How to emulate pandas.DataFrame indexing from within a custom class?

Question

I want to define a class which does not inherit from pandas.DataFrame but sometimes acts like it. For example, I can do:

import pandas
import numpy

class FalseDF(object):
    def __init__(self, df):
        self.df = df

    def __getitem__(self, item):
        return self.df.__getitem__(item)


df = pandas.DataFrame(numpy.reshape(numpy.arange(10), (2, 5)))
print(df)

which gives:

   0  1  2  3  4
0  0  1  2  3  4
1  5  6  7  8  9

and now:

fdf = FalseDF(df)
print(fdf[3])

gives:

0    3
1    8
Name: 3, dtype: int64

How can I now make the following syntax also work?

    print(fdf.iloc[1])

or

    print(fdf.loc[2])

scnerd · Accepted Answer · 2018-05-01 21:52:26Z

1

It might not capture all the behavior of a DataFrame, but for starters you could implement __getattr__ or, much more risky, __getattribute__ to pass on requests for attributes to the underlying dataframe:

class FalseDF:
    def __getattr__(self, key):
        return getattr(self.df, key)

answered May 1, 2018 at 21:52

scnerd

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