Pandas groupby意味着 - 进入数据帧？

Question

说我的数据看起来像这样:

date,name,id,dept,sale1,sale2,sale3,total_sale
1/1/17,John,50,Sales,50.0,60.0,70.0,180.0
1/1/17,Mike,21,Engg,43.0,55.0,2.0,100.0
1/1/17,Jane,99,Tech,90.0,80.0,70.0,240.0
1/2/17,John,50,Sales,60.0,70.0,80.0,210.0
1/2/17,Mike,21,Engg,53.0,65.0,12.0,130.0
1/2/17,Jane,99,Tech,100.0,90.0,80.0,270.0
1/3/17,John,50,Sales,40.0,50.0,60.0,150.0
1/3/17,Mike,21,Engg,53.0,55.0,12.0,120.0
1/3/17,Jane,99,Tech,80.0,70.0,60.0,210.0

我想要一个新列average,这是total_sale每个name,id,dept元组的平均值

我试过了

df.groupby(['name', 'id', 'dept'])['total_sale'].mean()

这确实返回了一个平均值的系列:

name  id  dept 
Jane  99  Tech     240.000000
John  50  Sales    180.000000
Mike  21  Engg     116.666667
Name: total_sale, dtype: float64

但我如何参考数据？该系列是一维形状(3,).理想情况下,我希望将其放回具有适当列的数据框中,以便我可以正确引用name/id/dept.

Answer 1

如果你调用.reset_index()你拥有的系列,它将为你提供一个你想要的数据帧(索引的每个级别将被转换为一列):

df.groupby(['name', 'id', 'dept'])['total_sale'].mean().reset_index()

编辑:响应OP的评论,将此列添加回原始数据框有点棘手.您没有与原始数据框中相同的行数,因此您无法将其指定为新列.但是,如果您将索引设置为相同,pandas则智能并且将为您正确填写值.试试这个:

cols = ['date','name','id','dept','sale1','sale2','sale3','total_sale']
data = [
['1/1/17', 'John', 50, 'Sales', 50.0, 60.0, 70.0, 180.0],
['1/1/17', 'Mike', 21, 'Engg', 43.0, 55.0, 2.0, 100.0],
['1/1/17', 'Jane', 99, 'Tech', 90.0, 80.0, 70.0, 240.0],
['1/2/17', 'John', 50, 'Sales', 60.0, 70.0, 80.0, 210.0],
['1/2/17', 'Mike', 21, 'Engg', 53.0, 65.0, 12.0, 130.0],
['1/2/17', 'Jane', 99, 'Tech', 100.0, 90.0, 80.0, 270.0],
['1/3/17', 'John', 50, 'Sales', 40.0, 50.0, 60.0, 150.0],
['1/3/17', 'Mike', 21, 'Engg', 53.0, 55.0, 12.0, 120.0],
['1/3/17', 'Jane', 99, 'Tech', 80.0, 70.0, 60.0, 210.0]
]
df = pd.DataFrame(data, columns=cols)

mean_col = df.groupby(['name', 'id', 'dept'])['total_sale'].mean() # don't reset the index!
df = df.set_index(['name', 'id', 'dept']) # make the same index here
df['mean_col'] = mean_col
df = df.reset_index() # to take the hierarchical index off again

Answer 2

添加 to_frame

df.groupby(['name', 'id', 'dept'])['total_sale'].mean().to_frame()

Answer 3

你很亲近。您只需要在周围添加一组括号[['total_sale']]来告诉 python 选择作为数据框而不是系列：

df.groupby(['name', 'id', 'dept'])[['total_sale']].mean()

如果您想要所有列：

df.groupby(['name', 'id', 'dept'], as_index=False).mean()[['name', 'id', 'dept', 'total_sale']]