How can I obtain the element-wise logical NOT of a pandas Series?
boolean-logic, operators, pandas, python
Solution
To invert a boolean Series, use `~s`:
In [7]: s = pd.Series([True, True, False, True])
In [8]: ~s
Out[8]:
0 False
1 False
2 True
3 False
dtype: bool
Using Python2.7, NumPy 1.8.0, Pandas 0.13.1:
In [119]: s = pd.Series([True, True, False, True]*10000)
In [10]: %timeit np.invert(s)
10000 loops, best of 3: 91.8 µs per loop
In [11]: %timeit ~s
10000 loops, best of 3: 73.5 µs per loop
In [12]: %timeit (-s)
10000 loops, best of 3: 73.5 µs per loop
As of Pandas 0.13.0, Series are no longer subclasses of `numpy.ndarray`; they are now subclasses of `pd.NDFrame`. This might have something to do with why `np.invert(s)` is no longer as fast as `~s` or `-s`.
Caveat: `timeit` results may vary depending on many factors including hardware, compiler, OS, Python, NumPy and Pandas versions.
Problem
I have a pandas `Series` object containing boolean values. How can I get a series containing the logical `NOT` of each value? For example, consider a series containing: ``` True True True False ``` The series I'd like to get would contain: ``` False False False True ``` This seems like it should be reasonably simple, but apparently I've misplaced my mojo =(