查找 2 pandas 之间的值，如果找到则进行计算

Question

我有两个数据框，一个是选择标准，另一个是结果。我需要查看结果以查看它们是否与选择匹配，如果匹配则执行计算，我相信我可能使用了错误的方法，虽然它让我接近答案，但我需要第二行的结果应该是 16.0但是显示 0.0 ， PS 希望我已经使用代码正确格式化，然后为结果加上块引号？干杯

import pandas as pd
import numpy as np

Sel = {'ID':[123,123,123,123,123],
        'M': [2,2,2,2,2],
        'R': [1,1,3,4,5],
        'S': [10,10,1,2,3],
       'BT': ['W','P','W','W','W'],
        'A': [10.0,10.0,10.0,10.0,10.0]
       
       }

df_sel = pd.DataFrame(Sel, columns = ['ID','M', 'R', 'S','BT','A'])

print (df_sel)

    ID  M  R   S BT     A
0  123  2  1  10  W  10.0
1  123  2  1  10  P  10.0
2  123  2  3   1  W  10.0
3  123  2  4   2  W  10.0
4  123  2  5   3  W  10.0

Res = {#'ID':[123,123,123,123,123],
        'M': [2,2,2,2,2],
        'R': [1,3,1,4,5],
        'S': [10,10,10,7,6],
       'BT': ['W','P','P','W','W'],
        'A': [3.6,1.6,1.5,5.6,6.0]
       }

df_res = pd.DataFrame(Res, columns = ['M', 'R', 'S', 'BT','A'])

print (df_res)

   M  R   S BT    A
0  2  1  10  W  3.6
1  2  3  10  P  1.6
2  2  1  10  P  1.5
3  2  4   7  W  5.6
4  2  5   6  W  6.0

# create a list of our conditions
conditions = [
    (df_sel['M'] == df_res['M']) & (df_sel['R'] == df_res['R']) & (df_sel['BT'] == df_res['BT']) & (df_sel['S'] == df_res['S']),
    (df_sel['M'] == df_res['M']) & (df_sel['R'] == df_res['R']) & (df_sel['BT'] == df_res['BT']) & (df_sel['S'] != df_res['S'])
    ]

# create a list of the values we want to assign for each condition
values = [df_sel['A']*df_res['A'],0.0]

# create a new column and use np.select to assign values to it using our lists as arguments
df_sel['result'] = np.select(conditions, values)

# display updated DataFrame
df_sel.head()

     ID   M   R   S   BT  A   result
0 123 2   1   10  W   10.0    36.0
1 123 2   1   10  P   10.0    0.0
2 123 2   3   1   W   10.0    0.0
3 123 2   4   2   W   10.0    0.0
4 123 2   5   3   W   10.0    0.0

Answer 1

您可以使用左连接 DataFrame.merge by all columns, so for not matched get misisng values, which are replaced by 0 in Series.mul method, DataFrame.pop 用于使用和删除列 A_:

df = df_sel.merge(df_res, on=['M','R','BT','S'], how='left', suffixes=('','_'))

df['result'] = df['A'].mul(df.pop('A_'), fill_value=0)

print (df)
    ID  M  R   S BT     A  result
0  123  2  1  10  W  10.0    36.0
1  123  2  1  10  P  10.0    15.0
2  123  2  3   1  W  10.0     0.0
3  123  2  4   2  W  10.0     0.0
4  123  2  5   3  W  10.0     0.0

查找 2 pandas 之间的值，如果找到则进行计算

Looking up values between 2 pandas and if found do a calculation

python

lookup

dataframe

pandas