These stats merely tell ggplot2::ggplot() which factor of an ordination to pull data from for a plot layer. They are invoked internally by the various geom_*_*() layers.

stat_rows(
  mapping = NULL,
  data = data,
  geom = "point",
  position = "identity",
  subset = NULL,
  elements = "all",
  ...,
  show.legend = NA,
  inherit.aes = TRUE
)

stat_cols(
  mapping = NULL,
  data = data,
  geom = "axis",
  position = "identity",
  subset = NULL,
  elements = "all",
  ...,
  show.legend = NA,
  inherit.aes = TRUE
)

Arguments

mapping

Set of aesthetic mappings created by aes(). If specified and inherit.aes = TRUE (the default), it is combined with the default mapping at the top level of the plot. You must supply mapping if there is no plot mapping.

data

The data to be displayed in this layer. There are three options:

If NULL, the default, the data is inherited from the plot data as specified in the call to ggplot().

A data.frame, or other object, will override the plot data. All objects will be fortified to produce a data frame. See fortify() for which variables will be created.

A function will be called with a single argument, the plot data. The return value must be a data.frame, and will be used as the layer data. A function can be created from a formula (e.g. ~ head(.x, 10)).

geom

The geometric object to use to display the data, either as a ggproto Geom subclass or as a string naming the geom stripped of the geom_ prefix (e.g. "point" rather than "geom_point")

position

Position adjustment, either as a string naming the adjustment (e.g. "jitter" to use position_jitter), or the result of a call to a position adjustment function. Use the latter if you need to change the settings of the adjustment.

subset

An integer, logical, or character vector indicating a subset of rows or columns for which to render graphical elements. NB: Internally, the subset will be taken from the rows of the fortified 'tbl_ord' comprising rows from only one of the matrix factors. It is still possible to pass a formula to the data parameter, but it will act on the fortified data before it has been restricted to one matrix factor.

elements

Character vector; which elements of each factor for which to render graphical elements. One of "all" (the default), "active", or any supplementary element type defined by the specific class methods (e.g. "score" for 'factanal', 'lda_ord', and 'cancord_ord' and "intraset" and "interset" for 'cancor_ord').

...

Additional arguments passed to ggplot2::layer().

show.legend

logical. Should this layer be included in the legends? NA, the default, includes if any aesthetics are mapped. FALSE never includes, and TRUE always includes. It can also be a named logical vector to finely select the aesthetics to display.

inherit.aes

If FALSE, overrides the default aesthetics, rather than combining with them. This is most useful for helper functions that define both data and aesthetics and shouldn't inherit behaviour from the default plot specification, e.g. borders().

Value

A ggproto layer.

Biplot layers

ggbiplot() uses ggplot2::fortify() internally to produce a single data frame with a .matrix column distinguishing the subjects ("rows") and variables ("cols"). The stat layers stat_rows() and stat_cols() simply filter the data frame to one of these two.

The geom layers geom_rows_*() and geom_cols_*() call the corresponding stat in order to render plot elements for the corresponding factor matrix. geom_dims_*() selects a default matrix based on common practice, e.g. points for rows and arrows for columns.

See also

Other biplot layers: biplot-geoms, biplot-stats

Examples

# FA of Swiss social data
swiss_fa <-
  ordinate(swiss, model = factanal, factors = 2L, scores = "regression")
# active and supplementary elements
get_rows(swiss_fa, elements = "active")
#>                      Factor1     Factor2
#> Fertility        -0.65238512  0.39335226
#> Agriculture      -0.63054439  0.33275063
#> Examination       0.68498141 -0.51036433
#> Education         0.99700850 -0.03128268
#> Catholic         -0.12417831  0.96118093
#> Infant.Mortality -0.09466294  0.17483734
head(get_rows(swiss_fa, elements = "score"))
#>                  Factor1    Factor2
#> Courtelary    0.07912746 -0.6344915
#> Delemont     -0.17926953  1.0783941
#> Franches-Mnt -0.58784929  1.2004233
#> Moutier      -0.42433417 -0.1583409
#> Neuveville    0.38211185 -0.6682790
#> Porrentruy   -0.37286722  1.0884740

# biplot using element filters and selection
# (note that filter precedes selection)
ggbiplot(swiss_fa) +
  geom_rows_point(elements = "score") +
  geom_rows_text(aes(label = name), elements = "score", subset = c(1, 4, 18)) +
  scale_alpha_manual(values = c(0, 1), guide = "none") +
  geom_cols_vector() +
  geom_cols_text_radiate(aes(label = name))
#> `subset` will be applied after data are restricted to score elements.