Different legends and fill colours for facetted ggplot?
Asked Answered
S

5

20

Sorry for not included any example data for my problem. I couldn’t find a way to easily produce an example shape file. Hopefully, experienced users of ggplot can see what I’d like to do from the description below.

I’ve got:

  • A data.frame X with information about sample plots (plotid, var1, var2, var3, var4, …)

  • A polygon shapefile Y with spatial information for the sample plots

Importation of the shapefile Y (with maptools) and fortifying as data.frame Z (ggplot2) works fine. melting X to X_melted works equally fine. merge-ing Z and X_melted to mapdf works as well.

That means that now we have a data.frame in long form with spatial information and var1, var2, var3, …

Now I want to plot this data frame like this:

pl1 <- ggplot(mapdf,aes(long,lat),group=group)
pl1 <- pl1 + geom_polygon(aes(group=group,fill=value),colour="black")
pl1 <- pl1 + facet_grid(variable ~ .)
pl1 <- pl1 + coord_equal(ratio = 1)
pl1

The result is a nice plot with one panel for each variable. The maps of the panels are identical, but fill colour varies with the values of the variables. Up to now, everything works like a charm… with one problem:

The variables have different min and max values. For example var1 goes from 0 to 5, var2 from 0 to 400, var3 from 5 to 10, etc. In that example, the legend for the fill colour goes from 0 to 400. var2 is nicely drawn, but var1 and var3 are basically in the same colour.

Is there a way I could use a different legend for each panel of the facet? Or is this simply not (yet) possible with facet_wrap or facet_grid in ggplot?

I could make individual plots for each variable and join them with viewports, but there a plenty of variables and this would be a lot of work.

Or is there maybe another package or method I could use to accomplish what I’d like to do?

And help would be very much appreciated. :)

Edit: With the help of the ggplot2-package description, I constructed an example that illustrates my problem:

ids <- factor(c("1.1", "2.1", "1.2", "2.2", "1.3", "2.3"))
values <- data.frame(
id = ids,
val1 = cumsum(runif(6, max = 0.5)),
val2 = cumsum(runif(6, max = 50))
)
positions <- data.frame(
id = rep(ids, each = 4),
x = c(2, 1, 1.1, 2.2, 1, 0, 0.3, 1.1, 2.2, 1.1, 1.2, 2.5, 1.1, 0.3,
0.5, 1.2, 2.5, 1.2, 1.3, 2.7, 1.2, 0.5, 0.6, 1.3),
y = c(-0.5, 0, 1, 0.5, 0, 0.5, 1.5, 1, 0.5, 1, 2.1, 1.7, 1, 1.5,
2.2, 2.1, 1.7, 2.1, 3.2, 2.8, 2.1, 2.2, 3.3, 3.2)
)

values <- melt(values)
datapoly <- merge(values, positions, by=c("id"))

p <- ggplot(datapoly, aes(x=x, y=y)) + geom_polygon(aes(fill=value, group=id),colour="black")
p <- p + facet_wrap(~ variable)
p

The panel on the right illustrates different values for var2 on the map. On the panel on the left however, all polygons have the same colour. This is logical, because only one colour gradient is used for all panels. Could I use a different colour gradient for each panel?

Spiro answered 27/9, 2010 at 14:55 Comment(0)
F
16

Currently there can be only one scale per plot (for everything except x and y).

Feathers answered 28/9, 2010 at 1:32 Comment(2)
Ok, thanks for the answer. Will this feature maybe be implemented anytime soon? ;)Spiro
It's extremely unlikely, because it's easy to work around by drawing separate plots.Feathers
N
5

Revisiting this question more than 10 years later, the excellent ggnewscale package solves the problem of having multiple colour scales. Caveat is that you'd need two seperate layers for your facet data, so you'd have to break it up a bit. The order in which new scales are added to the plot matters, so I recommend the order 'layer - scale - new_scale - layer - scale'. Subsequent new scales should repeat the 'new_scale - layer - scale' pattern.

library(ggplot2)
library(ggnewscale)

ids <- factor(c("1.1", "2.1", "1.2", "2.2", "1.3", "2.3"))
values <- data.frame(
  id = ids,
  val1 = cumsum(runif(6, max = 0.5)),
  val2 = cumsum(runif(6, max = 50))
)
positions <- data.frame(
  id = rep(ids, each = 4),
  x = c(2, 1, 1.1, 2.2, 1, 0, 0.3, 1.1, 2.2, 1.1, 1.2, 2.5, 1.1, 0.3,
        0.5, 1.2, 2.5, 1.2, 1.3, 2.7, 1.2, 0.5, 0.6, 1.3),
  y = c(-0.5, 0, 1, 0.5, 0, 0.5, 1.5, 1, 0.5, 1, 2.1, 1.7, 1, 1.5,
        2.2, 2.1, 1.7, 2.1, 3.2, 2.8, 2.1, 2.2, 3.3, 3.2)
)

values <- reshape2::melt(values)
#> Using id as id variables
datapoly <- merge(values, positions, by=c("id"))

ggplot(datapoly, aes(x=x, y=y)) + 
  geom_polygon(aes(fill=value, group=id),
               data = ~ subset(., variable == "val1"),
               colour="black") +
  scale_fill_distiller(palette = "Reds") +
  new_scale_fill() +
  geom_polygon(aes(fill=value, group=id),
               data = ~ subset(., variable == "val2"),
               colour="black") +
  scale_fill_distiller(palette = "Greens") +
  facet_wrap(~ variable)

Created on 2021-02-12 by the reprex package (v1.0.0)

Nonprofit answered 12/2, 2021 at 15:39 Comment(0)
M
4

With grid goodness

align.plots <- function(..., vertical=TRUE){
#http://ggextra.googlecode.com/svn/trunk/R/align.r
  dots <- list(...)
  dots <- lapply(dots, ggplotGrob)
  ytitles <- lapply(dots, function(.g) editGrob(getGrob(.g,"axis.title.y.text",grep=TRUE), vp=NULL))
  ylabels <- lapply(dots, function(.g) editGrob(getGrob(.g,"axis.text.y.text",grep=TRUE), vp=NULL))
  legends <- lapply(dots, function(.g) if(!is.null(.g$children$legends))
                    editGrob(.g$children$legends, vp=NULL) else ggplot2:::.zeroGrob)

  gl <- grid.layout(nrow=length(dots))
  vp <- viewport(layout=gl)
  pushViewport(vp)
  widths.left <- mapply(`+`, e1=lapply(ytitles, grobWidth),
                        e2= lapply(ylabels, grobWidth), SIMPLIFY=F)
  widths.right <- lapply(legends, function(g) grobWidth(g) + if(is.zero(g)) unit(0, "lines") else unit(0.5, "lines")) # safe margin recently added to ggplot2
  widths.left.max <- max(do.call(unit.c, widths.left))
  widths.right.max <- max(do.call(unit.c, widths.right))

  for(ii in seq_along(dots)){
    pushViewport(viewport(layout.pos.row=ii))
    pushViewport(viewport(x=unit(0, "npc") + widths.left.max - widths.left[[ii]],
                          width=unit(1, "npc") - widths.left.max + widths.left[[ii]] -
                                                 widths.right.max + widths.right[[ii]],
                          just="left"))
    grid.draw(dots[[ii]])
  upViewport(2)
  }
}



p <- ggplot(datapoly[datapoly$variable=="val1",], aes(x=x, y=y)) + geom_polygon(aes(fill=value, group=id),colour="black")
p1 <- ggplot(datapoly[datapoly$variable=="val2",], aes(x=x, y=y)) + geom_polygon(aes(fill=value, group=id),colour="black")
align.plots( p,p1)
Multilingual answered 28/9, 2010 at 2:19 Comment(2)
Hmmm, I just noticed that for that solution, you'd still need a separate plot for each variable. Maybe this could be accomplished with a loop. Any ideas if lattice or base could accomplish what I want without loops?Spiro
It seems to be outdatedFlossieflossy
C
2

At the risk of stating the obvious, it seems like you should be coloring by percents instead of raw values. Then your transformed values and your legend go from 0 to 1.

Cerebral answered 27/9, 2010 at 20:14 Comment(1)
Using percents could be a solution, but some information would obviously be lost. Imagine for example var1 = temperature (ranging from 15 to 20 degrees) and var2 = rel. humidity (ranging from 50 to 80 %). Percent values wouldn't be very clear for temperature and quite confusing for rel. humidity (percent of percent). ;)Spiro
T
1

Perhaps a little unorthodox, but you could try factoring your "value". For example:

p <- ggplot(datapoly, aes(x=x, y=y)) + geom_polygon(aes(fill=factor(value), group=id),colour="black")
p <- p + facet_wrap(~ variable)
p

ggplot2 uses factors to create legends. So if you could add a column that takes "value" and breaks it into factored ranges, you could replace "value" with the ranges.

Create a column, like "f":

    id variable        value   x    y f
1  1.1     val1   0.09838607 2.0 -0.5 0.09-0.13
2  1.1     val1   0.09838607 1.0  0.0 0.09-0.13
3  1.1     val1   0.09838607 1.1  1.0 0.09-0.13
4  1.1     val1   0.09838607 2.2  0.5 0.09-0.13
25 2.1     val1   0.13121347 1.0  0.0 0.13-0.20

...

Then use:

p <- ggplot(datapoly, aes(x=x, y=y)) + geom_polygon(aes(fill=f, group=id),colour="black")
p <- p + facet_wrap(~ variable)
p

You'd have to specify the categories that you want, which could be time consuming. But at least the graph would come out how you want it to. Basically, you'd be recoding the data into another column. Here are some examples:

http://www.statmethods.net/management/variables.html

Tacky answered 27/9, 2010 at 16:45 Comment(4)
Thanks for your answer. Setting space and scales free doesn't help, because it only changes x and y-axis, but not colour coding. I edited my question, which now has an example.Spiro
And, I don't believe it is possible to have more than one legend in a facet_grid.Tacky
Thanks again for your answer. Recoding values into factored ranges would indeed have different colours as a result. However, I'd like to plot 8 different variables with a wide range of values, and working with factors would result in a very huge number of factors. Additionally, the graph would be very 'chaotic', because "low values=colour1, high values=colour2" wouldn't work anymore.Spiro
Perhaps it would be best to subset them and plot them separately thenTacky

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