问子类的熊猫DataFrame，更新？

EN

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)

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

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

    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