Plot Frequency Distribution of One

I have a single series of values (ie one column of data), and I would like to create a plot with the range of data values on the x-axis and the frequency that each value appears in the data set on the y-axis.

What I would like is very close to a Kernel Density Plot:

# Kernel Density Plot
d <- density(mtcars$mpg) # returns the density data 
plot(d) # plots the results

and Frequency distribution in R on stackoverflow.

However, I would like frequency (as opposed to density) on the y-axis.

Specifically, I'm working with network degree distributions, and would like a double-log scale with open, circular points, ie this image.

I've done research into related resources and questions, but haven't found what I wanted:

Cookbook for R's Plotting distributions is close to what I want, but not precisely. I'd like to replace the y-axis in its density curve example with "count" as it is defined in the histogram examples.

The ecdf() function in R (ie this question) may be what I want, but I'd like the observed frequency, and not a normalized value between 0 and 1, on the y-axis.

This question is related to frequency distributions, but I'd like points, not bars.

EDIT:

The data is a standard power-law distribution, ie

dat <- c(rep(1, 1000), rep(10, 100), rep(100, 10), 100)

---

If you have discrete values for observations and want to make a plot with points on the log scale, then

dat <- c(rep(1, 1000), rep(10, 100), rep(100, 10), 100)

dd<-aggregate(rep.int(1, length(dat))~dat, FUN=sum)
names(dd)<-c("val","freq")

plot(freq~val, dd, log="xy")

might be what you are after.

---

The integral of a density is approximately 1 so multiplying the density$y estimate by the number of values should give you something on the scale of a frequency. If you want a "true" frequency then you should use a histogram:

d <- density(mtcars$mpg) 
d$y <- d$y * length(mtcars$mpg)  ; plot(d)

This is a histogram with breaks that are 1 unit each:

hist(mtcars$mpg, 
     breaks=trunc(min(mtcars$mpg)):(1+trunc(max(mtcars$mpg))), add=TRUE)

So this is the superposed comparison:

d <- density(mtcars$mpg) 
d$y <- d$y * length(mtcars$mpg)  ; plot(d, ylim=c(0,4) )
hist(mtcars$mpg, breaks=trunc(min(mtcars$mpg)):(1+trunc(max(mtcars$mpg))), add=TRUE)

You'll want to look at the density page where the default density bandwidth choice is criticized and alternatives offered. f you use the adjust parameter you might see a closer (smoothed correspondence to the histogram

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