如何获得 pandas 系列的元素逻辑非? [英] How can I obtain the element-wise logical NOT of a pandas Series?

问题描述

我有一个包含布尔值的熊猫 Series 对象.如何获得包含每个值的逻辑 NOT 的系列?

I have a pandas Series object containing boolean values. How can I get a series containing the logical NOT of each value?

例如，考虑一个包含以下内容的系列:

For example, consider a series containing:

True
True
True
False

我想得到的系列将包含:

The series I'd like to get would contain:

False
False
False
True

这看起来应该相当简单，但显然我把我的魔力放错了地方 =(

This seems like it should be reasonably simple, but apparently I've misplaced my mojo =(

推荐答案

要反转布尔系列，

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

使用 Python2.7、NumPy 1.8.0、Pandas 0.13.1:

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

从 Pandas 0.13.0 开始，Series 不再是 numpy.ndarray 的子类；它们现在是 pd.NDFrame 的子类.这可能与为什么 np.invert(s) 不再像 ~s 或 -s 一样快.

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.

警告:timeit 结果可能因许多因素而异，包括硬件、编译器、操作系统、Python、NumPy 和 Pandas 版本.

Caveat: timeit results may vary depending on many factors including hardware, compiler, OS, Python, NumPy and Pandas versions.

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