r - Add rows for missing data in a sequence -


i have data frame 3 columns give below:

  1. a catalog code
  2. spend on catalog code in given week
  3. the number of week in period

some dummy data below.

cat.code<-c("a","a","a","b","b","b","c","d") dol<-c(4,10,2,5,6,8,9,10) wk.purch<-c(1,2,3,1,5,2,3,4)  fk.data<-data.frame(cat.code,dol,wk.purch) > fk.data   cat.code dol wk.purch 1          4        1 2         10        2 3          2        3 4        b   5        1 5        b   6        5 6        b   8        2 7        c   9        3 8        d  10        4

i want add rows have dol = 0 when there no purchase in given week.

so, looking @ cat.code= a, want transform data frame add 2 more rows weeks 4 , 5 have 0 dol. have tried using expand.grid() , merge together, isn't working me.

thank you, all!

you can use merge/expand.grid

 transform(merge(expand.grid(cat.code= unique(fk.data$cat.code),            wk.purch=unique(fk.data$wk.purch)),         fk.data, all.x=true), dol= replace(dol, is.na(dol), 0))  #   cat.code wk.purch dol  #1                1   4  #2                2  10  #3                3   2  #4                4   0  #5                5   0  #6         b        1   5  #7         b        2   8  #8         b        3   0  #9         b        4   0  #10        b        5   6  #11        c        1   0  #12        c        2   0  #13        c        3   9  #14        c        4   0  #15        c        5   0  #16        d        1   0  #17        d        2   0  #18        d        3   0  #19        d        4  10  #20        d        5   0

or using data.table, can use similar approach cj. convert 'data.frame' 'data.table' (setdt(fk.data), , set key column 'cat.code' , 'wk.purch'. join output of cj , change na values in 'dol' '0'.

 library(data.table)#v1.9.5+  setdt(fk.data, key= c('cat.code', 'wk.purch'))[cj(cat.code=unique(cat.code),         wk.purch=unique(wk.purch))][is.na(dol), dol:=0][]

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