带有和不带有括号的python pandas函数

本文介绍了带有和不带有括号的python pandas函数的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！ 问题描述

我注意到，如果使用许多不带括号的DataFrame函数，其行为似乎类似于属性".

I notice that many DataFrame functions if used without parentheses seem to behave like 'properties' e.g.

In [200]: df = DataFrame (np.random.randn (7,2)) In [201]: df.head () Out[201]: 0 1 0 -1.325883 0.878198 1 0.588264 -2.033421 2 -0.554993 -0.217938 3 -0.777936 2.217457 4 0.875371 1.918693 In [202]: df.head Out[202]: <bound method DataFrame.head of 0 1 0 -1.325883 0.878198 1 0.588264 -2.033421 2 -0.554993 -0.217938 3 -0.777936 2.217457 4 0.875371 1.918693 5 0.940440 -2.279781 6 1.152370 -2.733546>

这是如何完成的，这是一种好的做法吗? 这是Linux上的熊猫0.15.1

How is this done and is it good practice ? This is with pandas 0.15.1 on linux

推荐答案

它们是不同的，不建议使用，一个清楚地表明这是一种方法，恰好输出结果，而另一个则显示了预期的输出.

They are different and not recommended, one clearly shows that it's a method and happens to output the results whilst the other shows the expected output.

这就是为什么您不应该这样做:

Here's why you should not do this:

In [23]: t = df.head In [24]: t.iloc[0] --------------------------------------------------------------------------- AttributeError Traceback (most recent call last) <ipython-input-24-b523e5ce509d> in <module>() ----> 1 t.iloc[0] AttributeError: 'function' object has no attribute 'iloc' In [25]: t = df.head() t.iloc[0] Out[25]: 0 0.712635 1 0.363903 Name: 0, dtype: float64

好吧，您不能使用括号正确地调用该方法并看到显示为有效的输出，但是如果您引用了该引用并尝试使用它，那么您将对方法进行操作，而不是对df的切片进行操作这不是您想要的.

So OK you don't use parentheses to call the method correctly and see an output that appears valid but if you took a reference to this and tried to use it, you are operating on the method rather than the slice of the df which is not what you intended.