#Swift #Observable

Is there any good practice for working with Observable and protocols?

I’d like to conform a protocol to Observable (so I could mock it in tests and previews, and pass around only protocol types in most of my code, not concrete types), but Observable macro seems to be geared towards working with concrete types

So what are your best practices and thoughts on Observable vs mocking/testing

I had a great time at @EdinbR last night, talking about interactive charts in R (and catching up with people I haven't seen in a while)

How to add tooltips and dropdowns
In R with {ggiraph}
By passing data from R to Observable

Slides: https://nrennie.rbind.io/talks/edinbR-interactive-charts/slides.html

If you're based in Edinburgh(-ish), come along on Thursday 15th May to the @EdinbR meetup!

I'll be chatting about interactive charts in #RStats (and beyond!) Jordan Richards will also be chatting about fast Bayesian inference (so I guess that also makes it a mini STOR-i CDT reunion as well!)

Register: https://www.meetup.com/edinbr/events/307742291

It's Day 8 of the #30DayChartChallenge, and the prompt is "Histogram"

Another #RStats + Observable combination
Kept it simple, but figured out more about small multiples (facets), sorting categories, and colour palettes in Observable today!

It's Day 7 of the #30DayChartChallenge, and the prompt is "Outliers"

Data wrangling in #RStats
Scatter plot made with Observable
Static tooltips for annotations (+ dynamic tooltips for exploring)

For Day 3 of the #30DayChartChallenge, the prompt is "Circular"

Sunburst plot showing countries where 1% have >10% of wealth
Data formatting #RStats to create JSON data
Figured out how to edit an imported D3 chart in Observable

Quarto + #RStats + Observable =

New blog post from me about:

What is Observable?
Why should R users care?
How do you use both together to make interactive charts?

Link: https://nrennie.rbind.io/blog/observable-r-users/

It's Day 1 of the #30DayChartChallenge, and the prompt is "Fractions"

Data from Our World in Data on wealth distribution
Data wrangling in #RStats
Waffle plot made with Observable

Being able to get `mgcv::gam` into JS/Observable via #RStats {webr} is just the bees knees.

#Observable Plot just has basic linear regression (it's nowhere near as robust as `geom_smooth()`), and it's almost zero effort to slide in fit data from other models thanks to the work of George & team.

It's still very much a WIP but I've got a usable `Textbox` #Observable Plot Mark in development.

It's sort of like a Plot.html, letting you specify HTML code for the mark text, and it renders it.

I now see why this hasn't existed before. Lots of edge cases/gnarly bits.

https://observablehq.com/@hrbrmstr/textbox-mark-html-text-mark

I'm rly backlogged on the #30DayChartChallenge b/c I got nerdswiped trying to make a new #Observable Plot mark for HTML styled text…and it's nearly working!

#Observable #Framework just added support for installing and using NPM modules! https://github.com/observablehq/framework/releases/tag/v1.6.0

Nothing fancy for the late entry to day 14 of the #30DayChartChallenge. Just a basic Season/Episode ratings #Observable Plot heatmap for selected TV shows from IMDB's catalog.

https://observablehq.com/@hrbrmstr/2024-30-day-chart-challenge-day-14-relationships-heatmap

For day 13 of the #30DayChartChallenge (relationships/family) we use #Observable and #D3 to explore the malware families used by threat actors, and let you tap into them to go to the entries on Malpedia.

Totally forgot to post the link yesterday :facepalm: https://observablehq.com/@hrbrmstr/2024-30-day-map-challenge-day-12-relationships-family

For day 10 of the #30DayChartChallenge (distribution/physical) we look at the historical, present, and projected distributions of cargo by travel mode via an interactive #observable notebook that lets you explore each cargo type.

A bit behind on the #30DayChartChallenge (sigh)

Day 9 • Distribution • Major/Minor

We take a look at major/minor quake densities across the globe over the last 30 days.

Nothing groundbreaking, as #Observable Plot makes this pretty easy.

https://observablehq.com/@hrbrmstr/2024-30-day-chart-challenge-day-09-distribution-major-minor

For day 8 of the 2024 #30DayChartChallenge (distribution / circular) we look at the historical make-up of the U.S. Congress (starting with the 32nd) with animated parliament plots in #Observable (#RStats data wrangling code included in the notebook).

https://observablehq.com/@hrbrmstr/2024-30-day-chart-challenge-day-08-distribution-circular

For day 6 (OECD) of #30DayChartChallenge I tapped into their database of "trust in the national government" via #RStats #WebR in #Observable.

Unsurprisingly, trust is in the .

Now I gotta dig in a bit more to know why Luxembourg is #1.

https://observablehq.com/@hrbrmstr/2024-30-day-chart-challenge-day-06-oecd

For day 5 of the #30DayChartChallenge (diverging) this #Observable notebook looks at 2023 U.S. state migration inbound/outbound flows through two different lenses.

The notebook has #RStats data wrangling code, too.

https://observablehq.com/@hrbrmstr/2024-30-day-chart-challenge-day-4-diverging

#30DayChartChallenge Day 4 •

Hit up — https://observablehq.com/@hrbrmstr/2024-30-day-chart-challenge-day-04-waffle — to see your GitHub activity % breakdown in a proper waffle chart (via my OBS Plot WafleMark) vs the daft radar chart GitHub uses.

Ended up having to write a Deno edge function to make this data available to #Observable notebooks.