unction(d) paste( as.character(d), collapse= " "))
> #doc = paste(dat, collapse = " ## ") # just some arbitrary separator
> character that isn't in your words
> counts = sapply(words, function(w) length(grep(w, dat)))
> names(counts) = words
> counts
> c
On Wed, Jul 27, 2016 at 11:19 PM, Sarah Goslee
wrote:
> You said you had 79 triplets and 8000 records.
>
> When I compared 100 triplets to 1 records it took 86 seconds.
>
> So obviously there is something you're not telling us about the format
> of your data.
>
>
- combs[rep(1:nrow(combs), length=100), ]
> > dat <- dat[rep(1:length(dat), length=1)]
> >
> > dim(combs)
> [1] 100 3
> > length(dat)
> [1] 1
> >
> > system.time(test <- sapply(seq_len(nrow(combs)),
> function(i)sum(sapply(dat, fu
Please re-read ?match *carefully* .
>
> Bert
>
> On Jul 27, 2016 6:15 AM, "sri vathsan" wrote:
>
> Hi,
>
> I created list of 3 combination numbers (mycombos, around 3 lakh
> combinations) and counting the occurrence of those combination in another
> list. Thi
Hi,
I created list of 3 combination numbers (mycombos, around 3 lakh
combinations) and counting the occurrence of those combination in another
list. This comparision list (mylist) is having around 8000 records.I am
using the following code.
myCounts <- sapply(1:nrow(myCombos), FUN=function(i) {
t;function(x,values) return(all(values %in% x)),c(11,12)
>> > }
>> > }
>> >
>> > svlist<-list(a=c(11,15,12,25),
>> > b=c(11,12),
>> > c=c(15,25),
>> > d=c(134,45,56),
>> > e=46,
>> > f=c(45,56),
>> &g
Hi,
I have a data frame like below.
11,15,12,25
11,12
15,25
134,45,56
46
45,56
15,12
66,45,56,24,14,11,25,12,134
I want to identify the frequency of pairs/triplets or higher that occurs in
the data. Say for example, in above data the occurrence of pairs looks like
below
item No of occurrence
tr)) {
> svdatstr[row,"maxA"]<-
>
> max(svdatstr[row,count_ind[as.logical(match(svdatstr[1,type_ind],"A",0))]])
> svdatstr[row,"maxB"]<-
>
> max(svdatstr[row,count_ind[as.logical(match(svdatstr[1,type_ind],"B",0))]])
> svdatstr[row,
Dear All,
I am trying to reshape the data with some conditions. A small part of the
data looks like below. Like this there will be more data with repeating ID.
Count id name type
117 335 sally A
19 335 sally A
167 335 sally B
18 340 susan A
56 340 susan A
22 340 susan B
53 340 susan B
135 351 lee
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