Data Analysis Tools: Python
Learning Resources
A Whirlwind Tour of Python by Jake VanderPlas
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This material is released under the "No Rights Reserved" CC0 license
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
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Copyright Creative Commons Attribution 3.0 - Charles R. Severance
Python for Data Analysis by Wes McKinney
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The 2nd edition ebook is available in CLIO
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The 3rd edition ebook is now available as an “Open Access” HTML version on the author's personal website.
Columbia affiliates can 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 Download and Installation
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.
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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.
Google Colab provides both free and paid level plans, see details here; Colab resource limits FAQ
