Beyond Basics: 50 Advanced SQL Questions for In-Depth Understanding! - Leetcode 1440 | 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.

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.

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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[EverydayDataScience]

SQL Schema:

Create Table If Not Exists Variables (name varchar(3), value int)
Create Table If Not Exists Expressions (left_operand varchar(3), operator ENUM('>', '<', '='), right_operand varchar(3))
Truncate table Variables
insert into Variables (name, value) values ('x', '66')
insert into Variables (name, value) values ('y', '77')
Truncate table Expressions
insert into Expressions (left_operand, operator, right_operand) values ('x', '>', 'y')
insert into Expressions (left_operand, operator, right_operand) values ('x', '<', 'y')
insert into Expressions (left_operand, operator, right_operand) values ('x', '=', 'y')
insert into Expressions (left_operand, operator, right_operand) values ('y', '>', 'x')
insert into Expressions (left_operand, operator, right_operand) values ('y', '<', 'x')
insert into Expressions (left_operand, operator, right_operand) values ('x', '=', 'x')

Pandas Schema:

data = [['x', 66], ['y', 77]]
variables = pd.DataFrame(data, columns=['name', 'value']).astype({'name':'object', 'value':'Int64'})
data = [['x', '>', 'y'], ['x', '<', 'y'], ['x', '=', 'y'], ['y', '>', 'x'], ['y', '<', 'x'], ['x', '=', 'x']]
expressions = pd.DataFrame(data, columns=['left_operand', 'operator', 'right_operand']).astype({'left_operand':'object', 'operator':'object', 'right_operand':'object'})

[IMAJAY]

ORACLE SQL for Practice

-- Create the Variables table with numeric value for the 'value' column
CREATE TABLE IF NOT EXISTS Variables (
name VARCHAR2(3),
value INT
);

-- Create the Expressions table with a string column for the operator
CREATE TABLE IF NOT EXISTS Expressions (
left_operand VARCHAR2(3),
operator VARCHAR2(1),
right_operand VARCHAR2(3),
CONSTRAINT chk_operator CHECK (operator IN ('>', '<', '='))
);

-- Clear the Variables table before inserting
TRUNCATE TABLE Variables;

-- Insert sample data into the Variables table
INSERT INTO Variables (name, value) VALUES ('x', 66);
INSERT INTO Variables (name, value) VALUES ('y', 77);

-- Clear the Expressions table before inserting
TRUNCATE TABLE Expressions;

-- Insert sample expressions
INSERT INTO Expressions (left_operand, operator, right_operand) VALUES ('x', '>', 'y');
INSERT INTO Expressions (left_operand, operator, right_operand) VALUES ('x', '<', 'y');
INSERT INTO Expressions (left_operand, operator, right_operand) VALUES ('x', '=', 'y');
INSERT INTO Expressions (left_operand, operator, right_operand) VALUES ('y', '>', 'x');
INSERT INTO Expressions (left_operand, operator, right_operand) VALUES ('y', '<', 'x');
INSERT INTO Expressions (left_operand, operator, right_operand) VALUES ('x', '=', 'x');

[vijaygupta]

Please help to update the table schema in video description so we can also do hands-on

[abhijeetjain]

CASE
WHEN e.operator = '>' AND v1.value > v2.value THEN 1
WHEN e.operator = '<' AND v1.value < v2.value THEN 1
WHEN e.operator = '=' AND v1.value = v2.value THEN 1
ELSE 0
END AS comparison_result

[balakumarankannan]

can you please provide the create and insert statements for this question

[williamlu]

WITH cte AS (SELECT e.left_operand, e.operator, e.right_operand, v1.value AS l, v2.value AS r,
CASE WHEN v1.value=v2.value then '='
WHEN v1.value < v2.value then '<'
WHEN v1.value > v2.value then '>' END AS test_op
FROM Expressions e JOIN Variables v1
ON e.left_operand = v1.name
JOIN Variables v2 on e.right_operand = v2.name)

SELECT left_operand, operator, right_operand,
CASE WHEN operator = test_op THEN 'true'
ELSE 'false' END AS value
FROM cte;