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In this video, we dive deeper into ranking methods and functions in Python using data frames. We discuss additional parameters that can help refine the ranking function, making it more flexible and adaptable to different data sets. We also explore the SQL equivalence of ranking methods, which will be helpful for those familiar with SQL. 👉 Watch our previous tutorial: How to Rank() Your Data In Python Pandas [Part 1]: • How to Rank() Your Data In Python Pandas [... 🧑💻 Go to the questions through the links below and follow along with us: 📌 Question 1: https://platform.stratascratch.com/co... 📌 Question 2: https://platform.stratascratch.com/co... 📌 Question 3: https://platform.stratascratch.com/co... 📌 Question 4: https://platform.stratascratch.com/co... ______________________________________________________________________ 👉 Subscribe to my channel: https://bit.ly/2GsFxmA 👉 Playlist for more data science interview questions and answers: https://bit.ly/3jifw81 👉 Playlist for data science interview tips: https://bit.ly/2G5hNoJ 👉 Playlist for data science projects: https://bit.ly/StrataScratchProjectsY... 👉 Practice more real data science interview questions: https://platform.stratascratch.com/co... ______________________________________________________________________ Timeline: Intro: (0:00) Percentage Ranking in Python: (0:43) Ranking in SQL: (4:10) Conclusion: (7:26) ______________________________________________________________________ About The Platform: I'm using StrataScratch (https://platform.stratascratch.com/co..., a platform that allows you to practice real data science interview questions. There are over 1000+ interview questions that cover coding (SQL and python), statistics, probability, product sense, and business cases. So, if you want more interview practice with real data science interview questions, visit https://platform.stratascratch.com/co.... All questions are free and you can even execute SQL and python code in the IDE, but if you want to check out the solutions from me or from other users, you can use ss15 for a 15% discount on the premium plans. ______________________________________________________________________ Contact: If you have any questions, comments, or feedback, please leave them here! Feel free to also email me at nathan@stratascratch.com _______________________________________________________________________ #pandaspythontutorial #pythondatascience #sqlrank