Python Data Science Handbook
Essential Tools for Working with Data
by Jake VanderPlas · first published 2016
12mentions
8recommended by
12HN commenters
2016–2026first – last mentioned
67% recommend25% neutral8% critical
Why HN recommends it
Practical Python tour of the NumPy, pandas, Matplotlib and scikit-learn stack, with code-first examples. It suits beginners in data science and self-taught programmers building personal projects.
Summarised by Claude from recommending comments
Revision History December 2016: First Edition 2016-11-17: First Release
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See also "Python Data Science Handbook" by Jake VanderPlas, which uses Jupyter notebooks too. [0] https://jakevdp.github.io/PythonDataScienceHandbook/
on “Python Textbook as a Jupyter Notebook” ↗…very hands-on in Python and helps you run code to "see" how ML works. If you're weak in software engineering and Python, I recommend A Whirlwind Tour Of Python by Jake VanderPlas, and its companion book Python Data Science Handbook. If you're strong in architecting / product management, I recommend Building Machine Learning Powered Applications by Emmanuel Ameisen since it explains it more from an SDLC perspective, including things…
on “The Hundred-Page Machine Learning Book” ↗…got interested in ML because of sport's analytics and betting markets so I read a lot of papers on that topic and books similar to Bayesian Sports Models in R by Andrew Mack[1].Also, Jake VanderPlas's Python Data Science Handbook is good[2]. Ideally, find a vertical you're interested in where experts have applied ML and read their papers/books and work backwards from there. [0]: https://statquest.org/statquest-store/ [1]: https://www.goodreads.com/book/show/216487475-bayesian-sport...…
on “DeepSeek could represent Nvidia CEO Jensen Huang's worst nightmare” ↗…Programming: Python: "Python Crash Course" by Eric Matthes Git: "Pro Git" by Scott Chacon and Ben Straub Machine Learning & Data Science Basics: "Introduction to Data Science" by Laura Igual and Santi Seguí "Python Data Science Handbook" by Jake VanderPlas Stage 2: Learning Machine Learning and Deep Learning Online Courses: Coursera: "Machine Learning" by Andrew Ng Coursera: "Deep Learning Specialization" by Andrew Ng Fast.ai: "Practical…
on “Ask HN: I am a full stack developer, where do I start learning for AI” ↗Think Bayes and Python Data Science Handbook are a good starting point. Below is the list of free books to learn ML/AI http://blog.paralleldots.com/data-scientist/list-must-read-b...
on “Ask HN: What free resources did you use to learn how to program ML/AI?” ↗…Programming Language - Computer Networking: Principles, Protocols and Practice - The Art of Unix Programming - An Introduction to Beginning Linux Programming - Sams Teach Yourself SQL in 24 Hours - The Python Data Science Handbook - Python Programming with OpenCV - Speaking Javascript - Scalable and Modular Architecture for CSS Wade through that lot and you will have learned about C, UNIX/Linux, networking, HTML CSS, Javascript,…
on “Stop Learning Frameworks” ↗Kaggle learn: https://www.kaggle.com/learn "Python Data Science Handbook" (O'Reilly) http://jakevdp.github.io/PythonDataScienceHandbook awesome-python#web-content-extracting: https://github.com/vinta/awesome-python#web-content-extracti... https://learnxinyminutes.com/docs/python/…
on “The World Excel Championship is being broadcast on ESPN” ↗Context: I did not study CS in college & wished I had so I read the python data science handbook, K&R's C, and Stroustrup's Programming Practice and Principles. I spend a significant amount of time bashing my head against getting code for personal projects to work (it usually did, eventually!). I…
…everyday. [PROGRAMMING] - "Fluent Python" - was afraid it'd be too basic, but not really. Enjoyed it a lot. - "Think Complexity" - about algorithm complexity, data structures, etc. Great read. - "Python Data Science Handbook" - meh. - "Fundamentals of Deep Learning" - good intro. Helped me solidify some concepts from Andrew Ng's ML course - "Deep Learning" - by Goodfellow and Bengio. Just started, but really liking it.…
on “Ask HN: Books you read in 2016?” ↗…of notebooks, https://github.com/jakevdp/PythonDataScienceHandbook/blob/ma..., under the Using Code Examples section, "attribution usually includes the title, author, publisher, and ISBN. For example: "Python Data Science Handbook, 2nd edition, by Jake VanderPlas (O’Reilly). Copyright 2023..." compared to the OP's link which has "The Python Data Science Handbook by Jake VanderPlas (O’Reilly). Copyright 2016..."
on “Python Data Science Handbook” ↗…you have any suggestions on good resources on this? I'd like to understand better why the data structures work the way they do and thus have an intuition on what operations to use when. The O'Reilly Python Data Science Handbook[0] seems like it might be useful here, but I'm not sure if it is still up to date. [0] https://www.oreilly.com/library/view/python-data-science/978...
on “An opinionated view of the Tidyverse “dialect” of the R language” ↗Hands-on Machine Learning with Scikit-Learn and TensorFlow [1] is more ML focused, but highly recommended. Out of the three books (Python for Data Analysis and Python Data Science Handbook) I learned the most from this one by far. [1] https://github.com/ageron/handson-ml
on “Python Data Science Handbook: Full Text in Jupyter Notebooks” ↗