Erin -
   Perhaps this reproducible example will help:

df = data.frame(a=sample(1:20,10000,replace=TRUE),
                b=sample(c('M','F'),10000,replace=TRUE),
                c=sample(LETTERS[1:8],10000,replace=TRUE))
tt = as.data.frame(table(df))
tt$bc = paste(tt$b,tt$c,sep='.')
tt$b=NULL
tt$c=NULL
answer = reshape(tt,idvar='a',timevar='bc',direction='wide')

                                        - Phil Spector
                                         Statistical Computing Facility
                                         Department of Statistics
                                         UC Berkeley
                                         spec...@stat.berkeley.edu



On Tue, 22 Jun 2010, Erin Hodgess wrote:

Dear R People:

I have the following data set with the columns DATE, GENDER, and Co.
Co has 8 possible options.



a.df[1:10,]
        DATE GENDER             Co
1  2009-04-16      F           Rash
2  2009-04-16      F          Other
3  2009-04-16      M      Botulinic
4  2009-04-16      M          Other
5  2009-04-16      M Constitutional
6  2009-04-16      F          Other
7  2009-04-16      M          Other
8  2009-04-16      M          Other
9  2009-04-16      F          Other
10 2009-04-16      F          Other


Using ftable, I created a table by Date, Co and Gender, which is great.




ftable(a.df$DATE,a.df$Co,a.df$GENDER)
                                F     M

2009-04-16 Botulinic           622   631
          Constitutional     1161  1124
          Gastrointestinal   1020  1029
          Hemorrhagic         472   477
          Neurological        812   777
          Other              6782  6702
          Rash                607   630
          Respiratory         962  1008
2009-04-17 Botulinic           690   626
          Constitutional     1088  1119
          Gastrointestinal   1009   984
          Hemorrhagic         509   482
          Neurological        735   794
          Other              6682  6722
          Rash                613   599
          Respiratory         970   931
2009-04-18 Botulinic           519   519
          Constitutional      953   964
          Gastrointestinal    831   898
          Hemorrhagic         416   394
          Neurological        613   693
          Other              5770  5749
          Rash                517   522
          Respiratory         794   822
2009-04-19 Botulinic           563   594
          Constitutional     1039   998
          Gastrointestinal    882   946
          Hemorrhagic         449   451
          Neurological        804   729
          Other              6022  6037
          Rash                545   529
          Respiratory         920   877

However, (because nothing would ever be that simple), I would like to
create a data frame from the ftable output.

The data frame would have 17 columns; the first is the date, and the
remaining 16 would be a column for male/Botulinic, female/Botulinic,
and so on.

Is there a good way to do this, please?

Thanks,
Erin



--
Erin Hodgess
Associate Professor
Department of Computer and Mathematical Sciences
University of Houston - Downtown
mailto: erinm.hodg...@gmail.com

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