Python Practice Repository

This repository contains a collection of Python practice notebooks and documents, each focusing on a specific Python concept or module. It is organized to help learners and practitioners understand and apply core Python topics through practical examples and exercises.

Contents & Concepts

Jupyter Notebooks

• Numpy_Pandas_MLS_Salary.ipynb: Data analysis using Pandas and Numpy on a real-world dataset (MLS player salaries).
• Pandas_Sklearn_DataAnalysis.ipynb / Pandas_Sklearn_DataAnalysis_v2.ipynb: Data preprocessing, feature engineering, and machine learning with Pandas and Scikit-learn (Titanic dataset).
• Python_Multiple_Inheritance.ipynb: Demonstrates multiple inheritance in Python with custom classes.
• Python_Regex.ipynb: Usage of Python's re module for regular expressions and string pattern matching.
• Python_OOP_BankAccount.ipynb: Object-Oriented Programming (OOP) concepts, including class design, methods, and validation.
• Python_Functions_Dictionary.ipynb: Creating and using functions, and working with dictionaries in Python.
• Python_Dictionary_MorseCode.ipynb: Dictionary usage for encoding strings into Morse code.
• Python_String_Manipulation.ipynb: String manipulation techniques, including connecting words and handling overlaps.
• Python_Custom_String_Transformation.ipynb: Custom string transformations based on rules and list inputs.
• Python_String_Reverse_Search.ipynb: String reversal and custom search functions.

Questions Folder (Documents)

• Python_Dictionary.docx: Exercises and explanations on Python dictionaries.
• Python_Basics.docx: Foundational Python concepts and syntax.
• Python_Lists.docx: Working with lists in Python.
• Python_Functions.docx: Function creation and usage in Python.
• Python_Regex_Module.docx: Regular expressions and the re module in Python.

How to Use

• Open the Jupyter notebooks to explore and run code examples for each concept.
• Refer to the documents in the questions folder for written exercises and explanations.

Purpose

This repository is designed for students and self-learners to practice and master Python programming concepts, ranging from basic syntax to advanced topics like OOP, data analysis, and regular expressions.

Feel free to explore, modify, and use these resources for your learning journey!