| gghistogram {ggplot} | R Documentation |
Draw a histogram
gghistogram(plot = .PLOT, aesthetics=list(), scale="prob", ..., data=NULL)
plot |
the plot object to modify |
aesthetics |
named list of aesthetic mappings, see details for more information |
scale |
other options, see details for more information |
... |
data source, if not specified the plot default will be used |
data |
Aesthetic mappings that this grob function understands:
Conceptually, the histogram is one of the most complicated
of the grob functions, becuase it takes a 1D data set and makes
it two dimensional. This necessitates an extra step, the pre_histogram
function which bins the data and returns the bins with their counts.
This data is then used my grob_histogram
to plot the points.
x:x position (required)
weight: observation weights
These can be specified in the plot defaults (see ggplot) or
in the aesthetics argument. If you want to modify the position
of the points or any axis options, you will need to add a position scale to
the plot. These functions start with ps, eg.
pscontinuous or pscategorical
Other options:
breaks:breaks argument passed to hist
scale:scale argument passed to hist
ggrect
Hadley Wickham <h.wickham@gmail.com>
m <- ggplot(movies, aesthetics=list(x=rating))
gghistogram(m)
gghistogram(m, breaks=100)
qplot(length, data=movies, type="histogram")
qplot(log(length), data=movies, type="histogram")
m <- ggplot(movies, Action ~ Comedy, aesthetics=list(x=rating), margins=TRUE)
gghistogram(m)
gghistogram(m, scale="freq")
gghistogram(m, colour="darkgreen", fill="white")
qplot(rating, data=movies, type="histogram")
qplot(rating, weight=votes, data=movies, type="histogram")
qplot(rating, weight=votes, data=movies, type=c("histogram", "density"))