# sample

From dplyr v0.3
0th

Percentile

##### Sample n rows from a table.

This is a wrapper around sample.int to make it easy to select random rows from a table. It currently only works for local tbls.

##### Usage
sample_n(tbl, size, replace = FALSE, weight = NULL, .env = parent.frame())sample_frac(tbl, size = 1, replace = FALSE, weight = NULL,
.env = parent.frame())
##### Arguments
tbl
tbl of data.
size
For sample_n, the number of rows to select. For sample_frac, the fraction of rows to select. If tbl is grouped, size applies to each group.
replace
Sample with or without replacement?
weight
Sampling weights. This expression is evaluated in the context of the data frame. It must return a vector of non-negative numbers the same length as the input. Weights are automatically standardised to sum to 1.
.env
Environment in which to look for non-data names used in weight. Non-default settings for experts only.
• sample
• sample_frac
• sample_n
##### Examples
by_cyl <- mtcars %>% group_by(cyl)

# Sample fixed number per group
sample_n(mtcars, 10)
sample_n(mtcars, 50, replace = TRUE)
sample_n(mtcars, 10, weight = mpg)

sample_n(by_cyl, 3)
sample_n(by_cyl, 10, replace = TRUE)
sample_n(by_cyl, 3, weight = mpg / mean(mpg))

# Sample fixed fraction per group
# Default is to sample all data = randomly resample rows
sample_frac(mtcars)

sample_frac(mtcars, 0.1)
sample_frac(mtcars, 1.5, replace = TRUE)
sample_frac(mtcars, 0.1, weight = 1 / mpg)

sample_frac(by_cyl, 0.2)
sample_frac(by_cyl, 1, replace = TRUE)

Documentation reproduced from package dplyr, version 0.3, License: MIT + file LICENSE

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