nodejs-polars VS plot

Polars: A blazingly fast DataFrame library written in Rust for data manipulation and analysis

It turns out we have many options for graphing libraries. Let’s take a look at D3. It advertises itself as “the JavaScript library for bespoke data visualization,” and is also the base of several other graphing libraries, including Observable Plot (developed by the same team as D3), Vega, and Plotly (we’ll come back to that one). The fact that so many people built other projects on top of D3 should give us an idea of what we’re in for – it’s clearly very useful, but probably not so easy to use.

If you want to sacrifice some of the flexibility for less verbosity try out ObservableHQ's Plot [1]

1: https://observablehq.com/plot/

well, Mike Bostock left to create Observable, and in its latest iteration Observable Plot https://observablehq.com/plot/ is amazing.

This makes the old data viz examples from NYT accessible to the rest of the population who aren't D3.js / canvas / svg whisperers like Mike

I think https://github.com/uwdata/mosaic is really promising here. See the example https://idl.uw.edu/mosaic/examples/linear-regression.html where the user can recalculate a linear regression based on their selection.

You'd still need to implement any custom selection widgets, data transformations (like other statistical tests) etc. still missing, but i like the technical design to build on top off. It uses https://github.com/observablehq/plot under the hood, which aims to have just as flexible a grammar as ggplot (already quite capable) but with interactive features (built by the creator of d3 and uses it under its hood).

I don't see that ever happening in a pleasant way.

However, we will likely have Vega support sometime soon in Scroll. Someone just needs to volunteer and add it (or someone has to fund us to add that).

We now have basics of ObservablePlot (https://observablehq.com/plot/) support (https://scroll.pub/blog/tables.html)

Neat!

This is one of my favorite spaces, so I'll add some generic advice which may or may not be helpful.

I once had the privilege of working for Max Roser and Hannah Ritchie at Our World in Data, as one of the engineers on their Grapher library (https://github.com/owid/owid-grapher), and learned a ton from them (and others on the team) about making great charts.

My one piece of advice from looking at your examples would be: don't neglect title, subtitle, and caption! They would be so easy to do well because you've already created your "simple headers thingies". A few words go along way. Check out "Storytelling with Data" by Cole Nussbaumer Knaflic for a great read on the subject. Owid's Grapher does those the best, IMO (followed closely by DataWrapper.de -- but that's not open source).

At some point, if you keep up with this, you'll also want to add a dataflow library and DSL. Hadley Wickham's dplyr in R was the GOAT, and I copied that in my Ohayo tool and in OWID Grapher's CoreTable library (https://github.com/owid/owid-grapher/tree/master/packages/%4...). Jeffrey Heer's newish Arquero (https://idl.uw.edu/arquero/) library is also along those lines.

Lately I've delving into Mike Bostock's new thing Plot (https://observablehq.com/plot/). So far, excited by it, but only spent a day or two with it at this point.

I don't use emacs anymore, but hopefully something helpful in the comments above.

If you like the idea of using D3 for data visualization but you want something a bit higher level, check out Observable Plot[1], a library by the D3 team that adds a lot of abstractions and conveniences on top of D3, specifically for building plots, charts and graphs.

And even beyond that, there's Observable Framework[2], a static site generator for building visualization sites (that supports Plot, D3 and lots of other libraries).

1: https://observablehq.com/plot/

2: https://observablehq.com/framework/

I love Vega(-lite) / Altair, the grammar of graphics plotting system is really great to build any kind of chart even when it wasn't thought through by the authors of the library. There are other wrappers for languages that lack viz libraries, such as Elixir / Livebook [0]

However, when I used it a couples years back it struggled with large vizs, I think due to Vega(-lite)'s way of embedding the data in the viz artifact.

Also, interactive is nice but often I just need a quick static plot, and matplotlib is more convenient for this, you can easily see the png in any environment etc.

These days I'm eager to see an Observable Plot [1] wrapper for Python !

[0] https://github.com/livebook-dev/vega_lite

[1] https://github.com/observablehq/plot