How to plot stacked point histograms?

Question

What's the ggplot2 equivalent of "dotplot" histograms? With stacked points instead of bars? Similar to this solution in R:

Plot Histogram with Points Instead of Bars

Is it possible to do this in ggplot2? Ideally with the points shown as stacks and a faint line showing the smoothed line "fit" to these points (which would make a histogram shape.)

Answer 1

ggplot2 does dotplots Link to the manual.

Here is an example:

library(ggplot2)

set.seed(789); x <- data.frame(y = sample(1:20, 100, replace = TRUE))

ggplot(x, aes(y)) + geom_dotplot()

In order to make it behave like a simple dotplot, we should do this:

ggplot(x, aes(y)) + geom_dotplot(binwidth=1, method='histodot')    

You should get this:

To address the density issue, you'll have to add another term, ylim(), so that your plot call will have the form ggplot() + geom_dotplot() + ylim()

More specifically, you'll write ylim(0, A), where A will be the number of stacked dots necessary to count 1.00 density. In the example above, the best you can do is see that 7.5 dots reach the 0.50 density mark. From there, you can infer that 15 dots will reach 1.00.

So your new call looks like this:

ggplot(x, aes(y)) + geom_dotplot(binwidth=1, method='histodot') + ylim(0, 15)

Which will give you this:

Usually, this kind of eyeball estimate will work for dotplots, but of course you can try other values to fine-tune your scale.

Notice how changing the ylim values doesn't affect how the data is displayed, it just changes the labels in the y-axis.

Answer 2

As @joran pointed out, we can use geom_dotplot

require(ggplot2)
ggplot(mtcars, aes(x = mpg)) + geom_dotplot()

---

Edit: (moved useful comments into the post):

The label "count" it's misleading because this is actually a density estimate may be you could suggest we changed this label to "density" by default. The ggplot implementation of dotplot follow the original one of Leland Wilkinson, so if you want to understand clearly how it works take a look at this paper.

An easy transformation to make the y axis actually be counts, i.e. "number of observations". From the help page it is written that:

When binning along the x axis and stacking along the y axis, the numbers on y axis are not meaningful, due to technical limitations of ggplot2. You can hide the y axis, as in one of the examples, or manually scale it to match the number of dots.

So you can use this code to hide y axis:

ggplot(mtcars, aes(x = mpg)) + 
  geom_dotplot(binwidth = 1.5) + 
  scale_y_continuous(name = "", breaks = NULL)

Answer 3

I introduce an exact approach using @Waldir Leoncio's latter method.

library(ggplot2); library(grid)

set.seed(789)
x <- data.frame(y = sample(1:20, 100, replace = TRUE))

g <- ggplot(x, aes(y)) + geom_dotplot(binwidth=0.8)
g  # output to read parameter

### calculation of width and height of panel
grid.ls(view=TRUE, grob=FALSE)
real_width <- convertWidth(unit(1,'npc'), 'inch', TRUE)
real_height <- convertHeight(unit(1,'npc'), 'inch', TRUE)

### calculation of other values
width_coordinate_range <- diff(ggplot_build(g)$panel$ranges[[1]]$x.range)
real_binwidth <- real_width / width_coordinate_range * 0.8  # 0.8 is the argument binwidth
num_balls <- real_height / 1.1 / real_binwidth  # the number of stacked balls. 1.1 is expanding value.
   # num_balls is the value of A

g + ylim(0, num_balls)

Answer 4

Apologies : I don't have enough reputation to 'comment'.

I like cuttlefish44's "exact approach", but to make it work (with ggplot2 [2.2.1]) I had to change the following line from :

### calculation of other values
width_coordinate_range <- diff(ggplot_build(g)$panel$ranges[[1]]$x.range)

to

### calculation of other values
width_coordinate_range <- diff(ggplot_build(g)$layout$panel_ranges[[1]]$x.range)