pandas -在两列中找到具有匹配值的行，并在另一列中将值相乘 [英] Pandas - find rows with matching values in two columns and multiply value in another column

问题描述

首先假设我们在下面有一个数据框:

First suppose we have a dataframe below:

import pandas as pd
data = pd.DataFrame({'id':['1','2','3','4','5','6','7','8'], 
                     'A':['foo', 'bar', 'foo', 'bar','foo', 'bar', 'foo', 'foo'],  
                     'C':['10','10','10','30','50','60','50','8'], 
                     'D':['9','8','7','6','5','4','3','2']})
print(data)

    A   C   D   id
0   foo 10  9   1
1   bar 10  8   2
2   foo 10  7   3
3   bar 30  6   4
4   foo 50  5   5
5   bar 60  4   6
6   foo 50  3   7
7   foo 8   2   8

我想做的是找到匹配行，然后进行一些计算.

What I would like to do is find match rows and then do some calculation.

for any two ids(idx, idy) in data.iterrows():
       if idx.A == idy.A and idx.C = idy.C:
       result = idx.D * idy.D

，然后生成一个具有三列['id']，['A']和['result']的新数据框.

and then generate a new dataframe with three columns ['id'], ['A'] and ['result'].

因此，预期结果的几行是:

So a few rows of expected result is:

     id   A   result   
0    1   foo   63   
1    3   foo   63   
2    5   foo   15
3    7   foo   15

我尝试过，但是结果是错误的逻辑或错误的代码/数据格式. 有人可以帮我吗?

I have tried but the results are either wrong logic or wrong code/data format. Can someone give me a hand please?

推荐答案

一种方法是对A + C进行分组，对产品进行计数并进行计数，过滤掉组中只有一个项目的项目，然后进行内部合并原始帧的A + C，例如:

One way is to groupby A + C, take the product and count, filter out those that only have a single item in the group, then inner merge back on A + C to your original frame, eg:

df.merge(
    df.groupby(['A', 'C']).D.agg(['prod', 'count'])
    [lambda r: r['count'] > 1],
    left_on=['A', 'C'],
    right_index=True
)

给你:

     A   C  D  id  prod  count
0  foo  10  9   1    63      2
2  foo  10  7   3    63      2
4  foo  50  5   5    15      2
6  foo  50  3   7    15      2

然后适当地拖放/重命名列.

Then drop/rename columns as appropriate.

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