On Dec 12, 2009, at 6:15 PM, Patrizio Frederic wrote:
hi Michael,
the following code should work
b <- a[match('first',names(a)): match('last',names(a))]
b[is.na(b)]<-0
This might not throw an error:
b <- apply(a[match('first',names(a)): match('last',names(a))], 1:2,
function(x) ifelse(is.na(x), 0, x) )
a[match('first',names(a)): match('last',names(a))] <- b
And this might actually replace a range of columns:
a[ , match('first',names(a)): match('last',names(a))] <- b
more cheer;
David
cheers,
Patrizio
2009/12/13 Michael Scharkow <mich...@underused.org>:
Dear all,
I'm stuck in a seemingly trivial task that I need to perform for many
datasets. Basically, I want to replace NA with 0 in a specified
range of
columns in a dataframe. I know the first and last column to be
recoded only
by its name.
I can select the columns starting like this
a[match('first',names(a)): match('last',names(a))]
The question is how can replace all NA with 0 in this subset of the
data?
Thanks and greetings,
Michael
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--
+-------------------------------------------------
| Patrizio Frederic, PhD
| Assistant Professor,
| Department of Economics,
| University of Modena and Reggio Emilia,
| Via Berengario 51,
| 41100 Modena, Italy
|
| tel: +39 059 205 6727
| fax: +39 059 205 6947
| mail: patrizio.frede...@unimore.it
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David Winsemius, MD
Heritage Laboratories
West Hartford, CT
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