Conditional cumulative sum with apply functions in R -

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may question addressed , answered in so, couldn't able find out. i'm computing cumulative sum conditions on large data frame. @ below example

data=data.frame("catg"=c("a","a","a","a","a","b","b","b","c","c","c","d","d","d","d","d","d","d","d","e","e","f"),"val"=c(67,42,12,32,28,1,11,9,38,61,75,99,22,44,89,99,51,34,82,99,74,42)) res=null uniqcatg=unique(data$catg) for(i in 1:length(uniqcatg))     res=c(res, cumsum(data[data$catg==uniqcatg[i],"val"])) data$res=res data

is there smart way without loops? (like apply functions)

or plyr::ddply...

require( plyr ) ddply( data , "catg" , transform , res = cumsum(val) ) #   catg val res #1      67  67 #2      42 109 #3      12 121 #4      32 153 #5      28 181 #6     b   1   1 #7     b  11  12 #8     b   9  21 #9     c  38  38 #10    c  61  99 #11    c  75 174 #12    d  99  99 #13    d  22 121 #14    d  44 165 #15    d  89 254 #16    d  99 353 #17    d  51 404 #18    d  34 438 #19    d  82 520 #20    e  99  99 #21    e  74 173 #22    f  42  42

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