[R] Converting "factors" to "numeric" in a dataframe

[Petr PIKAL]

Hi Michael


r-help-bounces at r-project.org napsal dne 18.03.2010 12:02:19:

> 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,

So why not transpose only numeric part, then set it to data frame and add 
column names from first column.

Something like (untested)

pcrdata<-read.csv("File_path",header=FALSE)

numdata<-t(pcrdata[,-1])
numdata<-data.frame(numdata)
names(numdata) <- pcrdata[,1]

Regards
Petr



> 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 at precheza.cz> wrote:
> 
> > Hi
> >
> > r-help-bounces at 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]]
> > >
> > > ______________________________________________
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> > > PLEASE do read the posting guide
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> posting-guide.html>
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> >
> >
> 
>    [[alternative HTML version deleted]]
> 
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