使用transform将结果广播到所有行：

df['StoreCt'] = df.groupby(['DC', 'Retailer']).transform('size')
print(df)

# Output:
  Retailer   DC  Product  Cs Volume  Velocity  StoreCt
0      joe  ABC     bars  Cs   Cost  Velocity        1
1      joe  DFC  drinks1  Cs   Cost  Velocity        3
2      joe  DFC  drinks2  Cs   Cost  Velocity        3
3    randy  ABC     bars  Cs   Cost  Velocity        1
4    peter  DFC  drinks2  Cs   Cost  Velocity        1
5     john  XYZ   drinks  Cs   Cost  Velocity        1
6      joe  XYZ   snacks  Cs   Cost  Velocity        1
7      joe  DFC    bars2  Cs   Cost  Velocity        3

要获得输出，可以对列重新排序：

cols = ['DC', 'Retailer', 'StoreCt', 'Product', 'Cs', 'Volume', 'Velocity']
df = df[cols].sort_values(['DC', 'Retailer'], ignore_index=True)
print(df)

# Output
    DC Retailer  StoreCt  Product  Cs Volume  Velocity
0  ABC      joe        1     bars  Cs   Cost  Velocity
1  ABC    randy        1     bars  Cs   Cost  Velocity
2  DFC      joe        3  drinks1  Cs   Cost  Velocity
3  DFC      joe        3  drinks2  Cs   Cost  Velocity
4  DFC      joe        3    bars2  Cs   Cost  Velocity
5  DFC    peter        1  drinks2  Cs   Cost  Velocity
6  XYZ      joe        1   snacks  Cs   Cost  Velocity
7  XYZ     john        1   drinks  Cs   Cost  Velocity