如何在熊猫中将一个* m数据帧与一个1 * m数据帧相乘？

Question

我有两个熊猫DataFrame要乘以：

frame_score: 
   Score1  Score2
0     100      80
1    -150      20
2    -110      70
3     180      99
4     125      20

frame_weights: 
   Score1  Score2
0     0.6     0.4

我试过了：

import pandas as pd
import numpy as np

frame_score = pd.DataFrame({'Score1'  : [100, -150, -110, 180, 125], 
                      'Score2'  : [80,  20, 70, 99, 20]})

frame_weights = pd.DataFrame({'Score1': [0.6], 'Score2' : [0.4]})

print('frame_score: \n{0}'.format(frame_score))
print('\nframe_weights: \n{0}'.format(frame_weights))

# Each of the following alternatives yields the same results
frame_score_weighted = frame_score.mul(frame_weights, axis=0)
frame_score_weighted = frame_score * frame_weights
frame_score_weighted = frame_score.multiply(frame_weights, axis=1)

print('\nframe_score_weighted: \n{0}'.format(frame_score_weighted))

返回：

frame_score_weighted:   
    Score1  Score2
0    60.0    32.0
1     NaN     NaN
2     NaN     NaN
3     NaN     NaN
4     NaN     NaN

第1至4行是NaN。我该如何避免呢？例如，第1行应为-90 8（-90 = -150 * 0.6; 8 = 20 * 0.4）。

例如，Numpy可以广播以匹配尺寸。

Answer 1

编辑：对于任意维度，尝试使用values类似数组的方式操作数据帧的值：

# element-wise multiplication
frame_score_weighted = frame_score.values*frame_weights.values

# change to pandas dataframe and rename columns
frame_score_weighted = pd.DataFrame(data=frame_score_weighted, columns=['Score1','Score2'])

#Out: 
   Score1  Score2
0    60.0    32.0
1   -90.0     8.0
2   -66.0    28.0
3   108.0    39.6
4    75.0     8.0

只需使用一些额外的索引来确保在进行乘法时提取所需的权重作为标量。

frame_score['Score1'] = frame_score['Score1']*frame_weights['Score1'][0]
frame_score['Score2'] = frame_score['Score2']*frame_weights['Score2'][0]

frame_score
#Out: 
   Score1  Score2
0    60.0    32.0
1   -90.0     8.0
2   -66.0    28.0
3   108.0    39.6
4    75.0     8.0