(aes(y+=+(..count..),label+=+scales::percent((..count..)/sum(..count..))),+stat="bin",colour="darkgreen")+
++++++q
++++}
++++perbar(mtcars$disp)|code-block|syntax|javascript|294680|entityMap^0|0|0^^$0|@$1|2|3|4|5|6|7|I|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|J|8|@]|9|@]|A|$E|F]]|$1|G|3|-4|5|6|7|K|8|@]|9|@]|A|$]]]|H|$]]

If you want percentage labels but actual Ns on the y axis, try this:

<pre><code> library(scales)
perbar=function(xx){
 q=ggplot(data=data.frame(xx),aes(x=xx))+
 geom_bar(aes(y = (..count..)),fill="orange")
 q=q+ geom_text(aes(y = (..count..),label = scales::percent((..count..)/sum(..count..))), stat="bin",colour="darkgreen") 
 q
 }
 perbar(mtcars$disp)
</code></pre>

blocks|key|297757|text|如果希望y轴上的百分比和条形图上的标签：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|297758|library(ggplot2)
library(scales)
ggplot(mtcars,+aes(x+=+as.factor(am)))+%2B
++geom_bar(aes(y+=+(..count..)/sum(..count..)))+%2B
++geom_text(aes(y+=+((..count..)/sum(..count..)),+label+=+scales::percent((..count..)/sum(..count..))),+stat+=+"count",+vjust+=+-0.25)+%2B
++scale_y_continuous(labels+=+percent)+%2B
++labs(title+=+"Manual+vs.+Automatic+Frequency",+y+=+"Percent",+x+=+"Automatic+Transmission")|code-block|syntax|javascript|297759|​|297760|📷|atomic|offset|length|297761|297762|添加条形图标签时，您可能希望通过在末尾添加以下内容来省略y轴以获得更清晰的图表：|297763|++theme(
++++++++axis.text.y=element_blank(),+axis.ticks=element_blank(),
++++++++axis.title.y=element_blank()
++)|297764|297765|297766|297767|entityMap|0|IMAGE|mutability|IMMUTABLE|imageUrl|https://ask.qcloudimg.com/http-save/yehe-900000/9dcfb9aeffcec432983b99f5efa67dbb.png|imageAlt|1|https://ask.qcloudimg.com/http-save/yehe-900000/9595250900b7d88d42f332af9c1f400c.png^0|0|0|0|0|1|0|0|0|0|0|0|0|1|1|0|0^^$0|@$1|2|3|4|5|6|7|16|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|17|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|18|8|@]|9|@]|A|$]]|$1|I|3|J|5|K|7|19|8|@]|9|@$L|1A|M|1B|1|1C]]|A|$]]|$1|N|3|H|5|6|7|1D|8|@]|9|@]|A|$]]|$1|O|3|P|5|6|7|1E|8|@]|9|@]|A|$]]|$1|Q|3|R|5|D|7|1F|8|@]|9|@]|A|$E|F]]|$1|S|3|H|5|6|7|1G|8|@]|9|@]|A|$]]|$1|T|3|J|5|K|7|1H|8|@]|9|@$L|1I|M|1J|1|1K]]|A|$]]|$1|U|3|H|5|6|7|1L|8|@]|9|@]|A|$]]|$1|V|3|-4|5|6|7|1M|8|@]|9|@]|A|$]]]|W|$X|$5|Y|Z|10|A|$11|12|13|-4]]|14|$5|Y|Z|10|A|$11|15|13|-4]]]]

If you want percentages on the y-axis and labeled on the bars:

<pre><code>library(ggplot2)
library(scales)
ggplot(mtcars, aes(x = as.factor(am))) +
 geom_bar(aes(y = (..count..)/sum(..count..))) +
 geom_text(aes(y = ((..count..)/sum(..count..)), label = scales::percent((..count..)/sum(..count..))), stat = "count", vjust = -0.25) +
 scale_y_continuous(labels = percent) +
 labs(title = "Manual vs. Automatic Frequency", y = "Percent", x = "Automatic Transmission")
</code></pre>

<a href="https://i.stack.imgur.com/ARTRs.png" rel="noreferrer"><img src="https://i.stack.imgur.com/ARTRs.png" alt="enter image description here"></a>

When adding the bar labels, you may wish to omit the y-axis for a cleaner chart, by adding to the end:

<pre><code> theme(
 axis.text.y=element_blank(), axis.ticks=element_blank(),
 axis.title.y=element_blank()
 )
</code></pre>

<a href="https://i.stack.imgur.com/nwj0p.png" rel="noreferrer"><img src="https://i.stack.imgur.com/nwj0p.png" alt="enter image description here"></a>

blocks|key|3022659|text|对于ggplot2版本2.1.0，它是|type|unstyled|depth|inlineStyleRanges|entityRanges|data|3022660|%2B+scale_y_continuous(labels+=+scales::percent)|code-block|syntax|javascript|3022661|entityMap^0|0|0^^$0|@$1|2|3|4|5|6|7|I|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|J|8|@]|9|@]|A|$E|F]]|$1|G|3|-4|5|6|7|K|8|@]|9|@]|A|$]]]|H|$]]

With ggplot2 version 2.1.0 it is

<pre><code>+ scale_y_continuous(labels = scales::percent)
</code></pre>

blocks|key|3022676|text|截至2017年3月，对于ggplot2+2.2.1，我认为最好的解决方案在Hadley+Wickham的R+for+data+science一书中有解释：|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|3022677|ggplot(mydataf)+%2B+stat_count(mapping+=+aes(x=foo,+y=..prop..,+group=1))|code-block|syntax|javascript|3022678|stat_count计算两个变量:默认情况下使用count，但您可以选择使用显示比例的prop。|3022679|entityMap^0|C|7|0|0|0|A|O|5|17|4|0^^$0|@$1|2|3|4|5|6|7|O|8|@$9|P|A|Q|B|C]]|D|@]|E|$]]|$1|F|3|G|5|H|7|R|8|@]|D|@]|E|$I|J]]|$1|K|3|L|5|6|7|S|8|@$9|T|A|U|B|C]|$9|V|A|W|B|C]|$9|X|A|Y|B|C]]|D|@]|E|$]]|$1|M|3|-4|5|6|7|Z|8|@]|D|@]|E|$]]]|N|$]]

As of March 2017, with <code>ggplot2</code> 2.2.1 I think the best solution is explained in Hadley Wickham's R for data science book:

<pre><code>ggplot(mydataf) + stat_count(mapping = aes(x=foo, y=..prop.., group=1))
</code></pre>

<code>stat_count</code> computes two variables: <code>count</code> is used by default, but you can choose to use <code>prop</code> which shows proportions.

blocks|key|3237112|text|以下是多面数据的变通方法。(+@Andrew接受的答案在这种情况下不起作用。)其思想是使用dplyr计算百分比值，然后使用geom_col创建绘图。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|3237113|library(ggplot2)
library(scales)
library(magrittr)
library(dplyr)

binwidth+<-+30

mtcars.stats+<-+mtcars+%25>%25
++group_by(cyl)+%25>%25
++mutate(bin+=+cut(hp,+breaks=seq(0,400,+binwidth),+
+++++++++++++++labels=+seq(0%2Bbinwidth,400,+binwidth)-(binwidth/2)),
+++++++++n+=+n())+%25>%25
++group_by(cyl,+bin)+%25>%25
++summarise(p+=+n()/n[1])+%25>%25
++ungroup()+%25>%25
++mutate(bin+=+as.numeric(as.character(bin)))

ggplot(mtcars.stats,+aes(x+=+bin,+y=+p))+%2B++
++geom_col()+%2B+
++scale_y_continuous(labels+=+percent)+%2B
++facet_grid(cyl~.)|code-block|syntax|javascript|3237114|这是图：|3237115|​|3237116|📷|atomic|offset|length|3237117|3237118|entityMap|0|IMAGE|mutability|IMMUTABLE|imageUrl|https://ask.qcloudimg.com/http-save/yehe-900000/7766afd3461b6dc34979dd06f3bef39d.png|imageAlt^0|0|0|0|0|0|1|0|0|0^^$0|@$1|2|3|4|5|6|7|Z|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|10|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|11|8|@]|9|@]|A|$]]|$1|I|3|J|5|6|7|12|8|@]|9|@]|A|$]]|$1|K|3|L|5|M|7|13|8|@]|9|@$N|14|O|15|1|16]]|A|$]]|$1|P|3|J|5|6|7|17|8|@]|9|@]|A|$]]|$1|Q|3|-4|5|6|7|18|8|@]|9|@]|A|$]]]|R|$S|$5|T|U|V|A|$W|X|Y|-4]]]]

Here is a workaround for faceted data. (The accepted answer by @Andrew does not work in this case.) The idea is to calculate the percentage value using dplyr and then to use geom_col to create the plot. 

<pre><code>library(ggplot2)
library(scales)
library(magrittr)
library(dplyr)

binwidth &lt;- 30

mtcars.stats &lt;- mtcars %&gt;%
 group_by(cyl) %&gt;%
 mutate(bin = cut(hp, breaks=seq(0,400, binwidth), 
 labels= seq(0+binwidth,400, binwidth)-(binwidth/2)),
 n = n()) %&gt;%
 group_by(cyl, bin) %&gt;%
 summarise(p = n()/n[1]) %&gt;%
 ungroup() %&gt;%
 mutate(bin = as.numeric(as.character(bin)))

ggplot(mtcars.stats, aes(x = bin, y= p)) + 
 geom_col() + 
 scale_y_continuous(labels = percent) +
 facet_grid(cyl~.)
</code></pre>

This is the plot:

<a href="https://i.stack.imgur.com/Y9P6g.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/Y9P6g.png" alt="enter image description here"></a>

blocks|key|299814|text|请注意，如果您的变量是连续的，则必须使用geom_histogram()，因为该函数将按“bin”对变量进行分组。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|299815|df+<-+data.frame(V1+=+rnorm(100))

ggplot(df,+aes(x+=+V1))+%2B++
++geom_histogram(aes(y+=+100*(..count..)/sum(..count..)))+

#+if+you+use+geom_bar(),+with+factor(V1),+each+value+of+V1+will+be+treated+as+a
#+different+category.+In+this+case+this+does+not+make+sense,+as+the+variable+is+
#+really+continuous.+With+the+hp+variable+of+the+mtcars+(see+previous+answer),+it+
#+worked+well+since+hp+was+not+really+continuous+(check+unique(mtcars$hp)),+and+one+
#+can+want+to+see+each+value+of+this+variable,+and+not+to+group+it+in+bins.
ggplot(df,+aes(x+=+factor(V1)))+%2B++
++geom_bar(aes(y+=+(..count..)/sum(..count..)))+|code-block|syntax|javascript|299816|entityMap^0|0|0^^$0|@$1|2|3|4|5|6|7|I|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|J|8|@]|9|@]|A|$E|F]]|$1|G|3|-4|5|6|7|K|8|@]|9|@]|A|$]]]|H|$]]

Note that if your variable is continuous, you will have to use geom_histogram(), as the function will group the variable by &quot;bins&quot;.
<pre><code>df &lt;- data.frame(V1 = rnorm(100))

ggplot(df, aes(x = V1)) + 
 geom_histogram(aes(y = 100*(..count..)/sum(..count..))) 

# if you use geom_bar(), with factor(V1), each value of V1 will be treated as a
# different category. In this case this does not make sense, as the variable is 
# really continuous. With the hp variable of the mtcars (see previous answer), it 
# worked well since hp was not really continuous (check unique(mtcars$hp)), and one 
# can want to see each value of this variable, and not to group it in bins.
ggplot(df, aes(x = factor(V1))) + 
 geom_bar(aes(y = (..count..)/sum(..count..))) 
</code></pre>

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

I'm looking for a way to get <code>ggplot</code> 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 

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

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

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

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

In the real case, I'll probably use <code>ggplot</code> instead of <code>qplot</code>, but the right way to use <a href="http://had.co.nz/ggplot2/stat_bin.html" rel="noreferrer">stat_bin</a> still eludes me.

I've also tried these four approaches:

<pre><code>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();
</code></pre>

but all 4 give:

<blockquote>
<pre><code>Error: ggplot2 doesn't know how to deal with data of class factor
</code></pre>
</blockquote>

The same error appears for the simple case of 

<pre><code>ggplot (data=mydataf, aes(levels(mydataf))) +
 geom_bar()
</code></pre>

so it's clearly something about how <code>ggplot</code> interacts with a single vector. I'm scratching my head, googling for that error gives a single <a href="http://groups.google.com/group/ggplot2/browse_thread/thread/0489a702f3afc83b" rel="noreferrer">result</a>.

Show percent % instead of counts in charts of categorical variables

我绘制了一个分类变量，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显示该类别中的值的百分比。当然，也可以使用计算出的百分比创建另一个变量，并绘制该变量的曲线图，但我必须这样做几十次，我希望在一个命令中就能实现。我在做一些实验，比如qplot(mydataf) +  stat_bin(aes(n = n...

问在分类变量图表中显示百分比而不是计数
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