[R] Structuring data for Correspondence Analysis

[John Kane]

Hi Alfredo,
I have not used SAS nor done a correspondence analysis in many years
but to give R-help readers an idea of what you are doing, we probably
need a short statement of the substantive  problem  that would lead to
the SAS program:
proc corresp data=table dim=2 outc=_coord;
   table Preference, Sex Age Time;

I believe that there are several packages in R that will do a
correspondence analysis (For one see
https://www.statmethods.net/advstats/ca.html). Have you checked out
any of the packages? If so which one are you thinking of using?

Next, we need to see some sample data. Have a look at these two links
that may help you give us more information on the problem and what you
are looking for.  It is important to supply some sample data. It does
not have to be much.  The very best way to supply the sample data is
to use the dput() function that you will find described in the links.

http://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example

 http://adv-r.had.co.nz/Reproducibility.html

On Fri, 29 Mar 2019 at 17:35, jim holtman <jholtman using gmail.com> wrote:
>
> I am not familiar with SAS, so what did you want your output to look like.
> There is the 'table' function that might do the job and then there is
> always 'dplyr' which can do the hard stuff.  So we need more information on
> what you want.
>
> Jim Holtman
> *Data Munger Guru*
>
>
> *What is the problem that you are trying to solve?Tell me what you want to
> do, not how you want to do it.*
>
>
> On Fri, Mar 29, 2019 at 6:35 AM Alfredo <alfredo.roccato using fastwebnet.it>
> wrote:
>
> > Hi, I am very new to r and need help from you to do a correspondence
> > analysis because I don't know how to structure the following data:
> >
> > Thank you.
> >
> > Alfredo
> >
> >
> >
> > library(ca,lib.loc=folder)
> >
> > table <- read.csv(file="C:\\Temp\\Survey_Data.csv", header=TRUE, sep=",")
> >
> > head (table, n=20)
> >
> >                 Preference   Sex        Age   Time
> >
> > 1           News/Info/Talk     M      25-30  06-09
> >
> > 2                Classical     F      >35    09-12
> >
> > 3          Rock and Top 40     F      21-25  12-13
> >
> > 4                     Jazz     M      >35    13-16
> >
> > 5           News/Info/Talk     F      25-30  16-18
> >
> > 6             Don't listen     F      30-35  18-20
> >
> > ...
> >
> > 19         Rock and Top 40     M      25-30  16-18
> >
> > 20          Easy Listening     F      >35    18-20
> >
> >
> >
> > In SAS I would simply do this:
> >
> > proc corresp data=table dim=2 outc=_coord;
> >
> >    table Preference, Sex Age Time;
> >
> > run;
> >
> >
> >
> > I don't know how convert in R a data frame to a frequency table to execute
> > properly this function:
> >
> > ca <- ca(<frequency table>, graph=FALSE)
> >
> >
> >         [[alternative HTML version deleted]]
> >
> > ______________________________________________
> > R-help using r-project.org mailing list -- To UNSUBSCRIBE and more, see
> > https://stat.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide
> > http://www.R-project.org/posting-guide.html
> > and provide commented, minimal, self-contained, reproducible code.
> >
>
>         [[alternative HTML version deleted]]
>
> ______________________________________________
> R-help using r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.



-- 
John Kane
Kingston ON Canada