This repository contains Jupyter Notebooks designed to guide you through the fundamentals of the Python programming language.
Python is a high-level, interpreted, and dynamically-typed programming language known for its readability and versatility. It boasts a large and active community, making it an excellent choice for beginners and experienced developers alike. Python's clean syntax and extensive libraries support a wide range of applications, from web development and data science to machine learning and automation.
This section covers the foundational elements of Python programming, including data types, expressions, variables, operators, and strings.
Explore Python's built-in data structures, which are essential for organizing and managing collections of data. Discover lists, tuples, dictionaries, and sets – their properties, common operations, and when to use each one effectively.
Core Python concepts are presented, beginning with conditional branching and progressing through loops, functions, exception handling, and object-oriented programming with classes. It covers controlling program flow, creating reusable code, managing errors, and building structured applications.
How to manipulate and analyze data using Python's powerful built-in capabilities and popular libraries. File operations using open(), structured data manipulation with Pandas DataFrames, and numerical computations with NumPy arrays. It covers essential techniques like reading/writing files, data filtering and analysis in Pandas, and array operations like indexing, slicing, and vector math in NumPy, highlighting their roles in data processing and analysis.
Discover how to interact with Application Programming Interfaces (APIs) to collect data from external sources using Python. We'll cover how to use APIs for structured data retrieval, understand HTTP requests, and employ libraries like requests and Beautiful Soup for extracting information from websites. Finally, we'll explore handling various file formats like CSV and JSON with Pandas.