You can use as.matrix() to convert your data.frame to a matrix, but that
loses the speed/space advantages of colMins (as well as causing issues if
some columns are not numeric). You could write to the maintainer of the
package to ask that data.frames be directly supported. In the meantime you
could use
vapply(yourDataFrame, which.min, FUN.VALUE=NA_real_)
or
vapply(yourDataFrame, min, FUN.VALUE=NA_real_)
instead of colMins.
-Bill
On Tue, Nov 30, 2021 at 10:55 AM Stephen H. Dawson, DSL via R-help <
r-help@r-project.org> wrote:
> Hi,
>
>
> I am working to understand the Rfast functions of colMins and colMaxs. I
> worked through the example listed on page 54 of the PDF.
>
> https://cran.r-project.org/web/packages/Rfast/index.html
>
> https://cran.r-project.org/web/packages/Rfast/Rfast.pdf
>
> My data is in a CSV file. So, I bring it into R Studio using:
> Data <- read.csv("./input/DataSet05.csv", header=T)
>
> However, I read the instructions listed on page 54 of the PDF saying I
> need to bring data into R using a matrix. I think read.csv brings the
> data in as a dataframe. I think colMins is failing because it is looking
> for a matrix but finds a dataframe.
>
> > colMaxs(Data)
> Error in colMaxs(Data) :
> Not compatible with requested type: [type=list; target=double].
> > colMins(Data, na.rm = TRUE)
> Error in colMins(Data, na.rm = TRUE) :
> unused argument (na.rm = TRUE)
> > colMins(Data, value = FALSE, parallel = FALSE)
> Error in colMins(Data, value = FALSE, parallel = FALSE) :
> Not compatible with requested type: [type=list; target=double].
>
> QUESTION
> What is the best practice to bring a csv file into R Studio so it can be
> accessed by colMaxs and colMins, please?
>
>
> Thanks,
> --
> *Stephen Dawson, DSL*
> /Executive Strategy Consultant/
> Business & Technology
> +1 (865) 804-3454
> http://www.shdawson.com <http://www.shdawson.com>
>
> ______________________________________________
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> and provide commented, minimal, self-contained, reproducible code.
>
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