loa_observer

Big fan of D3.js and now there is Observable Plot! I am building several data visualization software for exploratory data analysis:

RATH, auto exploratory data analysis: https://github.com/Kanaries/Rath

GraphicWalker, embeddable data exploration component: https://github.com/Kanaries/graphic-walker

They are using vega-lite for now. But there is a limit of building more fancy and customized visualizations. It seems Plot has a more flexible layer based visualization system that can support larger design space.

Is Plot stable enough now to migrate from vega-lite based system to Plot based? Are there any large milestone or roadmap of Plot in future?

How does the AI know which tool if best for me? What data does it use for decision ? I'm a little bit doubt whether its recommendation is trustable if it is using the official product description and some friendly comments on ProdctHunt which hardly tell the truth of the product.

I will build an AI-Powered Platform helps people discover platforms like yours that helps people discover AI tools.

Hope someone will develop a platform that helps people discover my platform.

RATH's autovis feature is based on a data view. If your queries generates a data view (tables with columns), it can handle it.

Wow! This is the tool I am looking for! What features do you plan to provide in premium version in future if you have one.

I'm really enjoying the Superus-101 playground for newbies! I've been playing around with it for a while now, and I find it really helpful for brainstorming. However, I did notice that the waiting time for a response can be a bit long. Do you think it would be possible to implement streaming and concurrent modes for generating new nodes in the graph?

It will not be uploaded to Kanaries' server if you are using the open-source version of RATH. The data is stored in the indexedDB in your browser. For the SaaS version of RATH, the data will be stored in AWS S3 in the US.

There will be a new SDK for integrate it soon.

Looking forward to your feedbacks! Here is a demo link you can try without login: https://rath.kanaries.net

Try this: https://rath.kanaries.net. (demo link from readme)

For a tableau open source alternative that runs in browser, you can try graphic-walker: https://github.com/Kanaries/graphic-walker

wow, that sounds great. I love the idea that it can generate locale files direct from a webpage. It's a pity that it is not available now.

I realized that I am old now....

Glad to see that there are grammar of graphics based visualization lib in dart!

No, it is a python package runs in your machine.

If you want to embed the visualization part only, you can export a vega-lite/vega specification and then use Vega-Embed: https://github.com/vega/vega-embed or React-Vega to embed in your web app.

At the graphic walker toolbar, active debug mode, there will appear a button on the top-right corner of the chart. Click it, and then you can export the chart spec.

Or Embed the entire Graphic Walker as a react component: https://github.com/Kanaries/graphic-walker

This PR had just tested running DuckDB-WASM. For more complex computation, I am planning to build a computation engine to generate SQL and push it to DuckDB or other databases. (I built a POC like this in another project, RATH, but the SQL is push to clickhouse instead.)

If you are interested in this, welcome to discuss with us in the PRs/issues on Github or in our Discord: https://discord.gg/Z4ngFWXz2U

Yes, it's a general visualization tool. But it depends on what you need for your data. Dimensions in non-numeric tabular data can be used with a 'count' to make charts of the distribution of values in the dimensions.

There is a WIP PR for combining DuckDB with Graphic Walker: https://github.com/Kanaries/graphic-walker/pull/18

WASM of Graphic Walker is coming soon！

Thanks!!!!!!!!!

I upload my csv file, and it seems still uses a fixed meta which is not from my data...quit confusing.

people don't want to pre-config the meta before uploading a csv file

Just fixed this, thanks for feedback.

If you are on Kanaries homepage (kanaries.net), the language setting is on the top right corner near login button. The language switch button icon looks like this one: https://www.flaticon.com/free-icon/language_4509733

If you are on RATH product page (rath.kanaries.net), the language setting is on the left bottom of the page.

I thought about "draw to create data" before, but it brings problems when your data contains high dimensions (lots of columns). Painted data only defines limited number of dimensions, for other columns, Some prediction model can be used to infer the values. but with higher dimension in data, the prediction gets less convincing.

thanks for sharing your thoughts and experience! I am fixing the descriptions.

Sorry for lack of information. Kanaries is the github organization's name, with a shorthand k6s.

RATH is one of an open source project under Kanaries. As for the meaning of RATH, it actually came from an animation called Sword Art Online. I was a little bit regret to named this repo with RATH and had deleted descriptions about the repo's name, but with no more good ideas for now.....

RATH is now under AGPL license, we are considering move to a less limited license like apache if there are more open-source users and developer in its community.

The related docs will be published soon, we are working on connecting RATH to more infra now, you can join the discord to the latest discussions. https://discord.com/invite/Z4ngFWXz2U

I tested 1 million rows * 12 columns. It works fine with pure client's web-workers and indexedDB. For larger datasets(like CSV file > 150MB), especially for the "mega automation" feature, It turns to be slow and sometimes lead crash in browsers.

For now, I have some temporally solutions, setting a sample size is the easiest.

Another way is put some heavy computation tasks to scaleable OLAP services, like a clickhouse clusters.

I will continue to research more ways to make the client handle as much data as possible and fast enough so more people can deploy it by their own with few costs.

Open Recall is an Open Source N-Back Task Game like Simply-Recall designed to improve working memory and cognitive abilities.

Research shows that N-Back training may lead to gains in fluid intelligence (IQ) and working memory ability (Soveri et al., 2017).

The N-Back task is a memory training game that is designed to improve working memory and cognitive abilities. To play the game, you will be presented with a sequence of items such as letters, numbers, or words. Your goal is to indicate whenever the current item matches the item that was presented "n" steps back in the sequence. The value of "n" determines the difficulty of the task. For example, if "n" is set to 1, you would need to recall the item that was presented one step back. If "n" is set to 2, you would need to recall the item that was presented two steps back, and so on. The game typically continues until you have completed a certain number of rounds or made a certain number of errors. To play, simply focus on the items as they are presented and try to recall the item that was presented "n" steps back. Good luck!

Software in 80s/90s requires much more design than it in today. Sometimes people even develop theories and systematize knowledge before developing.

Softwares today prefer to use "agile development" which usually be understood and used as "think less and start coding".

In 80s/90s, customers of software were targeted more on big business customers who can pay a lot more.

Today, more and more small customers even free users are targeted, so software companies focus on a more unstable user group than it in the past.