LeetCode 601 - Human Traffic of Stadium (Python and SQL) [Hard]
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In this advanced tutorial, we tackle LeetCode 601: Human Traffic of Stadium using both SQL and Python (Pandas). This is a challenging problem that teaches you how to identify 3 or more consecutive records based on a condition—a common real-world pattern in time series and event tracking.
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In this video, I walk through solving LeetCode 601 - Human Traffic of Stadium, a hard-level SQL and Python Pandas problem. The challenge requires identifying records with three or more consecutive IDs where each has 100 or more people, then returning results ordered by visit date.
I break down the solution step-by-step, starting with the SQL approach using LEAD and LAG window functions to check previous and next day attendance. I demonstrate how to build a CTE (Common Table Expression) to organize the logic, then filter for three different scenarios: when you're at the start, middle, or end of a consecutive sequence meeting the criteria.
Next, I show the Python Pandas equivalent using the shift function to replicate SQL's LEAD and LAG behavior. While the solution involves some repetitive filtering logic, I explain how to structure multiple conditions with proper parentheses and pipe operators to identify qualifying consecutive records.
By the end of this tutorial, you'll understand how to use window functions in both SQL and Pandas for analyzing sequential data patterns. This problem tests your ability to work with row-level comparisons across multiple adjacent records, a common data analysis task in real-world scenarios.
TIMESTAMPS
00:00 Problem Introduction & Overview
01:42 SQL Solution: Setting Up Lead and Lag Functions
03:14 Creating the CTE Structure
04:08 Building Filter Conditions
06:18 Python Pandas Solution: Using Shift Functions
08:07 Implementing Multiple Filter Conditions
09:53 Testing & Final Explanation
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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.
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