Pandas update field value with the output of another condition

Question

I have the following dataframe:

What I want to achieve is, if id1 is not equal to id2, I want to update the y values (in name column) with x value (x is when id1 equals to id2).

test = pd.DataFrame({'id1':[1, 1, 1, 2, 2, 1],
                     'id2': [1, 1, 1, 1, 1, 1],
                     'name': ['x', 'x', 'x', 'y', 'y', 'x']})

what I did is this:

test.loc[test['id1'] != test['id2'], 'name'] = test[test['id1'] == test['id2']]['name'].tolist()[0]

It works well, but I don't like the way I solved it (because of this .tolist()[0]). I feel there is another more correct solution.

Edit:

Sometimes we don't have id1==id2 in this Dataframe, so my solution will produce an error, because there no elements in test[test['id1'] == test['id2']]['name'].tolist()[0].

Answer 1

So you can use where then ffill / bfill and fillna to leave your dataframe untouched if no rows match id1 == id2:

test['name'] = (test['name'].where(test['id2'] == test['id1'])
                            .ffill().bfill().fillna(test['name']))

Output:

>>> test
   id1  id2 name
0    1    1    x
1    1    1    x
2    1    1    x
3    2    1    x
4    2    1    x
5    1    1    x