[R] Ids with matching number combinations?

[Ebert,Timothy Aaron]

Would an inner_join work? If not, please describe why so that we can improve our answer. This answer requires the dplyr package.
https://statisticsglobe.com/r-dplyr-join-inner-left-right-full-semi-anti

Regards,
Tim

-----Original Message-----
From: R-help <r-help-bounces using r-project.org> On Behalf Of PIKAL Petr
Sent: Friday, October 7, 2022 10:02 AM
To: Marine Andersson <marine.andersson using ki.se>; r-help using r-project.org
Subject: Re: [R] Ids with matching number combinations?

[External Email]

Hallo Marine

Could you please make your example more reproducible by using set.seed (and maybe smaller)?

If I understand correctly, you want to know if let say row 1 items from df2
(8,16) are both in item column of specific id?

If I am correct in guessing, I cannot find another solution than split your df according to id x <- split(df, df$id)[[1]]

and for each row of df2 test if within the specified id you can find both numbers.
sum(is.element(df2[1,], x$item))==2
[1] FALSE

So basically 2 cycles, one for df ids and the other for df2 rows.

But maybe somebody will give you more ingenious answer.

Cheers
Petr


> -----Original Message-----
> From: R-help <r-help-bounces using r-project.org> On Behalf Of Marine 
> Andersson
> Sent: Friday, October 7, 2022 1:58 PM
> To: r-help using r-project.org
> Subject: [R] Ids with matching number combinations?
>
> Hi,
>
> If I have two datasets like this:
> df=data.frame("id"=rep(1:10,10, each=10), "item1"=sample(1:20, 100,
> replace=T)
> df2=data.frame("a"=c(8, 8,10,9, 5, 1,2,1), "b"=c(16,18,11, 19,18,
11,17,12))
>
> How do I find out which ids in the df dataset that has a match for 
> both
the
> numbers occuring in the same row in the df2 dataframe? In the output I
would
> like to get the matching id and the rownumber from the df2.
>
> Output something like this
> Id                        Rownr
> 2                         1
> 5                         1
> 7                         4
>
> My actual problem is more complex with even more columns to be matched 
> and the datasets are large, hence the solution needs to be efficient.
>
> Kind regards,
>
>
>
>
>
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