One approach is to use the ggpattern
package written by Mike FC (no affiliation):
library(ggplot2)
#remotes::install_github("coolbutuseless/ggpattern")
library(ggpattern)
ggplot(data = df, aes(x = Class, fill = StudyTime, pattern = Nerd)) +
geom_bar_pattern(position = position_dodge(preserve = "single"),
color = "black",
pattern_fill = "black",
pattern_angle = 45,
pattern_density = 0.1,
pattern_spacing = 0.025,
pattern_key_scale_factor = 0.6) +
scale_fill_manual(values = colorRampPalette(c("#0066CC","#FFFFFF","#FF8C00"))(4)) +
scale_pattern_manual(values = c(Nerd = "stripe", NotNerd = "none")) +
labs(x = "Class", y = "Number of Students", pattern = "Nerd?") +
guides(pattern = guide_legend(override.aes = list(fill = "white")),
fill = guide_legend(override.aes = list(pattern = "none")))
The package appears to support a number of common geometries. Here is an example of using geom_tile
to combine a continuous variable with a categorical variable:
set.seed(40)
df2 <- data.frame(Row = rep(1:9,times=9), Column = rep(1:9,each=9),
Evaporation = runif(81,50,100),
TreeCover = sample(c("Yes", "No"), 81, prob = c(0.3,0.7), replace = TRUE))
ggplot(data=df2, aes(x=as.factor(Row), y=as.factor(Column),
pattern = TreeCover, fill= Evaporation)) +
geom_tile_pattern(pattern_color = NA,
pattern_fill = "black",
pattern_angle = 45,
pattern_density = 0.5,
pattern_spacing = 0.025,
pattern_key_scale_factor = 1) +
scale_pattern_manual(values = c(Yes = "circle", No = "none")) +
scale_fill_gradient(low="#0066CC", high="#FF8C00") +
coord_equal() +
labs(x = "Row",y = "Column") +
guides(pattern = guide_legend(override.aes = list(fill = "white")))