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Comment by eatonphil | Hacker News Reader

The thing I've wanted is a visualization library that also comes with the UI controls for configuring graphs: picking the graph type, picking the fields, picking the labels, picking the aggregation, axis settings, etc.

Almost no one is implementing libraries that do this. Everyone just keeps building "low-level" graph libraries that leave application developers to build up (in my case) crappy and inflexible configuration UIs.

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Ever try Perspective? https://github.com/finos/perspective

my experience has been that non of these solutions provide enough control granularity, and i keep coming back to d3.js (or other libraries like deck.gl) and building my own UI.

In a similar vein, my experience is that most visualizations that people are commonly making are reaching for what is available in R. https://r-graph-gallery.com/ggplot2-package.html

In my case that is 100% true. What I actually want is R but for the web. All the JS libraries are either too simple and rigid or too low level like d3.

Has anyone done any work to compile R to wasm?

You can't have it both ways. You can't have a completely open data representation and an abstraction at a higher level than d3. What you are calling too low level is basically dealing with the fact the data can be anything.

What we really need is a javascript dataframe that everyone uses by default but that is not going to happen. Javascript culture is practically all about reinventing and trying to improve the wheel so we can optimally go in circles.

I think there is an emergent self interest at the group level to keep things complex and salaries growing on the front end too. The complexity and absurdity is hardly a bug at the individual level if getting paid.

The biggest difference IMO is that there is no default data representation that 99.99% of people use in javascript like pandas/dataframes/numpy/zoo in python/R.

I would even say javascript has better visualization libraries than GGplot but because there is no javascriptDataframe.plot('line') the visualization libraries end up down their own path because of different data representations.

My experience also is that every visualization library will lack something if you want to do anything beyond the most standard visualizations. Almost by definition it has to be that way.

Agreed, I think. Though, ggplot is very tough competition. And a lot of the niceties of small multiples and such are going to be a super power for folks using them.

You don't want a visualization library, you want a full-featured BI toolset.

What OP posted isn't "low level", I'd describe it as low-feature, intermediate-level visualization library.

My personal favorites are Altair (Python/VegaLite) and Observable Plot. The latter just released a new version with GeoJSON support.

Cube has a nice set of React based examples, which helped highlight some of the better options along your thinking:

Dashboard - https://highcharts-demo.cube.dev/#/

Pivot - https://react-pivot-table-demo.cube.dev/#/

Query builder - https://react-dashboard-demo.cube.dev/#/explore

I personally would avoid BI in the stricter definition (Superset, PowerBI, Metabase etc) unless you are building internal tools, as they have significant baggage catering for their designed use case.

Yes, same here. I'd love an open source Power BI alternative.

Check out Apache Superset: https://superset.apache.org/

Originally from Airbnb. Very powerful and flexible OS frontend BI tool

a) Apache Superset is neither powerful nor flexible. It has the absolute minimum functionality to still be called a "BI tool", but just barely.

b) Sadly, Apache Superset is the only "BI tool" that is both free and open source, so you don't have any choice in the matter anyways.

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