Try this:
do.call(rbind,
apply(combn(names(x), 2),
2,
function(n)expand.grid(x[,n[1]], x[,n[2]])))
On Wed, Jun 10, 2009 at 11:47 AM, Moumita Das
<das.moumita.onl...@gmail.com>wrote:
> Hi friends,
> Please can anyone help me with an easier solution of doing the below
> mentioned work.
> Suppose i have a dataset like this:---
>
> i1 i2 i3 i4 i5
> 1 7 13 1 2
> 2 8 14 2 2
> 3 9 15 3 3
> 4 10 16 4 4
> 5 11 17 5 5
> 6 12 18 6 7
>
>
> *i1,i2,i3,i4,i5 are my items.I am able to find all possible pairs i.e
> Say this dataframe is "item_pairs"
> **i1,i2
> **i1,i3
> **i1,i4
> i1,i5
> **i2,i1
> **i2,i3
> i2,i4
> i2,i5
> **i3,i1
> **i3,i2
> **i3,i4
> **i3,i5
> **i4,i1
> **i4,i2
> **i4,i3
> i4,i5
> i5,i1
> i5,i2
> i5,i3
> i5,i4
>
> Pairs like (i1,i1) or (i2,i2) are not required.Now pair (i1,i2) is same as
> pair (i2,i1) .How can i chop off the second pair which is identicle to the
> first one,only that sequence of item numbers are different ,otherwise my
> dataset is same.
>
> I thought of something...like ....running loops for all rows and columns of
> this item_pairs dataframe and check if first item in a pair matches with
> any
> second item of previous pair and similarly **second item in a pair matches
> with any first item of previous pair* and keep entering them in a dataframe
> and get the unique pairs.
>
> But is there any other easier way of chopping off the identicle pairs?
> *-- *
> Thanks in advance
> Moumita
>
> [[alternative HTML version deleted]]
>
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>
--
Henrique Dallazuanna
Curitiba-Paraná-Brasil
25° 25' 40" S 49° 16' 22" O
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