Hacker News Reader

Comment by MattPalmer1086 | Hacker News Reader

The question I would ask is why should I use this over the many other JavaScript plotting libraries?

I just went through a process of evaluating around 7 different libraries and eventually decided on Plotly.

What is the USP of Observable Plot?

I think their examples gallery mostly speaks for itself: this is a VERY capable plotting library. https://observablehq.com/@observablehq/plot-gallery

Yes, there are lots of nice charts. Other libraries also have lots of nice charts too though!

For me the most useful features of Plot over other libraries are the declarative transforms: bin, stack, map, filter, etc. This means that a lot of the data munging that you would normally do before passing things off to the plotting library are done by Plot itself. Why would you want that? Well these transforms are now "facet aware" - if you want to facet on some some qualitative property, slap a `fx: property` on your mark and your transforms will then be run for each subplot.

Secondly, I simply find the API to be very tastefully built. The Geo API (https://observablehq.com/plot/marks/geo) is a particular highlight. I've used Plot for about 1.5 years for recreational side projects - it has genuinely kept me entertained for many hours in no small part due to its interface design.

Thanks, that is genuinely useful.

I may have a look at the transforms.

If you’re using plotly (js) and good at it then stick with it as it gives you so much flexibility - especially with scientific plotting.

I saw the examples for OP and did not see anything challenging Plotly for my use cases.

Yes, this is for charts on experimental data. Plotly seemed good for that.

Out of curiosity I’d love to see any examples where you think Plotly is especially strong for scientific plotting. I’ve used Plot lots and Plotly none, but I’d guess the big Plotly advantages right now are

- rich tooltips (coming soon in Plot)

- interactive pan & zoom

- multiple panels with shared scales? (like for marginal distributions; you can combine with HTML of course, but it’s not easy/built-in in Plot)

The interactive stuff and tooltips are useful for exploring the data for sure.

Reply on news.ycombinator.com