dplyr-verbs {ordr}

dplyr verbs for tbl_ord factors

Description

These functions adapt dplyr verbs to the factors of a tbl_ord.

The raw verbs are not defined for tbl_ords; instead, each verb has two analogues, corresponding to the two matrix factors. They each rely on a common workhorse function, which takes the composition of the dplyr verb with ⁠annotation_*⁠, applied to the factor, removes any variables corresponding to coordinates or already annotated, and only then assigns it as the new "*_annotation" attribute of .data (see annotation). Note that these functions are not generics and so cannot be extended to other classes.

Usage

pull_factor(.data, var = -1, .matrix)

pull_rows(.data, var = -1)

pull_cols(.data, var = -1)

rename_rows(.data, ...)

rename_cols(.data, ...)

select_rows(.data, ...)

select_cols(.data, ...)

mutate_rows(.data, ...)

mutate_cols(.data, ...)

transmute_rows(.data, ...)

transmute_cols(.data, ...)

cbind_rows(.data, ..., elements = "all")

cbind_cols(.data, ..., elements = "all")

left_join_rows(.data, ...)

left_join_cols(.data, ...)

Arguments

.data

An object of class 'tbl_ord'.

var

A variable specified as in dplyr::pull().

.matrix

A character string partially matched (lowercase) to several indicators for one or both matrices in a matrix decomposition used for ordination. The standard values are "rows", "cols", and "dims" (for both).

...

Comma-separated unquoted expressions as in, e.g., dplyr::select().

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').

Value

A tbl_ord; the wrapped model is unchanged.

Examples

# illustrative ordination: LDA of iris data
(iris_lda <- ordinate(iris, cols = 1:4, lda_ord, grouping = iris$Species))

# extract a coordinate or annotation
head(pull_rows(iris_lda, Species))
pull_cols(iris_lda, LD2)

# rename an annotation
rename_cols(iris_lda, species = name)

# select annotations
select_rows(iris_lda, species = name, .element)

# create, modify, and delete annotations
mutate_cols(iris_lda, vec.length = sqrt(LD1^2 + LD2^2))
transmute_cols(iris_lda, vec.length = sqrt(LD1^2 + LD2^2))

# bind data frames of annotations
iris_medians <-
  stats::aggregate(iris[, 1:4], median, by = iris[, 5, drop = FALSE])
iris_lda %>%
  # retain '.element' in order to match by `elements`
  select_rows(.element) %>%
  cbind_rows(iris_medians, elements = "active")