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SQL Exercise Repository

Welcome to the SQL Exercise Repository! This repository is designed to help you practice and enhance your SQL skills. Whether you're a beginner looking to learn the basics or an experienced developer aiming to sharpen your SQL proficiency, you'll find a variety of exercises covering a wide range of topics.

Table of Contents

  1. Introduction
  2. Getting Started
  3. Exercise Topics
  4. Contributing

Introduction

This repository contains a series of SQL exercises to help you practice and improve your SQL skills. Each exercise is designed to focus on specific aspects of SQL, from basic operations to more advanced topics like window functions, joins, and connecting SQL to Python.

Getting Started

To get started, clone this repository to your local machine:

git clone https://github.com/AvinashDarekar/sql-exercise-repository.git

Navigate to the repository and explore the exercises in the relevant folders. Each exercise may include SQL scripts, sample data, and instructions to guide you through the process.

Exercise Topics

Basic SQL Operations

  • Understand and practice fundamental SQL operations.

WHERE Clause and Operators

  • Learn how to filter data using the WHERE clause and various operators.

CREATE and INSERT Statements

  • Practice creating tables and inserting data into them.

JOIN Types

  • Explore different types of joins (INNER, LEFT, RIGHT, FULL) to combine data from multiple tables.

ORDER BY

  • Sort query results using the ORDER BY clause.

Temporary Tables

  • Use temporary tables to store and manipulate intermediate results.

Window Functions and Case Statements

  • Learn about window functions and use case statements for conditional logic.

Math Functions

  • Explore mathematical functions available in SQL.

GROUP BY and Aggregate Functions

  • Group data and perform aggregate functions like SUM, AVG, COUNT, etc.

Table Views and Connecting SQL to Python

  • Create and use table views and explore how to connect SQL to Python.

Contributing

Contributions are welcome! If you have additional exercises, improvements, or corrections, please submit a pull request.