controlling order of points in ggplot2 in R?

Question

Suppose I'm plotting a dense scatter plot in ggplot2 in R where each point might be labeled by a different color:

df <- data.frame(x=rnorm(500))
df$y = rnorm(500)*0.1 + df$x
df$label <- c("a")
df$label[50] <- "point"
df$size <- 2
ggplot(df) + geom_point(aes(x=x, y=y, color=label, size=size))

When I do this, the scatter point labeled "point" (green) is plotted on top of the red points which have the label "a". What controls this z ordering in ggplot, i.e. what controls which point is on top of which? For example, what if I wanted all the "a" points to be on top of all the points labeled "point" (meaning they would sometimes partially or fully hide that point)? Does this depend on alphanumerical ordering of labels? I'd like to find a solution that can be translated easily to rpy2. thanks

Answer 1

ggplot2 will create plots layer-by-layer and within each layer, the plotting order is defined by the geom type. The default is to plot in the order that they appear in the data.

Where this is different, it is noted. For example

geom_line

Connect observations, ordered by x value.

and

geom_path

Connect observations in data order

---

There are also known issues regarding the ordering of factors, and it is interesting to note the response of the package author Hadley

The display of a plot should be invariant to the order of the data frame - anything else is a bug.

---

This quote in mind, a layer is drawn in the specified order, so overplotting can be an issue, especially when creating dense scatter plots. So if you want a consistent plot (and not one that relies on the order in the data frame) you need to think a bit more.

---

Create a second layer

If you want certain values to appear above other values, you can use the subset argument to create a second layer to definitely be drawn afterwards. You will need to explicitly load the plyr package so .() will work.

set.seed(1234)
df <- data.frame(x=rnorm(500))
df$y = rnorm(500)*0.1 + df$x
df$label <- c("a")
df$label[50] <- "point"
df$size <- 2
library(plyr)
ggplot(df) + geom_point(aes(x = x, y = y, color = label, size = size)) +
  geom_point(aes(x = x, y = y, color = label, size = size), 
             subset = .(label == 'point'))

Update

In ggplot2_2.0.0, the subset argument is deprecated. Use e.g. base::subset to select relevant data specified in the data argument. And no need to load plyr:

ggplot(df) +
  geom_point(aes(x = x, y = y, color = label,  size = size)) +
  geom_point(data = subset(df, label == 'point'),
             aes(x = x, y = y, color = label, size = size))

---

Or use alpha

Another approach to avoid the problem of overplotting would be to set the alpha (transparancy) of the points. This will not be as effective as the explicit second layer approach above, however, with judicious use of scale_alpha_manual you should be able to get something to work.

eg

# set alpha = 1 (no transparency) for your point(s) of interest
# and a low value otherwise
ggplot(df) + geom_point(aes(x=x, y=y, color=label, size=size,alpha = label)) + 
  scale_alpha_manual(guide='none', values = list(a = 0.2, point = 1))