PythonDataScienceHandbook VS Wagtail

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/

If you like Python 🐍 then check out this project. Wagtail is a popular CMS, combining Django’s powerful customization capabilities with a slick user interface. The newest update brings Django 5.0 support, a new searchable and filterable listing UI, the accessibility checker built into the admin interface, and a brand new 10-step tutorial for developers. This release marks Wagtail's 10th birthday 🎂. Happy birthday to the team and all the best for the next ten years and beyond 🥳.

Repo : https://github.com/wagtail/wagtail

- The discussion thread we use to track all public feedback: https://github.com/wagtail/wagtail/discussions/9553. Comments very welcome.

Not so long ago, I submitted a Pull Request in wagtail to improve the admin performance, especially for non-superusers. Basically, it caches all the user's permissions on first access. However, I was pretty sure that this would load a lot of model fields that we never need but there isn't a tool that gives us that type of report. Therefore, I started building an app that keeps track of all fields accessed so you can easily know which ones haven't been used and apply the only/defer optimisation for Django querysets.

Wagtail would be a good example https://github.com/wagtail/wagtail/tree/main/wagtail/tests

Paarth moving from no contributions to the 21st most contributions - https://github.com/wagtail/wagtail/graphs/contributors.

Over the last few years, I have had the incredible opportunity to be a core team member of the Wagtail project. In that time, I have reviewed many new pull requests, and I’ve also had the chance to submit many of my own across Wagtail and many other projects.

Wagtail 2.15 is the most recent LTS (Long Term Support) release, so it’s not a bad release to stick to at all, at least until February 2023.