Most of the data visualized by these types of libraries don't have any sort of variance or confidence interval behind the data. You're looking at things like sa

Most of the data visualized by these types of libraries don't have any sort of variance or confidence interval behind the data. You're looking at things like sales forecasts, server latency, number of employee hours, or other precisely measurable quantities. The whole context around those numbers never talks about the notion of variability or reproducibility, so the idea of putting error bars on there doesn't help communicate anything. Why don't scientists use these libraries, making error bars an appealing thing to add? In my experience, D3 isn't a great too for interactive analysis: plot, stare, tweak, re-plot. I get bogged down in the details of the visualization, vs something like Matlab that almost always throws up a reasonable plot with interactive controls. Since D3 doesn't encourage the type of workflow that results in a graph with error bars, you get a self-reinforcing dynamic where nobody who works with D3 is interested in making it easy to create graphs with error bars.