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, eg:

df = DataFrame(pd.read_csv(path))

Answer 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                                                
>>>

Answer 2

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.

Answer 3

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

event

super(DataFrame,self).__init__()