Pandas BUGI: groupby issue with user function with mutation, and duplicate indices

Only happens when the user function mutates the input

Originally from: http://stackoverflow.com/questions/20691168/pandas-apply-to-data-frame-groupby/20705226#20705226

Could be auto-fixed or maybe just a better error report to the user (about the dups)

In [40]: df = DataFrame(dict(A = ['foo','foo','bar','bar'], B = np.random.randn(4)),index=[1,1,2,2])

In [41]: df
Out[41]: 
     A         B
1  foo  0.971425
1  foo -1.151693
2  bar  1.265031
2  bar -0.219011

[4 rows x 2 columns]

In [42]: def f(x):                                                
    x['std'] = x['B'].std()
    return x
   ....: 

Cannot straight perform the apply

In [44]: df.groupby('A').apply(f)
ValueError: cannot reindex from a duplicate axis

By using unique indices everything is ok (so straightforward to fix)

In [45]: df.reset_index().groupby('A').apply(f).set_index('index')
Out[45]: 
         A         B       std
index                         
1      foo  0.971425  1.501271
1      foo -1.151693  1.501271
2      bar  1.265031  1.049376
2      bar -0.219011  1.049376

[4 rows x 3 columns]

Comment From: TomAugspurger

Duplicate of https://github.com/pandas-dev/pandas/issues/19437