i have a pandas dataframe contains many columns like Name, Email, Mobile Number etc. . which looks like this :

```
Sr No.    Name    Email              Mobile Number
1.        John    joh***@gmail.com   1234567890,2345678901
2.        kylie   k.ki**@yahoo.com   6789012345
3.        jon     null               1234567890
4.        kia     kia***@gmail.com   6789012345
5.        sam     b.sam**@gmail.com  4567890123

```

I want to remove the rows which contains same Mobile Number. One person can have more than one number. I done this through *drop\_duplicates* function. I tried this:

```
newdf = df.drop_duplicates(subset = ['Mobile Number'],keep=False)

```

Here is output :

```
Sr No.    Name    Email              Mobile Number
1.        John    joh***@gmail.com   1234567890,2345678901
3.        jon     null               1234567890
5.        sam     b.sam**@gmail.com  4567890123

```

But the problem is it only removes the rows which are exactly same. but i want to remove the row which contains at least one same number *i.e Sr. No. 1 and 3* they have one same number. How can i remove them so the final output looks like this :

```
 final output:
 Sr No.    Name    Email              Mobile Number
 5.        sam     b.sam**@gmail.com  4567890123

```