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python - Access index in pandas.Series.apply

Lets say I have a MultiIndex Series s:

>>> s
     values
a b
1 2  0.1 
3 6  0.3
4 4  0.7

and I want to apply a function which uses the index of the row:

def f(x):
   # conditions or computations using the indexes
   if x.index[0] and ...: 
   other = sum(x.index) + ...
   return something

How can I do s.apply(f) for such a function? What is the recommended way to make this kind of operations? I expect to obtain a new Series with the values resulting from this function applied on each row and the same MultiIndex.

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I don't believe apply has access to the index; it treats each row as a numpy object, not a Series, as you can see:

In [27]: s.apply(lambda x: type(x))
Out[27]: 
a  b
1  2    <type 'numpy.float64'>
3  6    <type 'numpy.float64'>
4  4    <type 'numpy.float64'>

To get around this limitation, promote the indexes to columns, apply your function, and recreate a Series with the original index.

Series(s.reset_index().apply(f, axis=1).values, index=s.index)

Other approaches might use s.get_level_values, which often gets a little ugly in my opinion, or s.iterrows(), which is likely to be slower -- perhaps depending on exactly what f does.


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