How to add mean, and mode to ggplot histogram?

Borja_042 picture Borja_042 · Oct 29, 2017 · Viewed 19.1k times · Source

I need to add a mean line and the value of the mode for example to this kinds of plots:

I use this for calculate the number of bins:

bw <- diff(range(cars$lenght)) / (2 * IQR(cars$lenght) / length(cars$lenght)^(1/3))

And the plot:

ggplot(data=cars, aes(cars$lenght)) + 
  geom_histogram(aes(y =..density..), 
                 col="red",
                 binwidth = bw,
                 fill="green", 
                 alpha=1) + 
  geom_density(col=4) + 
  labs(title='Lenght Plot', x='Lenght', y='Times')

cars$lenght

168.8 168.8 171.2 176.6 176.6 177.3 192.7 192.7 192.7 178.2 176.8 176.8 176.8 176.8 189.0 189.0 193.8 197.0 141.1 155.9 158.8 157.3 157.3 157.3 157.3 157.3 157.3 157.3 174.6 173.2

Thanks in advance.

Answer

dule arnaux picture dule arnaux · Nov 1, 2017

I'm not sure how to replicate your data, so I used cars$speed in its place.

geom_vline will place vertical lines where you want, and you can calculate the mean and mode of the raw data on the fly. But if you want the mode as the histogram bin with the highest frequency, you can extract that from the ggplot object.

I'm not too sure how you want to define mode, so i plotted a bunch of different approaches.

# function to calculate mode
fun.mode<-function(x){as.numeric(names(sort(-table(x)))[1])}

bw <- diff(range(cars$length)) / (2 * IQR(cars$speed) / length(cars$speed)^(1/3))
p<-ggplot(data=cars, aes(cars$speed)) + 
  geom_histogram(aes(y =..density..), 
                 col="red",
                 binwidth = bw,
                 fill="green", 
                 alpha=1) + 
  geom_density(col=4) + 
  labs(title='Lenght Plot', x='Lenght', y='Times')

# Extract data for the histogram and density peaks
data<-ggplot_build(p)$data
hist_peak<-data[[1]]%>%filter(y==max(y))%>%.$x
dens_peak<-data[[2]]%>%filter(y==max(y))%>%.$x

# plot mean, mode, histogram peak and density peak
p%+%
  geom_vline(aes(xintercept = mean(speed)),col='red',size=2)+
  geom_vline(aes(xintercept = fun.mode(speed)),col='blue',size=2)+
  geom_vline(aes(xintercept = hist_peak),col='orange',size=2)+
  geom_vline(aes(xintercept = dens_peak),col='purple',size=2)+
  geom_text(aes(label=round(hist_peak,1),y=0,x=hist_peak),
            vjust=-1,col='orange',size=5)

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