Creating a class based on Pandas.DataFrame using the pandas.read_csv() function to initialize

Question

My goal is to create an object that behaves the same as a Pandas DataFrame, but with a few extra methods of my own on top of it. As far as I understand, one approach would be to extend the class, which I first tried to do as follows:

class CustomDF(pd.DataFrame):
    def  __init__(self, filename):
        self = pd.read_csv(filename)

But I get errors when trying to view this object, saying: 'CustomDF' object has no attribute '_data'.

My second iteration was to instead not inherit the object, but rather import it as a DataFrame into one of the object attributes, and have the methods work around it, like this:

class CustomDF():

    def  __init__(self, filename):
        self.df = pd.read_csv(filename)

    def custom_method_1(self,a,b,...):
        ...

    def custom_method_2(self,a,b,...):
        ...

This is fine, except that for all custom methods, I need to access the self.df attribute first to do anything on it, but I would prefer that my custom dataframe were just self.

Is there a way that this can be done? Or is this approach not ideal anyway?

Answer 1

The __init__ method is overwritten in your first example.

Use super and then add your custom code

class CustomDF(pd.DataFrame):
    def __init__(self, *args, **kw):
        super(CustomDF, self).__init__(*args, **kw)
        # Your code here

    def custom_method_1(self,a,b,...):
        ...