One idea. If sapply were to have an rm= parameter then the
4 solutions below would reduce to:
sapply( v, "[", 3, rm=NA )
sapply( v, function(x) if (length(x)>=3) x[3], rm=NULL )
sapply( 1:10, function(x) if (x%%2==0) x^2, rm=NULL )
sapply( 1:10, function(x) if(x%%2==0)x^2 else NA, rm=NA )
---
Date: Mon, 10 Nov 2003 00:23:17 -0500 (EST)
From: Gabor Grothendieck <[EMAIL PROTECTED]>
To: <[EMAIL PROTECTED]>, <[EMAIL PROTECTED]>, <[EMAIL PROTECTED]>
Cc: <[EMAIL PROTECTED]>
Subject: Re: [R] Subsetting a list of vectors
Dirk and Ray have provided two very clever solutions which
perform transformation and selection in one go
by returning NA and NULL respectively for unwanted elements
and then eliminating the NAs and NULLs.
I thought it would be worthwhile to bring them together and
make some further minor improvements.
Note that for the NULL solution we use the fact that
if(FALSE)... with no else leg equals NULL.
Problem 1. If v is a list of vectors, get the vector which is the
third element of each vector in v. Do not include any elements
for vectors with less than 3 elements.
Here the NA solution is particularly short:
as.numeric( na.omit( sapply( v, "[", 3 ) ) )
but the NULL solution seems closer to the list comprehension idea:
unlist( sapply( v, function(x) if (length(x)>=3) x[3] ) )
Problem 2. Express this Python program in R:
# give me the squares of the even numbers from 1-10, in a list.
>>> [ x*x for x in range(1,11) if x%2 == 0]
Here the NULL Solution is both short and closer to the Python one:
unlist( sapply( 1:10, function(x) if (x%%2==0) x^2 ) )
while the NA solution is:
as.numeric(na.omit(sapply(1:10,function(x)if(x%%2==0)x^2 else NA)))
--- On Mon 11/10, Gabor Grothendieck < [EMAIL PROTECTED] > wrote:
From: Gabor Grothendieck [mailto: [EMAIL PROTECTED]
To: [EMAIL PROTECTED], [EMAIL PROTECTED], [EMAIL PROTECTED]
Cc: [EMAIL PROTECTED]
Date: Mon, 10 Nov 2003 00:23:17 -0500 (EST)
Subject: Re: [R] Subsetting a list of vectors
<br><br>Dirk and Ray have provided two very clever solutions which <br>perform
transformation and selection in one go <br>by returning NA and NULL respectively for
unwanted elements <br>and then eliminating the NAs and NULLs. <br><br>I thought it
would be worthwhile to bring them together and <br>make some further minor
improvements.<br><br>Note that for the NULL solution we use the fact that
<br>if(FALSE)... with no else leg equals NULL.<br><br><br>Problem 1. If v is a list of
vectors, get the vector which is the<br>third element of each vector in v. Do not
include any elements <br>for vectors with less than 3 elements.<br><br>Here the NA
solution is particularly short:<br><br> as.numeric( na.omit( sapply( v, "[", 3 ) ) )
<br><br>but the NULL solution seems closer to the list comprehension idea:<br><br>
unlist( sapply( v, function(x) if (length(x)>=3) x[3] ) )<br><br><br>Problem 2.
Express this Python program in R:<br> # give me the squares of the even numbers
from !
1-10, in a list. <br> >>> [ x*x for x in range(1,11) if x%2 == 0]<br><br><br>Here
the NULL Solution is both short and closer to the Python one:<br><br> unlist( sapply(
1:10, function(x) if (x%%2==0) x^2 ) )<br><br>while the NA solution is:<br><br>
as.numeric(na.omit(sapply(1:10,function(x)if(x%%2==0)x^2 else
NA)))<br><br>______________________________________________<br>[EMAIL PROTECTED]
mailing list<br>https://www.stat.math.ethz.ch/mailman/listinfo/r-help<br>
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