Python多索引：查找具有2级索引的cordinate，DataFram

Question

我有一个带有多索引和列的空数据帧。我还有一个字符串列表，它是第二级索引的cordinate。因为我所有的第二级索引都是唯一的，所以我希望用我的字符串列表找到cordinate和输入值。看看下面的例子

df=
       DNA      Cat2                                 ....   
       Item     A   B   C   D   E   F   F   H   I   J   
DNA   Item
Cat2  A         0   0   0   0   0   0   0   0   0   0 
      B         0   0   0   0   0   0   0   0   0   0 
      C         0   0   0   0   0   0   0   0   0   0 
      D         0   0   0   0   0   0   0   0   0   0 
      E         0   0   0   0   0   0   0   0   0   0 
      F         0   0   0   0   0   0   0   0   0   0 
....

str_cord = [(A,B),(A,H),(A,I),(B,H),(B,I),(H,I)]
#and my output should be like below.

df_result=
       DNA      Cat2                                 ....   
       Item     A   B   C   D   E   F   F   H   I   J   
DNA   Item
Cat2  A         0   1   0   0   0   0   0   1   1   0 
      B         0   0   0   0   0   0   0   1   1   0 
      C         0   0   0   0   0   0   0   0   0   0 
      D         0   0   0   0   0   0   0   0   0   0 
      E         0   0   0   0   0   0   0   0   0   0 
      F         0   0   0   0   0   0   0   0   0   0 
      H         0   0   0   0   0   0   0   0   1   0
....

它看起来有点复杂，但我只想使用stru cord[0]作为df\u结果的cordinate。我试过用.loc，但似乎我需要输入一级索引。我正在寻找一种方法，我不必输入多索引level1和查找具有level2字符串的cordinate。希望有意义，提前谢谢！（哦，数据本身非常大，所以尽可能高效）

Answer 1

您可以使用：

for i, j in str_cord:
    idx = pd.IndexSlice
    df.loc[idx[:, i], idx[:, j]] = 1

样品：

L = list('ABCDEFGHIJ')
mux = pd.MultiIndex.from_product([['Cat1','Cat2'], L])

df = pd.DataFrame(0, index=mux, columns=mux)
print (df)
       Cat1                            Cat2                           
          A  B  C  D  E  F  G  H  I  J    A  B  C  D  E  F  G  H  I  J
Cat1 A    0  0  0  0  0  0  0  0  0  0    0  0  0  0  0  0  0  0  0  0
     B    0  0  0  0  0  0  0  0  0  0    0  0  0  0  0  0  0  0  0  0
     C    0  0  0  0  0  0  0  0  0  0    0  0  0  0  0  0  0  0  0  0
     D    0  0  0  0  0  0  0  0  0  0    0  0  0  0  0  0  0  0  0  0
     E    0  0  0  0  0  0  0  0  0  0    0  0  0  0  0  0  0  0  0  0
     F    0  0  0  0  0  0  0  0  0  0    0  0  0  0  0  0  0  0  0  0
     G    0  0  0  0  0  0  0  0  0  0    0  0  0  0  0  0  0  0  0  0
     H    0  0  0  0  0  0  0  0  0  0    0  0  0  0  0  0  0  0  0  0
     I    0  0  0  0  0  0  0  0  0  0    0  0  0  0  0  0  0  0  0  0
     J    0  0  0  0  0  0  0  0  0  0    0  0  0  0  0  0  0  0  0  0
Cat2 A    0  0  0  0  0  0  0  0  0  0    0  0  0  0  0  0  0  0  0  0
     B    0  0  0  0  0  0  0  0  0  0    0  0  0  0  0  0  0  0  0  0
     C    0  0  0  0  0  0  0  0  0  0    0  0  0  0  0  0  0  0  0  0
     D    0  0  0  0  0  0  0  0  0  0    0  0  0  0  0  0  0  0  0  0
     E    0  0  0  0  0  0  0  0  0  0    0  0  0  0  0  0  0  0  0  0
     F    0  0  0  0  0  0  0  0  0  0    0  0  0  0  0  0  0  0  0  0
     G    0  0  0  0  0  0  0  0  0  0    0  0  0  0  0  0  0  0  0  0
     H    0  0  0  0  0  0  0  0  0  0    0  0  0  0  0  0  0  0  0  0
     I    0  0  0  0  0  0  0  0  0  0    0  0  0  0  0  0  0  0  0  0
     J    0  0  0  0  0  0  0  0  0  0    0  0  0  0  0  0  0  0  0  0

---

str_cord = [('A','B'),('A','H'),('A','I'),('B','H'),('B','I'),('H','I')]

for i, j in str_cord:
    idx = pd.IndexSlice
    df.loc[idx[:, i], idx[:, j]] = 1

---

print (df)
       Cat1                            Cat2                           
          A  B  C  D  E  F  G  H  I  J    A  B  C  D  E  F  G  H  I  J
Cat1 A    0  1  0  0  0  0  0  1  1  0    0  1  0  0  0  0  0  1  1  0
     B    0  0  0  0  0  0  0  1  1  0    0  0  0  0  0  0  0  1  1  0
     C    0  0  0  0  0  0  0  0  0  0    0  0  0  0  0  0  0  0  0  0
     D    0  0  0  0  0  0  0  0  0  0    0  0  0  0  0  0  0  0  0  0
     E    0  0  0  0  0  0  0  0  0  0    0  0  0  0  0  0  0  0  0  0
     F    0  0  0  0  0  0  0  0  0  0    0  0  0  0  0  0  0  0  0  0
     G    0  0  0  0  0  0  0  0  0  0    0  0  0  0  0  0  0  0  0  0
     H    0  0  0  0  0  0  0  0  1  0    0  0  0  0  0  0  0  0  1  0
     I    0  0  0  0  0  0  0  0  0  0    0  0  0  0  0  0  0  0  0  0
     J    0  0  0  0  0  0  0  0  0  0    0  0  0  0  0  0  0  0  0  0
Cat2 A    0  1  0  0  0  0  0  1  1  0    0  1  0  0  0  0  0  1  1  0
     B    0  0  0  0  0  0  0  1  1  0    0  0  0  0  0  0  0  1  1  0
     C    0  0  0  0  0  0  0  0  0  0    0  0  0  0  0  0  0  0  0  0
     D    0  0  0  0  0  0  0  0  0  0    0  0  0  0  0  0  0  0  0  0
     E    0  0  0  0  0  0  0  0  0  0    0  0  0  0  0  0  0  0  0  0
     F    0  0  0  0  0  0  0  0  0  0    0  0  0  0  0  0  0  0  0  0
     G    0  0  0  0  0  0  0  0  0  0    0  0  0  0  0  0  0  0  0  0
     H    0  0  0  0  0  0  0  0  1  0    0  0  0  0  0  0  0  0  1  0
     I    0  0  0  0  0  0  0  0  0  0    0  0  0  0  0  0  0  0  0  0
     J    0  0  0  0  0  0  0  0  0  0    0  0  0  0  0  0  0  0  0  0