[FIXED] Find intersections in all dataset rows

Issue

I need to write a function.

It takes any value from the dataset as input and should look for an intersection in all rows.

For example: phone = 87778885566

The table is represented by the following fields:

1. key
2. id
3. phone
4. email

Test data:

• 1; 12345; 89997776655; [email protected]
• 2; 54321; 87778885566; [email protected]
• 3; 98765; 87776664577; [email protected]
• 4; 66678; 87778885566; [email protected]
• 5; 34567; 84547895566; [email protected]
• 6; 34567; 89087545678; [email protected]

The output should be:

• 2; 54321; 87778885566; [email protected]
• 4; 66678; 87778885566; [email protected]
• 5; 34567; 84547895566; [email protected]
• 6; 34567; 89087545678; [email protected]

It should check all values ​​and if values ​​intersect somewhere, return a dataset with intersections.

Solution

You could use recurssion:

import numpy as np

def relation(dat, values):
    d = dat.apply(lambda x: x.isin(values.ravel()))
    values1 = dat.iloc[np.unique(np.where(d)[0]),:]
    if set(np.array(values)) == set(values1.to_numpy().ravel()):
        return values1
    else:
        return relation(dat, values1.to_numpy().ravel())

relation(df.astype(str), np.array(['87778885566']))

       1            2               3
1  54321  87778885566   [email protected]
3  66678  87778885566  [email protected]
4  34567  84547895566  [email protected]
5  34567  89087545678  [email protected]

Answered By - onyambu