This is my data:
type<-rep(c(0,1),100) diff<-rnorm(100) data<-data.frame(type,diff)
If I want to plot historgram of diff
, I do this:
hist(data$diff)
But what I want to do to split my histogram according to type
. I could do this:
par(mfrow=c(1,2)) hist(data$diff[data$type==0]) hist(data$diff[data$type==1])
But what this is giving me are two different histograms side by side. What I want to do is produce a single histogram with diff
of 0
at one side and diff
of 1
at other side. Something like this with bars as continuous without the breaks or border in between. This presumably would mean the axis will be split into two for each factor.
Plot two histograms Using plot() will simply plot the histogram as if you'd typed hist() from the start. However, you can now use add = TRUE as a parameter, which allows a second histogram to be plotted on the same chart/axis.
Change the range of the x and y values on the axes by adding xlim and ylim as arguments to the hist() function: In the code chunk above, your histogram has an x-axis that is limited to values 100 to 700 , and the y-axis is limited to values 0 to 30 .
a histogram that is split into multiple histograms (each for a value of a categorical variable) and placed underneath each other for comparison. An example of such a split-histogram is shown in Figure 1.
You can use the ggplot2
package:
library(ggplot2) ggplot(data,aes(x=diff))+geom_histogram()+facet_grid(~type)+theme_bw()
You can also put them on the same plot by "dodging" them:
ggplot(data,aes(x=diff,group=type,fill=type))+ geom_histogram(position="dodge",binwidth=0.25)+theme_bw()
If you want them to overlap, the position has to be position="identity"
ggplot(data,aes(x=diff,group=type,fill=type))+ geom_histogram(position="identity",alpha=0.5,binwidth=0.25)+theme_bw()
If you want them to look like it does in the first one but without the border, you have to hack it a little:
data$diff[data$type==1] <- data$diff[data$type==1] + 6 ggplot(data,aes(x=diff,group=type,fill=type))+ geom_histogram(position="identity",alpha=0.5,binwidth=0.25)+theme_bw()+ scale_x_continuous(breaks=c(-2:2,4:8),labels=c(-2:2,-2:2))
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