Using pandas library

[ramitaherwahdan1978]

Also when using Pandas is looping through rows/columns rarely the best solution.
In fact Pandas even has a red warning about this.

Iterating through pandas objects is generally slow.
In many cases, iterating manually over the rows is not needed and can be avoided (using) a vectorized solution,
many operations can be performed using built-in methods or NumPy functions, (boolean) indexing.

So as example with your code,could eg use np.where.

import pandas as pd
import numpy as np

numbers = pd.DataFrame([[3],[8],[4],[9],[14],[17]], columns=['Numbers'])
numbers['Odd/Even'] = np.where(numbers['Numbers'] % 2, 'Odd', 'Even')

Output:
>>> numbers
   Numbers Odd/Even
0        3      Odd
1        8     Even
2        4     Even
3        9      Odd
4       14     Even
5       17      Odd

Thanks for answering but we didn't give students the numpy, is there other ways?