SQL to Python for Beginners

🚀 Course Title: SQL to Python for Beginners

🎉 Course Headline: Master the Art of Data Manipulation - Transition from SQL to Python with Ease!

🧭 Course Overview: Get ready to embark on a journey from the familiar territory of SQL to the exciting world of Python for data manipulation and analysis. In this course, you'll discover how to leverage the powerful Python Pandas library to replicate the core functionalities of SQL queries, setting you up for advanced analyst roles, data science, and machine learning endeavors. 📊

Whether you're a beginner or an intermediate user looking to expand your skillset, this course will guide you through the process of adopting Python for your data needs. By understanding how to translate SQL operations into Python code, you'll be well-equipped to handle complex datasets and perform sophisticated data analysis with greater efficiency. 💻

🔍 Prerequisites: This course is tailored for individuals who are already comfortable with SQL and eager to explore the world of Python. A basic understanding of Python or experience with another programming language will enhance your learning experience. To get started, make sure you have:

✅ Python 3.7 or above installed on your system ✅ The pandas library installed (you can install it using pip install pandas) ✅ An Integrated Development Environment (IDE) like PyCharm or VS Code at the ready ✅ Git installed (optional, for cloning the repository containing code examples)

📚 Core Concepts You'll Master: We'll cover a range of SQL concepts and show you their Python Pandas equivalents. Here's what you'll learn:

• SQL Limit: Learn to fetch only specific rows in Python.
• SQL Distinct: Understand how to retrieve unique values in your datasets.
• SQL Where: Filter records with conditions using Python.
• SQL WHERE / AND (Multiple Predicates): Combine multiple conditions to filter data in Python.
• SQL IN ( ): Check for values within a set of items in Python.
• SQL NOT IN ( ): Exclude rows where values are in a specified list in Python.
• SQL Aggregate Functions:
  • SQL MIN, SQL MAX
  • SQL COUNT, SQL COUNT DISTINCT
  • SQL AVERAGE / MEAN
• Mode (Not usually available in most SQL databases): Calculate the mode of your data in Python.
• SQL Group by Aggregates: Perform group-wise aggregate computations using Python.
• SQL Row Number over (partition by / order by): Assign unique row numbers to records within partitions in Python.
• SQL Case Statements: Implement conditional logic within your data operations.
• SQL Joins: Merge datasets based on related keys or criteria in Python. 🤖

Thank you for choosing this course to bridge the gap between SQL and Python! We're excited to help you unlock new capabilities and look forward to seeing you succeed as you apply these skills to real-world data challenges. Let's get started on this transformative learning adventure! 🎓🎉