Reputation: 43
Is there a way to plot a smoothed curve (x=var1, y=var2) and color it with respect to a third continuous variable (z=var3)? I am using the following code:
library(ggplot2)
x = runif(100,-20,20)
y = 2*x+x^2+rnorm(100,0,50)
z = 0.5*x+rnorm(100,0,2)
df = data.frame(x=x,y=y,z=z)
ggplot(data=df,aes(x=x,y=y))+geom_smooth(method='loess', aes(color=z),se=F)
However, the smoothed line is still solid blue.
Using the internal variable "..y.." instead of var3 colors the line with respect to var2.
ggplot(data=df,aes(x=x,y=y))+geom_smooth(method='loess', aes(color=..y..),se=F)
Is there another internal variable to call in order to color the line with respect to var3?
I am able to generate the desired plot with geom_line
, but I would like to have it smoothed instead.
Upvotes: 3
Views: 1269
Reputation: 8275
You're on the right track using geom_line
, you just need to use it on pre-smoothed data. Take your dataframe as above, then:
df$predict <- predict(loess(y~x, data = df))
ggplot(df, aes(x = x,y = predict)) +
geom_line(aes(colour = z))
This can generate ugly results if your x
has big gaps; they'll come out as flat segments between points. There are workarounds for that by feeding newdata=
to predict()
and storing it in a second dataframe, but then you need to also recalculate z
for those new x
values.
Upvotes: 4