# NOT RUN {
df <- data.frame(
x = runif(100),
y = runif(100),
z1 = rnorm(100),
z2 = abs(rnorm(100))
)
df_na <- data.frame(
value = seq(1, 20),
x = runif(20),
y = runif(20),
z1 = c(rep(NA, 10), rnorm(10))
)
# Default colour scale colours from light blue to dark blue
ggplot(df, aes(x, y)) +
geom_point(aes(colour = z2))
# For diverging colour scales use gradient2
ggplot(df, aes(x, y)) +
geom_point(aes(colour = z1)) +
scale_colour_gradient2()
# Use your own colour scale with gradientn
ggplot(df, aes(x, y)) +
geom_point(aes(colour = z1)) +
scale_colour_gradientn(colours = terrain.colors(10))
# Equivalent fill scales do the same job for the fill aesthetic
ggplot(faithfuld, aes(waiting, eruptions)) +
geom_raster(aes(fill = density)) +
scale_fill_gradientn(colours = terrain.colors(10))
# Adjust colour choices with low and high
ggplot(df, aes(x, y)) +
geom_point(aes(colour = z2)) +
scale_colour_gradient(low = "white", high = "black")
# Avoid red-green colour contrasts because ~10% of men have difficulty
# seeing them
# Use `na.value = NA` to hide missing values but keep the original axis range
ggplot(df_na, aes(x = value, y)) +
geom_bar(aes(fill = z1), stat = "identity") +
scale_fill_gradient(low = "yellow", high = "red", na.value = NA)
ggplot(df_na, aes(x, y)) +
geom_point(aes(colour = z1)) +
scale_colour_gradient(low = "yellow", high = "red", na.value = NA)
# }
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