How to fill geom_polygon with different colors above and below y = 0?

Question

Considering the following polygon plot:

ggplot(df, aes(x=year,y=afw)) +
  geom_polygon() +
  scale_x_continuous(\"\", expand=c(0,0), breaks=seq(1910,2010,10)         


        

Answer 1

Get the indices where the y value of two consecutive time steps have different sign. Use linear interpolation between these points to generate new x values where y is zero.

First, a smaller example to make it easier to get a feeling for the linear interpolation and which points are added to the original data:

# original data
d <- data.frame(x = 1:6,
                y = c(-1, 2, 1, 2, -1, 1))

# coerce to data.table
library(data.table)
setDT(d)

# make sure data is ordered by x
setorder(d, x)

# add a grouping variable
# only to keep track of original and interpolated points in this example
d[ , g := "orig"]

# interpolation
d2 = d[ , {
  ix = .I[c(FALSE, abs(diff(sign(d$y))) == 2)]
  if(length(ix)){
    pred_x = sapply(ix, function(i) approx(x = y[c(i-1, i)], y = x[c(i-1, i)], xout = 0)$y)
    rbindlist(.(.SD, data.table(x = pred_x, y = 0, g = "new")))} else .SD
}]

d2   
#           x  y  grp
# 1  1.000000 -1 orig
# 2  2.000000  2 orig
# 3  3.000000  1 orig
# 4  4.000000  2 orig
# 5  5.000000 -1 orig
# 6  6.000000  1 orig
# 13 1.333333  0  new
# 11 4.666667  0  new
# 12 5.500000  0  new

Plot with original and new points differentiated by color:

ggplot(data = d2, aes(x = x, y = y)) +
  geom_area(data = d2[y <= 0], fill = "red", alpha = 0.2) +
  geom_area(data = d2[y >= 0], fill = "blue", alpha = 0.2) +
  geom_point(aes(color = g), size = 4) +
  scale_color_manual(values = c("red", "black")) +
  theme_bw()

---

Apply on OP's data:

d = as.data.table(orig)
# setorder(d, year)

d2 = d[ , {
  ix = .I[c(FALSE, abs(diff(sign(d$afw))) == 2)]
  if(length(ix)){
    pred_yr = sapply(ix, function(i) approx(afw[c(i-1, i)], year[c(i-1, i)], xout = 0)$y)
    rbindlist(.(.SD, data.table(year = pred_yr, afw = 0)))} else .SD}]

ggplot(data = d2, aes(x = year, y = afw)) +
  geom_area(data = d2[afw <= 0], fill = "red") +
  geom_area(data = d2[afw >= 0], fill = "blue") +
  theme_bw()

---

In reply to @Jason Whythe's comment, the method above can be modified to account for grouped data. The interpolation is made within each group, and the plot is facetted by group:

# data grouped by 'id' 
d = data.table(
  id = rep(c("a", "b", "c"), c(6, 5, 4)),
  x = as.numeric(c(1:6, 1:5, 1:4)),
  y = c(-1, 2, 1, 2, -1, 1,
        0, -2, 0, -1, -2, 
        2, 1, -1, 1.5))

# again, this variable is just added for illustration 
d[ , g := "orig"]

d2 = d[ , {
  ix = .I[c(FALSE, abs(diff(sign(.SD$y))) == 2)]
  if(length(ix)){
    pred_x = sapply(ix, function(i) approx(x = d$y[c(i-1, i)], y = d$x[c(i-1, i)], xout = 0)$y)
    rbindlist(.(.SD, data.table(x = pred_x, y = 0, g = "new")))} else .SD
}, by = id]

ggplot(data = d2, aes(x = x, y = y)) +
  facet_wrap(~ id) +
  geom_area(data = d2[y <= 0], fill = "red", alpha = 0.2) +
  geom_area(data = d2[y >= 0], fill = "blue", alpha = 0.2) +
  geom_point(aes(color = g), size = 4) +
  scale_color_manual(values = c("red", "black")) +
  theme_bw()

---

For an alternative base solution adapted from @kohske's answer here (credits to him), see previous edits.