A Whirlwind Tour of Python by Jake VanderPlas

• Copyright 2016 O’Reilly Media, Inc., 978-1-491-96465-1

Python Data Science Handbook by Jake VanderPlas

• The text is released under the CC-BY-NC-ND license, and code is released under the MIT license.

Python for Everybody 

• Copyright Creative Commons Attribution 3.0 - Charles R. Severance

Python for Data Analysis by Wes McKinney

• The 2nd edition ebook is available in CLIO

• The 3rd edition ebook is now available as an “Open Access” HTML version on the author's personal website. 

  • McKinney W. (2022). Python for data analysis : data wrangling with pandas numpy and jupyter (Third). O'Reilly Media. Retrieved November 11 2022 from https://www.oreilly.com/library/view/-/9781098104023/.

Columbia affiliates find more books in CLIO.

Novice-level Python tutorials by Software Carpentry

• Plotting and Programming in Python
  • This lesson is an introduction to programming in Python 3 for people with little or no previous programming experience.
•  Programming with Python 
  • It provides three options (Jupyter Notebook, IPython interpreter, plain-vanilla Python interpreter) to launch Python interface.

LinkedIn Learning  

• CLIO portal (Columbia UNI authentication needed; only for current affiliates)
• Please search "Python" in the search box

Python is an open-source, interpreted, high-level and general-purpose programming language.

Jupyter is a widely-used Python IDE (Integrated Development Environment) for data analysis. Other popular Python IDEs for data analysis include Spyder, PyCharm, etc.

• Perkel, J. M. (2018). Why Jupyter is data scientists' computational notebook of choice. Nature, 563(7732), 145-147.

Anaconda is a popular Python distribution platform, with pre-installation of Jupyter Lab, Jupyter Notebook, Spyder, PyCharm, RStudio, etc. Here is the Anaconda cheatsheet.

• How to install Anaconda
• Getting started with Anaconda

Google Colab provides both free and paid level plans, see details here; Colab resource limits FAQ