python - How can I subclass a Pandas DataFrame?

Question

Subclassing Pandas classes seems a common need, but I could not find references on the subject. (It seems that Pandas developers are still working on it: Easier subclassing #60.)

There are some Stack?Overflow questions on the subject, but I am hoping that someone here can provide a more systematic account on currently the best way to subclass pandas.DataFrame that satisfies two, I think, general requirements:

import numpy as np
import pandas as pd

class MyDF(pd.DataFrame):
    # how to subclass pandas DataFrame?
    pass

mydf = MyDF(np.random.randn(3,4), columns=['A','B','C','D'])
print type(mydf)  # <class '__main__.MyDF'>

# Requirement 1: Instances of MyDF, when calling standard methods of DataFrame,
# should produce instances of MyDF.
mydf_sub = mydf[['A','C']]
print type(mydf_sub)  # <class 'pandas.core.frame.DataFrame'>

# Requirement 2: Attributes attached to instances of MyDF, when calling standard
# methods of DataFrame, should still attach to the output.
mydf.myattr = 1
mydf_cp1 = MyDF(mydf)
mydf_cp2 = mydf.copy()
print hasattr(mydf_cp1, 'myattr')  # False
print hasattr(mydf_cp2, 'myattr')  # False

And are there any significant differences for subclassing pandas.Series?

Answer 1

There is now an official guide on how to subclass Pandas data structures, which includes DataFrame as well as Series.

The guide is available here: https://pandas.pydata.org/pandas-docs/stable/development/extending.html#extending-subclassing-pandas

The guide mentions this subclassed DataFrame from the Geopandas project as a good example: https://github.com/geopandas/geopandas/blob/master/geopandas/geodataframe.py

As in HYRY's answer, it seems there are two things you're trying to accomplish:

1. When calling methods on an instance of your class, return instances of the correct type (your type). For this, you can just add the _constructor property which should return your type.
2. Adding attributes which will be attached to copies of your object. To do this, you need to store the names of these attributes in a list, as the special _metadata attribute.

Here's an example:

class SubclassedDataFrame(DataFrame):
    _metadata = ['added_property']
    added_property = 1  # This will be passed to copies

    @property
    def _constructor(self):
        return SubclassedDataFrame