Advanced SQL Prep: 50 Interview Questions to Secure Your Dream Job! - Leetcode 1407 | Data Science

Welcome to the first episode of our groundbreaking series designed to take your SQL skills to the next level! In this series, we're tackling 50 of the most challenging and insightful interview questions on #advanced SQL, aimed at transforming you from an intermediate user to a bona fide #sql expert. Whether you're preparing for a job #interview , seeking to enhance your data manipulation capabilities, or simply passionate about mastering the complexities of SQL, this series is your ultimate roadmap.

SQL Schema:
Create Table If Not Exists Users (id int, name varchar(30))
Create Table If Not Exists Rides (id int, user_id int, distance int)
Truncate table Users
insert into Users (id, name) values ('1', 'Alice')
insert into Users (id, name) values ('2', 'Bob')
insert into Users (id, name) values ('3', 'Alex')
insert into Users (id, name) values ('4', 'Donald')
insert into Users (id, name) values ('7', 'Lee')
insert into Users (id, name) values ('13', 'Jonathan')
insert into Users (id, name) values ('19', 'Elvis')
Truncate table Rides
insert into Rides (id, user_id, distance) values ('1', '1', '120')
insert into Rides (id, user_id, distance) values ('2', '2', '317')
insert into Rides (id, user_id, distance) values ('3', '3', '222')
insert into Rides (id, user_id, distance) values ('4', '7', '100')
insert into Rides (id, user_id, distance) values ('5', '13', '312')
insert into Rides (id, user_id, distance) values ('6', '19', '50')
insert into Rides (id, user_id, distance) values ('7', '7', '120')
insert into Rides (id, user_id, distance) values ('8', '19', '400')
insert into Rides (id, user_id, distance) values ('9', '7', '230')

Pandas Schema:
data = [[1, 'Alice'], [2, 'Bob'], [3, 'Alex'], [4, 'Donald'], [7, 'Lee'], [13, 'Jonathan'], [19, 'Elvis']]
users = pd.DataFrame(data, columns=['id', 'name']).astype({'id':'Int64', 'name':'object'})
data = [[1, 1, 120], [2, 2, 317], [3, 3, 222], [4, 7, 100], [5, 13, 312], [6, 19, 50], [7, 7, 120], [8, 19, 400], [9, 7, 230]]
rides = pd.DataFrame(data, columns=['id', 'user_id', 'distance']).astype({'id':'Int64', 'user_id':'Int64', 'distance':'Int64'})

In this first episode, we kick things off with a deep dive into a question that stumps many aspiring SQL professionals. We'll explore the intricacies of advanced query writing, focusing on techniques that go beyond the basics of SELECT statements and WHERE clauses. You'll learn about advanced joins, window functions, recursive queries, and much more.

What to Expect:

Detailed Explanations: We don't just solve the question; we dissect it. You'll understand not only the 'how' but also the 'why' behind each solution, ensuring you can apply these principles to a variety of SQL challenges.
Step-by-Step Approach: Our tutorials are designed to be easy to follow. We break down complex concepts into manageable parts, making advanced SQL more accessible than ever.
Real-World Applications: These aren't just theoretical exercises. Each question is selected for its relevance to real-world SQL problems, ensuring you gain practical skills that you can apply in a professional setting.
Interactive Learning: Engage with the content through quizzes and challenges presented throughout the series. Test your knowledge, practice new skills, and solidify your understanding of advanced SQL techniques.

Why This Series?

SQL remains one of the most in-demand skills in the tech industry, and for a good reason. It's the backbone of data analysis, database management, and many forms of programming. As data continues to drive decision-making in businesses worldwide, the ability to manipulate and retrieve data efficiently becomes increasingly valuable. This series is designed to equip you with these skills, ensuring you're not just ready for your next job interview but also prepared to tackle real-world data challenges.

Who Should Watch?

Intermediate SQL users looking to advance their skills.
Job seekers preparing for technical interviews.
Data professionals seeking to deepen their understanding of SQL.
Anyone with a passion for data and an eagerness to learn.
How to Get the Most Out of This Series:

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[dineshkumr]

Sir from my YT experience, you should use your image on thumbnail for personal brand so that people could just identify you thru thumb.

And if you need a thumb designer, can do it r you, i have some experience in this too

[gunjanpatil]

In the group by can we use only u.name instead of both u.id and u.name?