Python Fundamentals

This repository contains my step-by-step Python learning journey.

📁 Folder Structure

• 1_Basics/ — Covers print statements, variables, data types, operators, and string manipulations.
• 2_If_else/ — Covers conditional statements including if, elif, and else.
• 3_Import_Library/ — Demonstrates importing standard libraries and using their functions.
• 4_Loops/ — Covers for loops, while loops, and loop control statements.
• 5_Formatted_printing/ — Demonstrates different printing styles.
• 6_Lists/ — Covers list creation, nesting, mutability, and common list methods.
• 7_Tuples/ — Explains tuple properties, packing/unpacking, and immutability.
• 8_Sets/ — Demonstrates set operations, properties, and comparisons with lists.
• 9_Inline_Statements/ — Shows concise inline statement techniques and conditional expressions.
• 10_Functions/ — Explores defining and calling functions, arguments, return values, and scope.
• 11_Dictionary/ — Introduces dictionaries, key-value pairs, and common operations.
• 12_Matrices/ — Demonstrates matrix creation, indexing, and basic manipulations.
• 13_Scope_of_variables/ — Explains local and global variable scopes in Python.
• 14_File_Handling/ — Covers reading, writing, and manipulating files with Python.
• 15_Recursion/ — Demonstrates recursive functions, factorials, and problem-solving with recursion.
• 16_Binary_Search/ — Explains iterative and recursive approaches to binary search.
• 17_Exception_handling/ — Demonstrates Python’s error handling using try, except, else, finally, and custom exceptions.
• 18_Object_Oriented_Programming/ — Explains concepts like classes, objects, encapsulation, and inheritance.
• 19_Numpy/ — Introduces array creation, mathematical operations, and basic NumPy functionalities.
• 20_Pandas/ — Demonstrates data manipulation, analysis, and DataFrame operations.
• 21_Matplotlib/ — Shows how to visualize data using scatter plots, bar charts, histograms, pie charts, and subplots.

💡 About

Each folder includes small, focused Python programs demonstrating specific core concepts. This repository is designed to build a strong foundation through progressive, hands-on Python examples.