1d kernel density estimate.

Usage

stat_density(mapping = NULL, data = NULL, geom = "area", position = "stack", adjust = 1, 
  kernel = "gaussian", trim = FALSE, na.rm = FALSE, ...)

Arguments

adjust
see density for details
kernel
kernel used for density estimation, see density for details
trim
if TRUE, the default, densities are trimmed to the actual range of the data. If FALSE, they are extended by the default 3 bandwidths (as specified by the cut parameter to density)
na.rm
If FALSE (the default), removes missing values with a warning. If TRUE silently removes missing values.
mapping
The aesthetic mapping, usually constructed with aes or aes_string. Only needs to be set at the layer level if you are overriding the plot defaults.
data
A layer specific dataset - only needed if you want to override the plot defaults.
geom
The geometric object to use display the data
position
The position adjustment to use for overlappling points on this layer
...
other arguments passed on to layer. This can include aesthetics whose values you want to set, not map. See layer for more details.

Value

data.frame with additional columns: densitydensity estimate countdensity * number of points - useful for stacked density plots scaleddensity estimate, scaled to maximum of 1

Description

1d kernel density estimate.

Aesthetics

stat_density understands the following aesthetics (required aesthetics are in bold):

  • x
  • fill
  • y

Examples

m <- ggplot(movies, aes(x = rating)) m + geom_density()

# Adjust parameters m + geom_density(kernel = "rectangular")

m + geom_density(kernel = "biweight")

m + geom_density(kernel = "epanechnikov")

m + geom_density(adjust=1/5) # Very rough

m + geom_density(adjust=5) # Very smooth

# Adjust aesthetics m + geom_density(aes(fill=factor(Drama)), size=2)

# Scale so peaks have same height: m + geom_density(aes(fill=factor(Drama), y = ..scaled..), size=2)

m + geom_density(colour="darkgreen", size=2)

m + geom_density(colour="darkgreen", size=2, fill=NA)

m + geom_density(colour="darkgreen", size=2, fill="green")

# Change scales (m <- ggplot(movies, aes(x=votes)) + geom_density(trim = TRUE))

m + scale_x_log10()

m + coord_trans(x="log10")

m + scale_x_log10() + coord_trans(x="log10")

# Also useful with m + stat_bin()
stat_bin: binwidth defaulted to range/30. Use 'binwidth = x' to adjust this.

# Make a volcano plot ggplot(diamonds, aes(x = price)) + stat_density(aes(ymax = ..density.., ymin = -..density..), fill = "grey50", colour = "grey50", geom = "ribbon", position = "identity") + facet_grid(. ~ cut) + coord_flip()

# Stacked density plots # If you want to create a stacked density plot, you need to use # the 'count' (density * n) variable instead of the default density # Loses marginal densities qplot(rating, ..density.., data=movies, geom="density", fill=mpaa, position="stack")

# Preserves marginal densities qplot(rating, ..count.., data=movies, geom="density", fill=mpaa, position="stack")

# You can use position="fill" to produce a conditional density estimate qplot(rating, ..count.., data=movies, geom="density", fill=mpaa, position="fill")

# Need to be careful with weighted data m <- ggplot(movies, aes(x=rating, weight=votes)) m + geom_histogram(aes(y = ..count..)) + geom_density(fill=NA)
stat_bin: binwidth defaulted to range/30. Use 'binwidth = x' to adjust this. Warning message: sum(weights) != 1 -- will not get true density

m <- ggplot(movies, aes(x=rating, weight=votes/sum(votes))) m + geom_histogram(aes(y=..density..)) + geom_density(fill=NA, colour="black")
stat_bin: binwidth defaulted to range/30. Use 'binwidth = x' to adjust this.

library(plyr) # to access round_any movies$decade <- round_any(movies$year, 10) m <- ggplot(movies, aes(x=rating, colour=decade, group=decade)) m + geom_density(fill=NA)

m + geom_density(fill=NA) + aes(y = ..count..)

# Use qplot instead qplot(length, data=movies, geom="density", weight=rating)
Warning message: sum(weights) != 1 -- will not get true density

qplot(length, data=movies, geom="density", weight=rating/sum(rating))

See also

stat_bin for the histogram