重复随机采样行

Question

I have a dataframe containing 2 columns: column 1 are ID's and column 2 are values associated with each ID (totalling 59 different rows).

Example:

     [ID] [value] 
[1]   a   164  
[2]   b   167  
[3]   c   120  
[4]   d   117  
[5]   e   106 

I am assuming that the only way I can randomly sample from column 1 and keep the associated value in column 2, is by sampling rows. I need to randomly sample 50 x 1 row, 50 x 2 rows, 50 x 3 rows, 50 x 4 rows etc. up to 59 rows. Ideally, with each sample set output as a dataframe. So, I would end up with 59 sets of randomly sampled data. Essentially this is the same as creating random subsets of data.

I have this code which produces a df of 10 randomly sampled rows for example.

sample_df<-df[sample.int(nrow(df),size=10,replace=TRUE),]

The question is how can I adjust this code so that it produces 50 times 10 random rows? Should I be using a loop to generate all of the random samples that I need?

Answer 1

您可以使用lapply ，这将返回数据帧列表：

lapply(1:59, function(x) df[sample(nrow(df), size = x, replace = TRUE),])