51–60 of 64 posts
I've seen and used so many amazing in-house dashboarding and reporting tools, and this suite blows them all out of the water. Can't believe this is all open source too.
I think this is a great way to slice up the product/feature set from a monetization perspective: hosting w/ collaboration is paid, but the tools are all free to use.
HAVE FUN TESTING THAT. And when you don't, enjoy random countries being mixed up but it mostly working.
Would this be open source? I would really like to run this locally For the time being I hacked something using Observable Framework [1], but still, it isn't the full set 1: https://observablehq.com/framework/ Edit: nvm just saw the notebook kit
No? How would they make money?
Observable's pricing is bit out of bounds for what they offer. It feels like a lot of these data startups are just looking for large companies that will unsuspectingly spend a ton of money on something they don't need.
The video demonstrating the AI powered desktop app perfectly demonstrates my discomfort with AI. When asked to fix the mapping between county codes, it generated a lookup table itself. HAVE FUN TESTING THAT. And when you don't, enjoy random countries being mixed up but it mostly working.
In addition to the hardcoded lookup table, here are some other notes on the generated code:
1. Silently assuming that the first page of results contains all of the data feels a bit fragile. If we're not going to bother with paging otherwise, I'd at least assert that the first page contains everything.
2. Unlike the code comment claims, 2022 is not the latest year that has data available, 2023 is. The reason this is worrisome is not that the difference is massive, but because of methodological implications. It looks like the year 2022 came from "remembering" details from some other code that was analyzing this same data set instead of just looking at current version of the data set we're supposed to be analyzing.
3. The code for removing the world aggregate doesn't actually work (although it doesn't matter for the map). The place where it says d.country.id !== "WLD" should be either d.country.id !== "1W" or d.countryiso3code !== "WLD" instead. Also, if it would actually be important to filter this then presumably it would also be important to filter out a bunch of other aggregates as well.
4. The text says "darker colors indicating higher life expectancy", which is pretty much the opposite of how I would describe this color scheme.
5. The analysis given is: "Notice how certain regions tend to cluster together in terms of life expectancy, reflecting similar economic, healthcare, and social conditions". This is such a bland take. It feels like something I could have written before seeing the data. I would try to encourage the analyst to look for something more concrete and more interesting.
6. The actual thing that immediately pops out from the map is that the Central African Republic is a massive outlier with a life expectancy of 18.8 years, whereas every other country is over 50. This doesn't seem plausible. I would do something about that just so that it doesn't mess up the colors of the entire map.
However, I definitely don't want to have to type "" in order to calculate 1 + 2, and I don't want to have to scan past that in order to find the actual calculations. So I guess I'll have to keep being inspired by Bostock Observable Notebooks 1.0, which I can keep writing in GitHub-flavored Markdown, because it's free software and already checked into Git.
I'd love to love them but I don't: I can't seem to justify moving away from Python to use this. What advantages does JS offer for this use case? I' ve never felt that I couldn't do any visualization with Python (but I don't do nice newspaper figures).
i dont understand why Observable insists on topological execution. isn't out of order execution one of the biggest complaints about notebooks?
I'd love to love them but I don't: I can't seem to justify moving away from Python to use this. What advantages does JS offer for this use case? I' ve never felt that I couldn't do any visualization with Python (but I don't do nice newspaper figures).
Yes but, probably what they are shooting for are mini apps that you can just copy pasted into a front-end codebase and not some weird-ass python dsl
I'd love to love them but I don't: I can't seem to justify moving away from Python to use this. What advantages does JS offer for this use case? I' ve never felt that I couldn't do any visualization with Python (but I don't do nice newspaper figures).
It depends where you're coming from, I suppose. The web is pretty popular. Web developers are more familiar with HTML, CSS, and JavaScript, and with various visualization libraries in the JavaScript ecosystem. I quite like Observable Plot [1]. I'm not familiar enough with Python or Jupyter to know how you would build similar visualizations with them. What would you use? [1] https://observablehq.com/@observablehq/plot…