Announcing ggraph: A grammar of graphics for relational data
data-imaginist.com
data-imaginist.com
Some other projects that might be of your interest:
Since UI design potentially encompasses almost all interactions with designed objects, you must be working with a very narrow definition of what a UI is.
What about the question of "parametric" vs "strategic" choices in UI design? Surely strategic design decisions require a level of investigation into the user's motivations (etc.) that is well outside the remit of data visualization.
Tutorial/Intro: http://minimaxir.com/2016/12/interactive-network/
Practical example using HaveIBeenPwned data: http://minimaxir.com/2016/12/pwned-network/
The catch is that this trick uses the ggnetwork library, which is less-actively developed than ggraph. I remember trying to port the interactive code to ggraph but with not much success (since ggnetwork serves a more of a translator for native ggplot2 functions, while ggraph offers more flexibility). Now that the official release of graph is out, I'll give these types of visualizations another try.
It performs well with large networks (> 1000 nodes) and makes nice javascript plots that can be zoomed, highlighted and dragged about.
There's a REST endpoint and a Pandas (Python/Jupyter) convenience library, so should be quick to use even if the data is in a database. Our customers are primarily doing stuff like security incident investigations over Splunk event logs, for example.
For anyone interested in bigger datasets, just send a note to info@graphistry.com .
http://sachaepskamp.com/files/Cookbook.html
Also the section on penalized Ising models is great, I haven't seen anything else like it.
The problem with ggplot and friends is R. It's frankly painful and archaic to work with.