在数据框中每组采样 n 个随机行 [英] Sample n random rows per group in a dataframe

问题描述

来自这些问题 - 来自R 数据帧的子集 &对数据框中的随机行进行采样 我可以很容易地看到如何随机采样(选择)来自 df 的 'n' 行，或源自 df 中特定因子级别的 'n' 行.

From these questions - Random sample of rows from subset of an R dataframe & Sample random rows in dataframe I can easily see how to randomly sample (select) 'n' rows from a df, or 'n' rows that originate from a specific level of a factor within a df.

以下是一些示例数据:

df <- data.frame(matrix(rnorm(80), nrow=40))
df$color <-  rep(c("blue", "red", "yellow", "pink"), each=10)

df[sample(nrow(df), 3), ] #samples 3 random rows from df, without replacement.

例如只需从粉红色"颜色中随机抽取 3 行 - 使用 library(kimisc):

To e.g. just sample 3 random rows from 'pink' color - using library(kimisc):

library(kimisc)
sample.rows(subset(df, color == "pink"), 3)

或编写自定义函数:

sample.df <- function(df, n) df[sample(nrow(df), n), , drop = FALSE]
sample.df(subset(df, color == "pink"), 3)

但是，我想从因子的每个级别中抽取 3(或 n)个随机行.IE.新的 df 将有 12 行(3 行来自蓝色，3 行来自红色，3 行来自黄色，3 行来自粉红色).显然可以多次运行，为每种颜色创建 newdfs，然后将它们绑定在一起，但我正在寻找一个更简单的解决方案.

However, I want to sample 3 (or n) random rows from each level of the factor. I.e. the new df would have 12 rows (3 from blue, 3 from red, 3 from yellow, 3 from pink). It's obviously possible to run this several times, create newdfs for each color, and then bind them together, but I am looking for a simpler solution.

推荐答案

您可以使用 ave 为每个具有特定因子水平的元素分配一个随机 ID.然后可以选择一定范围内的所有随机ID.

You can assign a random ID to each element that has a particular factor level using ave. Then you can select all random IDs in a certain range.

rndid <- with(df, ave(X1, color, FUN=function(x) {sample.int(length(x))}))
df[rndid<=3,]

如果您感兴趣的话，这样做的好处是可以保留原始行顺序和行名称.此外，您可以重新使用 rndid 向量来相当轻松地创建不同长度的子集.

This has the advantage of preserving the original row order and row names if that's something you are interested in. Plus you can re-use the rndid vector to create subset of different lengths fairly easily.

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