3 ms·

I think one of the overarching factors is that those new to data visualization (and web development) see D3's beautiful examples and assume that the D3 library

by danso 8y ago

I think one of the overarching factors is that those new to data visualization (and web development) see D3's beautiful examples and assume that the D3 library is directly and fundamentally responsible for the visual quality. I've seen this a bit with R's ggplot2 as well among relatively experienced data scientists. To be sure, ggplot2 is a fantastic library and the fact that its defaults look great are a testament to the library's well-thought out design. But such design grace can be achieved in any library (e.g. matplotlib), albeit with less graceful APIs.

bunderbunder 8y ago
You can absolutely get there. But the trouble with most libraries I've used is that they are either limiting or confusing. For example, Seaborn is very easy to learn, but it's mostly just a set of canned visualizations, with limited flexibility. Matplotlib is very flexible, but just. so. hard. to. learn. I had a machine learning class in grad school where most everyone agreed the single most difficult homework was one that asked us to use Matplotlib to generate a few visualizations of what the models were doing. Comparatively speaking, learning ggplot2 is a sublime experience. After about a week, you feel like you have super powers. D3 does feel overcomplicated for just building static visualizations, but if you're building custom interactive stuff, learning it can be nearly as joyous an experience.
- _Wintermute 8y ago
  Regarding ggplot, matplotlib and seaborn I found the opposite. If you want some pre-canned visualisation then ggplot2 is fantastic, but as soon as you stray away from the examples it turns into a mess, you can't just drop down into base graphics but have to mess about with grob and grid. Whereas seaborn has similar pre-canned plots, but it's all built on matplotlib so you still have that flexibility if you want it.
cup-of-tea 8y ago
Yeah. If you come to d3 but you've never made a beautiful image in SVG before you're going to have a bad time. You have to be good at SVG, CSS and javascript already. D3 will not help.

by danso 8y ago

bunderbunder 8y ago

You can absolutely get there. But the trouble with most libraries I've used is that they are either limiting or confusing. For example, Seaborn is very easy to learn, but it's mostly just a set of canned visualizations, with limited flexibility. Matplotlib is very flexible, but just. so. hard. to. learn. I had a machine learning class in grad school where most everyone agreed the single most difficult homework was one that asked us to use Matplotlib to generate a few visualizations of what the models were doing. Comparatively speaking, learning ggplot2 is a sublime experience. After about a week, you feel like you have super powers. D3 does feel overcomplicated for just building static visualizations, but if you're building custom interactive stuff, learning it can be nearly as joyous an experience.

_Wintermute 8y ago
Regarding ggplot, matplotlib and seaborn I found the opposite. If you want some pre-canned visualisation then ggplot2 is fantastic, but as soon as you stray away from the examples it turns into a mess, you can't just drop down into base graphics but have to mess about with grob and grid. Whereas seaborn has similar pre-canned plots, but it's all built on matplotlib so you still have that flexibility if you want it.

cup-of-tea 8y ago

Yeah. If you come to d3 but you've never made a beautiful image in SVG before you're going to have a bad time. You have to be good at SVG, CSS and javascript already. D3 will not help.