pandas: drop duplicates in groupby 'date'

Question

In the dataframe below, I would like to eliminate the duplicate cid values so the output from df.groupby('date').cid.size() matches the output from df.groupby('date').cid.nunique().

I have looked at this post but it does not seem to have a solid solution to the problem.

df = pd.read_csv('https://raw.githubusercontent.com/108michael/ms_thesis/master/crsp.dime.mpl.df')

df.groupby('date').cid.size()

date
2005       7
2006     237
2007    3610
2008    1318
2009    2664
2010     997
2011    6390
2012    2904
2013    7875
2014    3979

df.groupby('date').cid.nunique()

date
2005      3
2006     10
2007    227
2008     52
2009    142
2010     57
2011    219
2012     99
2013    238
2014    146
Name: cid, dtype: int64

Things I tried:

1. df.groupby([df['date']]).drop_duplicates(cols='cid') gives this error: AttributeError: Cannot access callable attribute 'drop_duplicates' of 'DataFrameGroupBy' objects, try using the 'apply' method
2. df.groupby(('date').drop_duplicates('cid')) gives this error: AttributeError: 'str' object has no attribute 'drop_duplicates'

Answer 1

You don't need groupby to drop duplicates based on a few columns, you can specify a subset instead:

df2 = df.drop_duplicates(["date", "cid"])
df2.groupby('date').cid.size()
Out[99]: 
date
2005      3
2006     10
2007    227
2008     52
2009    142
2010     57
2011    219
2012     99
2013    238
2014    146
dtype: int64