- x
A (grouped) data frame, a vector or factor.
- ...
not used.
- by
Optional vector or factor. If supplied, a crosstable is created.
If x is a data frame, by can also be a character string indicating the
name of a variable in x.
- drop_levels
Logical, if FALSE, factor levels that do not occur in
the data are included in the table (with frequency of zero), else unused
factor levels are dropped from the frequency table.
- weights
Optional numeric vector of weights. Must be of the same length
as x. If weights is supplied, weighted frequencies are calculated.
- remove_na
Logical, if FALSE, missing values are included in the
frequency or crosstable, else missing values are omitted.
- proportions
Optional character string, indicating the type of
percentages to be calculated. Only applies to crosstables, i.e. when by is
not NULL. Can be "row" (row percentages), "column" (column percentages)
or "full" (to calculate relative frequencies for the full table).
- name
Optional character string, which includes the name that is used
for printing.
- verbose
Toggle warnings.
- select
Variables that will be included when performing the required
tasks. Can be either
a variable specified as a literal variable name (e.g., column_name),
a string with the variable name (e.g., "column_name"), or a character
vector of variable names (e.g., c("col1", "col2", "col3")),
a formula with variable names (e.g., ~column_1 + column_2),
a vector of positive integers, giving the positions counting from the left
(e.g. 1 or c(1, 3, 5)),
a vector of negative integers, giving the positions counting from the
right (e.g., -1 or -1:-3),
one of the following select-helpers: starts_with(), ends_with(),
contains(), a range using : or regex(""). starts_with(),
ends_with(), and contains() accept several patterns, e.g
starts_with("Sep", "Petal").
or a function testing for logical conditions, e.g. is.numeric() (or
is.numeric), or any user-defined function that selects the variables
for which the function returns TRUE (like: foo <- function(x) mean(x) > 3),
ranges specified via literal variable names, select-helpers (except
regex()) and (user-defined) functions can be negated, i.e. return
non-matching elements, when prefixed with a -, e.g. -ends_with(""),
-is.numeric or -(Sepal.Width:Petal.Length). Note: Negation means
that matches are excluded, and thus, the exclude argument can be
used alternatively. For instance, select=-ends_with("Length") (with
-) is equivalent to exclude=ends_with("Length") (no -). In case
negation should not work as expected, use the exclude argument instead.
If NULL, selects all columns. Patterns that found no matches are silently
ignored, e.g. extract_column_names(iris, select = c("Species", "Test"))
will just return "Species".
- exclude
See select, however, column names matched by the pattern
from exclude will be excluded instead of selected. If NULL (the default),
excludes no columns.
- ignore_case
Logical, if TRUE and when one of the select-helpers or
a regular expression is used in select, ignores lower/upper case in the
search pattern when matching against variable names.
- regex
Logical, if TRUE, the search pattern from select will be
treated as regular expression. When regex = TRUE, select must be a
character string (or a variable containing a character string) and is not
allowed to be one of the supported select-helpers or a character vector
of length > 1. regex = TRUE is comparable to using one of the two
select-helpers, select = contains("") or select = regex(""), however,
since the select-helpers may not work when called from inside other
functions (see 'Details'), this argument may be used as workaround.
- collapse
Logical, if TRUE collapses multiple tables into one larger
table for printing. This affects only printing, not the returned object.
- row.names
NULL or a character vector giving the row
names for the data frame. Missing values are not allowed.
- optional
logical. If TRUE, setting row names and
converting column names (to syntactic names: see
make.names) is optional. Note that all of R's
base package as.data.frame() methods use
optional only for column names treatment, basically with the
meaning of data.frame(*, check.names = !optional).
See also the make.names argument of the matrix method.
- stringsAsFactors
logical: should the character vector be converted
to a factor?
- add_total
For crosstables (i.e. when by is not NULL), a row and
column with the total N values are added to the data frame. add_total has
no effect in as.data.frame() for simple frequency tables.