# viridis is the default colour/fill scale for ordered factors
set.seed(596)
dsamp <- diamonds[sample(nrow(diamonds), 1000), ]
ggplot(dsamp, aes(carat, price)) +
geom_point(aes(colour = clarity))
# Use viridis_d with discrete data
txsamp <- subset(txhousing, city %in%
c("Houston", "Fort Worth", "San Antonio", "Dallas", "Austin"))
(d <- ggplot(data = txsamp, aes(x = sales, y = median)) +
geom_point(aes(colour = city)))
d + scale_colour_viridis_d()
# Change scale label
d + scale_colour_viridis_d("City\nCenter")
# Select palette to use, see ?scales::pal_viridis for more details
d + scale_colour_viridis_d(option = "plasma")
d + scale_colour_viridis_d(option = "inferno")
# scale_fill_viridis_d works just the same as
# scale_colour_viridis_d but for fill colours
p <- ggplot(txsamp, aes(x = median, fill = city)) +
geom_histogram(position = "dodge", binwidth = 15000)
p + scale_fill_viridis_d()
# the order of colour can be reversed
p + scale_fill_viridis_d(direction = -1)
# Use viridis_c with continuous data
(v <- ggplot(faithfuld) +
geom_tile(aes(waiting, eruptions, fill = density)))
v + scale_fill_viridis_c()
v + scale_fill_viridis_c(option = "plasma")
# Use viridis_b to bin continuous data before mapping
v + scale_fill_viridis_b()
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