Python:如何从一个数据帧中行查找数据,并基于列匹配在另一个数据帧中乘法

使用 mul 对于多个by Series 创建人 set_index :

df3 = df1.mul(df2.set_index('name')['factor'])
print (df3)
    A   B   C   D
0  20  27  36  32
1  10  12  16  72
2  10  30  24  32
3  18  27  36  32
4   8  21  40  56
5  18  21  16  64
6  10  21  32  72
7  20  12  40  48

详细信息:

print (df2.set_index('name')['factor'])
name
A    2
B    3
C    4
D    8
Name: factor, dtype: int64

编辑:

如果缺少某些类别,则可能使用 fillna 谢谢 Wen :

s = df2.set_index('name').drop('D')['factor']
print (s)
name
A    2
B    3
C    4
Name: factor, dtype: int64

df3 = df1.mul(s).fillna(df1)
print (df3)
      A     B     C    D
0  20.0  27.0  36.0  4.0
1  10.0  12.0  16.0  9.0
2  10.0  30.0  24.0  4.0
3  18.0  27.0  36.0  4.0
4   8.0  21.0  40.0  7.0
5  18.0  21.0  16.0  8.0
6  10.0  21.0  32.0  9.0
7  20.0  12.0  40.0  6.0

编辑1:

如果需要比较 DataFrame 通过 系列 :

s = df2.set_index('name')['factor']
print (s)
name
A    2
B    3
C    4
D    8
Name: factor, dtype: int64

df1['A'] = (np.log(df1['A']) * s['A']) ** 3
print (df1)
           A   B   C  D
0  97.664572   9   9  4
1  33.351293   4   4  9
2  33.351293  10   6  4
3  84.862013   9   9  4
4  21.313578   7  10  7
5  84.862013   7   4  8
6  33.351293   7   8  9
7  97.664572   4  10  6

对于所有列:

df1 = (np.log(df1) * s) ** 3
print (df1)
           A           B           C            D
0  97.664572  286.409295  678.896108  1364.068975
1  33.351293   71.933325  170.508622  5431.168861
2  33.351293  329.617932  368.145163  1364.068975
3  84.862013  286.409295  678.896108  1364.068975
4  21.313578  198.944581  781.316579  3772.578718
5  84.862013  198.944581  170.508622  4603.732789
6  33.351293  198.944581  575.466599  5431.168861
7  97.664572   71.933325  781.316579  2945.161306