子类化Pandas DataFrame，可以更新吗？

Question

继承还是不继承？

关于Pandas子类化问题的最新消息是什么？（其他大多数线程都使用3-4年）。

我希望做类似…

import pandas as pd

class SomeData(pd.DataFrame):
    # Methods
    pass

ClsInstance = SomeData()

# Create a new column on ClsInstance?

Answer 1

这就是我的方法。我遵循了发现的建议：

• 子类化熊猫数据结构
• 修复完成问题

以下示例仅显示了构造的新子类的用法pandas.DataFrame。如果您按照我的第一个链接中的建议进行操作，则也可以考虑使用子类化pandas.Series，以考虑获取pandas.DataFrame子类的一维切片。

import pandas as pd
import numpy as np

class SomeData(pd.DataFrame):
    # This class variable tells Pandas the name of the attributes
    # that are to be ported over to derivative DataFrames.  There
    # is a method named `__finalize__` that grabs these attributes
    # and assigns them to newly created `SomeData`
    _metadata = ['my_attr']

    @property
    def _constructor(self):
        """This is the key to letting Pandas know how to keep
        derivative `SomeData` the same type as yours.  It should
        be enough to return the name of the Class.  However, in
        some cases, `__finalize__` is not called and `my_attr` is
        not carried over.  We can fix that by constructing a callable
        that makes sure to call `__finlaize__` every time."""
        def _c(*args, **kwargs):
            return SomeData(*args, **kwargs).__finalize__(self)
        return _c

    def __init__(self, *args, **kwargs):
        # grab the keyword argument that is supposed to be my_attr
        self.my_attr = kwargs.pop('my_attr', None)
        super().__init__(*args, **kwargs)

    def my_method(self, other):
        return self * np.sign(self - other)

示范

mydata = SomeData(dict(A=[1, 2, 3], B=[4, 5, 6]), my_attr='an attr')

print(mydata, type(mydata), mydata.my_attr, sep='\n' * 2)

   A  B
0  1  4
1  2  5
2  3  6

<class '__main__.SomeData'>

an attr



newdata = mydata.mul(2)

print(newdata, type(newdata), newdata.my_attr, sep='\n' * 2)

   A   B
0  2   8
1  4  10
2  6  12

<class '__main__.SomeData'>

an attr



newerdata = mydata.my_method(newdata)

print(newerdata, type(newerdata), newerdata.my_attr, sep='\n' * 2)

   A  B
0 -1 -4
1 -2 -5
2 -3 -6

<class '__main__.SomeData'>

an attr

陷阱

这种方法很烂 pd.DataFrame.equals

newerdata.equals(newdata)  # Should be `False`

TypeError                                 Traceback (most recent call

last)
python-input-304-866170ab179e> in ()
----> 1 newerdata.equals(newdata)
python-input-304-866170ab179e>

~/anaconda3/envs/3.6.ml/lib/python3.6/site-

packages/pandas/core/generic.py in equals(self, other)
1034 the same location are considered equal.
1035 “”“
-> 1036 if not isinstance(other, self._constructor):
1037 return False
1038 return self._data.equals(other._data)

TypeError: isinstance() arg 2 must be a type or tuple of types

发生的事情是该方法希望type在_constructor属性中找到类型的对象。相反，它找到了我可打电话的地方，以解决__finalize__我遇到的问题。

解决

equals在类定义中使用以下方法重写该方法。

    def equals(self, other):
        try:
            pd.testing.assert_frame_equal(self, other)
            return True
        except AssertionError:
            return False

newerdata.equals(newdata)  # Should be `False`

False