r - Inserting NA rows when missing data -


i have data set missing values in sequence:

seq<-c(1,2,3,4,6,7,10,11,12,18,19,20) data<-c(3,4,5,4,3,2,1,2,3,5,4,3) df<-data.frame(seq, data)

i'd add rows data set approximating have missing values, , filling in data na. time have gap larger 2, add na row (or multiple rows if gap large). result this:

newseq<-c(1,2,3,4,6,7,8.5,10,11,12,14,16,18,19,20) newdata<-c(3,4,5,4,3,2,na,1,2,3,na,na,18,19,20) newdf<-data.frame(newseq,newdata)

so ignore when gap < 2, add na row anytime there gap > 2. if there still > 2 gap after adding na row, add until gap filled.

not elegant, how it:

seq<-c(1,2,3,4,6,7,10,11,12,18,19,20) data<-c(3,4,5,4,3,2,1,2,3,5,4,3) df<-data.frame(seq, data)  first <- df$seq second <- df$data  for(i in length(first):2) {   gap <- first[i] - first[i - 1]   if(gap > 2) {     steps <- ifelse(gap %% 2 == 1, gap %/% 2, (gap %/% 2) -1)     new_values_gap <- gap / (steps + 1)     new_values <- vector('numeric')     for(j in 1:steps) {       new_values <- c(new_values, first[i - 1] + j * new_values_gap)     }     first <- c(first[1:i - 1], new_values, first[i:length(first)])     second <- c(second[1:i - 1], rep(na, length(new_values)), second[i:length(second)])   } }  newdf <- data.frame(newseq = first, newdata = second)  > newdf  ##    newseq newdata ## 1     1.0       3 ## 2     2.0       4 ## 3     3.0       5 ## 4     4.0       4 ## 5     6.0       3 ## 6     7.0       2 ## 7     8.5      na ## 8    10.0       1 ## 9    11.0       2 ## 10   12.0       3 ## 11   14.0      na ## 12   16.0      na ## 13   18.0       5 ## 14   19.0       4 ## 15   20.0       3

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