Bl.ocks VS iPython

- elijah meeks has some force collision label work that he's done, though I don't know where it lives. I'd google around, it may have lived on bl.ocks.org; there may be more up-to-date stuff too. Source: 11 months ago

D3 is luckily a very popular library with lots of resources available. I'd suggest also checking out bl.ocks and Observable for great examples. The latter one is amazing if you just want to do statistics/visualization work, since it acts like a Jupyter-like notebook environment. Source: about 2 years ago

Yeah, for that use case, https://bl.ocks.org is better than CodePen. Publish a GitHub gist, replace gist.github.com with bl.ocks.org, and sneak in "/raw" between the username and the gist id. You can even point to specific commit hashes. - Source: Hacker News / about 2 years ago

The harder way: Follow an example of someone coding the visualization on their local set up (which may be hard to find depending on what your are looking for as a lot of D3 examples have migrated to Observable). But here is an old glossary of examples it is on an old website called Bl.ocks that showed D3 examples using Github gists. Source: over 2 years ago

That's great, and hey maybe I'll steal some of your recipes from your blog too :) Currently I'm following https://bl.ocks.org/ for inspiration and don't have too many other sources to read through, but your blog seems like it's filled w/ topics on data viz & getting around pain points, I'm all about it! Source: over 2 years ago

Third, if possible use a command line interpreter to test things out. I recommend ipython for this purpose. You can use your browser's developer console this way if you are learning Javascript. Source: about 1 year ago

IJulia is an interactive notebook environment powered by the Julia programming language. Its backend is integrated with that of the Jupyter environment. The interface is web-based, similar to the iPython notebook. It is open-source and cross-platform. - Source: dev.to / about 1 year ago

Also, take a look at installing iPthon to give you a much richer shell environment. This underpins Jupyter Notebooks, so is well known, proven and trusted. Source: about 1 year ago

I know this isn't quite what you're asking for, but IPython (https://ipython.org/) is very capable as a Python + bash (or other) shell, as it allows you to easily integrate the system shell into the interactive environment. Although they now recommend Xonsh (https://xon.sh/) for such purposes. Source: about 1 year ago

Either an online python interpreter like replit.com or simply any python interpreter, like `ipython`, or the default, barebones one that ships with the python installation pacakge. Source: over 1 year ago