I am trying to plot a 5 dimensional plot in R. I am currently using the rgl
package to plot my data in 4 dimensions, using 3 variables as the x,y,z, coordinates, an
Here is a ggplot2
option. I usually shy away from 3D plots as they are hard to interpret properly. I also almost never put in 5 continuous variables in the same plot as I have here...
ggplot(df, aes(x=var1, y=var2, fill=var3, color=var4, size=var5^2)) +
geom_point(shape=21) +
scale_color_gradient(low="red", high="green") +
scale_size_continuous(range=c(1,12))
While this is a bit messy, you can actually reasonably read all 5 dimensions for most points.
A better approach to multi-dimensional plotting opens up if some of your variables are categorical. If all your variables are continuous, you can turn some of them to categorical with cut
and then use facet_wrap
or facet_grid
to plot those.
For example, here I break up var3
and var4
into quintiles and use facet_grid
on them. Note that I also keep the color aesthetics as well to highlight that most of the time turning a continuous variable to categorical in high dimensional plots is good enough to get the key points across (here you'll notice that the fill and border colors are pretty uniform within any given grid cell):
df$var4.cat <- cut(df$var4, quantile(df$var4, (0:5)/5), include.lowest=T)
df$var3.cat <- cut(df$var3, quantile(df$var3, (0:5)/5), include.lowest=T)
ggplot(df, aes(x=var1, y=var2, fill=var3, color=var4, size=var5^2)) +
geom_point(shape=21) +
scale_color_gradient(low="red", high="green") +
scale_size_continuous(range=c(1,12)) +
facet_grid(var3.cat ~ var4.cat)