[R] Seeking to Dummify Categorical Variables

[David Winsemius]

> On Apr 2, 2017, at 11:48 AM, BR_email <br at dmstat1.com> wrote:
> 
> Hi R'ers:
> I need a jump start to obtain my objective.
> Assistance is greatly appreciated.
> Bruce
> 
> *******
> #Given Gender Dataset
> r1       <- c( 1, 2, 3)
> c1       <- c( "male", "female", "NA")
> GENDER <- data.frame(r1,c1)
> names(d1_3) <- c("ID","Gender")

#ITYM:
names(GENDER) <- c("ID","Gender")

> GENDER
> --------------
> _OBJECTIVE_: To dummify GENDER,
> i.e., to generate two new numeric columns,
>        Gender_male and Gender_female,
> such that:
> when Gender="male"   then Gender_male=1 and Gender_female=0
> when Gender="female" then Gender_male=0 and Gender_female=1
> when Gender="NA"     then Gender_male=0 and Gender_female=0
> 
> So, with the given dataset, the resultant dataset would be as follows:
> Desired Extended Gender Dataset
> ID Gender Gender_male Gender_female
> 1      male              1                   0
> 2   female              0                   1
> 3       NA               0                   0

With that correction I think you might want:

> model.matrix( ID ~ Gender+0, data=GENDER )
  Genderfemale Gendermale GenderNA
1            0          1        0
2            1          0        0
3            0          0        1
attr(,"assign")
[1] 1 1 1
attr(,"contrasts")
attr(,"contrasts")$Gender
[1] "contr.treatment"

If you assigned that to an object name, say "obj" you could get your desired result with:

> obj <- model.matrix( ID ~ Gender+0, data=GENDER )
> cbind(GENDER[ , 1, drop=FALSE], obj[,-3] )
  ID Genderfemale Gendermale
1  1            0          1
2  2            1          0
3  3            0          0


I get the sense that you are trying to replicate a workflow that you developed in some other language and I think it would be more efficient for you to actually learn R rather than trying to write SAS or SPSS in R. If you like getting "into the weeds" of the language then I suggest trying to read the code in the `lm` function. It might help to refer back to Venables and Ripley's "S Programming" or reading Wickham's "Advanced R" pages on the web.

-- 
> Bruce Ratner, Ph.D.
> 
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David Winsemius
Alameda, CA, USA