问题
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:
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' methoddf.groupby(('date').drop_duplicates('cid'))gives this error:AttributeError: 'str' object has no attribute 'drop_duplicates'
回答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
来源:https://stackoverflow.com/questions/37105609/pandas-drop-duplicates-in-groupby-date