Welcome to the Python-Basics repository!! 🎉 For Blogs - https://medium.com/@sudhamsr/python-for-data-science-introduction-to-python-ace25b97bea9
This repository is a beginner-friendly collection of Python programming concepts, designed to provide a strong foundation in Python for new learners.
- Contains Jupyter notebooks explaining key Python concepts.
- Each notebook focuses on a single topic for step-by-step learning.
- Includes examples, notes, and practice code.
- Covers everything from Python basics to intermediate topics.
- Python basics: variables, operators, data types
- Control flow: conditions, loops, and iterations
- Functions, modules, and scope
- Data structures: lists, tuples, sets, and dictionaries
- Object-Oriented Programming (OOP)
- File handling and error handling
- Useful modules like
math,re(regex), and package management withpip - Virtual environments for project management
- Extra notes: f-strings, lambdas, operator summary, comparisons, and more
- Basics of Python
- Variables & Operators
- Arithmetic Operators
- Primitive Data Types
- Type Casting
- Unicode and Literals
- Strings
- Booleans
- Lists
- Tuples
- Sets
- Dictionary
- Taking Input in Python
- Conditional Flow Statements
- Loops and Iterations
- Functions
- Variable Scope & Annotations
- Modules & Built-in Functions
- Arrays
- NumPy Arrays
- Object-Oriented Programming (OOP)
- Regular Expressions
- Math Module
- PIP – Package Manager
- Try, Except, Finally
- Errors & Exceptions
- File Handling
- Virtual Environment
- Comparison of List, Tuple, Set, and Dictionary
- Formatted Strings (f-strings)
- Lambda Functions (More about Lambda)
- More about Loops
- More about OOP
- Summary of Operators
- Examples – Python Numbers
- Clone or download this repository.
- Open the
.ipynbfiles in Jupyter Notebook or Google Colab. - Run the examples and try modifying them for practice.