加速操作

pandas has support for accelerating certain types of binary numerical and boolean operations using the numexpr library and the bottleneck libraries.
pandas 支持对特定的通过使用 numexpr库和bottleneck 库，对特定的二进制数和布尔操作进行加速。

These libraries are especially useful when dealing with large data sets, and provide large speedups. numexpr uses smart chunking, caching, and multiple cores. bottleneck is a set of specialized cython routines that are especially fast when dealing with arrays that have nans.
这些库在处理大数据集时非常有用，并且能够极大地加速运算。numexpr使用切块、缓存、与多核等手段。bottleneck是一个专用的cython API，它在处理包含 nan 的数组时速度很快。

Here is a sample (using 100 column x 100,000 row DataFrames):
请看实例（使用10万行，100列的 DataFrame）：

You are highly encouraged to install both libraries. See the section Recommended Dependencies for more installation info.
强烈建议你安装这两个库。更多信息，参见Recommended Dependencies

These are both enabled to be used by default, you can control this by setting the options:
默认情况下，这两个库都是激活的，你可以通过下列设置来更改

New in version 0.20.0.

pd.set_option('compute.use_bottleneck', False)
pd.set_option('compute.use_numexpr', False)