R – Count by factor in ggplot2 chart

ggplot2r

Given the following ggplot2 chart:

ggplot(my_data, aes(colour=my_factor) +   
                geom_point(aes(x=prior, y=current)) +   
                facet_grid(gender ~ age)

I would like to make the size of the points be proportional to the count of my_factor for that prior/current combination.

ggplot(my_data, aes(colour=my_factor, 
                size=<something-here>(my_factor)) +   
                geom_point(aes(x=prior, y=current)) + 
                facet_grid(gender ~ age)

Any ideas?

== Edit ==

Here's a very trivial example based on mpg dataset. Let's define "great_hwy" as hwy > 35, and "great_cty" as cty > 25:

mpg$great_hwy[mpg$hwy > 35]  <-1
mpg$great_hwy[mpg$hwy <= 35] <-0
mpg$great_hwy <- factor(mpg$great_hwy)

mpg$great_cty[mpg$cty > 25]  <- 1
mpg$great_cty[mpg$cty <= 25] <- 0
mpg$great_cty <- factor(mpg$great_cty)

If we plot great_hwy vs. great_cty, it won't tell us much:

ggplot(mpg) + geom_point(aes(x=great_cty, y=great_hwy))

How could I make the data points bigger in size depending on the number of x/y points? Hope this clears it up, but let me know otherwise.

Best Answer

You can certainly do this by counting external to ggplot, but one of the great things about ggplot is that you can do many of these statistics internally!

Using your mpg example above:

ggplot(mpg) + 
  geom_point(aes(x=great_cty, y=great_hwy, 
                 size=..count..), stat="bin")

alt text

Any ggplots side-by-side (or n plots on a grid)

The function grid.arrange() in the gridExtra package will combine multiple plots; this is how you put two side by side.

require(gridExtra)
plot1 <- qplot(1)
plot2 <- qplot(1)
grid.arrange(plot1, plot2, ncol=2)

This is useful when the two plots are not based on the same data, for example if you want to plot different variables without using reshape().

This will plot the output as a side effect. To print the side effect to a file, specify a device driver (such as pdf, png, etc), e.g.

pdf("foo.pdf")
grid.arrange(plot1, plot2)
dev.off()

or, use arrangeGrob() in combination with ggsave(),

ggsave("foo.pdf", arrangeGrob(plot1, plot2))

This is the equivalent of making two distinct plots using par(mfrow = c(1,2)). This not only saves time arranging data, it is necessary when you want two dissimilar plots.

Appendix: Using Facets

Facets are helpful for making similar plots for different groups. This is pointed out below in many answers below, but I want to highlight this approach with examples equivalent to the above plots.

mydata <- data.frame(myGroup = c('a', 'b'), myX = c(1,1))

qplot(data = mydata, 
    x = myX, 
    facets = ~myGroup)

ggplot(data = mydata) + 
    geom_bar(aes(myX)) + 
    facet_wrap(~myGroup)

Update

the plot_grid function in the cowplot is worth checking out as an alternative to grid.arrange. See the answer by @claus-wilke below and this vignette for an equivalent approach; but the function allows finer controls on plot location and size, based on this vignette.

Rotating and spacing axis labels in ggplot2

Change the last line to

q + theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1))

By default, the axes are aligned at the center of the text, even when rotated. When you rotate +/- 90 degrees, you usually want it to be aligned at the edge instead:

alt text

The image above is from this blog post.

Best Answer

Related Solutions

R – Side-by-side plots with ggplot2

Any ggplots side-by-side (or n plots on a grid)

Appendix: Using Facets

Update

Rotating and spacing axis labels in ggplot2

Related Topic