Proper way to extend Python class

Question

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
– mypetlion, Commented Jun 29, 2018 at 19:21

jedwards · Accepted Answer · 2018-06-29 19:24:28Z

1

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:

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.

answered Jun 29, 2018 at 19:24

jedwards

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user25064 · Accepted Answer · 2018-06-29 19:24:04Z

1

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

>>> 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                                                
>>>

answered Jun 29, 2018 at 19:24

user25064

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2 Comments

Tahlor Over a year ago

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

user25064 Over a year ago

You can create an initializer method (not called __init__) that monkey patches your new attributes onto the data frame after it is created

user8886706 · Accepted Answer · 2018-06-29 19:21:40Z

0

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

event

super(DataFrame,self).__init__()

answered Jun 29, 2018 at 19:21

user8886706

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