My problem is that using "[" every time i want to extract my data of
interest is cumbersome and verbose for the next guy suffering through
reading my code. Since my extractions are always on the same columns and
depend on either "<", ">" or neither, a wrapper function or perhaps
different function besides "[" will likely solve my problem. Indeed
Rui's example achieves exactly what i wanted. Keep in mind my grasp of R
remains limited and you might think my problem is more complex than it
is. So i'm only inviting further solution's to this problem for the sake
of improving my grasp of R. You certainly have my understanding should
this go beyond what you might invest your time in :)
No less, your example code:
eg$grpcol[with(eg,grpcol!="Default" & A<1 & B<1)] <- "ABTooLow")
already provides educational material for me, thank you.
Chrs, K
On 06/12/12 18:00, Jeff Newmiller wrote:
You ask me to provide code when you have only described your solution rather
than your problem. That limits my options more than I care to allow for
investing my time.
When I think of problems that require repetitive subsetting I tend to look for solutions involving aggregation
(?aggregate, ?plyr::ddply), which requires creating one or more grouping columns which can be formulated with the
cut function or with logical indexed assignment (e.g. a sequence of statements something like
eg$grpcol[with(eg,grpcol!="Default" & A<1 & B<1)] <- "ABTooLow").
So... what is your problem?
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Karl Brand <k.br...@erasmusmc.nl> wrote:
Hi Jeff,
Subset is indeed what's reuqired here. But using it every time it's
needed was generating excessive amounts of obtuse code. So for the sake
of clarity and convenience i wanted a wrapper function to replace these
repetitious subsets.
Although Rui's example works just fine, love to see any idiomatic ways
you might attempt this (also for the sake of improving my grasp of R).
Cheers,
Karl
On 06/12/12 15:57, Jeff Newmiller wrote:
You have not indicated why the subset function is insufficient for
your needs...
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Playing
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Karl Brand <k.br...@erasmusmc.nl> wrote:
Esteemed UseRs,
I've got many biggish data frames which need a lot subsetting, like
in
this example:
# example
eg <- data.frame(A = rnorm(10), B = rnorm(10), C = rnorm(10), D =
rnorm(10))
egsub <- eg[eg$A < 0 & eg$B < 1 & eg$C > 0, ]
egsub
egsub2 <- eg[eg$A > 1 & eg$B > 0, ]
egsub2
# To make this clearer than 1000s of lines of extractions with []
# I tried to make a function like this:
# func(data="eg", A="< 0", B="< 1", C="> 0")
# Which would also need to be run as
# func(data="eg", A="> 1", B="> 0", C=NA)
#end
Noteably:
-the signs* "<" and ">" need to be flexible _and_ optional
-the quantities also need to be flexible
-column header names i.e, A, B and C don't need flexibility,
i.e., can remain fixed
* "less than" and "greater than" so google picks up this thread
Once again i find just how limited my grasp of R is...Is do.call()
the
best way to call binary operators like < & > in a function? Is an
ifelse
statement needed for each column to make filtering on it optional?
etc....
Any one with the patience to show their working version of such a
funciton would receive my undying Rdulation. With thanks in advance,
Karl
--
Karl Brand
Dept of Cardiology and Dept of Bioinformatics
Erasmus MC
Dr Molewaterplein 50
3015 GE Rotterdam
T +31 (0)10 703 2460 |M +31 (0)642 777 268 |F +31 (0)10 704 4161
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