如何在不使用 python 循环的情况下创建引用数据框和字典的当前列的条件列

我有一个数据场

import pandas as pd

df = pd.DataFrame({"type":  ["A" ,"A1" ,"A" ,"A1","B" ],
                  "group":  ["g1", "g2","g2","g2","g1"]})

我有一本字典

 dic ={"AlphaA": {"A":  {"g1":"A_GRP1",  "g2":"A_GRP2"},
                  "A1": {"g1":"A1_GRP1", "g2":"A1_GRP2"}},
       "AlphaB": {"B":  {"g1":"B_GRP1",  "g2":"B_GRP2"}},
      }

我必须创建一个列名"value"，它将使用数据框架和字典并为其指定值

Conditions to be applied:

1. 如果类型为"A"或"A1"，则应参考字典键AlphaA，获取相应组的值，并将其分配给新列
2. 如果类型为"B"，则应参考字典键AlphaB并获得相应组的值

Example of row one:
type is "A" hence refering dictionary key "AlphaA"
group is "g1
therefore :

dictt["AlphaA"]["A"]["g1"]          #would be the answer  

Required Output

 final_df = pd.DataFrame({"type" :  ["A" ,"A1" ,"A" ,"A1","B" ],
                          "group":  ["g1", "g2","g2","g2","g1"],
                          "value":  ["A_GRP1", "A1_GRP2", "A_GRP2",
                                     "A1_GRP2", "B_GRP1"]})

I was able to achieve this using loops but its is taking lot of time,
hence looking for some speedy technique.