Create a Pandas Column using For Loop

In Pandas you can create a new column by iterating over an existing column (a Series) with a for loop, collecting computed values into a Python list and assigning that list back to the DataFrame as a new column.

For Example: This example creates a new column that doubles the numbers in another column.

 Number Double
0 1 2
1 2 4
2 3 6

Explanation:

• labels is created to store results.
• Each value in column "Number" is checked using %.
• "Even" or "Odd" is appended to the list.
• A new column "Label" is created from that list.

Let's see more examples to understand it better.

More Examples

Example 1: This example checks each voter’s age and creates a new column "Voter" showing whether the person is eligible to vote.

Output

Voter_name Voter_age Voter
0 Geek1 15.0 No
1 Geek2 23.0 Yes
2 Geek3 25.0 Yes
3 Geek4 9.0 No
4 Geek5 67.0 Yes
5 Geek6 54.0 Yes
6 Geek7 42.0 Yes
7 Geek8 NaN Not Sure

Explanation:

• If age ≥ 18 -> "Yes".
• If age < 18 -> "No".
• If age is NaN -> "Not Sure".
• A new "Voter" column is created with results.

Example 2: In this example, we classify salaries into "High" or "Low" categories and store them in a new column.

 Employee Salary Category
0 A 25000 Low
1 B 60000 High
2 C 40000 Low
3 D 80000 High

Explanation:

• Salaries ≥ 50,000 are labeled "High".
• Others are labeled "Low".
• New column "Category" stores these labels.