One-Hot Encoding in [R] | Categorical to Dummy Variables [duplicate]

by 
dd <- read.table(text="
   RACE        AGE.BELOW.21     CLASS
   HISPANIC          0          A
   ASIAN             1          A
   HISPANIC          1          D
   CAUCASIAN         1          B",
  header=TRUE)


  with(dd,
       data.frame(model.matrix(~RACE-1,dd),
                  AGE.BELOW.21,CLASS))
 ##   RACEASIAN RACECAUCASIAN RACEHISPANIC AGE.BELOW.21 CLASS
 ## 1         0             0            1            0     A
 ## 2         1             0            0            1     A
 ## 3         0             0            1            1     D
 ## 4         0             1            0            1     B

The formula ~RACE-1 specifies that R should create dummy variables from the RACE variable, but suppress the intercept (so that each column represents whether an observation comes from a specified category); the default, without -1, is to make the first column an intercept term (all ones), omitting the dummy variable for the baseline level (first level of the factor) from the model matrix.

More generally, you might want something like

 dd0 <- subset(dd,select=-CLASS)
 data.frame(model.matrix(~.-1,dd0),CLASS=dd$CLASS)

Note that when you have multiple categorical variables you will have to something a little bit tricky if you want full sets of dummy variables for each one. I would think of cbind()ing together separate model matrices, but I think there’s also some trick for doing this all at once that I forget …

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