r - Split dataframe, then select random observations from list, and the lists merge back into a dataframe -


i have data frame 3 variables (subject, trialtype, , rt), , need select randomly half of rt observations each subject, , re-create data frame selection.

in browsing list i've got here

split_df <- split(bucnidata_rt,                    list(bucnidata_rt$subject, bucnidata_rt$trialtype))

(this gives series of split_df[1], split_df[2], ....)

but can not subset using this

split_df[1] <- sample(nrow(split_df[1]), 24), ]

i think because sample works on data frames , split_df[1] list.

to re-merge do:

remerged_df <- unsplit(split_df[1],                        list(bucnidata_rt$subject, bucnidata_rt$trialtype))

could please me step 2?

i propose different approach using dplyr if don't mind. can group subject , randomly select 50% of observations of each group:

library(dplyr)  bucnidata_rt %>%                      group_by(subject) %>%                sample_frac(size = 0.5)

edit

here's way, closer started. use mtcars dataset in case:

split_df <- split(mtcars, mtcars$cyl)   #split `cyl`  #randomly select 50% of rows per group, without replacement split_df <- lapply(split_df, function(x) x[sample(seq_len(nrow(x)), nrow(x)/2, replace=false),])    #merge randomly selected list elements 1 data.frame remerged_df <- do.call(rbind, split_df)  #check result nrow(remerged_df) #[1] 15

edit #2 corrected dplyr method after comment @gregor


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