Pandas Inconsistent results between 'nlargest' and 'sort_values' function

df = pd.DataFrame({'a': [-2, -1, 1, 10, 8, 11, -1],
       'b': list('abdceff'),
       'c': [1.0, 2.0, 4.0, 3.2, np.nan, 3.0, 4.0]})    

df
Out[316]: 
    a  b    c
0  -2  a  1.0
1  -1  b  2.0
2   1  d  4.0
3  10  c  3.2
4   8  e  NaN
5  11  f  3.0
6  -1  f  4.0

df.nlargest(5, ['a', 'c'])
Out[317]: 
    a  b    c
6  -1  f  4.0
5  11  f  3.0
3  10  c  3.2
4   8  e  NaN
2   1  d  4.0

df.sort_values(by=['a','c'], ascending=False).head(5)
Out[318]: 
    a  b    c
5  11  f  3.0
3  10  c  3.2
4   8  e  NaN
2   1  d  4.0
6  -1  f  4.0

I think their results should be the same.

Comment From: TomAugspurger

nlargest doesn't sort the values (which is part of why it's faster).

You can sort afterwards.

In [32]: df.sort_values(['a', 'c'], ascending=False).head(5)
Out[32]:
    a  b    c
5  11  f  3.0
3  10  c  3.2
4   8  e  NaN
2   1  d  4.0
6  -1  f  4.0

In [33]: df.nlargest(5, ['a', 'c']).sort_values(['a', 'c'], ascending=False)
Out[33]:
    a  b    c
5  11  f  3.0
3  10  c  3.2
4   8  e  NaN
2   1  d  4.0
6  -1  f  4.0