Draw Histograms and Kernel Density Plots, possibly conditioned on other variables.
histogram(x, data, …)
densityplot(x, data, …)
# S3 method for formula
histogram(x,
data,
allow.multiple, outer = TRUE,
auto.key = FALSE,
aspect = "fill",
panel = lattice.getOption("panel.histogram"),
prepanel, scales, strip, groups,
xlab, xlim, ylab, ylim,
type = c("percent", "count", "density"),
nint = if (is.factor(x)) nlevels(x)
else round(log2(length(x)) + 1),
endpoints = extend.limits(range(as.numeric(x),
finite = TRUE), prop = 0.04),
breaks,
equal.widths = TRUE,
drop.unused.levels =
lattice.getOption("drop.unused.levels"),
…,
lattice.options = NULL,
default.scales = list(),
default.prepanel =
lattice.getOption("prepanel.default.histogram"),
subscripts,
subset)# S3 method for numeric
histogram(x, data = NULL, xlab, …)
# S3 method for factor
histogram(x, data = NULL, xlab, …)
# S3 method for formula
densityplot(x,
data,
allow.multiple = is.null(groups) || outer,
outer = !is.null(groups),
auto.key = FALSE,
aspect = "fill",
panel = lattice.getOption("panel.densityplot"),
prepanel, scales, strip, groups, weights,
xlab, xlim, ylab, ylim,
bw, adjust, kernel, window, width, give.Rkern,
n = 512, from, to, cut, na.rm,
drop.unused.levels =
lattice.getOption("drop.unused.levels"),
…,
lattice.options = NULL,
default.scales = list(),
default.prepanel =
lattice.getOption("prepanel.default.densityplot"),
subscripts,
subset)
# S3 method for numeric
densityplot(x, data = NULL, xlab, …)
do.breaks(endpoints, nint)
The object on which method dispatch is carried out.
For the formula
method, x
can be a formula of the form
~ x | g1 * g2 * …
, indicating that histograms or kernel
density estimates of the x
variable should be produced
conditioned on the levels of the (optional) variables g1
,
g2
, …. x
should be numeric (or possibly a factor
in the case of histogram
), and each of g1
, g2
,
… should be either factors or shingles.
As a special case, the right hand side of the formula can contain
more than one term separated by ‘+’ signs (e.g., ~ x1 +
x2 | g1 * g2
). What happens in this case is described in the
documentation for xyplot
. Note that in either form,
all the terms in the formula must have the same length after
evaluation.
For the numeric
and factor
methods, x
is the
variable whose histogram or Kernel density estimate is drawn.
Conditioning is not allowed in these cases.
For the formula
method, an optional data source (usually a
data frame) in which variables are to be evaluated (see
xyplot
for details). data
should not be
specified for the other methods, and is ignored with a warning if it
is.
A character string indicating the type of histogram that is to be
drawn. "percent"
and "count"
give relative frequency
and frequency histograms respectively, and can be misleading when
breakpoints are not equally spaced. "density"
produces a
density histogram.
type
defaults to "density"
when the breakpoints are
unequally spaced, and when breaks
is NULL
or a
function, and to "percent"
otherwise.
An integer specifying the number of histogram bins, applicable only
when breaks
is unspecified or NULL
in the call.
Ignored when the variable being plotted is a factor.
A numeric vector of length 2 indicating the range of x-values that
is to be covered by the histogram. This applies only when
breaks
is unspecified and the variable being plotted is not a
factor. In do.breaks
, this specifies the interval that is to
be divided up.
Usually a numeric vector of length (number of bins + 1) defining the
breakpoints of the bins. Note that when breakpoints are not equally
spaced, the only value of type
that makes sense is density.
When breaks
is unspecified, the value of
lattice.getOption("histogram.breaks")
is first checked. If
this value is NULL
, then the default is to use
breaks = seq_len(1 + nlevels(x)) - 0.5
when x
is a factor, and
breaks = do.breaks(endpoints, nint)
otherwise. Breakpoints calculated in such a manner are used in all
panels. If the retrieved value is not NULL
, or if
breaks
is explicitly specified, it affects the display in
each panel independently. Valid values are those accepted as the
breaks
argument in hist
. In particular, this
allows specification of breaks
as an integer giving the
number of bins (similar to nint
), as a character string
denoting a method, or as a function.
When specified explicitly, a special value of breaks
is
NULL
, in which case the number of bins is determined by
nint
and then breakpoints are chosen according to the value
of equal.widths
.
A logical flag, relevant only when breaks=NULL
. If
TRUE
, equally spaced bins will be selected, otherwise,
approximately equal area bins will be selected (typically producing
unequally spaced breakpoints).
Integer, giving the number of points at which the kernel density is
to be evaluated. Passed on as an argument to density
.
A function, called once for each panel, that uses the packet (subset
of panel variables) corresponding to the panel to create a display.
The default panel functions panel.histogram
and
panel.densityplot
are documented separately, and have
arguments that can be used to customize its output in various ways.
Such arguments can usually be directly supplied to the high-level
function.
See xyplot
.
See xyplot
.
See xyplot
.
See xyplot
.
See xyplot
.
See xyplot
.
See xyplot
. Note that the default panel function for
histogram
does not support grouped displays, whereas the one
for densityplot
does.
See xyplot
.
See xyplot
.
See xyplot
.
See xyplot
.
See xyplot
.
See xyplot
.
See xyplot
.
Fallback prepanel function. See xyplot
.
numeric vector of weights for the density
calculations, evaluated in the non-standard manner used for
groups
and terms in the formula, if any. If this is
specified, it is subsetted using subscripts
inside the panel
function to match it to the corresponding x
values.
At the time of writing, weights
do not work in conjunction
with an extended formula specification (this is not too hard to fix,
so just bug the maintainer if you need this feature).
Arguments controlling bandwidth. Passed on as arguments to
density
.
The choice of kernel. Passed on as arguments to
density
.
Logical flag, passed on as argument to density
.
This argument is made available only for ease of implementation, and
will produce an error if TRUE
.
Controls range over which density is evaluated. Passed on as
arguments to density
.
Logical flag specifying whether NA
values should be ignored.
Passed on as argument to density
, but unlike in
density
, the default is TRUE
.
Further arguments. See corresponding entry in
xyplot
for non-trivial details.
An object of class "trellis"
. The
update
method can be used to
update components of the object and the
print
method (usually called by
default) will plot it on an appropriate plotting device.
histogram
draws Conditional Histograms, and densityplot
draws Conditional Kernel Density Plots. The default panel function
uses the density
function to compute the density
estimate, and all arguments accepted by density
can be
specified in the call to densityplot
to control the output.
See documentation of density
for details.
These and all other high level Trellis functions have several
arguments in common. These are extensively documented only in the
help page for xyplot
, which should be consulted to learn more
detailed usage.
do.breaks
is an utility function that calculates breakpoints
given an interval and the number of pieces to break it into.
Sarkar, Deepayan (2008) Lattice: Multivariate Data Visualization with R, Springer. http://lmdvr.r-forge.r-project.org/
xyplot
,
panel.histogram
,
density
,
panel.densityplot
,
panel.mathdensity
,
Lattice
# NOT RUN {
require(stats)
histogram( ~ height | voice.part, data = singer, nint = 17,
endpoints = c(59.5, 76.5), layout = c(2,4), aspect = 1,
xlab = "Height (inches)")
histogram( ~ height | voice.part, data = singer,
xlab = "Height (inches)", type = "density",
panel = function(x, ...) {
panel.histogram(x, ...)
panel.mathdensity(dmath = dnorm, col = "black",
args = list(mean=mean(x),sd=sd(x)))
} )
densityplot( ~ height | voice.part, data = singer, layout = c(2, 4),
xlab = "Height (inches)", bw = 5)
# }
Run the code above in your browser using DataLab