如何基於通配符加入熊貓數據框？

Question

我有兩個dataframes DF & DF2，我想用*合併它們作爲通配符

import pandas as pd 
data = [[".",".",1],["AB.","B.",3],["B.",".",2]] 
data2 = [["A","B","1"],["ABC","BC",4],["B","A",2]] 
columns = ["Type1","Type2","Value"] 
df = pd.DataFrame(data,columns=columns) 
df2 = pd.DataFrame(data2,columns=columns) 
print(df) 
print(df2) 
    Type1 Type2 Value 
0  *  *  1 
1 AB* B*  3 
2 B*  *  2 
    Type1 Type2 Value 
0  A  B  1 
1 ABC BC  4 
2  B  A  2 

通常這裏DF2的第二行應與線1和線2 而在DF2線0應只匹配df1的第一行。 不知怎的，我想獲得像

df2.merge(df,how='left',on=["Type1","Type2"]) 

但這裏的結果不匹配任何東西。

這是我希望得到的結果。

data3 = [["A","B","1","1"],["ABC","BC",4,1],["ABC","BC",4,3],["B","A",2,1],["B","A",2,2]] 
columns3 = ["Type1","Type2","Value_x","Value_y"] 
results = pd.DataFrame(data3,columns=columns3) 
print(results) 
    Type1 Type2 Value_x Value_y 
0  A  B  1  1 
1 ABC BC  4  1 
2 ABC BC  4  3 
3  B  A  2  1 
4  B  A  2  2 

請注意，df2表實際上有超過100萬行，所以我無法承擔效率原因的循環。

Answer 1

最後我決定使用下面的代碼。這將數據幀傳輸到SQLite數據庫，然後執行連接並最終將其返回到另一個數據幀。這不是最佳的，但它的工作原理。

import sqlite3 
conn = sqlite3.connect(':memory:') 
df.to_sql('df', conn, index=False) 
df2.to_sql('df2', conn, index=False) 
query = """ 
SELECT [df2].[Type1], 
     [df2].[Type2], 
     [df2].[value], 
     [df].[value] 
FROM ([df] 
     LEFT OUTER JOIN [df2] 
        ON [df].[type1] LIKE [df2].[type1] 
        AND [df].[type2] LIKE [df2].[type2]) 
""" 
df3 = pd.read_sql_query(query, conn) 
conn.close()