These functions can be used to do basic calculations with or without case weights.
Usage
get_case_weights(info, .data, call = rlang::caller_env())
averages(x, wts = NULL, na_rm = TRUE)
medians(x, wts = NULL)
variances(x, wts = NULL, na_rm = TRUE)
correlations(x, wts = NULL, use = "everything", method = "pearson")
covariances(x, wts = NULL, use = "everything", method = "pearson")
pca_wts(x, wts = NULL)
are_weights_used(wts, unsupervised = FALSE)Arguments
- info
A data frame from the
infoargument within steps- .data
The training data
- call
The execution environment of a currently running function, e.g.
caller_env(). The function will be mentioned in error messages as the source of the error. See thecallargument ofabort()for more information.- x
A numeric vector or a data frame
- wts
A vector of case weights
- na_rm
A logical value indicating whether
NAvalues should be removed during computations.- use
Used by
correlations()orcovariances()to pass argument tocor()orcov()- method
Used by
correlations()orcovariances()to pass argument tocor()orcov()- unsupervised
Can the step handle unsupervised weights
Details
get_case_weights() is designed for developers of recipe steps, to return a
column with the role of "case weight" as a vector.
For the other functions, rows with missing case weights are removed from calculations.
For averages() and variances(), missing values in the data (not the
case weights) only affect the calculations for those rows. For
correlations(), the correlation matrix computation first removes rows with
any missing values (equal to the "complete.obs" strategy in stats::cor()).
are_weights_used() is designed for developers of recipe steps and is used
inside print method to determine how printing should be done.
