This repository contains a series of Jupyter notebooks aimed at refreshing your Python skills, specifically tailored for learners with some basic understanding of the language. The content of this project is inspired by various sources, including the book Python for Data Analysis by Wes McKinney and the LinkedIn Learning course Python Data Structures and Algorithms by Robin Andrews.

• 0 Some Basics.ipynb: (Incomprehensive) Review of fundamental Python concepts and built-in methods. This is a miscellaneous selection based on my personal use (or lack thereof).

• 1a Data Structures.ipynb: Exploration of common data structures in Python, including lists, tuples, dictionaries, and sets.

• 1b Data Structures.ipynb: Continuation of data structures exploration, focusing on sets and more advanced types.

• 2 Regular Expressions.ipynb: Utilizing regular expressions for pattern matching and text processing tasks.

• 3 Functions.ipynb: Understanding functions in Python, parameter passing, return values, and function decorators.

• 4 Common Libraries.ipynb: Introduction to Python packages and modules, and how to import and use them effectively.

• 5 Algorithms.ipynb: Overview of basic algorithms.

Contributions to this project are welcome! If you have suggestions for improvements, find errors, or want to add new content, feel free to fork this repository, make your changes, and submit a pull request.