Python Pandas 在分组和聚合后排序
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Python Pandas sorting after groupby and aggregate
提问by Tomas Rasymas
I am trying to sort data (Pandas) after grouping and aggregating and I am stuck. My data:
我试图在分组和聚合后对数据 (Pandas) 进行排序，但我被卡住了。我的数据：
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:
之后，我对我的数据进行了排序：
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:
我想按 from_year 和 out_days 总和对我的数据进行排序，并期望数据为：
out_days
sum
from_year name
2012 John4 11
John 10
John6 4
2011 John1 18
John 15
2010 John 17
I am trying
我在尝试
print(days_off_yearly.sort_values(["from_year", ("out_days", "sum")], ascending=False).head(10))
But getting KeyError: 'from_year'.
但是得到 KeyError: 'from_year'。
Any help appreciated.
任何帮助表示赞赏。
采纳答案by jezrael
You can use sort_values, but first reset_indexand then set_index:
您可以使用sort_values, 但首先reset_index然后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
