- x
A (grouped) data frame, numeric vector or factor.
- ...
not used.
- split
Character vector, indicating at which breaks to split variables,
or numeric values with values indicating breaks. If character, may be one
of "median", "mean", "quantile", "equal_length", or "equal_range".
"median" or "mean" will return dichotomous variables, split at their
mean or median, respectively. "quantile" and "equal_length" will split
the variable into n_groups groups, where each group refers to an interval
of a specific range of values. Thus, the length of each interval will be
based on the number of groups. "equal_range" also splits the variable
into multiple groups, however, the length of the interval is given, and
the number of resulting groups (and hence, the number of breaks) will be
determined by how many intervals can be generated, based on the full range
of the variable.
- n_groups
If split is "quantile" or "equal_length", this defines
the number of requested groups (i.e. resulting number of levels or values)
for the recoded variable(s). "quantile" will define intervals based
on the distribution of the variable, while "equal_length" tries to
divide the range of the variable into pieces of equal length.
- range
If split = "equal_range", this defines the range of values
that are recoded into a new value.
- lowest
Minimum value of the recoded variable(s). If NULL (the default),
for numeric variables, the minimum of the original input is preserved. For
factors, the default minimum is 1. For split = "equal_range", the
default minimum is always 1, unless specified otherwise in lowest.
- labels
Character vector of value labels. If not NULL, categorize()
will returns factors instead of numeric variables, with labels used
for labelling the factor levels.
- 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. find_columns(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.
- append
Logical or string. If TRUE, recoded or converted variables
get new column names and are appended (column bind) to x, thus returning
both the original and the recoded variables. The new columns get a suffix,
based on the calling function: "_r" for recode functions, "_n" for
to_numeric(), "_f" for to_factor(), or "_s" for
slide(). If append=FALSE, original variables in x will be
overwritten by their recoded versions. If a character value, recoded
variables are appended with new column names (using the defined suffix) to
the original data frame.
- 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.