如何在函数内调用动态变量名？

Question

I need to convert categorical variables into multiple dichotomous ("dummy") variables to use in a logistic regression. Say my data frame is:

    tdf <- data.frame(first=sample(c("A", "B", "C", "D"), 100, replace=T),
                      lobe = sample(c("RUL", "RML", "RLL", "LUL", "LLL"), 100, replace=T),
                      continuous=sample(1:100, 100),
                      smoker = sample(c("never", "less20", "more20"), 100, replace=T)
                      )

I could manually do

first. <- with (tdf,  factor (first))
dummies <-  model.matrix(~ first.)
dummies <- dummies[,-1]
tdf <- cbind(tdf, dummies)

Note that it is important to call the factor "first." (or more generally, "variable.") because the dummy variables will inherit this prefix into their respective names, making it easier to identify them later ('variable1.factor2', 'variable1.factor3' etc).

My question is: How can do this using a function that would programatically assign variable names:

dummify <- function(df, vectorOfColIndices) {
  cn <- colnames(df) 
  for (i in vectorOfColIndices) {
    t. <- with (tdf,  factor (df[i])) # temporary factor
    assign (cn[i], t.) # give it the proper 'Variable.' name
    dummies <-  model.matrix(~ ????) # Stuck here: how do I call this newly created structure?
    ...
  }
}

So that I can later transform a data frame like this:

vd <- c(1,2,4) # columns that need to be converted into dummy vars
df <- dummify(df, vd)

Answer 1

dummify <- function( df , col.indicies.to.add.dummies ) {

    for ( i in names( df )[ col.indicies.to.add.dummies ] ) {

        t. <- with( df , factor( df[ , i] ) )

        dummies <-  model.matrix( ~t. ) 

        colnames( dummies ) <- paste( i , levels( t. ) , sep = "." )

        dummies <- dummies[ , -1 ]

        df <- cbind( df , dummies )

    }

    df
}

Answer 2

Agree with Dason's comment that there are not many situations in which you should have to manually create dummies. And, if you do Anthony's solution is fine. I present this alternative just for fun :)

dummify <- function(df, vectorOfColIndices) {
  for (i in vectorOfColIndices) {
    var <- paste(names(df)[i], ".", sep="")
    assign(var, df[[i]])
    df <- cbind(df, model.matrix(reformulate(var))[, -1])
  }
  return(df)
}