From Rookie to Rockstar: Mastering Advanced SQL Interview Questions! - Data Science | Leetcode 1783

Welcome to this 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 Players (player_id int, player_name varchar(20))
Create table If Not Exists Championships (year int, Wimbledon int, Fr_open int, US_open int, Au_open int)
Truncate table Players
insert into Players (player_id, player_name) values ('1', 'Nadal')
insert into Players (player_id, player_name) values ('2', 'Federer')
insert into Players (player_id, player_name) values ('3', 'Novak')
Truncate table Championships
insert into Championships (year, Wimbledon, Fr_open, US_open, Au_open) values ('2018', '1', '1', '1', '1')
insert into Championships (year, Wimbledon, Fr_open, US_open, Au_open) values ('2019', '1', '1', '2', '2')
insert into Championships (year, Wimbledon, Fr_open, US_open, Au_open) values ('2020', '2', '1', '2', '2')

Pandas Schema:
data = [[1, 'Nadal'], [2, 'Federer'], [3, 'Novak']]
players = pd.DataFrame(data, columns=['player_id', 'player_name']).astype({'player_id':'Int64', 'player_name':'object'})
data = [[2018, 1, 1, 1, 1], [2019, 1, 1, 2, 2], [2020, 2, 1, 2, 2]]
championships = pd.DataFrame(data, columns=['year', 'Wimbledon', 'Fr_open', 'US_open', 'Au_open']).astype({'year':'Int64', 'Wimbledon':'Int64', 'Fr_open':'Int64', 'US_open':'Int64', 'Au_open':'Int64'})

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.
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.

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.

[architectaq]

another approach to solve this:

with cte as
(select wimbledon as player_id from championships
union all
select Fr_open from championships
union all
select US_open from championships
union all
select Au_open from championships)

select t2.player_id, t2.player_name, count(*) as total_won
from cte t1
join players t2 on t1.player_id = t2.player_id
group by 1, 2;