问题描述
从这些问题 - & 我可以很容易地看到如何随机抽样来自df的行，或n行，源自df中的一个因素的特定级别。
From these questions - Random sample of rows from subset of an R dataframe & Random rows in dataframe in R I can easily see how to randomly sample '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.
只需从粉红色颜色中抽取3个随机行 - 使用库（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，我想要做的是创建一个新的df，其中包含来自所有级别的3（或n）个随机行。即新的df将有12行（3从蓝色，3从红色，3从黄色，3从粉红色）。显然可以运行这几次，为每种颜色创建newdf，然后将它们绑定在一起。然而，我正在努力制定一个更简单的解决方案，因为当我需要这么多层次的时候。
However, what I am trying to do is create a new df that contains 3 (or n) random row from all levels 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. However, I am trying to work out a simpler solution, for when there are many, many levels that I need to do this across.
推荐答案
您可以使用 ave 为具有特定因素级别的每个元素分配一个随机ID。然后，您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,]
如果这是您感兴趣的东西，则具有保留原始行顺序和行名的优点。此外，您可以重新使用 rndid 矢量以相当容易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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