How can I map True/False to 1/0 in a Pandas DataFrame?

I have a column in python pandas DataFrame that has boolean True/False values, but for further calculations I need 1/0 representation. Is there a quick pandas/numpy way to do that?

EDIT: The answers below do not seem to hold in the case of numpy that, given an array with both integers and True/False values, returns dtype=object on such array. In order to proceed with further calculations in numpy, I had to set explicitly np_values = np.array(df.values, dtype = np.float64).

True is 1 in Python, and likewise False is 0*:

    >>> True == 1
    >>> False == 0

You should be able to perform any operations you want on them by just treating them as though they were numbers, as they are numbers:

    >>> issubclass(bool, int)
    >>> True * 5

So to answer your question, no work necessary - you already have what you are looking for.

  • Note I use is as an English word, not the Python keyword is - True will not be the same object as any random 1.