- 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.