Hi petr,

Thanks for the reply.

My original data is in "comma separated variable" (csv) format with variable
names in column 1 and numeric data in the remaining columns. The "read.csv"
command reads this data set into object name "pcrdata" as a dataframe where
the variable names and numeric data are conserved (as required). However,
when I transpose the table it becomes a matrix and all the data become
"character". Using the "as.data.frame" command coerces the matrix to a
dataframe but, at the same time, changes all the data to "factor". As far as
I can see, for my analysis I need to coerce the data in the matrix, formed
by transposition of the raw data, to "factor" in row 1 and "numeric" for the
remaining rows before then converting the matrix to a dataframe, using the
"as.data.frame" command. Is this the information you required and, if so, is
what I am asking at all possible?

Best wishes,

Mike

On 17 March 2010 15:13, Petr PIKAL <petr.pikal@precheza.cz> wrote:

> Hi
>
> r-help-bounces@r-project.org napsal dne 17.03.2010 15:23:34:
>
> > I am currently trying to write a program that minimises the amount of
> work
> > required for “auditable” qPCR data. At the moment I am using an Excel
> (.csv)
> > spreadsheet as source data that has been transposed to the column format
> > required for R to read. Unfortunately, this means I have* *to manually
> > confirm the whole data set prior to doing any analysis, which is taking
> a
> > considerable amount of time! My idea now is to read the raw data in
> directly
> > and get R to do the transformation prior to analysis. The problem I now
> have
> > is that, upon transposition, the data are converted to “character” in a
> > matrix, rather than “factor” and “numeric” in a dataframe. I have
> succeeded
> > in changing the matrix to a dataframe (via as.data.frame(object)), but
> this
> > then converts all the data to “factor” which I can’t use for my analysis
> > since, other than the column headings, I need the data to be numeric. I
> have
> > tried coercing the data to numeric using the as() and as.numeric()
> commands,
> > but this has no effect on the data format. I have no experience in
> > programming and so am at a loss as to what to do: am I making a basic
> error
> > in my programming or missing something essential (or both!)?
> >
> >
> >
> > I am using R version 2.9.0 at the moment, but this will change as soon
> as I
> > have sorted this issue out. Below is the code I have put together, as
> you
> > can see it is VERY brief but essential to allow my analysis to proceed:
> >
> >
> >
> > pcrdata<-read.csv("File_path",header=FALSE)
> ^^^^^^^^^^^^^^^^
>
> This is supposed to be data frame already. As you did not show us any of
> possible clues of data type like
>
> str(pcrdata)
>
> it is difficult to say.
>
> However from your description your original data are in columns which have
> numeric and character data together which is not possible. I believe that
> there are options for reading such data.
>
> >
> > pcrdata<-as.data.frame(t(pcrdata))
>
> OK. Here you say you get data in columns but they are all character.
>
> >
> > pcrdata[2:51]<-as.numeric(as.character(pcrdata))
> >
>
> Here it depends whether they are all numeric or if some of them shall be
> character (factor). Functions like those above can not be used directly on
> data frames. You need to use apply.
>
> apply(pcrdata, 1, as.character)
>
> Exact sequence of required functions is impossible to guess without
> knowing structure of your objects.
>
> You shall also consult R intro and R data manuals.
>
> Regards
> Petr
>
>
> >
> >
> > Any help would be gratefully appreciated,
> >
> >
> >
> > Mike Glanville
> >
> >    [[alternative HTML version deleted]]
> >
> > ______________________________________________
> > R-help@r-project.org mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html<http://www.r-project.org/posting-guide.html>
> > and provide commented, minimal, self-contained, reproducible code.
>
>

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