python pandas remove duplicates in series

Question

Is there a function to enforce that the index is unique or is it only possibly to handle this in python 'itself' by converting to dict and back or something like that?

As noted in the comments below: python pandas is a project built on numpy/scipy.

to_dict and back works, but I bet this gets slow when you get BIG.

In [24]: a = pandas.Series([1,2,3], index=[1,1,2])

In [25]: a
Out[25]: 
1    1
1    2
2    3

In [26]: a = a.to_dict()

In [27]: a
Out[27]: {1: 2, 2: 3}

In [28]: a = pandas.Series(a)

In [29]: a
Out[29]: 
1    2
2    3

Answer 1

BTW we plan on adding a drop_duplicates method to Series like DataFrame.drop_duplicates in the near future.

Answer 2

Use groupby and last()

In [279]: s
Out[279]: 
a    1
b    2
b    3
b    4
e    5

In [280]: grouped = s.groupby(level=0)

In [281]: grouped.first()
Out[281]: 
a    1
b    2
e    5

In [282]: grouped.last()
Out[282]: 
a    1
b    4
e    5