# 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
True
>>> False == 0
True
```

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
>>> True * 5
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`

.

From: stackoverflow.com/q/17383094

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