How to control ylim for a faceted plot with different scales in ggplot2?

In the following example, how do I set separate ylims for each of my facets?

qplot(x, value,  data=df, geom=c("smooth")) + facet_grid(variable ~ ., scale="free_y")

In each of the facets, the y-axis takes a different rang开发者_开发百科e of values and I would like to different ylims for each of the facets.

The defaults ylims are too long for the trend that I want to see.

This was brought up on the ggplot2 mailing list a short while ago. What you are asking for is currently not possible but I think it is in progress.

As far as I know this has not been implemented in ggplot2, yet. However a workaround - that will give you ylims that exceed what ggplot provides automatically - is to add "artificial data". To reduce the ylims simply remove the data you don't want plot (see at the and for an example).

Here is an example:

Let's just set up some dummy data that you want to plot

df <- data.frame(x=rep(seq(1,2,.1),4),f1=factor(rep(c("a","b"),each=22)),f2=factor(rep(c("x","y"),22)))
df <- within(df,y <- x^2)

Which we could plot using line graphs

p <- ggplot(df,aes(x,y))+geom_line()+facet_grid(f1~f2,scales="free_y")
print(p)

Assume we want to let y start at -10 in first row and 0 in the second row, so we add a point at (0,-10) to the upper left plot and at (0,0) ot the lower left plot:

ylim <- data.frame(x=rep(0,2),y=c(-10,0),f1=factor(c("a","b")),f2=factor(c("x","y")))
dfy <- rbind(df,ylim)

Now by limiting the x-scale between 1 and 2 those added points are not plotted (a warning is given):

p <- ggplot(dfy,aes(x,y))+geom_line()+facet_grid(f1~f2,scales="free_y")+xlim(c(1,2))
print(p)

Same would work for extending the margin above by adding points with higher y values at x values that lie outside the range of xlim.

This will not work if you want to reduce the ylim, in which case subsetting your data would be a solution, for example to limit the upper row between -10 and 1.5 you could use:

p <- ggplot(dfy,aes(x,y))+geom_line(subset=.(y < 1.5 | f1 != "a"))+facet_grid(f1~f2,scales="free_y")+xlim(c(1,2))
print(p)

There are actually two packages that solve that problem now: https://github.com/zeehio/facetscales, and https://cran.r-project.org/package=ggh4x. I would recommend using ggh4x because it has very useful tools, such as facet grid multiple layers (having 2 variables defining the rows or columns), scaling the x and y-axis as you wish in each facet, and also having multiple fill and colour scales. For your problems the solution would be like this:

library(ggh4x)

scales <- list(
  # Here you have to specify all the scales, one for each facet row in your case
  scale_y_continuous(limits = c(2,10),
  scale_y_continuous(breaks = c(3, 4))
)
qplot(x, value,  data=df, geom=c("smooth")) +
 facet_grid(variable ~ ., scale="free_y") +
 facetted_pos_scales(y = scales)

I have one example of function facet_wrap

ggplot(mpg, aes(displ, hwy)) +
  geom_point() +
  facet_wrap(vars(class), scales = "free", 
             nrow=2,ncol=4)

Above code generates plot as: my level too low to upload an image, click here to see plot