将特定权重乘以列，然后在新列中相加 [英] Multiply specific weights to columns and add together in new column

问题描述

我有三列数据，并且想要将不同的标量值相乘，然后将它们求和成一列.假设我想将Attibute_1乘以10，将Attribute_2乘以5，将Attribute_3乘以2

I have three columns of data and want to multiply different scalar values to each and then sum them into a column. Let's suppose I want to multiply Attibute_1 by 10, Attribute_2 by 5, and Attribute_3 by 2

Attribute_1   |   Attribute_2   |   Attribute_3   |    Score    |
_________________________________________________________________
      10              10                15              180
       5               5                10               95

是否有一种类似于"sumproduct"功能的优雅解决方案?

Is there an elegant solution that is similar to a "sumproduct" kind of functionality?

例如

cols = [df['Attribute_1'], df['Attribute_2'], df['Attribute_3']]
weights = [10, 5, 2]
df['Score'] = cols * weights

我不想要以下解决方案，因为如果我有许多列和许多权重，我正在寻找更优雅的东西.

I do not want the following solution because I am looking for something more elegant if I have many columns and many weights.

df['Score'] = df['Attribute_1'] * 10 + df['Attribute_2'] * 5 + df['Attribute_3'] * 2

感谢您的帮助！

推荐答案

您可以使用mul方法:

attributes = ["Attribute_1", "Attribute_2", "Attribute_3"]
weights = [10, 5, 2]

df['Score'] = df[attributes].mul(weights).sum(1)
df

# Attribute_1   Attribute_2   Attribute_3   Score
#0         10            10            15     180
#1          5             5            10      95

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