Grouping
Similarly, we can group histograms of a variable, just like we did with bar charts earlier. To do this, we use the facet_grid() function, which divides the plot to make the graphs easier to interpret. In facet_grid(), we simply specify in a formula (x ~ y) how the variable should be divided on the x-axis or y-axis. Here, we want to divide by gender on the y-axis.
histGroup <- ggplot(
pss,
aes(
agea,
fill = gndr
)
) +
geom_histogram(
aes(y = ..density..),
alpha = 0.2
) +
geom_density(alpha = 0.2) +
facet_grid(
.~ gndr
) +
scale_fill_manual(
name = "Gender",
labels = c(
"Female",
"Male"
),
values = beyonce_palette(72)
) +
labs(
x = "Age in years",
y = "Density",
title = "Histogram of Age"
)
histGroup## Warning: The dot-dot notation (`..density..`) was deprecated in ggplot2 3.4.0.
## ℹ Please use `after_stat(density)` instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.## Warning: Removed 157 rows containing non-finite outside the scale range
## (`stat_bin()`).## Warning: Removed 157 rows containing non-finite outside the scale range
## (`stat_density()`).
Adjustments
Next, we will modify the labels above the histograms and remove the legend (to avoid duplication!).
histGroup <- ggplot(
pss,
aes(
agea,
fill = gndr
)
) +
geom_histogram(
aes(y = ..density..),
alpha = 0.2,
bins = 30,
position = "identity"
) +
geom_density(alpha = 0.2) +
facet_grid(
.~ gndr
) +
scale_fill_manual(values = beyonce_palette(72)) +
labs(
x = "Age in years",
y = "Density",
title = "Histogram of Age"
) +
theme(legend.position = "none")
histGroup## Warning: Removed 157 rows containing non-finite outside the scale range
## (`stat_bin()`).## Warning: Removed 157 rows containing non-finite outside the scale range
## (`stat_density()`).
Alternatively, you can also create a Ridgeline plot. More on that on the next page!