ranktransform {datawizard} | R Documentation |
(Signed) rank transformation
Description
Transform numeric values with the integers of their rank (i.e., 1st smallest,
2nd smallest, 3rd smallest, etc.). Setting the sign
argument to TRUE
will
give you signed ranks, where the ranking is done according to absolute size
but where the sign is preserved (i.e., 2, 1, -3, 4).
Usage
ranktransform(x, ...)
## S3 method for class 'numeric'
ranktransform(x, sign = FALSE, method = "average", verbose = TRUE, ...)
## S3 method for class 'data.frame'
ranktransform(
x,
select = NULL,
exclude = NULL,
sign = FALSE,
method = "average",
ignore_case = FALSE,
regex = FALSE,
verbose = TRUE,
...
)
Arguments
x |
Object.
|
... |
Arguments passed to or from other methods.
|
sign |
Logical, if TRUE , return signed ranks.
|
method |
Treatment of ties. Can be one of "average" (default),
"first" , "last" , "random" , "max" or "min" . See rank() for
details.
|
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.
|
Value
A rank-transformed object.
Selection of variables - the select
argument
For most functions that have a select
argument (including this function),
the complete input data frame is returned, even when select
only selects
a range of variables. That is, the function is only applied to those variables
that have a match in select
, while all other variables remain unchanged.
In other words: for this function, select
will not omit any non-included
variables, so that the returned data frame will include all variables
from the input data frame.
See Also
Other transform utilities:
normalize()
,
rescale()
,
reverse()
,
standardize()
Examples
ranktransform(c(0, 1, 5, -5, -2))
# Won't work
# ranktransform(c(0, 1, 5, -5, -2), sign = TRUE)
head(ranktransform(trees))
[Package
datawizard version 0.12.2
Index]