Python Pandas sorting after groupby and aggregate

Question

I am trying to sort data (Pandas) after grouping and aggregating and I am stuck. My data:

data = {'from_year': [2010, 2011, 2012, 2011, 2012, 2010, 2011, 2012], 'name': ['John', 'John1', 'John', 'John', 'John4', 'John', 'John1', 'John6'], 'out_days': [11, 8, 10, 15, 11, 6, 10, 4]} persons = pd.DataFrame(data, columns=["from_year", "name", "out_days"]) days_off_yearly = persons.groupby(["from_year", "name"]).agg({"out_days": [np.sum]}) print(days_off_yearly)

After that I have my data sorted:

 out_days sum from_year name 2010 John 17 2011 John 15 John1 18 2012 John 10 John4 11 John6 4

I want to sort my data by from_year and out_days sum and expecting data to be:

 out_days sum from_year name 2012 John4 11 John 10 John6 4 2011 John1 18 John 15 2010 John 17

I am trying

print(days_off_yearly.sort_values(["from_year", ("out_days", "sum")], ascending=False).head(10))

But getting KeyError: 'from_year'.

Any help appreciated.

jezrael · Accepted Answer · 2017-02-15 14:47:11Z

You can use sort_values, but first reset_index and then set_index:

#simplier aggregation days_off_yearly = persons.groupby(["from_year", "name"])['out_days'].sum() print(days_off_yearly) from_year name 2010 John 17 2011 John 15 John1 18 2012 John 10 John4 11 John6 4 Name: out_days, dtype: int64 print (days_off_yearly.reset_index() .sort_values(['from_year','out_days'],ascending=False) .set_index(['from_year','name'])) out_days from_year name 2012 John4 11 John 10 John6 4 2011 John1 18 John 15 2010 John 17

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