thank you David and Bert, these solutions will work for me... Andras
On Saturday, July 15, 2017 6:05 PM, Bert Gunter <bgunter.4...@gmail.com>
wrote:
...
and here is a slightly cleaner and more transparent way of doing the
same thing (setdiff() does the matching)
> with(df, setdiff(ID,ID[samples %in% c("B","C") ]))
[1] 3
-- Bert
Bert Gunter
"The trouble with having an open mind is that people keep coming along
and sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
On Sat, Jul 15, 2017 at 9:23 AM, Bert Gunter <bgunter.4...@gmail.com> wrote:
> If I understand correctly, no looping (ave(), for()) or type casting
> (as.character()) is needed -- indexing and matching suffice:
>
>> with(df, ID[!ID %in% unique(ID[samples %in% c("B","C") ])])
> [1] 3 3
>
>
>
> Cheers,
>
> Bert
>
>
> Bert Gunter
>
> "The trouble with having an open mind is that people keep coming along
> and sticking things into it."
> -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
>
>
> On Sat, Jul 15, 2017 at 8:54 AM, David Winsemius <dwinsem...@comcast.net>
> wrote:
>>
>>> On Jul 15, 2017, at 4:01 AM, Andras Farkas via R-help
>>> <r-help@r-project.org> wrote:
>>>
>>> Dear All,
>>>
>>> wonder if you could please assist with the following
>>>
>>> df<-data.frame(ID=c(1,1,1,2,2,3,3,4,4,5,5),samples=c("A","B","C","A","C","A","D","C","B","A","C"))
>>>
>>> from this data frame the goal is to extract the value of 3 from the ID
>>> column based on the logic that the ID=3 in the data frame has NO row that
>>> would pair 3 with either "B", AND/OR "C" in the samples column...
>>>
>>
>> This returns a vector that determines if either of those characters are in
>> the character values of that factor column you created. Coercing to
>> character is needed because leaving samples as a factor generated an invalid
>> factor level warning and gave useless results.
>>
>> with( df, ave( as.character(samples), ID, FUN=function(x) {!any(x %in%
>>c("B","C"))}))
>> [1] "FALSE" "FALSE" "FALSE" "FALSE" "FALSE" "TRUE" "TRUE" "FALSE" "FALSE"
>> [10] "FALSE" "FALSE"
>>
>> You can then use it to extract and consolidate to a single value (although
>> wrapping with as.logical was needed because `ave` returned character class
>> values):
>>
>> unique( df$ID[ as.logical( # fails without this since "FALSE" != FALSE
>> with( df,
>> ave( as.character(samples), ID, FUN=function(x)
>>{!any(x %in% c("B","C"))})))
>> ] )
>> #[1] 3
>>
>> The same sort of logic could also be constructed with a for-loop:
>>
>>> for (x in unique(df$ID) ) { if ( !any( df$samples[df$ID==x] %in%
>>> c("b","C")) ) print(x) }
>> [1] 3
>>
>> Although you are warned that for-loops do not return values and you might
>> need to make an assignment rather than just printing.
>>
>> --
>>
>> David Winsemius
>> Alameda, CA, USA
>>
>> ______________________________________________
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