Should be a faster way to get numerical values for categorical data
#### Code Sample, a copy-pastable example if possible

Running the following with a huge DataFrame with lots of variance within "huge_col" can often cause massive memory overuse:
`pd.get_dummies(huge_df["huge_col"]).values.argmax(1) #times out`

The point here, of course, is to be able to convert the elements of "huge_col" into a column of integers rather than the one-hot coded vectors that `pd.get_dummies()` returns. However, this method of doing so is inefficient since it expands out the one-hot coded vectors in memory. Adding an option to `get_dummies` to allow for integer return values or introducing a different function seems like an ideal solution to this issue. If there is an alternative, straightforward solution that's recommended, please do suggest!

Thanks.
