poorman (version 0.2.6)

slice: Subset rows by position

Description

Subset rows by their original position in the data.frame. Grouped data.frames use the position within each group.

Usage

slice(.data, ...)
slice_head(.data, ..., n, prop)
slice_tail(.data, ..., n, prop)
slice_min(.data, order_by, ..., n, prop, with_ties = TRUE)
slice_max(.data, order_by, ..., n, prop, with_ties = TRUE)
slice_sample(.data, ..., n, prop, weight_by = NULL, replace = FALSE)

Value

An object of the same type as .data. The output has the following properties:

• Each row may appear 0, 1, or many times in the output.

• Columns are not modified.

• Groups are not modified.

• Data frame attributes are preserved.

Arguments

.data

A data.frame.

...

For slice(): integer row values.

Provide either positive values to keep, or negative values to drop. The values provided must be either all positive or negative. Indices beyond the number of rows in the input are silently ignored.

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. If the proportion of a group size is not an integer, it is rounded down.

order_by

The variable to order by.

with_ties

logical(1). Should ties be kept together? The default, TRUE, may return more rows than you request. Use FALSE to ignore ties, and return the first n rows.

weight_by

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

logical(1). Should sampling be performed with (TRUE) or without (FALSE, the default) replacement.

Examples

slice(mtcars, c(1, 2, 3))
mtcars %>% slice(1:3)

# Similar to head(mtcars, 1)
mtcars %>% slice(1L)

# Similar to tail(mtcars, 1):
mtcars %>% slice(n())
mtcars %>% slice(5:n())
# Rows can be dropped with negative indices:
slice(mtcars, -(1:4))

# First and last rows based on existing order
mtcars %>% slice_head(n = 5)
mtcars %>% slice_tail(n = 5)

# Grouped operations:
mtcars %>% group_by(am, cyl, gear) %>% slice_head(n = 2)