I would consider trying the plyr package using the llply function.
With something like:
require(plyr)
func <- function(xx)
{
xx[is.na(xx)] <- 0
return(xx)
}
llply(your.df.list, func)
What I wondering is why you want to do this.
Best,
Tal
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On Mon, May 31, 2010 at 11:21 AM, Kang Min <ngokangmin@gmail.com> wrote:
> Hi,
>
> I have a list of 100 data frames, each data frame has 50 obs of 377
> variables.
>
> I would like to replace all the NAs with 0 in all the dataframes.
> Should I have a for loop for every data frame?
>
> Below is an extract of how the data looks like.
>
> List of 100
> $ :'data.frame': 50 obs. of 377 variables:
> ..$ ACHRPO: int [1:50] NA NA NA NA NA NA NA NA NA NA ...
> ..$ ACTEEX: int [1:50] NA NA NA NA NA NA NA NA NA NA ...
> ..$ ACTIML: int [1:50] NA NA NA NA NA NA NA NA NA NA ...
> ..$ ADENMA: int [1:50] NA NA NA 2 NA NA NA NA NA NA ...
>
> $ :'data.frame': 50 obs. of 377 variables:
> ..$ ACHRPO: int [1:50] NA NA NA NA NA NA NA NA NA NA ...
> ..$ ACTEEX: int [1:50] NA NA NA NA 2 NA NA NA NA NA ...
> ..$ ACTIML: int [1:50] NA NA NA NA 1 NA NA NA NA NA ...
> ..$ ADENMA: int [1:50] NA NA NA NA NA NA NA NA NA NA ...
>
> Thanks.
> Kang Min
>
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