Fabrizio Pollastri wrote:
> Ok. To be more clear, consider the real python package Pandas.
>
> This package defines a Series class and a DataFrame class.
> The DataFrame is a matrix that can have columns of
> different type.
>
> If I write
>
> import pandas as pd
> df = pd.DataFrame({'A':[1,2,3],'B':[4,5,6]})
>
> a data frame with two cols named A and B is created.
>
> If I write
>
> col_A = df['A']
>
> the returned col_A is an instance of Series.
>
> Now , let suppose that I want to extend some functionality of pandas
> by adding new methods to both Series and DataFrame classes.
>
> One way to do this is to redefine this classes in a new package
> (new_pandas) as follow
>
> import pandas as pd
>
> class Series(pd.Series):
> ...
> add new methods
> ...
>
> class DataFrame(pd.DataFrame):
> ...
> add new methods
> ...
>
> When I use the new package as a pandas substitute and write
>
> import new_pandas as np
> df = np.DataFrame({'A':[1,2,3],'B':[4,5,6]})
> col_A = df['A']
>
> col_A is an instance of the original pandas and not of the new pandas,
> losing all the added functionality.
A quick look into the pandas source reveals that the following might work:
# untested
class DataFrame(pd.DataFrame):
@property
def _constructor(self):
return DataFrame # your class
# your new methods
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