How to make a list in pandas based on multiple columns?

Question

Python

Good afternoon!

There is a DataFrame

import pandas as pd
df = pd.DataFrame({'movie': [9999999,  2,  3, 1, 9999999],
                  'rating': [3,  2,  9999999, 9999999, 3],
                  'name': [1,  2,  4, 5, 10]})

You need to add one more column, which will contain data according to the following logic...
If the movie column is 9999999, then the value from the rating column is taken, if the rating is 9999999, then name
tried to write the following code, but it seems to me that the idea is fundamentally wrong so I'm here...

kol = []
for l in df:
    for i in l:
        if i['movie'] != 9999999:
            k = i['movie']
        elif i['rating'] != 9999999:
            k = i['rating']
        else:
            k = i['name']
        kol.append(k)
df['sum'] = kol

Answer 1

You can move the calculations into a function and apply apply.

import pandas as pd
df = pd.DataFrame({'movie': [9999999,  2,  3, 1, 9999999],
                  'rating': [3,  2,  9999999, 9999999, 3],
                  'name': [1,  2,  4, 5, 10]})

def process(row):
    result = row['movie']
    if row['movie'] == 9999999:
        if row['rating'] == 9999999:
            result = row['name']
        else:
            result = row['rating']
    return result

df['sum'] = df.apply(process, axis=1)