Data visualization authors fight defaults and fragile plot exports
Scientific plot authors and data-visualization developers need more control over chart layout, styling, and exported output than their libraries’ defaults make easy. They report laborious manual tweaking, slow callback-based workarounds, and cases where math labels are missing from SVG exports. The signals span different libraries and workflows, so a useful product would likely need to start with one ecosystem rather than promise a universal fix.
For scientific plot authors and data-visualization developers. Mentioned from Jun 2017 to May 2024 on GitHub and Hacker News.
4 different people described this problem in 4 separate discussions.
- Indie fit
- 5.0/10
- Pain
- 6.0/10
- Frequency
- 5.8/10
- Willingness to pay
- 0.0/10
- Momentum
- 5.0/10
- Who pays
- Professionals
- Competition
- Medium
- Build difficulty
- Medium
What people said
Quoted word for word. Follow a link to read the whole discussion.
My pet-peeve with matplotlib is the terrible layout of multiple plots on a grid. It's tedious (requires quite a bit of redundant typing), setting aspect ratios is tricky, getting margins right is an effort of trial and error -- setting reasonable font-sizes will almost certainly get you overlapping axes labels (especia…
Users can also render KaTeX labels on plots with an extension, but since these are separate DOM elements, they are missing from the SVG export. We use canvas2svg to convert the plot canvas to SVG, and presumably if KaTeX could generate SVG as well, we could find a way to merge things together
Build brief
See what to build and who will buy it
- 3 product ideas with the smallest useful version and pricing
- 4 places to find your first customers
- 2 more quotes from people who have this problem
- Current workarounds, existing solutions and risks