For example, a person represented as a node may have attributes like age, gender, salary, etc. In a complex network, we also have attributes or features associated with each node and edge. It is made up of a collection of two generic objects - (1) node: which represents an entity, and (2) edge: which represents the connection between any two nodes. Network or Graph is a special representation of entities which have relationships among themselves. For more details, see this separate blog. It can be thought of as the 4th option in the list discussed below. Update 2nd Feb, 2021: I recently released Jaal, a python package for network visualization. Nodebox for Data Visualization from Lynn ChernyĮTA: Web video of my talk is here on the Pydata vimeo site.Every code from this article is published in this repository. My talk was generally well-received, although I think I flummoxed the stats graphics people a little bit who probably weren't expecting something so "sketchy" from me. Hey, I love those other tools too, and use Matplotlib (and d3 too!) regularly.Ī few quick comments on the Nodebox eco-system: The current focus of the team in Leuven is on Nodebox 3, a block-diagram visual programming tool, not the 2 variants I talked about (Nodebox 1 and Nodebox OpenGL). I think NB3 veers away from usefulness for the data science crowd that might benefit from a Python alternative to Processing. If the enormous success of the java-based Processing is anything to go by, I'm not crazy in thinking a Python tool like it should be huge! After all, it's cuddly Python! So at the end of my talk, someone actually asked me why he should have sat there for 45 minutes if I was not talking about thriving open source code with a huge community behind it. My response was, more or less, "It's already super useful which I hope I showed, and more people could be working on it than just the original authors." That's how open source works, right? (By the way: That guy apologized to me later, but I didn't take it badly when he said it.)Ī couple more comments on my slides: My own data experiments in the deck weren't incredibly successful, largely due to issues with the database I used. (Also, it proved less useful on older Gutenberg books, because old-fashioned vernacular nouns don't appear in the db, like "momma." So out went Pride and Prejudice and out came my credit card for Kindle books.) Hence, all my fiction gender plots look kind of like these, with heavy weights towards male and neutral nouns: I wanted to explore Shane Bergsma's gender-of-nouns database collected off Google news, and what I found was that it thinks everything is really "male." Cuz most news articles are about men, probably. The pdf of my slides is here and the code zip file is here. Do check my appendices: I figured out a bunch of issues related to paths in Nodebox 1, running NB 1 from the command line, and the like.Ī couple nice post-conference mentions: Jake Vanderplas's take on Matplotlib history and visualization in Python, which has some interesting comments. I spent a while talking to Ben Lorica at PyData, and he nicely mentioned Nodebox in his well-RT'ed article on how Python Data Tools Just Keep Getting Better.Īlso, before the conference, I was interviewed for a podcast about data vis skills.
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