On 6/7/2011 8:08 AM, wwreith wrote:
I am learning ggplot2 commands and I have figured out how to create
histograms and density curves but I am not sure how to add a density curve
on top of a histogram.
Here are the two graphs that I created.
## Histogram
t<-rnorm(500)
w<-qplot(t, main="Normal Random Sample", fill=I("blue"), colour=I("black"),
geom="histogram")
w
##Density Curve
t<-rnorm(500)
r<-qplot(t, main="Normal Random Sample", colour=I("black"), geom="density",
adjust=4)
r
# First, ggplot2 works with data.frame's as its input
DF <- data.frame(t=rnorm(500))
# Convert the two graphs from gplot to ggplot syntax
w <- ggplot(DF, aes(x=t)) +
geom_histogram(fill="blue", colour="black") +
opts(title="Normal Random Sample")
r <- ggplot(DF, aes(x=t)) +
geom_density(colour="black", adjust=4) +
opts(title="Normal Random Sample")
# Now with the layer specifications, it is easy to combine
ggplot(DF, aes(x=t)) +
geom_histogram(fill="blue", colour="black") +
geom_density(colour="black", adjust=4) +
opts(title="Normal Random Sample")
# That was probably not what you want since the histogram is in
# counts and the density curve is in density. Put them both on the
# same scale (density)
ggplot(DF, aes(x=t)) +
geom_histogram(aes(y=..density..), fill="blue", colour="black")+
geom_density(colour="black", adjust=4) +
opts(title="Normal Random Sample")
# If you want it on the count scale, that is trickier and requires
# knowing (setting) the binwidth and keeping that value in sync in
# two places.
# In this example, the binwidth is 0.2 (set in geom_histogram and also
# used in the aes of geom_density).
ggplot(DF, aes(x=t)) +
geom_histogram(fill="blue", colour="black", binwidth=0.2) +
geom_density(aes(y=0.2*..count..), colour="black", adjust=4) +
opts(title="Normal Random Sample")
--
Brian S. Diggs, PhD
Senior Research Associate, Department of Surgery
Oregon Health & Science University
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