本文介绍了groupby和聚合后的Python Pandas排序的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!
问题描述
我试图在对数据(熊猫)进行分组和汇总后进行排序,但我陷入了困境.我的数据:
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)
之后,我对数据进行了排序:
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
我想按from_year和out_days的总和对数据进行排序,并希望数据为:
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
我正在尝试
print(days_off_yearly.sort_values(["from_year", ("out_days", "sum")], ascending=False).head(10))
但是得到KeyError:'from_year'.
But getting KeyError: 'from_year'.
任何帮助表示赞赏.
推荐答案
您可以使用 sort_values
,但首先是reset_index
,然后是set_index
:
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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