partition {nuggets} | R Documentation |
Convert the selected columns of the data frame into either dummy logical columns (for logicals and factors), or into membership degrees of fuzzy sets (for numeric columns), while leaving the remaining columns untouched. Each column selected for transformation typically yields in multiple columns in the output.
partition(
.data,
.what = everything(),
...,
.breaks = NULL,
.labels = NULL,
.na = TRUE,
.keep = FALSE,
.method = "crisp",
.right = TRUE
)
.data |
the data frame to be processed |
.what |
a tidyselect expression (see tidyselect syntax) specifying the columns to be transformed |
... |
optional other tidyselect expressions selecting additional columns to be processed |
.breaks |
for numeric columns, this has to be either an integer scalar
or a numeric vector. If |
.labels |
character vector specifying the names used to construct
the newly created column names. If |
.na |
if |
.keep |
if |
.method |
The method of transformation for numeric columns. Either
|
.right |
If |
Concretely, the transformation of each selected column is performed as follows:
logical column x
is transformed into pair of logical columns,
x=TRUE
andx=FALSE
;
factor column x
, which has levels l1
, l2
, and l3
, is transformed
into three logical columns named x=l1
, x=l2
, and x=l3
;
numerical columnx
is transformed accordingly to .method
argument:
if .method="crisp"
, the column is first transformed into a factor
with intervals as factor levels and then it is processed as a factor
(see above);
for other .method
(triangle
or raisedcos
), several new columns
are created, where each column has numeric values from the interval
[0,1]
and represents a certain fuzzy set (either triangular or
raised-cosinal).
Details of transformation of numeric columns can be specified with
additional arguments (.breaks
, .labels
, .right
).
A tibble created by transforming .data
.
Michal Burda