- data
A data frame to pivot.
- id_cols
<tidy-select
> A set of columns that
uniquely identifies each observation. Defaults to all columns in data
except for the columns specified in names_from
and values_from
.
Typically used when you have redundant variables, i.e. variables whose
values are perfectly correlated with existing variables.
- id_expand
Should the values in the id_cols
columns be expanded by
expand()
before pivoting? This results in more rows, the output will
contain a complete expansion of all possible values in id_cols
. Implicit
factor levels that aren't represented in the data will become explicit.
Additionally, the row values corresponding to the expanded id_cols
will
be sorted.
- names_from, values_from
<tidy-select
> A pair of
arguments describing which column (or columns) to get the name of the
output column (names_from
), and which column (or columns) to get the
cell values from (values_from
).
If values_from
contains multiple values, the value will be added to the
front of the output column.
- names_prefix
String added to the start of every variable name. This is
particularly useful if names_from
is a numeric vector and you want to
create syntactic variable names.
- names_sep
If names_from
or values_from
contains multiple
variables, this will be used to join their values together into a single
string to use as a column name.
- names_glue
Instead of names_sep
and names_prefix
, you can supply
a glue specification that uses the names_from
columns (and special
.value
) to create custom column names.
- names_sort
Should the column names be sorted? If FALSE
, the default,
column names are ordered by first appearance.
- names_vary
When names_from
identifies a column (or columns) with
multiple unique values, and multiple values_from
columns are provided,
in what order should the resulting column names be combined?
"fastest"
varies names_from
values fastest, resulting in a column
naming scheme of the form: value1_name1, value1_name2, value2_name1, value2_name2
. This is the default.
"slowest"
varies names_from
values slowest, resulting in a column
naming scheme of the form: value1_name1, value2_name1, value1_name2, value2_name2
.
- names_expand
Should the values in the names_from
columns be expanded
by expand()
before pivoting? This results in more columns, the output
will contain column names corresponding to a complete expansion of all
possible values in names_from
. Implicit factor levels that aren't
represented in the data will become explicit. Additionally, the column
names will be sorted, identical to what names_sort
would produce.
- names_repair
What happens if the output has invalid column names?
The default, "check_unique"
is to error if the columns are duplicated.
Use "minimal"
to allow duplicates in the output, or "unique"
to
de-duplicated by adding numeric suffixes. See vctrs::vec_as_names()
for more options.
- values_fill
Optionally, a (scalar) value that specifies what each
value
should be filled in with when missing.
This can be a named list if you want to apply different fill values to
different value columns.
- values_fn
Optionally, a function applied to the value in each cell
in the output. You will typically use this when the combination of
id_cols
and names_from
columns does not uniquely identify an
observation.
This can be a named list if you want to apply different aggregations
to different values_from
columns.
- unused_fn
Optionally, a function applied to summarize the values from
the unused columns (i.e. columns not identified by id_cols
,
names_from
, or values_from
).
The default drops all unused columns from the result.
This can be a named list if you want to apply different aggregations
to different unused columns.
id_cols
must be supplied for unused_fn
to be useful, since otherwise
all unspecified columns will be considered id_cols
.
This is similar to grouping by the id_cols
then summarizing the
unused columns using unused_fn
.
- ...
Additional arguments passed on to methods.