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 the example, instead of:
(index) Name Fave.Number
1 John 7
2 Phil 14
3 Robert 23
I end up with
(index) Name Fave.Number
1 John 7
3 Phil 14
5 Robert 23
This isnt a problem at the moment but I guess it could be if I used the
table later in loops. Is there an easy way to re-index the table?
Kind regards
Jim
Wacek Kusnierczyk wrote:
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 I have a dataframe with characters in, eg
names.and.numbers
(index) Name Fave.Number
1 John 7
2 Tony 12
3 Phil 14
4 Adam 22
5 Robert 23
Now, imagine I have a vector of names, ie:
names = c("John,Phil,Robert")
this is a one-element vector of string(s) that are concatenated names
(strings with names).
or you mean: names = c("John", "Phil", "Robert")
All I want to do is get the subset of the dataframe which corresponds
to the names in the vector "Names". IE
(index) Name Fave.Number
1 John 7
2 Phil 14
3 Robert 23
this should do:
names.and.numbers[names.and.numbers$Name %in% names,]
if names is as you say above, do
names.and.numbers[names.and.numbers$Name %in% strsplit(names,","), ]
you do create a logical vector here (what does 'large' mean?), but no
loop is involved at the surface.
vQ
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