I have a DataFrame
我有一个DataFrame
Input
A B C D
0 one 50 35 1.5
1 two 30 40 2.0
2 one 50 35 3.0
3 three 40 35 3.5
4 one 40 35 2.5
and I need to apply a math function on column D and fill with it a new column E, but before I need to group columns B and C. For example the math function will applied on values 1.5 and 3.0 for couple (50,35)
我需要在D列上应用数学函数并在其中填充新的列E,但在我需要对列B和C进行分组之前。例如,数学函数将应用于值为1.5和3.0的情侣(50,35)
B C A D
50 35 one 1.5
one 3.0
40 35 three 3.5
one 2.5
30 40 two 2.0
The values are calculated with a custom function that receive in input a numpy array and output an array with same length.
这些值是使用自定义函数计算的,该函数在输入中接收numpy数组并输出具有相同长度的数组。
Output
A B C D E
0 one 50 35 1.5 4.5
1 two 30 40 2.0 4.5
2 one 50 35 3.0 3.5
3 three 40 35 3.5 6.8
4 one 40 35 2.5. 8.9
Can someone help me?
有人能帮我吗?
1 个解决方案
#1
3
I believe need GroupBy.transform for return Series with same size as original DataFrame:
我认为需要GroupBy.transform返回与原始DataFrame大小相同的Series:
def func(x):
print (x)
#custom function, e.g. multiple all together
return x.prod()
df['E'] = df.groupby(['B','C'])['D'].transform(func)
print (df)
A B C D E
0 one 50 35 1.5 4.50
1 two 30 40 2.0 2.00
2 one 50 35 3.0 4.50
3 three 40 35 3.5 8.75
4 one 40 35 2.5 8.75
#1
3
I believe need GroupBy.transform for return Series with same size as original DataFrame:
我认为需要GroupBy.transform返回与原始DataFrame大小相同的Series:
def func(x):
print (x)
#custom function, e.g. multiple all together
return x.prod()
df['E'] = df.groupby(['B','C'])['D'].transform(func)
print (df)
A B C D E
0 one 50 35 1.5 4.50
1 two 30 40 2.0 2.00
2 one 50 35 3.0 4.50
3 three 40 35 3.5 8.75
4 one 40 35 2.5 8.75