When exploring a data set, I often need to df.apply(pd.Series.nunique) or df.apply(lambda x: x.nunique()). How about adding this as nunique()-method parallel to DataFrame.count() (count and unique are also the two most basic infos displayed by DataFrame.describe())?
I think there are also use cases for this as a groupby-method, for example when checking a candidate primary key for different lines (values):
>>> import pandas as pd
>>> df = pd.DataFrame({'id': ['spam', 'eggs', 'eggs', 'spam'], 'value': [1, 5, 5, 2]})
>>> df.groupby('id').filter(lambda g: (g.apply(pd.Series.nunique) > 1).any())
id value
0 spam 1
3 spam 2
jorisvandenbossche, udaykumar156, sergylog and ostwalprasad
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