This is in essence apply_row_dfw()
/apply_column_dfw()
, but with the
results saved as new annotations. As such, the usage is almost identical to
these functions, except that only a single matrix can be used, and must be
specified (matrix specification differs also slightly).
annotate_row_from_apply(
.ms,
.matrix,
...,
names_prefix = "",
names_sep = "_",
names_glue = NULL,
names_sort = FALSE,
names_vary = "fastest",
names_expand = FALSE
)annotate_column_from_apply(
.ms,
.matrix,
...,
names_prefix = "",
names_sep = "_",
names_glue = NULL,
names_sort = FALSE,
names_vary = "fastest",
names_expand = FALSE
)
A matrixset
with updated meta info.
matrixset
object
a tidyselect matrix name: matrix name as a bare name or a character.
expressions, separated by commas. They can be specified in one of the following way:
a function name, e.g., mean
.
a function call, where you can use .m
to represent the current matrix
(for apply_matrix
), .i
to represent the current row (for apply_row
)
and .j
for the current column (apply_column
). Bare names of object
traits can be used as well. For instance, lm(.i ~ program)
.
The pronouns are also available for the multivariate version, under certain circumstances, but they have a different meaning. See the "Multivariate" section for more details.
a formula expression. The pronouns .m
, .i
and .j
can be used as
well. See examples to see the usefulness of this.
The expressions can be named; these names will be used to provide names to the results.
See
the same arguments of tidyr::pivot_wider()
In the context of grouping, the apply_*_dfw()
functions stack the results
for each group value.
In the case of annotate_*_from_matrix()
, a tidyr::pivot_wider()
is
further applied to ensure compatibility of the dimension.
The pivot_wider()
arguments names_prefix
, names_sep
, names_glue
,
names_sort
, names_vary
and names_expand
can help you control the final
annotation trait names.
A conscious choice was made to provide this functionality only for
apply_*_dfw()
, as this is the only version for which the output dimension
is guaranteed to respect the matrixset
paradigm.
On that note, see the section 'Grouped matrixset
'.
annotate_row()
/annotate_column()
.
# This is the same example as in annotate_row(), but with the "proper" way
# of doing it
ms <- annotate_row_from_apply(student_results, "failure", mn = mean)
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