# Python Resources

## Awesome Lists of Python

* [feiskyer](https://github.com/feiskyer/python-tutorials)
* [CodementorIO](https://github.com/CodementorIO/Python-Learning-Resources)
* [Data Science Python](https://github.com/ujjwalkarn/DataSciencePython)
* [Statistics with Python](https://github.com/svaksha/pythonidae/blob/master/Statistics.md)
* [Data Flair Python Tutorial](https://github.com/data-flair/python-tutorial)
* [Awesome Geoscience](https://github.com/softwareunderground/awesome-open-geoscience)
* [Awesome Data Science](https://github.com/krzjoa/awesome-python-data-science)
* [Awesome Jupyter](https://github.com/markusschanta/awesome-jupyter)
* [Awesome Sentiment Analysis](https://github.com/xiamx/awesome-sentiment-analysis)
* [Awesome Python in Education](https://github.com/quobit/awesome-python-in-education)
* [Project Based Learning](https://github.com/tuvtran/project-based-learning)
* [Recommended Python Learning Resources](https://forums.fast.ai/t/recommended-python-learning-resources/26888)
* [Wikibooks Python](https://en.wikibooks.org/wiki/Python_Programming/Links)

## Python Online IDE

* [Python Tutor](https://www.pythontutor.com/)
* [Skulpt](https://skulpt.org/) Python run in browser

## Python Interactive Learning

* [Kikodo](https://www.kikodo.io/) Online python learning

## Python Sympy

* [Live Sympy](https://live.sympy.org/)

## Python Interactive Learning

* [Thinkcspy by Runestone](https://runestone.academy/runestone/books/published/thinkcspy/index.html) is an interactive course inspired by Think Python
* [Automate Boring Stuff](https://automatetheboringstuff.com/2e/) online for free (use <https://repl.it/languages/python3> if you don't have local python installation)
* [Exercism](https://exercism.io/tracks/python/exercises), [Practicepython](https://www.practicepython.org/), [Edabit](https://edabit.com/challenges/python3)—these are all beginner-friendly and difficulty levels are marked
* [Codewars](https://www.codewars.com/), [Adventofcode](https://adventofcode.com/), [Projecteuler](https://projecteuler.net/)—more challenging
* [Checkio](https://py.checkio.org/), [Codingame](https://www.codingame.com/start), [Codecombat](https://codecombat.com/)—gaming based challenges
* [/r/dailyprogrammer](https://www.reddit.com/r/dailyprogrammer)—not active currently, but there's plenty of past challenges with discussions
* [codingbat.com](https://codingbat.com)
* [educative](https://www.educative.io/)
* <https://www.freecodecamp.org/learn/>
* [anvil.works](https://anvil.works) is a fun website to tinker around with.
* [www.codedamn.com](https://www.codedamn.com)
* [www.RealPython.com](https://www.realpython.com) have good tutorials for beginners.
* Hackerrank
* Sololearn

## Python Library

* [Python Stacks](https://www.pythonstacks.com/) : curated python library

## Python

* [Python in 1 Minutes](https://www.youtube.com/c/PythonIn1Minute/videos)

## Python

* [Streamlit—The fastest way to create data apps](https://www.streamlit.io/)

## Python Tutorials

* [Preface - 100 Page Python Intro](https://learnbyexample.github.io/100_page_python_intro/preface.html) License: CC-BY-NC
* [Preface - Python resources for everybody](https://learnbyexample.github.io/py_resources/) License: CC

## Python by Projects

* [norvig/pytudes: Python programs, usually short, of considerable difficulty, to perfect particular skills.](https://github.com/norvig/pytudes)
* [karan/Projects-Solutions: Links to others' solutions to Projects (https://github.com/karan/Projects/)](https://github.com/karan/Projects-Solutions)
* [tuvtran/project-based-learning: Curated list of project-based tutorials](https://github.com/tuvtran/project-based-learning#python)
* [Code with Repl.it - Python projects for beginners](https://www.codewithrepl.it/)

## Python

* [Python-I](https://primerlabs.io/books/python-i/)

## Python Learning

* [Python on Exercism](https://exercism.org/tracks/python)

## Python Cheatsheet

* [Comprehensive Python Cheatsheet](https://gto76.github.io/python-cheatsheet/)

## Python

* [Preface - Python resources for everybody](https://learnbyexample.github.io/py_resources/preface.html)
* [ROSALIND - Problems](https://rosalind.info/problems/list-view/)

## Visual Python

* [Ryven - Flow-based visual scripting for Python](https://ryven.org/)

## Python Learning

* [Getting started—pandas 1.4.1 documentation](https://pandas.pydata.org/docs/getting_started/index.html)
* [Think DSP](https://greenteapress.com/thinkdsp/html/index.html)
* [From Python to Numpy](https://www.labri.fr/perso/nrougier/from-python-to-numpy/)
* [Lessons](https://datacarpentry.org/lessons/)
* [GitHub - ossu/data-science: Path to a free self-taught education in Data Science!](https://github.com/ossu/data-science)
* [GitHub - jvns/pandas-cookbook: Recipes for using Python's pandas library](https://github.com/jvns/pandas-cookbook)
* [Chris Albon](https://chrisalbon.com/)
* [Mr. P Solver - YouTube](https://www.youtube.com/c/mrpsolver)
* [Intermediate Python Programming Course - YouTube](https://www.youtube.com/watch?v=HGOBQPFzWKo)
* [Neural Networks from Scratch](https://nnfs.io/)
* [Fluent Python](https://www.oreilly.com/library/view/fluent-python/9781491946237/)
* [Introducing Python, 2nd Edition](https://www.oreilly.com/library/view/introducing-python-2nd/9781492051374/)
* [Computational Physics: Problem Solving with Python, 3rd Edition - Wiley](https://www.wiley.com/en-us/Computational+Physics%3A+Problem+Solving+with+Python%2C+3rd+Edition-p-9783527413157)
* [Classical Mechanics - A Computational Approach with Examples Using Mat](https://www.taylorfrancis.com/books/mono/10.1201/9781351024389/classical-mechanics-christopher-kulp-vasilis-pagonis)
* [Dynamical Systems with Applications using Python](https://link.springer.com/book/10.1007/978-3-319-78145-7)
* [Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib](https://www.oreilly.com/library/view/numerical-python/9781484242469/)
* [Scipy Lecture Notes—Scipy lecture notes](http://scipy-lectures.org/)
* [Learning Scientific Programming with Python](https://www.cambridge.org/core/books/learning-scientific-programming-with-python/DEFE574792AE43C8B9AD23C8C39AB87F)
* [Python Programming Tutorials](https://pythonprogramming.net/)
* [Composing Programs](https://composingprograms.com/)
* [Preface - Python resources for everybody](https://learnbyexample.github.io/py_resources/)
* [Python Programming And Numerical Methods: A Guide For Engineers And Scientists—Python Numerical Methods](https://pythonnumericalmethods.berkeley.edu/notebooks/Index.html)

## Python

* [Python Tutor - Visualize Python, Java, C, C++, JavaScript, TypeScript, and Ruby code execution](https://pythontutor.com/)

## Python and Panda

* [Mito - Home](https://www.trymito.io/)
* [Datasette: An open source multi-tool for exploring and publishing data](https://datasette.io/)
* [VizierDB, a Data-Centric Notebook](https://vizierdb.info/)
* [A GUI for pandas - bamboolib](https://bamboolib.8080labs.com/)

## Python ML Frameworks

* [A Beginner's Guide to Python Machine Learning and Data Science Frameworks - Pathmind](https://wiki.pathmind.com/python-ai)
* [MindSpore](https://mindspore.cn/docs/programming_guide/en/master/index.html)
* [Comparison of AI Frameworks - Pathmind](https://wiki.pathmind.com/comparison-frameworks-dl4j-tensorflow-pytorch)
* [PyTorch vs TensorFlow in 2022](https://www.assemblyai.com/blog/pytorch-vs-tensorflow-in-2022/)
* [Pytorch vs. Tensorflow: Deep Learning Frameworks 2021 - Built In](https://builtin.com/data-science/pytorch-vs-tensorflow)

## Pandas

* [Modern Polars](https://kevinheavey.github.io/modern-polars/)
* Pandas