如何计算在熊猫集团

Question

对不起值这么愚蠢......我想在大熊猫数据帧

m_supplier_name   m_eshop_order_number 
1 Axxxx     202-0147880-7096352 
2 Bxxxx     304-3926447-6272314 
3 Bxxxx     306-6312344-4699555 
4 Cxxxx     305-0612485-9987518 
5 Cxxxx     306-6591383-8935534 
6 Cxxxx     261620209654-1987667522016 
7 Bxxxx     306-3078039-1083529 
8 Bxxxx     305-6383385-7949949 
9 Dxxxx     P1824098 
    … … 

汇总和统计数据这是我的大熊猫查询：

print mdata.groupby(['m_supplier_name','m_order_number']).size() 

这给了我：

m_supplier_name  m_order_number 
Axxxx     028-8286652-7920300   1 
         303-2594460-9759543   1 
         303-8120802-8687554   1 
Bxxxx     302-0806465-2917902   1 
Cxxxx     252589706005-2022820755015 1 
         302-1196139-4993924   1 
         303-5646700-0910740   1 
         304-1917413-4299541   1 
         305-6425830-6893162   1 
         306-6204117-1493102   1 
Dxxxx     028-7321508-2210762   1 

但我实际上是每个供应商寻找这个。

m_supplier_name  m_order_number 
Axxxx     028-8286652-7920300   3 
         303-2594460-9759543   
         303-8120802-8687554   
Bxxxx     302-0806465-2917902   1 
Cxxxx     252589706005-2022820755015 6 
         302-1196139-4993924   
         303-5646700-0910740   
         304-1917413-4299541   
         305-6425830-6893162   
         306-6204117-1493102   
Dxxxx     028-7321508-2210762   1 

目标是存储m_order_numbers的数量在原单数据帧每行的新列。

m_supplier_name   m_eshop_order_number  m_orders_per_supplier 
1 Axxxx    202-0147880-7096352   1 
2 Bxxxx    304-3926447-6272314   4 
3 Bxxxx    306-6312344-4699555   4 
4 Cxxxx    305-0612485-9987518   3 
5 Cxxxx    306-6591383-8935534   3 
6 Cxxxx    261620209654-1987667522016 3 
7 Bxxxx    306-3078039-1083529   4 
8 Bxxxx    305-6383385-7949949   4 
9 Dxxxx    P1824098     1 
    … … 

Answer 1

可以使用transform：

mdata['m_orders_per_supplier'] = mdata.groupby('m_supplier_name')['m_supplier_name'] 
             .transform('size') 
print (mdata) 
    m_supplier_name  m_eshop_order_number m_orders_per_supplier 
1   Axxxx   202-0147880-7096352      1 
2   Bxxxx   304-3926447-6272314      4 
3   Bxxxx   306-6312344-4699555      4 
4   Cxxxx   305-0612485-9987518      3 
5   Cxxxx   306-6591383-8935534      3 
6   Cxxxx 261620209654-1987667522016      3 
7   Bxxxx   306-3078039-1083529      4 
8   Bxxxx   305-6383385-7949949      4 
9   Dxxxx     P1824098      1