Line plots in ggformula. gf_path() differs from gf_line() in that points
are connected in the order in which they appear in data.
gf_freqpoly(object = NULL, gformula = NULL, data = NULL, alpha, color,
group, linetype, size, binwidth, bins, center, boundary, xlab, ylab, title,
subtitle, caption, geom = "path", stat = "bin", position = "identity",
show.legend = NA, show.help = NULL, inherit = TRUE,
environment = parent.frame(), ...)When chaining, this holds an object produced in the earlier portions of the chain. Most users can safely ignore this argument. See details and examples.
A formula with shape ~ x or y ~ x.
Faceting can be achieved by including | in the formula.
A data frame with the variables to be plotted.
Opacity (0 = invisible, 1 = opaque).
A color or a formula used for mapping color.
Used for grouping.
A linetype (numeric or "dashed", "dotted", etc.) or a formula used for mapping linetype.
A numeric size or a formula used for mapping size.
The width of the bins. The default is to use bins
bins that cover the range of the data. You should always override
this value, exploring multiple widths to find the best to illustrate the
stories in your data.
The bin width of a date variable is the number of days in each time; the bin width of a time variable is the number of seconds.
Number of bins. Overridden by binwidth. Defaults to 30
The center of one of the bins. Note that if center is above or
below the range of the data, things will be shifted by an appropriate
number of widths. To center on integers, for example, use
width = 1 and center = 0, even if 0 is outside the range
of the data. At most one of center and boundary may be
specified.
A boundary between two bins. As with center, things
are shifted when boundary is outside the range of the data. For
example, to center on integers, use width = 1 and boundary =
0.5, even if 0.5 is outside the range of the data. At most one of
center and boundary may be specified.
Label for x-axis. See also gf_labs().
Label for y-axis. See also gf_labs().
Title, sub-title, and caption for the plot.
See also gf_labs().
Title, sub-title, and caption for the plot.
See also gf_labs().
Title, sub-title, and caption for the plot.
See also gf_labs().
A character string naming the geom used to make the layer.
A character string naming the stat used to make the layer.
Either a character string naming the position function used for the layer or a position object returned from a call to a position function.
A logical indicating whether this layer should be included in
the legends. NA, the default, includes layer in the legends if any
of the attributes of the layer are mapped.
If TRUE, display some minimal help.
A logical indicating whether default attributes are inherited.
An environment in which to look for variables not found in data.
Additional arguments. Typically these are
(a) ggplot2 aesthetics to be set with attribute = value,
(b) ggplot2 aesthetics to be mapped with attribute = ~expression, or
(c) attributes of the layer as a whole, which are set with attribute = value.
a gg object
Positional aesthetics are specified using the formula in gformula.
Setting and mapping of additional attributes can be done through the
use of additional arguments.
Attributes can be set can be set using arguments of the form attribute = value or
mapped using arguments of the form attribute = ~ expression.
In formulas of the form A | B, B will be used to form facets using
facet_wrap() or facet_grid().
This provides an alternative to
gf_facet_wrap() and
gf_facet_grid() that is terser and may feel more familiar to users
of lattice.
Evaluation of the ggplot2 code occurs in the environment of gformula.
This will typically do the right thing when formulas are created on the fly, but might not
be the right thing if formulas created in one environment are used to create plots
in another.
# NOT RUN {
gf_histogram(~ Sepal.Length | Species, alpha = 0.2, data = iris, bins = 20) %>%
gf_freqpoly(~ Sepal.Length, data = iris, color = ~Species, bins = 20)
gf_freqpoly(~ Sepal.Length, color = ~Species, data = iris, bins = 20)
gf_dens(~ Sepal.Length, data = iris, color = "navy") %>%
gf_freqpoly(~ Sepal.Length, y = ~..density.., data = iris, color = "red", bins = 20)
# }
Run the code above in your browser using DataLab