You're welcome, Satish.

Yes, questions that are seeking solutions in R code are appropriate for
this group.  It's helpful if you provide sample data (for example, using
dput()) and sample R code that folks can use.  And it's helpful if you show
the results that you are hoping to achieve (as you did).

Jean

On Mon, Mar 28, 2016 at 1:15 PM, Satish Vadlamani <
satish.vadlam...@gmail.com> wrote:

> Jean:
> Wow. Thank you so much for this. I will read up igraph and then see if
> this is going to work for me for the larger dataset.
>
> Thanks for the wonderful snippet code you wrote. Basically, the
> requirement is this:
> TLA1 (Top Level Assembly) and its components should belong to the same
> group. If a component belongs to a different TLA (say TLA2), then that TLA1
> and all of its components should belong to the same as that of TLA1.
>
> Are these types of questions appropriate for this group?
>
> Thanks,
> Satish
>
>
> On Mar 28, 2016 9:10 AM, "Adams, Jean" <jvad...@usgs.gov> wrote:
>
>> Satish,
>>
>> If you rearrange your data into a network of nodes and edges, you can use
>> the igraph package to identify disconnected (mutually exclusive) groups.
>>
>> # example data
>> df <- data.frame(
>>   Component = c("C1", "C2", "C1", "C3", "C4", "C5"),
>>   TLA = c("TLA1", "TLA1", "TLA2", "TLA2", "TLA3", "TLA3")
>> )
>>
>> # characterize data as a network of nodes and edges
>> nodes <- levels(unlist(df))
>> edges <- apply(df, 2, match, nodes)
>>
>> # use the igraph package to identify disconnected groups
>> library(igraph)
>> g <- graph(edges)
>> ngroup <- clusters(g)$membership
>> df$Group <- ngroup[match(df$Component, nodes)]
>> df
>>
>>   Component  TLA Group
>> 1        C1 TLA1     1
>> 2        C2 TLA1     1
>> 3        C1 TLA2     1
>> 4        C3 TLA2     1
>> 5        C4 TLA3     2
>> 6        C5 TLA3     2
>>
>> Jean
>>
>> On Sun, Mar 27, 2016 at 7:56 PM, Satish Vadlamani <
>> satish.vadlam...@gmail.com> wrote:
>>
>>> Hello All:
>>> I would like to get some help with the following problem and understand
>>> how
>>> this can be done in R efficiently. The header is given in the data frame.
>>>
>>> *Component, TLA*
>>> C1, TLA1
>>> C2, TLA1
>>> C1, TLA2
>>> C3, TLA2
>>> C4, TLA3
>>> C5, TLA3
>>>
>>> Notice that C1 is a component of TLA1 and TLA2.
>>>
>>> I would like to form groups of mutually exclusive subsets and create a
>>> new
>>> column called group for this subset. For the above data, the subsets and
>>> the new group column value will be like so:
>>>
>>> *Component, TLA, Group*
>>> C1, TLA1, 1
>>> C2, TLA1, 1
>>> C1, TLA2, 1
>>> C3, TLA2, 1
>>> C4, TLA3, 2
>>> C5, TLA3, 2
>>>
>>> Appreciate any help on this. I could have looped through the observations
>>> and tried some logic but I did not try that yet.
>>>
>>> --
>>>
>>> Satish Vadlamani
>>>
>>>         [[alternative HTML version deleted]]
>>>
>>> ______________________________________________
>>> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
>>> https://stat.ethz.ch/mailman/listinfo/r-help
>>> PLEASE do read the posting guide
>>> http://www.R-project.org/posting-guide.html
>>> and provide commented, minimal, self-contained, reproducible code.
>>>
>>
>>

        [[alternative HTML version deleted]]

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