Make Frequency Histogram for Factor Variables

Make Frequency Histogram for Factor Variables

It seems like you want barplot(prop.table(table(animals))):

However, this is not a histogram.

Create histogram (not barplot) from categorical variable

Thanks to Zheyuan Li I already have my answer. Instead of forcing a histogram, I can simply create a barplot that looks excatly like a histogram:

par(oma=c(2,0,0,0))   #so labels are not cut off   
barplot(table(hhincome2), space = 0, # set space between bars to zero
              ylab = "Frequency", main = "Netto houshold income",
              border="black", col="grey",las=2) 
axis(1, at =  hhincome,labels = FALSE) # at x-axis at category borders
box()

Edit: I just found an alternative way:

h <- hist(as.numeric(hhincome2) #as.numeric converst factor levels to numeric values
          , xlab = "", ylab = "Frequency", main = "Netto houshold income \n(with normal disttribution curve)",
             border="black", col="grey",las=2, 
          xaxt='n') #this supresses the x-axis which would disply levels instead values
axis(1, at =  hhincome2, labels = hhincome2, las=2) #just add factor level labels as labels
box()

This way it's possible to add a normal disttribution curve as well:

xfit<-seq(min(as.numeric(hhincome2)),max(as.numeric(hhincome2)),length=1100) 
yfit<-dnorm(xfit,mean=mean(as.numeric(hhincome2)),sd=sd(as.numeric(hhincome2))) 
yfit <- yfit*diff(h$mids[1:2])*length(as.numeric(hhincome2)) 
lines(xfit, yfit, col="black", lwd=2)

Get a histogram plot of factor frequencies (summary)

Update in light of clarified Q

set.seed(1)
dat2 <- data.frame(fac = factor(sample(LETTERS, 100, replace = TRUE)))
hist(table(dat2), xlab = "Frequency of Level Occurrence", main = "")

gives:

Here we just apply hist() directly to the result of table(dat). table(dat) provides the frequencies per level of the factor and hist() produces the histogram of these data.

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Original

There are several possibilities. Your data:

dat <- data.frame(fac = rep(LETTERS[1:4], times = c(3,3,1,5)))

Here are three, from column one, top to bottom:

• The default plot methods for class "table", plots the data and histogram-like bars
• A bar plot - which is probably what you meant by histogram. Notice the low ink-to-information ratio here
• A dot plot or dot chart; shows the same info as the other plots but uses far less ink per unit information. Preferred.

Code to produce them:

layout(matrix(1:4, ncol = 2))
plot(table(dat), main = "plot method for class \"table\"")
barplot(table(dat), main = "barplot")
tab <- as.numeric(table(dat))
names(tab) <- names(table(dat))
dotchart(tab, main = "dotchart or dotplot")
## or just this
## dotchart(table(dat))
## and ignore the warning
layout(1)

this produces:

If you just have your data in variable factor (bad name choice by the way) then table(factor) can be used rather than table(dat) or table(dat$fac) in my code examples.

For completeness, package lattice is more flexible when it comes to producing the dot plot as we can get the orientation you want:

require(lattice)
with(dat, dotplot(fac, horizontal = FALSE))

giving:

And a ggplot2 version:

require(ggplot2)
p <- ggplot(data.frame(Freq = tab, fac = names(tab)), aes(fac, Freq)) + 
    geom_point()
p

giving:

Plot histograms over factor variables

Something like this?

set.seed(1234)
df <- data.frame(weekday=rep(sort(unique(weekdays(.leap.seconds))), each=24), 
                       hour=rep(1:24, 7), count=sample(2:600, 24*7, replace=T))

df$weekday <- factor(df$weekday, levels=c("Monday", "Tuesday", "Wednesday", 
                      "Thursday", "Friday", "Saturday", "Sunday"), ordered=T)
df$hour <- factor(df$hour)

require(ggplot2)    
p <- ggplot(data = df, aes(x=hour)) 
p <- p + geom_histogram(aes(weights=count, fill=weekday))
p <- p + scale_fill_brewer(palette="Set3")
p <- p + facet_wrap( ~ weekday, ncol=1)
p

ploting histogram and finding frequency from data?

To plot a bar plot from one categorical variable is as simple as

library(ggplot2)

ggplot(df1, aes(x)) + geom_bar()

Data

x <- scan(what = character(), text = "
A
A
A
B
B
C
C
C
C
C
D")

df1 <- data.frame(x)

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