Simple or Stratified Random Sampling

Draws a random sample of rows from a data frame. Sampling can be performed globally across the whole data set or separately within groups defined by one or more columns.

Usage

sample_by_group(data, n = 1, by = NULL)

Arguments

data

A data.frame from which rows are sampled.

n

A non-negative integer giving the number of rows to sample from each group. If a group contains fewer than n rows, all rows in that group are returned. Defaults to 1.

by

A character vector specifying the grouping columns, for example "group" or c("group1", "group2"). If NULL, sampling is performed over the entire data frame. Defaults to NULL.

Value

A data.frame containing the sampled rows, with row names reset.

Details

When by = NULL, the function samples up to n rows from the full data frame. When by is supplied, the data are split by the selected grouping columns and up to n rows are sampled independently from each group.

If a group contains fewer than n rows, all rows from that group are returned. The function does not set a random seed; use set.seed before calling it if reproducible sampling is required.

Examples

# Sample 2 rows from the full iris data set
sample_by_group(iris, n = 2)
#>   Sepal.Length Sepal.Width Petal.Length Petal.Width    Species
#> 1          5.1         2.5          3.0         1.1 versicolor
#> 2          5.4         3.7          1.5         0.2     setosa

# Sample 1 row per Species
sample_by_group(iris, n = 1, by = "Species")
#>   Sepal.Length Sepal.Width Petal.Length Petal.Width    Species
#> 1          5.1         3.5          1.4         0.2     setosa
#> 2          6.6         2.9          4.6         1.3 versicolor
#> 3          6.2         3.4          5.4         2.3  virginica

# Sample 2 rows per combination of cyl and am
sample_by_group(mtcars, n = 2, by = c("cyl", "am"))
#>     mpg cyl  disp  hp drat    wt  qsec vs am gear carb
#> 1  22.8   4 140.8  95 3.92 3.150 22.90  1  0    4    2
#> 2  21.5   4 120.1  97 3.70 2.465 20.01  1  0    3    1
#> 3  18.1   6 225.0 105 2.76 3.460 20.22  1  0    3    1
#> 4  21.4   6 258.0 110 3.08 3.215 19.44  1  0    3    1
#> 5  14.7   8 440.0 230 3.23 5.345 17.42  0  0    3    4
#> 6  15.2   8 304.0 150 3.15 3.435 17.30  0  0    3    2
#> 7  32.4   4  78.7  66 4.08 2.200 19.47  1  1    4    1
#> 8  22.8   4 108.0  93 3.85 2.320 18.61  1  1    4    1
#> 9  21.0   6 160.0 110 3.90 2.620 16.46  0  1    4    4
#> 10 19.7   6 145.0 175 3.62 2.770 15.50  0  1    5    6
#> 11 15.0   8 301.0 335 3.54 3.570 14.60  0  1    5    8
#> 12 15.8   8 351.0 264 4.22 3.170 14.50  0  1    5    4

# Reproducible sampling
set.seed(123)
sample_by_group(iris, n = 1, by = "Species")
#>   Sepal.Length Sepal.Width Petal.Length Petal.Width    Species
#> 1          4.8         3.1          1.6         0.2     setosa
#> 2          5.6         2.9          3.6         1.3 versicolor
#> 3          5.7         2.5          5.0         2.0  virginica