cl-cookbook VS PythonDataScienceHandbook

> the problem with Lisp is that it's sorta bundled with Emacs

What's the problems with Alive, SLT, Slyblime, and Vlime? I mean, I use Emacs, but I was using Emacs before getting into Scheme and CL anyway.

> Every website that teaches Lisp is in ugly HTML+CSS-only style

I dunno, I feel like the Community Spec (<https://cl-community-spec.github.io/pages/index.html>) and the Cookbook (<https://lispcookbook.github.io/cl-cookbook/>) are fine.

> I like the philosophy of (s-exp) but modern lisps have ruined its simplicity for me by introducing additional bracket notations [like this].

Yes, that additional notation is a terrible blight on the perfection that is S-expressions, I wholeheartedly agree.

check out the editor section, there's more than Emacs these days: https://lispcookbook.github.io/cl-cookbook/editor-support.ht...

- https://github.com/CodyReichert/awesome-cl for libraries

- https://www.classcentral.com/report/best-lisp-courses/#ancho...

- a recent overview of the ecosystem: https://lisp-journey.gitlab.io/blog/these-years-in-common-li... (shameless plug, on HN: https://news.ycombinator.com/item?id=34321090)

Q4: the Cookbook should get you straight to the point: build a website, web scraper, DB access, reference of data structures… https://lispcookbook.github.io/cl-cookbook/

It's a good book!

Modern companions would be:

- the Cookbook: https://lispcookbook.github.io/cl-cookbook/ (check out the editors section: Atom/Pulsar, VSCode, Sublime, Jetbrains, Lem...)

- https://github.com/CodyReichert/awesome-cl to find libraries

Also:

- https://stevelosh.com/blog/2018/08/a-road-to-common-lisp/

- https://news.ycombinator.com/item?id=34321090 2022 in review

https://leanpub.com/lovinglisp -- this one is great, and the first thing I recommend

https://lispcookbook.github.io/cl-cookbook/ -- also great and up to date

https://awesome-cl.com/ -- for anything else.

Little help to boost your videos: https://lispcookbook.github.io/cl-cookbook/ look at the banner. Cheers.

For more beginner-friendly, I suggest P. Siebels Practical Common Lisp or The CL Cookbook. Both of those should be available in Emacs info format! If authors are lurking in here :-)

the code snippet used for the example is here: https://github.com/LispCookbook/cl-cookbook/pull/472

Python Data Science Handbook

Python Data Science Handbook — learn to use Python libraries such as NumPy, Pandas, Matplotlib, Scikit-Learn, and related tools to effectively store, manipulate, and gain insight from data

I don't know what tools you will be using but if you will be using Python you can start with Python Data Science Handbook by Jake VanderPlas and Data Science & Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting DataData Science & Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data which gives a very good outlook on the data science and big data frame work. PS: Jake's book is also available as jupyter notebooks so you can read and run the code at the same time.

Python Data Science Handbook by Jake VanderPlas (https://jakevdp.github.io/PythonDataScienceHandbook/)

Otherwise you can work through courses on Datacamp, Coursera, Udemy, etc, or check out this book for a more general non-spatial perspective.

7. Data Science Handbook Are you looking for a comprehensive guide to data science with Python? Look no further than the Data Science Handbook by Jake VanderPlas. This repository contains the entire book, which introduces essential tools and techniques used in data science, including IPython, NumPy, Pandas, Matplotlib, and Scikit-Learn. It’s a fantastic resource for anyone looking to deepen their understanding of data science concepts and best practices.

I can recommend https://jakevdp.github.io/PythonDataScienceHandbook/