hi Michael,
the following code should work
b <- a[match('first',names(a)): match('last',names(a))]
b[is.na(b)]<-0
a[match('first',names(a)): match('last',names(a))] <- b
cheers,
Patrizio
2009/12/13 Michael Scharkow <michael at
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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> and provide commented, minimal, self-contained, reproducible code.
>
--
+-------------------------------------------------
| Patrizio Frederic, PhD
| Assistant Professor,
| Department of Economics,
| University of Modena and Reggio Emilia,
| Via Berengario 51,
| 41100 Modena, Italy
|
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