Proper way to extend Python class

I'm looking to extend a Panda's DataFrame, creating an object where all of the original DataFrame attributes/methods are in tact, while making a few new attributes/methods available. I also need the ability to convert (or copy) objects that are already DataFrames to my new class. What I have seems to work, but I feel like I might have violated some fundamental convention. Is this the proper way of doing this, or should I even be doing it in the first place?

import pandas as pd

class DataFrame(pd.DataFrame):
def __init__(self, df):
df.__class__ = DataFrame # effectively 'cast' Pandas DataFrame as my own


the idea being I could then initialize it directly from a Pandas DataFrame, e.g.:

df = DataFrame(pd.read_csv(path))


You're mixing up inheritance and composition. Your DataFrame class both "has a" and "is a" pd.DataFrame.
– mypetlion
Jun 29 at 19:21

DataFrame

pd.DataFrame

self = df doesn't do anything
– juanpa.arrivillaga
Jun 29 at 20:33

self = df

3 Answers
3

I'd probably do it this way, if I had to:

import pandas as pd

class CustomDataFrame(pd.DataFrame):
@classmethod
def convert_dataframe(cls, df):
df.__class__ = cls
return df

def foo(self):
return "Works"


df = pd.DataFrame([1,2,3])
print(df)
#print(df.foo()) # Will throw, since .foo() is not defined on pd.DataFrame

cdf = CustomDataFrame.convert_dataframe(df)
print(cdf)
print(cdf.foo()) # "Works"


Note: This will forever change the df object you pass to convert_dataframe:

convert_dataframe

print(type(df)) # <class '__main__.CustomDataFrame'>
print(type(cdf)) # <class '__main__.CustomDataFrame'>


If you don't want this, you could copy the dataframe inside the classmethod.

If you just want to add methods to a DataFrame just monkey patch before you run anything else as below.

DataFrame

>>> import pandas
>>> def foo(self, x):
... return x
...
>>> foo
<function foo at 0x00000000009FCC80>
>>> pandas.DataFrame.foo = foo
>>> bar = pandas.DataFrame()
>>> bar
Empty DataFrame
Columns:
Index:
>>> bar.foo(5)
5
>>>


Thanks for the response, I actually wanted to add some attributes to the dataframe that specifically interact with the methods, I've updated the question
– Tahlor
Jun 29 at 20:07

You can create an initializer method (not called __init__) that monkey patches your new attributes onto the data frame after it is created
– user25064
Jun 29 at 20:10

__init__

if __name__ == '__main__':
app = DataFrame()
app()


event

super(DataFrame,self).__init__()


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