Pandas hierarchical data - copy data for all "child" values ​​that have the same "parent" value

Question

I am trying to figure out a way to transfer data, in this case user information ('email_address', 'name') for all sub-companies ('companyID') that belong to the same parent company ('parent_companyID').

My sample DataFrame:

In [1]: sample_data = pd.DataFrame(
{'companyID': {0: 112, 1: 223, 2: 434, 3: 777, 4: 790},
 'email_address': {0: '[e-mail]',  1: '', 2: '[e-mail]', 3: '[e-mail]', 4: ''},
 'name': {0: 'Joe', 1: '', 2: '', 3: '', 4: 'George'},
 'parent_companyID': {0: 555, 1: 555, 2: 555, 3: 999, 4: 999}}
)

or for better readability:

    companyID   email_address        name    parent_companyID
0   112         [e-mail]   Joe         555
1   223                                          555
2   434         [e-mail]               555
3   777         [e-mail]               999
4   790                              George      999

I searched many times and did not seem to find a similar question that helped me solve this problem. I made a lot of hits by doing this through MultiIndex, but did not achieve anything close to the desired result, which:

    companyID   email_address        name    parent_companyID
0   112         [e-mail]   Joe         555
1   112                                          555
2   112         [e-mail]               555
3   223         [e-mail]   Joe         555
4   223                                          555
5   223         [e-mail]               555
6   434         [e-mail]   Joe         555
7   434                                          555    
8   434         [e-mail]               555
9   777         [e-mail]               999
10  777                              George      999
11  790         [e-mail]               999
12  790                              George      999

- , , , . , , , . , , , . , , ! ...

Answer 1

Self Merge!

• pd.merge
• , 'companyID', ,
• 'companyID' ... , ' ' . , str.strip
• , , .

---

on = 'parent_companyID'
mrg = sample_data.merge(sample_data, on=on, suffixes=[' ', ''])
cols = sample_data.columns.tolist()
cols.remove('companyID')
cols.insert(0, 'companyID ')
mrg[cols].rename(columns=str.strip)

    companyID       email_address     name  parent_companyID
0         112  [e-mail]  112Name               555
1         112                                            555
2         112  [e-mail]                        555
3         223  [e-mail]  112Name               555
4         223                                            555
5         223  [e-mail]                        555
6         434  [e-mail]  112Name               555
7         434                                            555
8         434  [e-mail]                        555
9         777  [e-mail]                        999
10        777                      790Name               999
11        790  [e-mail]                        999
12        790                      790Name               999