geom_histogram {ggplot2} | R Documentation |
Histogram
geom_histogram(mapping=NULL, data=NULL, stat="bin", position="stack", ...)
mapping |
mapping between variables and aesthetics generated by aes |
data |
dataset used in this layer, if not specified uses plot dataset |
stat |
statistic used by this layer |
position |
position adjustment used by this layer |
... |
ignored |
geom_histogram is an alias for geom_bar + stat_bin so you will need to look at the documentation for those objects to get more information about the parameters.
This page describes geom_histogram, see layer
and qplot
for how to create a complete plot from individual components.
A layer
The following aesthetics can be used with geom_histogram. Aesthetics are mapped to variables in the data with the aes
function: geom\_histogram(\code{aes}(x = var))
x
: x position (required)
min
: minimum of interval (required)
max
: maximum of interval (required)
colour
: border colour
fill
: internal colour
min
: minimum of interval (required)
size
: size
linetype
: line type
max
: maximum of interval (required)
geom_histogram only allows you to set the width of the bins (with the binwidth parameter), not the number of bins, and it certainly does not suport the use of common heuristics to select the number of bins. In practice, you will need to use multiple bin widths to discover all the signal in the data, and having bins with meaningful widths (rather than some arbitrary fraction of the range of the data) is more interpretable.
Hadley Wickham, http://had.co.nz/
stat_bin
: for more details of the binning alogirithm
position_dodge
: for creating side-by-side barcharts
position_stack
: for more info on stacking
## Not run: # Simple examles qplot(rating, data=movies, geom="histogram") qplot(rating, data=movies, weight=votes, geom="histogram") qplot(rating, data=movies, weight=votes, geom="histogram", binwidth=1) qplot(rating, data=movies, weight=votes, geom="histogram", binwidth=0.1) # More complex m <- ggplot(movies, aes(x=rating)) m + geom_histogram() m + geom_histogram(aes(y = ..density..)) + geom_density() m + geom_histogram(binwidth=1) m + geom_histogram(binwidth=0.5) m + geom_histogram(binwidth=0.1) # Add aesthetic mappings m + geom_histogram(aes(weight = votes)) m + geom_histogram(aes(y = ..count..)) m + geom_histogram(aes(fill = ..count..)) # Change scales m + geom_histogram(aes(fill = ..count..)) + scale_fill_gradient("Count", low="green", high="red") m <- m + aes(x=votes) m + geom_histogram() + scale_x_log() m + geom_histogram() + scale_x_sqrt() # Change coordinate systems m + geom_histogram() + coord_trans(x = "sqrt") m + geom_histogram() + coord_trans(y = "sqrt") # Set aesthetics to fixed value m + geom_histogram(colour="darkgreen", fill="white") + aes(x=rating) # Use facets m <- m + facet_grid(Action ~ Comedy) m + geom_histogram() # Multiple histograms on the same graph # see ?position, ?position_fill, etc for more details ggplot(diamonds, aes(x=price)) + geom_bar() hist_cut <- ggplot(diamonds, aes(x=price, fill=cut)) hist_cut + geom_bar() # defaults to stacking hist_cut + geom_bar(position="fill") hist_cut + geom_bar(position="dodge") ## End(Not run)