JS Bin VS PythonDataScienceHandbook

JS Bin is one of the useful JavaScript debugging tools designed for developers working with HTML, CSS, and JavaScript. It gives them the opportunity to test and debug their code snippets in a real-world setting. The fact that this tool is open-source is fantastic.

If I paste both in jsbin.com, the both show all content on 1 line.

A running example in https://jsbin.com/ might be easier to help with

JSBin : Front end playground, Output is not framed, so it allows you to share those snippets that will break inside an iframe.

> What if you want introduce some diagramming or Latex rendering in your blog ?

Then you are starting to step beyond what I was referring to as “a simple blog” (text, formatting, maybe some pictures or SVG).

Though there are options that don't require a CI/CD pipeline. Depending on what Latext you need MathJax may do the trick (just include the JS in your standard page header, and drop the Latex code straight in inline where needed as per their standard example: https://jsbin.com/?html,output. There are similar charting options like mermaid too. I don't know of inline charting options off the top of my head but I expect several exist.

Post your code on codesandbox.io or jsitor.com or jsbin.com or jsfiddle.net or whatever other site you prefer. Then we can look at it and see what is wrong. Otherwise, it's like showing us a picture of your cat and asking whether we think you might be allergic to it.

Important note: do not perform tests with WeakRefs in dev tools. Your objects won't be GCed in it due to DevTools specific behaviour. Instead, use jsbin, codesandbox, runkit or perform tests in Node.js. Localhost is okay when you open files using http:// protocol, as file:// also has specific behaviour.

https://jsbin.com/ (Type in the code; press go)

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/