Thanks, it works except that I had to add xx <- as.data.frame(xx)
into func.
I am trying to calculate diversity indices using the vegan package,
and the functions require zeroes instead of NAs.
Thanks.
Kang Min
On May 31, 5:09 pm, Tal Galili wrote:
> I would consider trying the plyr package usi
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
Contact
Details:-
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
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