如何在python中使用True/False语句测试所有可能的组合? [英] How to test all possible combinations with True/False Statement in python?

问题描述

我有两个DataFrame，每个列都包含True/False语句.我正在寻找一种方法来测试所有可能的组合，并找出df1中每一行的"True"在df2中相应行中的"True"在哪里.

I have two DataFrames where each column contain True/False statements. I am looking for a way to test all possible combinations and find out where "True" for each row in df1 also is "True" in the corresponding row in df2.

参考下面的数据，逻辑将是这样的:

In reference to the data below, the logic would be something like this:

对于每行，从"Main1"列开始，测试行是否等于True，以及"Sub1"列中的行是否也为True.接下来，测试"Main1"中的行是否等于true，以及"Sub1"列中的行是否为True，而"sub2"列中的行是否也为True.在这种情况下，如果所有值均为True，则输出将为True.然后对所有列和所有可能的组合重复.

For each row, starting in column "Main1", test if row is equal to True and if row in column "Sub1" also is True. Next, test if row in "Main1" is equal to true and if rows in column "Sub1" is True and column "sub2" also is True. In this case, if all values are True, the output would be True. Then repeat for all columns and all possible combinations.

df1:

   Main1  Main2  Main3
0   True  False   True
1  False  False  False
2  False   True   True
3  False  False   True
4  False   True   True
5   True   True   True
6   True  False  False

df2:

    Sub1   Sub2   Sub3
0  False  False   True
1  False   True  False
2   True  False   True
3  False  False  False
4   True   True  False
5  False  False  False
6   True   True   True

输出将类似于以下内容.

The output would be similar to something like this.

当然，我可以手动执行此操作，但这将是及时的，并且可能会出现错误.

Of course, I could do this manually but it would be timely as well as there would be rooms for errors.

   Main1Sub1  Main1Sub1Sub2  ...  Main3Sub2Sub3  Main3Sub3
0      False          False  ...          False       True
1      False          False  ...          False      False
2      False          False  ...          False       True
3      False          False  ...          False      False
4      False          False  ...          False      False
5      False          False  ...          False      False
6       True           True  ...          False      False

[7 rows x 18 columns]

感谢您提供有关如何解决此问题的帮助！

Any help on how to tackle this problem is appreciated!

推荐答案

您可以在 pandas 中进行识别的功能所考虑的组合中所有列均等于 True 的行.我在下面提供了一个示例，其中考虑了2列或3列的所有组合.

You can use the combinations() function in itertools to extract all the possible combinations of the columns of the 2 data frames, and then use the product() function in pandas to identify the rows where all the columns in the considered combination are equal to True. I included an example below, which considers all combinations of either 2 or 3 columns.

import pandas as pd
from itertools import combinations

df1 = pd.DataFrame({"Main1": [True, False, False, False, False, True, True],
                    "Main2": [False, False, True, False, True, True, False],
                    "Main3": [True, False, True, True, True, True, False]})

df2 = pd.DataFrame({"Sub1": [False, False, True, False, True, False, True],
                    "Sub2": [False, True, False, False, True, False, True],
                    "Sub3": [True, False, True, False, False, False, True]})

df3 = df1.join(df2)

all_combinations = list(combinations(df3.columns, 2)) + \
                   list(combinations(df3.columns, 3))

for combination in all_combinations:

   df3["".join(list(combination))] = df3[list(combination)].product(axis=1).astype(bool)

df3.drop(labels=["Main1", "Main2", "Main3", "Sub1", "Sub2", "Sub3"], axis=1, inplace=True)

df3

   Main1Main2  Main1Main3  ...  Main3Sub2Sub3  Sub1Sub2Sub3
0       False        True  ...          False         False
1       False       False  ...          False         False
2       False       False  ...          False         False
3       False       False  ...          False         False
4       False       False  ...          False         False
5        True        True  ...          False         False
6       False       False  ...          False          True

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