DataFrame customers +-------------+--------+ | Column Name | Type | +-------------+--------+ | customer_id | int | | name | object | | email | object | +-------------+--------+
There are some duplicate rows in the DataFrame based on the email column.
Write a solution to remove these duplicate rows and keep only the first occurrence.
The result format is in the following example.
Example 1: Input: +-------------+---------+---------------------+ | customer_id | name | email | +-------------+---------+---------------------+ | 1 | Ella | emily@example.com | | 2 | David | michael@example.com | | 3 | Zachary | sarah@example.com | | 4 | Alice | john@example.com | | 5 | Finn | john@example.com | | 6 | Violet | alice@example.com | +-------------+---------+---------------------+ Output: +-------------+---------+---------------------+ | customer_id | name | email | +-------------+---------+---------------------+ | 1 | Ella | emily@example.com | | 2 | David | michael@example.com | | 3 | Zachary | sarah@example.com | | 4 | Alice | john@example.com | | 6 | Violet | alice@example.com | +-------------+---------+---------------------+ Explanation: Alic (customer_id = 4) and Finn (customer_id = 5) both use john@example.com, so only the first occurrence of this email is retained.
{"headers":{"customers":["customer_id","name","email"]},"rows":{"customers":[[1,"Ella","emily@example.com"],[2,"David","michael@example.com"],[3,"Zachary","sarah@example.com"],[4,"Alice","john@example.com"],[5,"Finn","john@example.com"],[6,"Violet","alice@example.com"]]}}