r - data frame splitting based on specific conditions -

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consider data frame having 1200 records , 30 variables. want divide data frame 6 sample each sample size of 200. far tried following r code:

createsample<-function(df) {  totalsample<-ceiling((nrow(df)/200))  samplesize=200   for(i in 1:totalsample)    {         ## user should have define file name , start & end row         file <-'demo.csv'         start <- (i-1)*samplesize         end <- (i*samplesize)         function1(file,start,end)    ## call function again control reaches here         }      } createsample(rawdata) ## function call

above code result unbound error, because can’t access first records 0 index value, instead in r can access first records index value 1.

  expectation is:   in first iteration of loop want access 1-200 records.   in next iteration want access 201-400 records. till total 6   time repetition, because loop execute total of 6 times.   reading data frame want start , end value should dynamically change in each iteration..   example: in first iteration    start<-1    end<-200    in second iteration:    start<-201    end<-400   , on...  in advance….

as don't know second function mentioned in op's post, can skip part , instead split dataset list of data.frames have each n rows (i.e. 200. last list element have remaining rows if nrow of dataset not multiple of n).

createsample <- function(df, n, sample=false){    seqn <- seq_len(nrow(df))    g1 <- (seqn-1)%/%n +1    start <- unname(tapply(seqn, g1, head, 1))    end <- unname(tapply(seqn, g1, tail, 1))    if(sample){    g1 <- sample(g1)    }    list(splitdat=lapply(split(seqn, g1), function(i) df[i,]),         start=start,         end=end)  }  createsample(yourdat, 200) createsample(yourdat, 200, true)

note: added option randomly sample observations in function.


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