james perkins wrote:
> Thanks a lot for that. Its the %in% I needed to work out mainly
>
> large didn't mean anything in particular, just that it gets quite long
> with the real data.
> I did mean: names = c("John", "Phil", "Robert")
>
> The only problem is that using the method you suggest is that
james perkins wrote:
> Thanks a lot for that. Its the %in% I needed to work out mainly
>
> large didn't mean anything in particular, just that it gets quite long
> with the real data.
> I did mean: names = c("John", "Phil", "Robert")
>
> The only problem is that using the method you suggest is that
Thanks a lot for that. Its the %in% I needed to work out mainly
large didn't mean anything in particular, just that it gets quite long
with the real data.
I did mean: names = c("John", "Phil", "Robert")
The only problem is that using the method you suggest is that I lose the
indexing, ie in t
james perkins wrote:
> Hi,
>
> I have a very simple problem but I can't think how to solve it without
> using a for loop and creating a large logical vector. However given
> the nature of the problem I am sure there is a "1-liner" that could do
> the same thing much more efficiently.
>
> bascially
On 6/13/2008 10:07 AM, james perkins wrote:
Hi,
I have a very simple problem but I can't think how to solve it without
using a for loop and creating a large logical vector. However given the
nature of the problem I am sure there is a "1-liner" that could do the
same thing much more efficientl
Hi,
I have a very simple problem but I can't think how to solve it without
using a for loop and creating a large logical vector. However given the
nature of the problem I am sure there is a "1-liner" that could do the
same thing much more efficiently.
bascially I have a dataframe with charac
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