These functions can be used to do basic calculations with or without case weights.

## Usage

```
get_case_weights(info, .data)
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

`info`

argument within steps- .data
The training data

- x
A numeric vector or a data frame

- wts
A vector of case weights

- na_rm
A logical value indicating whether

`NA`

values should be removed during computations.- use
Used by

`correlations()`

or`covariances()`

to pass argument to`cor()`

or`cov()`

- method
Used by

`correlations()`

or`covariances()`

to pass argument to`cor()`

or`cov()`

- 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.