Drop duplicates while preserving NaNs in pandas

Question

When using the drop_duplicates() method I reduce duplicates but also merge all NaNs into one entry. How can I drop duplicates while preserving rows with an empty entry (like np.nan, None or '')?

import pandas as pd
df = pd.DataFrame({'col':['one','two',np.nan,np.nan,np.nan,'two','two']})

Out[]: 
   col
0  one
1  two
2  NaN
3  NaN
4  NaN
5  two
6  two


df.drop_duplicates(['col'])

Out[]: 
   col
0  one
1  two
2  NaN

Answer 1

Try

df[(~df.duplicated()) | (df['col'].isnull())]

The result is :

col
0   one
1   two
2   NaN
3   NaN     
4   NaN

Answer 2

Well, one workaround that is not really beautiful is to first save the NaN and put them back in:

temp = df.iloc[pd.isnull(df).any(1).nonzero()[0]]
asd = df.drop_duplicates('col')
pd.merge(temp, asd, how='outer')
Out[81]: 
   col
0  one
1  two
2  NaN
3  NaN
4  NaN