2882 Drop Duplicate Rows

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.

The result format is in the following example.

For the whole problem statement, please refer here.

Plans

• Use pandas to handle the data.

• Find duplicate rows based on the email column.

• Keep only the first occurrence of each duplicate.

• Provide the cleaned DataFrame.

Solution

import pandas as pd

def dropDuplicateEmails(customers: pd.DataFrame) -> pd.DataFrame:
    # Drop duplicate rows based on email column
    return customers.drop_duplicates(subset='email', keep='first').reset_index(drop=True)

Explanation

1. Import Pandas

   • We start by importing the Pandas library, which provides data structures and operations for manipulating numerical tables and time series.

2. Define the Function

   • We define a function dropDuplicateEmails that takes a single argument customers, which is a DataFrame containing customer data.

3. Dropping Duplicate Rows

   • We use the drop_duplicates method on the DataFrame customers to remove duplicate rows based on the email column.

   • The subset='email' argument specifies that we are looking for duplicates in the email column.

   • The keep='first' argument specifies that we want to keep only the first occurrence of each duplicate.

   • The reset_index(drop=True) method is used to reset the index of the resulting DataFrame after dropping duplicates.

4. Return the Result

   • We return the cleaned DataFrame after dropping duplicate rows based on the email column.