ggplot2 histogram binwidth [duplicate] - r

Question

This question already has answers here:
Different breaks per facet in ggplot2 histogram
(4 answers)
Closed 8 years ago.
I would like to create multiple histograms within one plot (using facet_wrap).
This could be an example code:
df <- data.frame(p1 = rnorm(100,5,2), p2 = rnorm(100,80,20), group = rep(LETTERS[1:4],25))
library(ggplot2)
library(reshape)
plotData <- melt(df, id.vars = "group", measure.vars = c("p1","p2") )
m <- ggplot(plotData, aes(x = value, color = group, fill = group, group = group))
m <- m + geom_bar(position=position_dodge())
m <- m + facet_wrap( ~ variable,scales = "free_x")
print(m)
Now, I would like to modify the plot that it creates per parameter ("p1,"p2") let's say 10 bins.
Up to now, I could not find a way to do this as binwidth/breaks calculation should be dependent on a subset of data.
Is it possible at all?
I want to share my solution (taken from the answered question linked above) extended by the possibility to overlay the histograms with density curves scaled to histogram counts:
df <- data.frame(p1 = rnorm(1000,5,2), p2 = rnorm(1000,80,20), group = rep(LETTERS[1:4],25))
library(ggplot2)
library(reshape)
library(plyr)
plotData <- melt(df, id.vars = "group", measure.vars = c("p1","p2") )
nBins <- 10
groupedData <- dlply(plotData, .(variable))
groupedBinWidth <- llply(groupedData, .fun = function(data, nBins) {
r <- range(data$value, na.rm = TRUE, finite = TRUE)
widthOfBins = (r[2] - r[1])/nBins
if (is.na(widthOfBins) || is.infinite(widthOfBins) || (widthOfBins <= 0)) widthOfBins <- NULL
widthOfBins
}, nBins = nBins)
densData <- dlply(plotData, .(variable, group), .fun = function(subData){
param <- subData$variable[1]
group <- subData$group[1]
d <- density(subData$value)
bw <- groupedBinWidth[[param]]
data.frame(x = d$x, y = d$y * nrow(subData) * bw , group = group, variable = param)
})
hls <- mapply(function(x, b) geom_bar(aes(x = value), position = position_dodge(), data = x, binwidth = b),
groupedData, groupedBinWidth)
dLay <- mapply(function(data) geom_density(data = data, aes(x = x, y = y), stat = "identity", fill = NA, size = 1),
densData)
m <- ggplot(plotData, aes(x = value, color = group, fill = group, group = group))
m <- m + hls
m <- m + dLay
m <- m + facet_wrap( ~ variable,scales = "free")
print(m)

Answer 1

Try this - really ugly code, but works if I understand you correctly. You might want to play with geom_density and maybe remove fill to make it more readable.
nbin<- 5
m <- ggplot(plotData, aes(x = value, color = group, fill = group, group = group))
m <- m + geom_histogram(data = subset(plotData, variable == "p1"), binwidth=diff(range(subset(plotData, variable == "p1")$value))/nbin)
m <- m + geom_histogram(data = subset(plotData, variable == "p2"), binwidth=diff(range(subset(plotData, variable == "p2")$value))/nbin)
m <- m + facet_wrap( ~ variable,scales = "free_x")
print(m)