slice_sample: Sample function for logs

Description

Sample function for logs

Usage

slice_sample(.data, ..., n, prop, by = NULL, weight_by = NULL, replace = FALSE)
# S3 method for log
slice_sample(.data, ..., n, prop, weight_by = NULL, replace = FALSE)
# S3 method for grouped_log
slice_sample(.data, ..., n, prop, weight_by = NULL, replace = FALSE)

Arguments

.data

A data frame, data frame extension (e.g. a tibble), or a lazy data frame (e.g. from dbplyr or dtplyr). See Methods, below, for more details.

...

Arguments passed on to dplyr::slice_sample

n,prop

Provide either n, the number of rows, or prop, the proportion of rows to select. If neither are supplied, n = 1 will be used. If n is greater than the number of rows in the group (or prop > 1), the result will be silently truncated to the group size. prop will be rounded towards zero to generate an integer number of rows.

A negative value of n or prop will be subtracted from the group size. For example, n = -2 with a group of 5 rows will select 5 - 2 = 3 rows; prop = -0.25 with 8 rows will select 8 * (1 - 0.25) = 6 rows.

n, prop

<tidy-select> Optionally, a selection of columns to group by for just this operation, functioning as an alternative to group_by(). For details and examples, see ?dplyr_by.

weight_by

<data-masking> Sampling weights. This must evaluate to a vector of non-negative numbers the same length as the input. Weights are automatically standardised to sum to 1.

replace

Should sampling be performed with (TRUE) or without (FALSE, the default) replacement.

Methods (by class)

slice_sample(log): Sample n cases of a log.
slice_sample(grouped_log): Sample n cases from a grouped_log.