I have multiple A* columns with corresponding B* columns (A and B have the corresponding numbers at the end of the column names).
When the REFNO value = A# value and the ‘MNGR’ is not BOB,
I need to put the value from corresponding B# column into the ‘AGE’ column and the corresponding # number in the ‘FLAG’ column

The next step is to set the same AGE and FLAG values that occurred first in the group to all employee in that group (group by MNGR, YEAR).
The A* and B* columns can be more than 10 columns.

But I got error:
Expected a 1D array, got an array with shape (8, 2)

df = pd.DataFrame({
    'EMPLID': [12, 13, 14, 15, 16, 17, 18, 19],
    'MNGR': ['BOB', 'JIM', 'RHONDA', 'RHONDA', 'JIM', 'RHONDA', 'RHONDA', 'BOB'],
    'YEAR': [2012, 2013, 2012, 2012, 2012, 2013, 2012, 2012],
    'REFNO': [2, 3, 4, 4, 5, 6, 4, 2],
    'A1': [1,3,2,4,5,4,3,1],
    'A2': [2,4,4,5,7,5,4,2],
    'A3': [3,5,8,6,8,6,5,3],
    'B1': [21,31,41,44,51,61,71,81],
    'B2': [22,32,42,45,52,62,72,82],
    'B3': [23,33,43,46,53,63,73,83]
    })

for i in(1,3):     
    df['AGE', 'FLAG'] = df.loc[(df['REFNO'] == df[f'A{i}']) & (df['MNGR'] != 'BOB'), 
                               [f'B{i}','i']]

df2 = df.groupby(['MNGR', 'YEAR']).first()

The next step is to fill every record in the group with the same AGE and FLAG that occurs first (this can be done by regular merging of df and df2)

Expected output:

   EMPLID    MNGR  YEAR  REFNO  A1  A2  A3  B1  B2  B3  AGE  FLAG
0      12     BOB  2012      2   1   2   3  21  22  23   0   0
1      13     JIM  2013      3   3   4   5  31  32  33  31   1
2      14  RHONDA  2012      4   2   4   8  41  42  43  42   2
3      15  RHONDA  2012      4   4   5   6  44  45  46  42   2
4      16     JIM  2012      5   5   7   8  51  52  53  51   1
5      17  RHONDA  2013      6   4   5   6  61  62  63  63   3
6      18  RHONDA  2012      4   3   4   5  71  72  73  42   2
7      19     BOB  2012      2   1   2   3  81  82  83  0    0