position_jitternormal {ggforce} | R Documentation |
Jitter points with normally distributed random noise
Description
ggplot2::geom_jitter()
adds random noise to points using a uniform
distribution. When many points are plotted, they appear in a rectangle. This
position jitters points using a normal distribution instead, resulting in
more circular clusters.
Usage
position_jitternormal(sd_x = NULL, sd_y = NULL, seed = NA)
Arguments
sd_x , sd_y |
Standard deviation to add along the x and y axes. The
function uses If omitted, defaults to 0.15. As with |
seed |
A random seed to make the jitter reproducible.
Useful if you need to apply the same jitter twice, e.g., for a point and
a corresponding label.
The random seed is reset after jittering.
If |
Examples
# Example data
df <- data.frame(
x = sample(1:3, 1500, TRUE),
y = sample(1:3, 1500, TRUE)
)
# position_jitter results in rectangular clusters
ggplot(df, aes(x = x, y = y)) +
geom_point(position = position_jitter())
# geom_jitternormal results in more circular clusters
ggplot(df, aes(x = x, y = y)) +
geom_point(position = position_jitternormal())
# You can adjust the standard deviations along both axes
# Tighter circles
ggplot(df, aes(x = x, y = y)) +
geom_point(position = position_jitternormal(sd_x = 0.08, sd_y = 0.08))
# Oblong shapes
ggplot(df, aes(x = x, y = y)) +
geom_point(position = position_jitternormal(sd_x = 0.2, sd_y = 0.08))
# Only add random noise to one dimension
ggplot(df, aes(x = x, y = y)) +
geom_point(
position = position_jitternormal(sd_x = 0.15, sd_y = 0),
alpha = 0.1
)