stata - how do I remove one factor level in R? -

i need drop variables data frame in r. data has column 18 factors:

1. agriculture
2. fisheries ...
3. unclassified

i need remove factor #18 before creating dummy variables "the person x works in y industry". is, need keep first 17 levels (the classified levels)

in stata remove level

drop if rama1 == 99 

(rama1 factor column , 99 "unclassified")

then create dummies in stata (one binary variable per industry) run:

quietly tabulate rama1, generate(rama1_) 

that in r is:

for(i in unique(data$rama1)) { data[paste("type", i, sep="")] <- ifelse(data$rama1 == i, 1, 0) } 

any ideas? highly welcome

to remove levels, either way approached bondeddust or jlhoward works fine. create dummy variables, depend on want/how want formulated.

for example, removed factor, want rows show <na> or 0.

---

base r

the easiest way using model.matrix in base r. building on example bondeddust;

df <- data.frame(x=as.factor(sample(letters[1:5],100, replace=true)), y=1:100)  # remove e , level is.na(df$x) <- df$x == "e" df$x <- factor(df$x) 

yields this:

> head(df)      x y 1    d 1 2    c 2 3    3 4 <na> 4 5    d 5 6    6 

then, can run model.matrix dummy variables our factor level. default change nas 0.

> model.matrix(~x, df)     (intercept) xb xc xd 1             1  0  0  1 2             1  0  1  0 3             1  0  0  0 5             1  0  0  1 6             1  0  0  0 8             1  1  0  0 9             1  0  0  0 11            1  0  0  0 12            1  0  1  0 

caret

an alternative way use caret package, may give more power when running these factors/releveling across test/holdout models.

it contains dummyvars function you.

> xx <- dummyvars(~x, df) > predict(xx, df)     x.a x.b x.c x.d 1     0   0   0   1 2     0   0   1   0 3     1   0   0   0 4    na  na  na  na 5     0   0   0   1 6     1   0   0   0 7    na  na  na  na