Day 23: PostgreSQL Day 23 | SQL Conditional Statement Practice in Bhojpuri

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📘 PostgreSQL Day 23 | Conditional Statements in SQL (CASE WHEN Explained with Examples)

Welcome to Day 23 of the PostgreSQL SQL Series!
In this video, we explore conditional statements in SQL using the powerful CASE WHEN THEN ELSE END construct.

Conditional logic is a core concept used across SQL, programming languages, Excel, backend, and frontend development. This session focuses on understanding how CASE works, why order matters, and how to use it in real-world queries.

🔹 What You’ll Learn in This Video
1️⃣ Introduction to Conditional Logic in SQL

What conditional statements are and why they are important

Understanding if–else logic in SQL

How SQL decides which condition to execute

2️⃣ CASE WHEN THEN ELSE Syntax Explained

We break down the full structure of a SQL CASE statement:

CASE
WHEN condition THEN result
WHEN condition THEN result
ELSE result
END
Key takeaways:

Multiple WHEN clauses are allowed

ELSE is optional but recommended

Conditions are evaluated top to bottom

Once a condition matches, remaining checks are skipped

3️⃣ Example 1: Categorizing Movies by Duration

Using the movies table, we classify films into duration categories based on movie length:

Over 2.5 hours (more than 150 minutes)

Over 1.5 hours (91–150 minutes)

Less than 1.5 hours (90 minutes or less)

This example demonstrates:

Writing CASE statements inside SELECT

Assigning readable aliases

Why condition order is critical for correct results

4️⃣ Why Order of WHEN Conditions Matters

We explain an important concept:

Always check more restrictive conditions first

Incorrect ordering can make later conditions unreachable

Example:

WHEN movie_length 150 THEN ...
WHEN movie_length 90 THEN ...

5️⃣ Example 2: Classifying Movies by Domestic Earnings

We move to a more advanced use case by joining tables:

movies

movie_revenues

Movies are categorized as:

Box Office Hit (earnings 150M)

Normal (earnings 80M)

Flop (earnings ≤ 80M)

This example introduces:

CASE with joined tables

Realistic business logic classification

6️⃣ Handling NULL Values Gracefully

Some movies have missing earnings data.
We handle this using:

WHEN domestic_earnings IS NULL THEN 'Information Missing'
This ensures:

Cleaner output

Better data interpretation

No silent NULL values in results

7️⃣ What’s Next?

The video ends with a new challenge:

Classify movie directors by continent based on nationality

India, China, Japan → Asia

France, Germany, Italy → Europe

Others → Other

This challenge is solved in the next video.

🔑 Key Concepts Covered

CASE WHEN THEN ELSE in SQL

Hierarchical condition evaluation

Importance of condition order

Column aliasing best practices

JOIN usage with conditional logic

Handling NULL values explicitly

🎯 Who is this video for?

SQL beginners

Backend developers

Data analysts

Anyone preparing for SQL interviews

📌 Part of the PostgreSQL 30 Days Learning Series

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📂 Playlists –
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