Reputation: 1293
I'm analyzing a series that varies around zero. And to see where there are parts of the series with a tendency to be mostly positive or mostly negative I'm plotting a geom_smooth
. I was wondering if it is possible to have the color of the smooth line be dependent on whether or not it is above or below 0. Below is some code that produces a graph much like what I am trying to create.
set.seed(5)
r <- runif(22, max = 5, min = -5)
t <- rep(-5:5,2)
df <- data.frame(r+t,1:22)
colnames(df) <- c("x1","x2")
ggplot(df, aes(x = x2, y = x1)) + geom_hline() + geom_line() + geom_smooth()
I considered calculating the smoothed values, adding them to the df and then using a scale_color_gradient
, but I was wondering if there is a way to achieve this in ggplot
directly.
Upvotes: 11
Views: 1766
Reputation: 67778
You may use the n
argument in geom_smooth
to increase "number of points to evaluate smoother at" in order to create some more y values close to zero. Then use ggplot_build
to grab the smoothed values from the ggplot
object. These values are used in a geom_line
, which is added on top of the original plot. Last we overplot the y = 0 values with the geom_hline
.
# basic plot with a larger number of smoothed values
p <- ggplot(df, aes(x = x2, y = x1)) +
geom_line() +
geom_smooth(linetype = "blank", n = 10000)
# grab smoothed values
df2 <- ggplot_build(p)[[1]][[2]][ , c("x", "y")]
# add smoothed values with conditional color
p +
geom_line(data = df2, aes(x = x, y = y, color = y > 0)) +
geom_hline(yintercept = 0)
Upvotes: 10
Reputation: 56159
Something like this:
# loess data
res <- loess.smooth(df$x2, df$x1)
res <- data.frame(do.call(cbind, res))
res$posY <- ifelse(res$y >= 0, res$y, NA)
res$negY <- ifelse(res$y < 0, res$y, NA)
# plot
ggplot(df, aes(x = x2, y = x1)) +
geom_hline() +
geom_line() +
geom_line(data=res, aes(x = x, y = posY, col = "green")) +
geom_line(data=res, aes(x = x, y = negY, col = "red")) +
scale_color_identity()
Upvotes: 6