我正在尝试在groupby
Columns
中pandas
两个df
并返回max
值。然后,我希望针对相同的max
对这些Columns
值进行排序。
这是我的尝试:
将熊猫作为pd导入
d = ({
'year' : ['2016','2016','2016','2016','2016','2015','2015','2015','2015','2014','2014','2014','2014'],
'Val' : ['A','B','D','T','S','D','T','T','U','T','T','V','C'],
'Num' : [1,2,4,5,3,6,4,3,2,5,6,1,2],
})
df = pd.DataFrame(data = d)
df = df.groupby(['year','Val']).Num.max()
输出:
year Val
2014 C 2
T 6
V 1
2015 D 6
T 4
U 2
2016 A 1
B 2
D 4
S 3
T 5
我已经尝试过产生以下内容
df = df.sort_values(['year','Num'], ascending=False)
预期输出:
year Val
2014 T 6
C 2
V 1
2015 D 6
T 4
U 2
2016 T 5
D 4
S 3
B 2
A 1
答案 0 :(得分:1)
因此,您需要groupby
和transform
sort_values
df.groupby('year').transform(pd.Series.sort_values,ascending=False)
Out[42]:
year Val
2014 C 6
T 2
V 1
2015 D 6
T 4
U 2
2016 A 5
B 4
D 3
S 2
T 1
Name: Num, dtype: int64
答案 1 :(得分:1)
使用transform对max返回的值进行排序
data = ({
'year' : ['2016','2016','2016','2016','2016','2015','2015','2015','2015','2014','2014','2014','2014'],
'Val' : ['A','B','D','T','S','D','T','T','U','T','T','V','C'],
'Num' : [1,2,4,5,3,6,4,3,2,5,6,1,2],
})
df = pd.DataFrame(data = data)
grouped = df.groupby(['year','Val']).max()
print(grouped)
print(grouped.transform(pd.Series.sort_values,ascending=False))
输出:
Num
year Val
2014 C 2
T 6
V 1
2015 D 6
T 4
U 2
2016 A 1
B 2
D 4
S 3
T 5
输出 2:
Num
year Val
2015 D 6
2014 T 6
2016 T 5
D 4
2015 T 4
2016 S 3
B 2
2015 U 2
2014 C 2
2016 A 1
2014 V 1