Modifying column values in Pandas?

Question

How do I modify a coumn value in Pandas where new values are two times the previous values?

I tried this:

employees.loc['salary'] = employees['salary']*2

Input: DataFrame employees

+---------+--------+
| name    | salary |
+---------+--------+
| Jack    | 19666  |
| Piper   | 74754  |
| Mia     | 62509  |
| Ulysses | 54866  |

Output:

| name    | salary |
+---------+--------+
| Jack    | 39332  |
| Piper   | 149508 |
| Mia     | 125018 |
| Ulysses | 109732 |

remove the .loc and it will work. employees['salary'] = employees['salary']*2 — Emi OB
– Emi OB, Commented Aug 8, 2024 at 8:05
This question is similar to: Modify column data based on other column in pandas. If you believe it’s different, please edit the question, make it clear how it’s different and/or how the answers on that question are not helpful for your problem. — Emi OB
– Emi OB, Commented Aug 8, 2024 at 8:06
employees.loc['salary'] will create a new row with the index salary. You could use employees.loc[:, 'salary'] = ... but there is no point as already commented - just remove the .loc — user19077881
– user19077881, Commented Aug 8, 2024 at 9:10

Peaky_001 · Accepted Answer · 2024-08-08 10:48:37Z

1

as @Emi OB said you just need to modify the 'salary' column by assigning it to itself multiplied by 2.

employees['salary'] = employees['salary'] * 2

or You can use the apply method to apply a lambda function to each element in the salary column.

employees['salary'] = employees['salary'].apply(lambda x: x * 2)

with both ways you get this output :

      name  salary
0     Jack   39332
1    Piper  149508
2      Mia  125018
3  Ulysses  109732

answered Aug 8, 2024 at 8:14

Peaky_001

1,1579 silver badges13 bronze badges

Sign up to request clarification or add additional context in comments.

1 Answer 1