On Thu, 26 Jun 2025 03:45:50 +0530
Daniel Lobo <danielobo9...@gmail.com> wrote:
> Hi,
>
> I have a dataframe for which all columns are numeric but categorical.
I don't understand what that means. Perhaps an example?
> There are some missing values as well
>
> Typically, I have CSV file saved in drive, and then read it using
> read.csv command
Is that relevant?
> Can I use as.matrix(na.omit(<<my dataframe loaded using read.csv>>))
> to convert such dataframe to matrix?
>
> I there any data loss or change that may occur if I use as.matrix
> command?
I think your question is too vague for anyone to be able to answer this.
> I remember that some experts recommends not to use as.matrix()
> command to convert a dataframe to matrix.
My guess is that the problem is that as.matrix() will coerce all of the
columns of a data frame to a common class, which might yield unexpected
results.
> Any guidance will be very helpful.
It's possible that data.matrix() might be useful.
But basically you should think carefully about what the nature of the
entries of your data frame could possibly be, and then design your code
to accommodate all of these possibilities, throwing an error if any
entry does not conform to any of the possibilities that you envisage.
cheers,
Rolf Turner
--
Honorary Research Fellow
Department of Statistics
University of Auckland
Stats. Dep't. (secretaries) phone:
+64-9-373-7599 ext. 89622
Home phone: +64-9-480-4619
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