🧠 A comprehensive reference of Python fundamentals from the first sessions of a data science course.

📍 Overview

This document serves as a comprehensive record of my learnings from the initial sessions of a data science course focused on Python programming. It covers fundamental concepts and operations in Python, including string manipulation, list and dictionary operations, control flow, functions, and basic object-oriented programming. Each section provides detailed explanations and code examples to illustrate the concepts learned. This document is intended to serve as a reference guide for revisiting key Python programming techniques essential for data science applications.

🧵 Session 1: Strings and Basic Operations

1. String Creation:

• Strings can be created using single or double quotes.
• Example:

'h', 'This is also string', "Now I'm ready to use single quotes,inside a string"

2. Printing Strings:

• Use the print() function to display strings.
• Example:

print('Hello world1')
print('Hello world2')

3. Escape Characters:

• Use \\\\t for a tab and \\\\n for a new line.
• Example:

print('use\\\\t to print a tab')
print('\\\\n')
print('See what I mean?')

4. String Variables:

• Assign strings to variables and print them.