Leetcode 183 - Customers Who Never Order (Python and SQL) [EASY] скачать в хорошем качестве

Leetcode 183 - Customers Who Never Order (Python and SQL) [EASY]

🧠 Don’t miss out! Get FREE access to my Skool community — packed with resources, tools, and support to help you with Data, Machine Learning, and AI Automations! 📈 https://www.skool.com/data-and-ai-aut... In this video, we solve LeetCode Problem 183: Customers Who Never Order using both SQL and Python (Pandas). It’s a great real-world-style question that teaches you how to handle anti-joins—finding data that doesn't exist in another table. Leetcode 183 Customers who never order: https://leetcode.com/problems/custome... 🚀 Hire me for Data Work: https://ryanandmattdatascience.com/da... 👨‍💻 Mentorships: https://ryanandmattdatascience.com/me... 📧 Email: ryannolandata@gmail.com 🌐 Website & Blog: https://ryanandmattdatascience.com/ 🖥️ Discord:   / discord   📚 *Practice SQL & Python Interview Questions: https://stratascratch.com/?via=ryan 📖 *SQL and Python Courses: https://datacamp.pxf.io/XYD7Qg 🍿 WATCH NEXT LeetCode Playlist:    • Leetcode Data Science Interview Questions   LeetCode 181:    • LeetCode 181 - Employees Earning More Than...   LeetCode 511:    • LeetCode 511- Game Play Analysis 1  (Pytho...   LeetCode 180:    • LeetCode 180 - Consecutive Numbers (Python...   In this video, I solve LeetCode 183: Customers Who Never Order in both SQL and Python Pandas. This easy-level database problem asks you to find all customers who have never placed an order by comparing two tables - a customers table and an orders table. I walk through the logic step-by-step, showing you exactly how to identify which customer IDs don't appear in the orders table. For the SQL solution, I demonstrate a clean approach using SELECT with a NOT IN subquery that checks if customer IDs exist in the orders table. I explain why it's important to use proper table aliases and show you how to rename columns in your output to match the expected format. On the Python Pandas side, I break down how to use pd.merge() to perform a left join between the two dataframes, filter for null values to find customers without orders, and rename columns appropriately. I also explain the X and Y suffixes that Pandas automatically adds to duplicate column names after a merge and show you the complete dataframe transformation process. Whether you're preparing for data analyst interviews, learning SQL and Pandas, or just working through LeetCode database problems, this tutorial gives you practical solutions you can apply immediately. By the end, you'll understand multiple approaches to solving table comparison problems in both SQL and Python. *#LeetCode #SQL #PythonPandas #DataAnalytics #CodingInterview* TIMESTAMPS 00:00 Problem Introduction 01:00 SQL Solution Explanation 03:00 Running the SQL Query 03:23 Python Pandas Solution 05:17 Reviewing Merged Data Frame 06:27 Final Python Solution OTHER SOCIALS: Ryan’s LinkedIn:   / ryan-p-nolan   Matt’s LinkedIn:   / matt-payne-ceo   Twitter/X: https://x.com/RyanMattDS Who is Ryan Ryan is a Data Scientist at a fintech company, where he focuses on fraud prevention in underwriting and risk. Before that, he worked as a Data Analyst at a tax software company. He holds a degree in Electrical Engineering from UCF. Who is Matt Matt is the founder of Width.ai, an AI and Machine Learning agency. Before starting his own company, he was a Machine Learning Engineer at Capital One. *This is an affiliate program. We receive a small portion of the final sale at no extra cost to you.