Leetcode #2882: Drop Duplicate Rows
In this guide, we solve Leetcode #2882 Drop Duplicate Rows in Python and focus on the core idea that makes the solution efficient.
You will see the intuition, the step-by-step method, and a clean Python implementation you can use in interviews.
Problem Statement
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.
Quick Facts
- Difficulty: Easy
- Premium: No
- Tags: Pandas
Intuition
The constraints allow a direct scan that keeps only the essential state.
By translating the requirements into a clean loop, the logic stays easy to reason about.
Approach
Iterate through the data once, updating the state needed to compute the answer.
Return the final state after the traversal is complete.
Steps:
- Parse the input.
- Iterate and update state.
- Return the computed answer.
Example
DataFrame customers
+-------------+--------+
| Column Name | Type |
+-------------+--------+
| customer_id | int |
| name | object |
| email | object |
+-------------+--------+
Python Solution
import pandas as pd
def dropDuplicateEmails(customers: pd.DataFrame) -> pd.DataFrame:
return customers.drop_duplicates(subset=['email'])
Complexity
The time complexity is O(n). The space complexity is O(1) to O(n).
Edge Cases and Pitfalls
Watch for boundary values, empty inputs, and duplicate values where applicable. If the problem involves ordering or constraints, confirm the invariant is preserved at every step.
Summary
This Python solution focuses on the essential structure of the problem and keeps the implementation interview-friendly while meeting the constraints.