My Python Resources (extracted from My Tech Resources due to Github README.markdown length limit & truncation) - James Lavin
July 12, 2020 · View on GitHub
DESCRIPTION
Links to Ruby & Rails resources I have found useful or think might be helpful to future me or Python developers like me.
PYTHON
- Awesome Python (curated list of awesome Python frameworks, libraries, software and resources | Github
PYTHON - ALGORITHMS
- Intro to Algorithms - MIT
- Intro to Algorithms: Social Network Analysis - Michael Littman, Brown University (Udacity)
PYTHON - CONDA
- Conda (package manager): Documentation & Github | Cheatsheet
PYTHON - CYTHON
- Cython
- Speeding up scientific python code using Cython - EuroSciPy 2014
- Cython: Speed up Python and NumPy, Pythonize C, C++, and Fortran, SciPy2013 Tutorial, Part 1 - Kurt Smith, Part 2, Part 3, Part 4
- Very gentle introduction to Cython - William Stein
- The Cython compiler for Python - Dr. Stefan Behnel (2014)
- Cython - Making Python as fast as C (Mandarin) - Mosky
PYTHON - COMPUTER VISION
PYTHON - DATA ANALYSIS
- AnacondaCON 2017
- Python Data Science Handbook - Jake VanderPlas
- Introduction to Python & Machine Learning (with Analytics Vidhya Hackathons) - Kunal Jain
- Statistics and Machine Learning in Python - Edouard Duchesnay, Tommy Löfstedt (PDF) (Actual link is ftp://ftp.cea.fr/pub/unati/people/educhesnay/pystatml/StatisticsMachineLearningPythonDraft.pdf, but a Github bug prevents ftp links from rendering in Markdown files)
- Code for "Python for Data Analysis, 2nd ed" - Wes McKinney
- Dataquest.io missions
- Harvard CS109: Data Science (2013): slides, video lectures & labs and solutions
- Harvard CS109: Data Science (2014)
- Open Courses: Free Data Science Training Courses (DataCamp.com)
- Intro to Python for Econometrics, Statistics and Data Analysis - Kevin Sheppard
- Data Mining With Python - Finn Arup Nielsen
- Clustering US Senators with K-Means - Dataquest.io
- A Complete Tutorial to Learn Data Science with Python from Scratch - Kunal Jain
- Python: Getting Started With Data Analysis - Al-Ahmadgaid Asaad
- Quantitative Economics - Thomas Sargent & John Stachurski & Python index
- Think Stats: Probability and Statistics for Programmers
- Natural Language Processing with Python
- Mining the Social Web (Git repo)
- Practical Data Science in Python - Radim Řehůřek
- scientific-python-lectures - JR Johansson
- Learn Python Through Public Data Hacking & slides
- iPython notebooks for Wes McKinney's "PyData" 2nd ed
- Bayesian Statistics Made (As) Simple (As Possible) - Allen Downey (2012)
- Social Network Analysis With Python - Maksim Tsvetovat (2012)
- Web Scraping: Reliably and Efficiently Pull Data From Pages That Don't Expect It - Asheesh Laroia (PyCon 2012)
- Social Network Analysis with Python - Maksim Tsvetovat (PyCon 2012)
- [Web scraping: Reliably and efficiently pull data from pages that don't expect it - Asheesh Laroia (2012)](http://www.youtube.com/watch?v=52wxGESwQS()
- Python for Open Data Lovers: Explore It, Analyze It, Map It - Jackie Kazil, Dana Bauer (2012)
- Interactive Data Exploration and Visualization in IPython - Tamara Knutsen (DataScience.LA 2014)
- Learn Python for Science - NumPy, SciPy and Matplotlib
- A Billion Rows per Second: Metaprogramming Python for Big Data - New Circle Training
- Python's Role in Big Data Analytics: Past, Present, and Future - Travis Oliphant (EuroPython 2014)
- Python as Super Glue for the Modern Scientific Workflow - Joshua Bloom (SciPy 2012)
- Intro to Prediction Using Python - Luke Gotszling
- R vs Python - Round 1 Round 2 Round 3
PYTHON - DATA ANALYSIS - AIRFLOW
PYTHON - DATA ANALYSIS - BLAZE
- Docs & Github
- Blaze ("extends NumPy and Pandas to distributed and out-of-core computing")
- Introducing Blaze - HMDA Practice - Matt Rocklin
- Dask - enables parallel computing through task scheduling and blocked algorithms
PYTHON - DATA ANALYSIS - EXCEL INTEGRATION
PYTHON - DATA ANALYSIS - KAYAK (DEEP NEURAL NETWORKS)
PYTHON - DATA ANALYSIS - MLPY
PYTHON - DATA ANALYSIS - NUMBA
- Numba: Pydata & Github
- Numba vs. Cython: Take 2 - Jake Vanderplas
- Accelerating Python Libraries with Numba (Part 1) - Aron Ahmadia & Part 2
- Numba Overview - Stan Seibert
PYTHON - DATA ANALYSIS - NUMPY
- Intro to Numerical Computing with NumPy - Alex Chabot-Leclerc (SciPy 2019 Tutorial)
- A Visual Intro to NumPy and Data Representation - Jay Alammar
- Python For Data Science Cheat Sheet: NumPy Basics (DataCamp.com)
- (Tentative) NumPy Tutorial
- Numpy User Guide & PDF
- Numpy Reference Guide & PDF
- NumPy and iPython - Valentin Haenel (SciPy 2013) - Pt 1 & Pt 2
- An introduction to Numpy and Scipy - M. Scott Shell
- Numpy: Multidimensional Data Arrays - J.R. Johansson
- An Exercise With Matplotlib and Numpy (gets and analyzes weather data)- Mike Hansen
PYTHON - DATA ANALYSIS - OLAP
- Cubes (OLAP HTTP server): Website & Github
- CubesViewer
PYTHON - DATA ANALYSIS - PANDAS
- Intro to Data Processing in Python with Pandas - Daniel Chen (SciPy 2019 Tutorial)
- Data Analysis with PANDAS (cheatsheet)
- Python For Data Science Cheat Sheet - Pandas Basics (DataCamp.com)
- Python PANDAS Tutorial - TutorialsPoint.com (PDF)
- Pandas documentation (PDF)
- Installation
- FAQ
- Overview
- 10 Minutes to Pandas
- Tutorials
- Cookbook
- Intro to Data Structures
- Essential Basics
- Text Data
- Options and Settings
- Indexing and Selecting Data
- MultiIndex / Advanced Indexing
- Computational Tools
- Missing Data
- Group By: Split-Apply-Combine
- Merge, Join and Concatenate
- Reshaping and Pivot Tables
- Time Series / Date Functionality
- Time Deltas
- Categorical Data
- Plotting
- I/O Tools (Text, Excel, CSV, JSON, HDF5, ...)
- Remote Data Access
- Enhancing Peformance
- Sparse Data Structures
- Caveats and Gotchas
- rpy2 / R Interface
- Pandas Ecosystem
- Comparison With R / R Libraries
- Comparison With SQL
- API Reference
- Easier data analysis in Python with pandas (video series) - Kevin Markham (DataSchool.io) & iPython notebooks
- Modern Pandas (7-part series) - Tom Augspurger
- Visual Guide to Pandas - Jason Wirth (ChiPy 2013)
- Pandas tutorials - PyData.org
- Tidy Data in Python Mini-Course - Vincent Lan
- Things in Pandas I Wish I'd Had Known Earlier - Sebastian Raschka
- Cheat Sheet: The Pandas DataFrame Object
- Intro to PANDAS Data Structures - Greg Reda, Working With DataFrames & Using PANDAS on the MovieLens Database
- Statistical Data Analysis in Python (4 videos) - Christopher Fonnesbeck 1 2 3 4 & iPython notebooks
- Keynote - Wes McKinney (PyCon Singapore 2013)
- Data Analysis in Python with Pandas - Wes McKinney (2012 PyData Workshop)
- Time Series Data Analysis with Pandas - Wes McKinney (ciPy 2012)
- Applied Time Series Econometrics in Python and R - Jeffrey Yau (PyData 2016)
- Python Data Visualization Cookbook
- Python Pandas Tutorial - Mikhail Semeniuk
- Remote Data Access
- Diving into Open Data with IPython Notebook & Pandas - Julia Evans (PyCon 2014) & Pandas Cookbook (iPython Notebooks)
- Detailed Look at Pandas' Indexes - Trent Hauck (O'Reilly 2014)
- NumPy/SciPy/Pandas Cheat Sheet
- Python Pandas Tutorial - Mikhail Semeniuk
- Time series analysis with Pandas - Nikolay Koldunov
- 10 Things I Hate About Pandas - Wes McKinney
- Python and Pandas for Sentiment Analysis and Investing - "sentdex"
- Manipulating/querying dataframes with Pandas (or dplyr)
PYTHON - DATA ANALYSIS - PANDAS - DATA STORAGE
PYTHON - DATA ANALYSIS - PANDAS - EXCEL INTEGRATION
- Common Excel Tasks Demonstrated in Pandas - Chris Moffitt, Part 1 & Part 2
- Combining Data From Multiple Excel Files - Chris Moffitt
- Pandas Pivot Table Explained - Chris Moffitt
- Openpyxl: library to read/write Excel 2010 xlsx/xlsm/xltx/xltm files
PYTHON - DATA ANALYSIS - PANDAS - PERFORMANCE
- Apache Arrow and the "10 Things I Hate About pandas" - Wes McKinney
- Performance Pandas - Jeff Reback
PYTHON - DATA ANALYSIS - PYBRAIN
PYTHON - DATA ANALYSIS - PYMC
- PyMC user guide
- PyMC Github
- PyMC tutorial
- Bayesian data analysis with PyMC3 - Thomas Wiecki (PyData 2013)
PYTHON - DATA ANALYSIS - PYML
PYTHON - DATA ANALYSIS - PYSYFT
- PySyft: library for encrypted, privacy preserving deep learning
- PySyft tutorials
- A generic framework for privacy preserving deep learning - Theo Ryffel, et al
PYTHON - DATA ANALYSIS - PYTABLES
- PyTables.org
- PyTables.github.io
- github.com/Pytables
- Python and HDF5 - Fast Storage for Large Data - Mike Müller (PyCon 2012)
- HDF5 is for lovers - Anthony Scopatz (SciPy 2012)
- Managing Large Datasets with Python and HDF5 - Andrew Collette (2014)
- Modern scientific computing and big data analytics in Python - Edward Schofield (PyCon Australia 2013)
PYTHON - DATA ANALYSIS - R INTERFACES
- RPy2 documentation
- RMagic for iPython Notebook
- Using R Within the iPython Notebook
- RMagic Functions Extension
PYTHON - DATA ANALYSIS - SCIKIT-LEARN
- API
- Documentation
- User Guide
- Machine Learning in Python with Scikit-Learn - DataSchool.io
- scikit-learn video: #1: Intro to machine learning with scikit-learn | #2: Setting up Python for machine learning | #3: Machine learning first steps with the Iris dataset | #4: Model training and prediction with K-nearest neighbors | #5: Choosing a machine learning model | #6: Linear regression (plus pandas & seaborn) | #7: Optimizing your model with cross-validation | #8: Efficiently searching for optimal tuning parameters | #9: Better evaluation of classification models
- Realtime Predictive Analytics Using scikit-learn and RabbitMQ - Michael Becker (PyCon 2014)
- Know Thy Neighbor: Scikit and the K-Nearest Nearest Neighbor Algorithm - Portia Burton (PyCon 2014)
- Intro to Machine Learning: Pattern Recognition for Fun and Profit - Sebastian Thrun and Katie Malone (Udacity)
- SciKit-Learn Tutorial - Jake VanderPlas (PyData 2012)
- Intro to Scikit-learn (1) - Gaël Varoquaux, Jake Vanderplas, Olivier Grisel (SciPy 2013) 2 & 3
- Tutorial on statistical-learning for scientific data processing
- Practical Machine Learning in Python - Matt Spitz (2012)
- Intro to Interactive Predictive Analytics in Python with scikit-learn - Olivier Grisel (PyCon 2012)
- How to Get Started with Machine Learning - Melanie Warrick (PyCon 2014)
- Social Network Analysis With Python - Maksim Semeniuk (2012)
- Intro to scikit-learn: Machine Learning in Python - Jake VanderPlas & Olivier Grisel (PyCon 2014), 2014 tutorial materials, 2013 tutorial materials & Jake VanderPlas (PyData 2012)
- Intro to Scikit-Learn - Jake Vanderplas, Intermediate Scikit-Learn
- Diving deeper into Machine Learning with Scikit-learn - Olivier Grisel and Jake VanderPlas (PyCon 2014)
- Advanced Machine Learning with scikit-learn - Olivier Grisel (2013)
- Statistical Machine Learning for Text Classification With Scikit-learn and NLTK - Olivier Grisel (PyCon 2011)
- Scikit-learn video tutorials
- Enough Machine Learning to Make Hacker News Readable Again - Ned Jackson Lovely (PyGotham 2014) & (PyCon 2014
- Building a Beer Recommender, slides & live demo
- Forecasting beer consumption with sklearn
- scikit-learn-book - gmonce
PYTHON - DATA ANALYSIS - SCIKIT-LEARN - DEPLOYMENT
- sklearn-porter - Transpile trained scikit-learn estimators to C, Java, JavaScript and others
- Train and host Scikit-Learn models in Amazon SageMaker by building a Scikit Docker container - Morgan Du and Thomas Hughes (AWS)
- Machine Learning as a Service with TensorFlow - Kirill Dubovikov
- Google Cloud Datalab: Overview | Quickstart | How-To Guides | Documentation
- Google Cloud ML Engine: Overview | Quickstart | Getting Predictions with scikit-learn and XGBoost - Google Cloud
- Google Cloud Natural Language: Overview | Quickstart | Documentation | How-To Guides | Analyzing Entities | Content Classification Tutorial
PYTHON - DATA ANALYSIS - SCIPY
- SciPy Reference Guide & PDF & Github
- SciPy Cookbook
- Scientific Python lecture notes - EuroScipy tutorial team & PDF
- SciPy: Library of scientific algorithms for Python - JR Johansson
- Topical Software (add-on software relevant to SciPy, categorized by scientific discipline or computational topic)
PYTHON - DATA ANALYSIS - SPYRE
- Live example
- Spyre (Github)
- From DataFrame to Web Application in 10 Minutes - Adam Hajari (PyData NYC 2014)
PYTHON - DATA ANALYSIS - SQL
- Comparing Pandas with SQL
- Translating SQL to pandas. And back - Greg Reda (PyData NYC 2014)
- pandasql (query Pandas with SQL)
PYTHON - DATA ANALYSIS - STATSMODELS
- StatsModels documentation
- Statsmodels
- Statsmodels tutorial - Skipper Seabold (ciPy 2012) & code
- Included datasets
- Multiple Regression using Statsmodels
PYTHON - DATA ANALYSIS - SYMPY
- SymPy: Website | Docs
- Symbolic Computing With SymPy (SciPy 2013) - 1 2 3 4 5 & 6
- Sympy - Symbolic algebra in Python - JR Johansson
PYTHON - DATA ANALYSIS - TPOT
- TPot: Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming: Documentation | Github
PYTHON - DATA ANALYSIS - VIDEOS
PYTHON - DATA ANALYSIS - XRAY
PYTHON - DATABASE ADAPTERS
PYTHON - DJANGO
PYTHON - DOCUMENTATION
- Basic Doctest Python - Daniel Arbuckle
- doctest: Test interactive Python examples
- Intro to doctest2 for existing users of doctest
- Documentation, Testing and Packaging - Jake Vanderplas
PYTHON - FALCON (API FRAMEWORK)
PYTHON - FINANCE
- QuantStart.com
- Financial analysis Python tutorial - Thomas Wiecki
- Python for Quant Finance - Yves Hilpisch (PyData NY 2014)
- Python Charting Stocks/Forex for Technical Analysis - Sentdex
- Quantopian - the people behind Zipline
- Building Quant Equity Strategies in Python - Dr. Jess Stauth
- ultra-finance - real-time financial data collection, analyzing & backtesting trading strategies
- Practical Approaches to Problems in the Financial Industry using Python - Andy Fundinger (PyGotham 2014)
- Quant.StackExchange.com
PYTHON - FINANCE - IBPY
- IbPy (Interactive Brokers online trading system Python API
- How to use IBPy Python with Interactive Brokers TWS API For Automated Trading - Sentdex
- Using Python, IbPy and the Interactive Brokers API to Automate Trades
PYTHON - FINANCE - TA-LIB
PYTHON - FINANCE - QUANTLIB
PYTHON - FINANCE - ZIPLINE
PYTHON - FLASK
PYTHON - FUNCTIONAL PROGRAMMING
- Functional Programming in Python - Daniel Kirsch (PyData Berlin 2016)
- Learning Data Science Using Functional Python - Joel Grus
PYTHON - FUNCTIONAL PROGRAMMING - MOCHI
PYTHON - GAMES
- Making Games with Python & Pygame
- Invent Your Own Computer Games With Python, 2nd ed
- PyGame.org & tutorials
PYTHON - GAMES - ARCADE
PYTHON - GAMES - CHESS
- Jerry & Building Jerry
- PyStockfish (chess engine)
- Sunfish (simple, extensible chess program)
- Chessnut (another simple chess program
- PyChess.org
- TalkChess.com computer chess club (not just Python)
PYTHON - GETTING STARTED
- Why use Python? Personally, I was blown away by Python's statistical analysis tools and the amazing interactive graphics producible with data processed by Python. Some examples: time-series (ARMA) modeling/forecasting, discrete-choice modeling, vector autoregression modeling/forecasting
- I use and recommend Anaconda: Docs, Install Anaconda & Getting started guide
- I use and recommend using iPython Notebook. A great way to start is by skimming through some of the many iPython Notebooks on the web. You can find many at this gallery of links to iPython Notebooks.
- I recommend these Python learning materials and these free online books
- If you're feeling ambitious and don't want to start with Python but jump straight to data analysis, the Harvard CS 109 ("Data Science") lectures listed under PYTHON - DATA ANALYSIS seem excellent.
PYTHON - GETTING STARTED - ANACONDA
- If you're installing Python on your computer, I recommend Continuum Analytics' Anaconda.
- Advanced Features of Conda Part 1 & Part 2
PYTHON - GENERATORS & ITERATORS
- Loop like a native: while, for, iterators, generators - Ned Batchelder
- Python generator functions for massive performance improvements with lists - sentdex
- Iteration and generators: The Python way
- Fun with iterators and generators - Malcolm Tredinnick
- Generators: The Final Frontier - David Beazley (PyCon 2014)
PYTHON - GRAMPS (GENEALOGY)
PYTHON - GRAPHICS
PYTHON - GRAPHICS - 3D VISUALIZATION
PYTHON - GRAPHICS - AVOPLOT
PYTHON - GRAPHICS - BEARCART
PYTHON - GRAPHICS - BOKEH
- Data Applications with Bokeh - Bryan Van De Ven (PyData 2016)
- Bokeh in iPython Notebook - ContinuumIO
- Tutorial
- Gallery
- Bokeh User Guide
- Bokeh Reference
- New in Bokeh 0.6
- Interactive Browser Visualizations from Python with Bokeh - Bryan Van De Ven (PyData 2014) & tutorial files & slides
- Bokeh: An Extensible Implementation of the Grammar of Graphics in Python - Peter Wang & Hugo Shi (2012)
- Data Analysis with Python, Pandas, and Bokeh - Chris Metcalf
PYTHON - GRAPHICS - GGPLOT
- Data Visualization for Social Science - Kieran Healy (Duke)
- Ggplot for Python - Greg Lamp (PyData 2014 Silicon Valley), Github tutorial & slides
- Analyzing MLB data with ggplot - Greg Lamp & slides
PYTHON - GRAPHICS - MAPS
- Making Interactive Maps For the Web - Zain Memon (2012)
- Spatial Data and Web Mapping With Python
- Using Geospatial Data with Python - Kelsey Jordahl (SciPy2013), Part 1 of 6, Part 2, Part 3, Part 4, Part 5, Part 6
PYTHON - GRAPHICS - MAPS - FOLIUM
PYTHON - GRAPHICS - MATPLOTLIB
- Intro to Matplotlib - Hannah Aizenman & Thomas Caswell (SciPy 2019 Tutorial)
- Intro Notes: Matplotlib
- Matplotlib API, PDF documentation, examples index, examples gallery & screenshots gallery
- Pyplot API
- Matplotlib - Chris Fonnesbeck
- Matplotlib Intro - Jake Vanderplas Matplotlib In-depth
- Beyond Defaults: Creating Polished Visualizations Using Matplotlib - Hannah Aizenman (PyConUS 2014)
- Matplotlib: Past, Present and Future - Michael Droettboom (SciPy 2013)
- Matplotlib - 2D and 3D plotting in Python - JR Johansson
- Tutorial: Advanced Matplotlib - library author John Hunter
- Plotting With MatPlotLib - Mike Müller
- Intro to NumPy and Matplotlib
- An exercise with matplotlib and numpy
- matplotlib: Lessons From Middle Age - John Hunter
- Advanced Matplotlib - Ryan May
- Plotting With Matplotlib - Mike Mueller
- Anatomy of Matplotlib (1 of 3) - Benjamin Root (SciPy 2013), (2 of 3), (3 of 3) & iPython Notebooks
PYTHON - GRAPHICS - MATPLOTLIB - MPLD3
PYTHON - GRAPHICS - MATPLOTLIB - SEABORN
PYTHON - GRAPHICS - TUFTE SLOPE GRAPHS
PYTHON - GRAPHICS - VINCENT
- Vincent (Python to Vega translator)
- Intro to Pandas and Vincent
- Mapping Data in Python with Pandas and Vincent
PYTHON - IPYTHON NOTEBOOK / JUPYTER
- All About Jupyter - Brian Granger
- iPython
- Documentation
- Documentation & Keyboard Shortcuts & Cookbook
- Quick reference sheets
- The iPython Notebook Revolution - Catherine Devlin (2013)
- Gallery of interesting iPython Notebooks
- iPython.org example notebooks
- Learning iPython for Interactive Computing and Data Visualization - Cyrille Rossant
- iPython Interactive Computing and Visualization Cookbook
- iPython Minibook code - Cyrille Rossant
- IPython: Python at your fingertips - Fernando Pérez (PyCon 2012)
- IPython In Depth: High-Productivity Interactive and Parallel Python - Fernando Pérez (PyCon 2014) & (PyCon 2012)
- iPython: Tools for the Entire Lifecycle of Research Computing - Fernando Perez et al. (ciPy 2012)
- Mining Social Web APIs With iPython Notebook - Matthew Russell (PyCon 2014)
PYTHON - IPYTHON NOTEBOOK - DEBUGGING
PYTHON - IPYTHON NOTEBOOK - INTERESTING NOTEBOOKS
PYTHON - IPYTHON NOTEBOOK - MAGIC
PYTHON - IPYTHON NOTEBOOK - NBCONVERT
- Converts iPython Notebooks to HTML, Latex, Reveal.js slideshows, Markdown, reStructured Text, or Python scripts
- Now part of iPython
- Converting notebooks to other formats
PYTHON - IPYTHON NOTEBOOK - NOTEBOOK.JS
PYTHON - LEARNING
PYTHON - LEARNING - BASICS
- Python for Beginners - Microsoft
- Python Programming Tutorials - Socratica
- Simple programs
- Programming for Absolute Beginners: Building Skills in Programming - Steven F. Lott
- Learn Python - Nina Zakharenko
- Beginner's Guide: For Non-Programmers | For Programmers
- Google's Python Class
- Hackr.io Python resources list
- Introduction to Programming With Python - Microsoft Virtual Academy (Jumpstart)
- Coursera.org Python courses
- EdX.org Python courses
- Udemy.com Python courses & non-free
- Python Notes/Cheatsheet
- Introduction to Computing using Python - David Joyner (Georgia Institute of Technology & EdX)
- Invent With Python
- Beginner Python 3+ tutorials - Harrison Kinsley & All tutorials
- Python 3 Tutorial - Bernd Klein or Python 2 Tutorial
- Learn to Program: The Fundamentals - Jennifer Campbell and Paul Gries - U of Toronto (Coursera)
- Programming Foundations with Python: Learn Object-Oriented Programming - Kunal Chawla (Udacity)
- Python for Informatics: Exploring Information - Charles Severance, PDF & videos
- Intro to Python - Keven Sheppard
- Programming for Everybody (Getting Started with Python) - Charles Severance (University of Michigan)
- Python Data Structures - Charles Severance (University of Michigan)
- Using Python to Access Web Data - Charles Severance (University of Michigan)
- Using Databases With Python - Charles Severance (University of Michigan)
- Let's Learn Python - Trevor Payne
- Hello, Little Turtles!
- Python Programming - Introduction - TDChannel
- Google's Python Class: Website, Google Python Class Day 1, Pt 1: Intro & Strings, Day 1, Pt 2: Lists, Sorting and Tuples, Day 1, Pt 3, Day 2, Pt 1: Regular Expressions, Day 2, Pt 2: Utilities: OS & Commands, Day 2, Pt 3: Utilities: URLs, and HTTP, Exceptions, Day 2, Pt 4: Closing Thoughts
- An Introduction to Interactive Programming in Python - Rice University (Coursera) & Course 2
- Short Python tutorials - Bucky Roberts
- Python for Programmers: A Project-Based Tutorial - Alexandra Strong, Kantharine Jarmul and Christine Cheung
- Documentation, Testing, and Packaging - Jake Vanderplas
- Introduction to Computer Science and Programming - MIT & on Youtube
- An introduction to Python for absolute beginners - Bob Dowling
- Introduction to Python for Computational Science and Engineering (A Beginner's Guide) - Hans Fangohr
- Intro to Computer Science and Programming Using Python (part 1) - MIT
- Introduction to Programming Using Python - Brian Heinold
- Python Design Patterns 1 - Brandon Rhodes
- Hands-On Introduction to Using Python in the Atmospheric and Oceanic Sciences - Johnny Wei-Bing Lin (free 1st ed)
- Object Oriented Design - Niko Wilbert
- How to write actually object-oriented Python - Per Fagrell (PyGotham 2014)
- The Hitchiker's Guide to Python
- Command line Python scripts
- A hands-on introduction to Python for beginning programmers - Jessica McKellar (PyCon 2014) & (PyCon 2013)
- Intro to Electrical Engineering and Computer Science I - MIT
- Learn Python the Hard Way
- The best way to learn Python - Charl Botha: Part 1: Install Anaconda on Linux, Part 2: Install Anaconda on Windows, Part 3: Variables, control flow, plotting!, Part 4: slicing, string interpolation, list comprehension, Part 5: Object-oriented programming and bouncing balls
- Python Tutor: Visualize Python code execution - Philip Guo
- Gotcha — Mutable default arguments & Common Gotchas
- Python Koans
PYTHON - LEARNING - BOOKS (FREE)
- The Python Tutorial (Python 3) & Python 2
- Automate the Boring Stuff - Al Sweigart
- A Byte of Python
- Functional Programming in Python - David Mertz
- Fundamentals of Python - Richard L. Halterman
- Python Programming
- Python Tutorial (TutorialsPoint.com)
- Think Complexity
- Think Python
- Programming Python, 4th ed
- Building Skills in Python
- Dive into Python 3
- Building Skills in Object-Oriented Design
- Hacking Secret Ciphers with Python
- Hands-On Python Tutorial
- How to Think Like a Computer Scientist: Learning with Python & PDF
- Official Python Documentation
PYTHON - LEARNING - VIDEOS
- Python for Everybody - Full Course with Dr. Chuck (University of Michigan Professor Charles Severance)
- Python Tutorial for Beginners [Full Course] 2019 - Mosh Hamedani
- Full Python Programming Course | Python Tutorial for Beginners | Learn Python (2019)
- Python Tutorial For Beginners | Python Full Course From Scratch - Edureka
- SciPy: Austin 2019 | Japan 2019 | Austin 2018 | Austin 2017 | Austin 2016
- PyCon: 2019 | 2018 | 2017 | 2016
- PyData: Amsterdam 2019 | Miami 2019 | NYC 2018 | London 2018 | Berlin 2018
- PyVideo.org
- Khan Academy
- Introduction to Computational Thinking and Data Science - MIT
- Python Fundamentals Training
- Python Course - Kevin Sheppard (University of Oxford)
- Python for Developers - Luiz Eduardo Borges
- Transforming Code into Beautiful, Idiomatic Python - Raymond Hettinger (2013)
- Python 3.3: Trust Me, It's Better Than 2.7 - Brett Cannon (PyCon US 2013
- Python for Ruby Programmers - Mike Leone (LA Ruby Conf 2013)
- PyGotham 2014 talks (click on talk to see video link)
- Super Advanced Python - Raymond Chandler III
- Keynote - Raymond Hettinger (2013)
- All Your Ducks In A Row: Data Structures in the Std Lib and Beyond - Brandon Rhodes (PyCon 2014)
- Militarizing Your Backyard with Python: Computer Vision and the Squirrel Hordes - Kurt Grandis (PyCon 2012)
- Decorators 101: A Gentle Introduction to Functional Programming - Jillian Munson (PyGotham 2014)
PYTHON - MODULES & PACKAGING
- Tutorial on Installing Packages, Tutorial on Packaging & Distributing Packages, Tool Recommendations & Advanced Packaging Topics
- Python Packaging User Guide
- Python Tutorial - Modules
- Sample project with best practices- Python Packaging Authority
- Python Module Index & Standard Library
- Modules 101: how to avoid spaghetti, big balls of mud and houses of straw! - Graeme Cross (PyCon Australia 2013)
- Hitchhiker's Guide to Python: Structuring Your Project & Packaging Your Code
- How to Setup a new Python Project - Felix Wick (EuroPython 2014)
- 5 Simple Rules For Building Great Python Packages
- Distributing Python Modules (Python 3.4)
- Nobody Expects the Python Packaging Authority - Nick Coghlan (PyCon Australia 2013)
- Importing iPython Notebooks as Modules
- Youtube
- Python Packages and You - Harold Abnabit
- Python packaging simplified, for end users, app developers - Asheesh Laroia (PyCon 2014)
PYTHON - MODULES & PACKAGING - VERSIONEER
PYTHON - MODULES & PACKAGING - WHEELS
- Grug make fire! Grug make wheel! - Russell Keith-Magee (PyCon Australia 2014)
- Wheel
- PythonWheels.com
PYTHON - NATURAL LANGUAGE PROCESSING (NLP)
PYTHON - PERFORMANCE
- Fast Python, Slow Python - Alex Gaynor (PyCon 2014)
- Tools for high-performance computing applications - JR Johansson
- Beginners' Guide to Concurrency and Parallelism in Python - Marcus McCurdy
PYTHON - PERFORMANCE - DASK
- Dask - minimal task scheduling abstraction and parallel arrays (ContinuumIO): Github | Documentation
- Dask Youtube channel
- Dask Joblib - Many Scikit-Learn algorithms are written for parallel execution using Joblib
PYTHON - PODCASTS
- Django Chat
- Import This
- PG Podcast - Philip J. Guo (videos)
- Podcast.init
- PythonBytes
- Talk Python to Me
- Test & Code
PYTHON - PYLAB
- DON'T USE PYLAB!!!
- Please Stop Using Pylab
PYTHON - PYPI
PYTHON - PYTORCH
- PyTorch: Documentation
- Artificial Intelligence - Leonardo Araujo dos Santos: Downloadable PDF | Online version
PYTHON - SPYDER
PYTHON - TESTING
- Improve your testing with Pytest and Mock - Gabe Hollombe (PyCon SG 2015)
- Why I use py.test and maybe you should too - Andy Todd (PyCon Australia 2013)
- Testing Your Code (Python Guide)
- Getting Started Testing - Ned Batchelder (PyCon 2014)
- Documentation, Testing and Packaging - Jake Vanderplas
- Version Control and Unit Testing for Scientific Software Tutorial, Part 2 of 3 - Matt Davis (SciPy 2013)
PYTHON - TESTING - MOCK
PYTHON - TESTING - NOSE
PYTHON - TEXT ANALYSIS
PYTHON - TEXT ANALYSIS - FASTTEXT
PYTHON - TEXT ANALYSIS - GENSIM
- Gensim: Website | Github | Tutorials | Quick Start Jupyter Notebook | API docs
PYTHON - TEXT ANALYSIS - NATURAL LANGUAGE TOOLKIT (NLTK)
- Statistical Machine Learning for Text Classification With Scikit-learn and NLTK - Olivier Grisel (PyCon 2011)
- Enough Machine Learning to Make Hacker News Readable Again - Ned Jackson Lovely (PyGotham 2014) & (PyCon 2014
- Getting Started with NLTK
- How to Use Stanford Named Entity Recognizer (NER) in Python NLTK and Other Programming Languages
PYTHON - TEXT ANALYSIS - PATTERN
PYTHON - TEXT ANALYSIS - PYTEXT
PYTHON - TEXT ANALYSIS - SPACY
- Spacy.io: Industrial-strength NLP | Training
- Spacy 101: The most important concepts, explained in simple terms
- Spacy Course - Ines Montani | Course.spacy.io
PYTHON - TEXT ANALYSIS - STANFORD CORENLP
PYTHON - TEXT ANALYSIS - TEXTBLOB
- TextBlob: ReadTheDocs, PDF, Quickstart guide, Github
- Tutorial: Simple Text Classification with Python and TextBlob - Steven Loria
PYTHON - TEXT ANALYSIS - TWITTER CLIENTS
- Intro to Text Mining using Twitter Streaming API and Python - Adil Moujahid
- Analyzing a NHL Playoff Game with Twitter - Daniel Forsyth
- Introduction to tweepy, Twitter for Python - Ahmet Novalić
- Tweepy
PYTHON - VIDEOS
PYTHON - VIDEOGREP
PYTHON - VS CODE (VISUAL STUDIO CODE)
- Python development with Visual Studio Code - Luciana Abud
- Supercharge your data science workflow with VS Code - Jeffrey Mew & Sid Unnithan
PYTHON - WEB
PYTHON - WEB - PYODIDE (SCIENTIFIC STACK IN WEB ASSEMBLY)
- Pyodide - The Python scientific stack, compiled to WebAssembly: Docs
PYTHON - WEB SCRAPING
- Web Scraping 101 with Python & Web Scraping 201: finding the API - Greg Reda
- Intro to Web (and data!) Scraping with Python - Katharine Jarmul (PyCon 2014)
- Scrape Websites with Python + Beautiful Soup 4 + Requests -
- Scrapy & Github
- Web scraping: Reliably and efficiently pull data from pages that don't expect it - Asheesh Laroia
- Web scraping tutorial series