ggplot2 make missing value in geom_tile not blank

Question

In the geom_tile() layer in the ggplot2 data visualization package for R, when a cell contains no data it is not drawn. E.g. http://docs.ggplot2.org/current/geo

Answer 1

This answer may perhaps be a bit too 'cute', but could one solution be to simply change the background color of your plot to be the minimum color in your scale? For instance:

+ opts(plot.background = theme_rect(colour = "blue")

If your plot has a more complex structure and this ends up making the background blue in areas where you don't want that to happen, you could plot a geom_rect layer first that extends to through the ranges of your data only.

Answer 2

For posterity, here is the right solution compatible with ggplot2 version 1.9.3

+ theme(panel.background=element_rect(fill="blue", colour="blue")

• In joran's answer, the plot.background is the whole plot including the title and legend etc. The panel.background is the area where the data appears.

• In the latest version of ggplot2, opts has been replaced with theme and theme_rect has been replaced with element_rect.

• In specifying element_rect, color is the boundary of the rectangle while fill is the interior of the rectangle.

I had originally used,

+ geom_rect(aes(xmin=-Inf, xmax=Inf, ymin=-Inf, ymax=Inf), fill="blue")

but when adding geom_raster rather than geom_tile over the the background and generate pdf output, pdf viewers had a very hard time rendering the plot, using substantially more cpu cycles and memory.

Answer 3

This issue can also be fixed by an option in scale_fill_continuous

scale_fill_continuous(na.value = 'salmon')

Edit below:

This only fills in the explicitly (i.e. values which are NA) missing values. (It may have worked differently in previous versions of ggplot, I'm too lazy to check)

See the following code for an example:

library(tidyverse)
Data <- expand.grid(x = 1:5,y=1:5) %>%
  mutate(Value = rnorm(25))

Data %>%
  filter(y!=3) %>%
ggplot(aes(x=x,y=y,fill=Value))+
  geom_tile()+
  scale_fill_continuous(na.value = 'salmon')

Data %>%
  mutate(Value=ifelse(1:n() %in% sample(1:n(),22),NA,Value)) %>%
  ggplot(aes(x=x,y=y,fill=Value))+
  geom_tile()+
  scale_fill_continuous(na.value = 'salmon')

An easy fix for this is to use the complete function to make the missing values explicit.

Data %>%
  filter(1:n() %in% sample(1:n(),22)) %>%
  complete(x,y) %>%
  ggplot(aes(x=x,y=y,fill=Value))+
  geom_tile()+
  scale_fill_continuous(na.value = 'salmon')

In some cases the expand function may be more useful than the complete function.

Answer 4

If your data is a grid-like data, how about adding another geom_tile() for NA by subset()?

# Generate data
pp <- function (n, r = 4) {
  x    <- seq(-r*pi, r*pi, len = n)
  df   <- expand.grid(x = x, y = x)
  df$r <- sqrt(df$x^2 + df$y^2)
  df$z <- cos(df$r^2)*exp(-df$r/6)
  df
}
pp20 <- pp(20)[sample(20*20, size = 200),]

df_grid  <- expand.grid(x = unique(pp20$x), y = unique(pp20$x))
df_merge <- merge(pp20, df_grid, by = c("x", "y"), all = TRUE)

# Missing values
ggplot(df_merge, aes(x = x, y = y)) +
  geom_tile(data = subset(df_merge, !is.na(z)), aes(fill = z)) +
  geom_tile(data = subset(df_merge,  is.na(z)), aes(colour = NA),
    linetype = 0, fill = "pink", alpha = 0.5)