Leetcode 182 - Duplicate Emails - Python Solution | FAANG Interviews - Everyday Data Science

📚 Resources:
- Question: https://leetcode.com/problems/duplica...
- Leetcode SQL Playlist:    • Leetcode SQL  
- Leetcode SQL solution:    • LeetCode Interview SQL Question with ...  

- Pandas Schema:
data = [[1, '[email protected]'], [2, '[email protected]'], [3, '[email protected]']]
person = pd.DataFrame(data, columns=['id', 'email']).astype({'id':'Int64', 'email':'object'})

In this exciting video, we dive headfirst into the world of FAANG interviews, armed with Python and the powerful Pandas library for data science! 🚀

Join me on this thrilling journey as we tackle some of the most challenging and sought-after interview questions asked by FAANG companies like Facebook, Apple, Amazon, Netflix, and Google. Whether you're a seasoned data scientist or just getting started, this video has something for everyone.

🧠 What You'll Learn:
- Step-by-step solutions to real FAANG interview questions.
- Python and Pandas techniques tailored for data science.
- Insider tips and strategies to ace your FAANG interview.

📈 Boost Your Career: Mastering these questions not only prepares you for FAANG interviews but also equips you with valuable skills for your data science career. Plus, you'll be better equipped to excel in technical interviews across the tech industry.

🔥 Why Watch? This video is your one-stop-shop for conquering FAANG interviews with Python and Pandas. We break down complex problems into easy-to-understand solutions, so you can build confidence and excel in your next technical interview.

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Ready to conquer FAANG interviews with Python and Pandas? Let's get started! 💪🐍📊 #FAANGinterviews #datascience #leetcode #TechInterviews #CareerSuccess #Python #Pandas