[R] Seeking to Dummify Categorical Variables

[BR_email]

Rui:
I tried your suggestion, which was not fruitful.
Another R-helper suggested the code below, which worked perfectly.
Thanks for your suggestion and time spent.

Regards,
Bruce

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


Bruce Ratner, Ph.D.
The Significant Statistician™
(516) 791-3544
Statistical Predictive Analtyics -- www.DMSTAT1.com
Machine-Learning Data Mining and Modeling -- www.GenIQ.net
  

Rui Barradas wrote:
> Hello,
>
> Try the following.
>
> GENDER$Gender_male <- as.integer(GENDER$Gender == "male")
> GENDER$Gender_female <- as.integer(GENDER$Gender == "female")
>
> Hope this helps,
>
> Rui Barradas
>
> Em 02-04-2017 19:48, BR_email escreveu:
>> 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")
>> 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
>>
>
>
>