Rath
plot
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Rath | plot | |
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43 | 38 | |
3,921 | 3,816 | |
3.4% | 5.6% | |
7.1 | 9.1 | |
2 days ago | 1 day ago | |
TypeScript | HTML | |
GNU Affero General Public License v3.0 | ISC License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Rath
- FLaNK Stack for 15 May 2023
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Observable Plot: The JavaScript library for exploratory data visualization
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?
- Show HN: RATH – Open-Source Copilot and Autopilot for Data Analysis
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How to send emails in Node.js (Detailed Steps)
I am also working on an Awesome Open Source project named: RATH. Check it out on GitHub!
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Ask HN: What do you use for basic data analysis, visuals, and graphing?
I'm considering https://github.com/Kanaries/Rath, which seems to be an OSS version of Tableau. Has anyone used it for this type of thing?
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Show HN: Turn Your Pandas Dataframe to a Tableau-Style UI for Visual Analysis
Ah, there’s a really nice profiler implemented in one of their other projects here (AGPLv3): https://github.com/Kanaries/Rath/tree/master/packages/rath-c...
There’s a lot of really nice features in this other tool, the author’s thought of everything: https://github.com/Kanaries/Rath
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6 Ideas for building ChatGPT Chrome Extensions
Don't forget to check out my GitHub project:https://github.com/Kanaries/Rath We are also having a website for RATH now!
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Data Painter – A Different Way to Interact with Your Data
It allows you to do on-flight data labeling, cleaning, or even create new features does not exist in the original dataset. Everything can be done with a brush tool(painter), You can even play with your data with your fingers on mobile. RATH is an open-source alternative to Tableau, but with more automation. Feedback and suggestions are appreciated! Read Data Painter Docs for more details, or check out RATH GitHub.
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MCM/ICM 2023 is Here (Download historical MCM/ICM Problems)
RATH is an Open Source Automated Data Analysis and Visualization tool that can help you uncover insights and patterns in your data quickly and efficiently. Check out RATH Source Code on GitHub and Free RATH Playground.
plot
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Vega-Altair: Declarative Visualization in Python
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 !
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Observable 2.0, a static site generator for data apps
Good questions.
1. It’s just JavaScript so you can fetch stuff dynamically too (see https://observablehq.com/framework/lib/duckdb). But yeah, only client-side. (Though see https://github.com/observablehq/framework/issues/234.)
2. Sure, it’s all open source, I bet you could make that work. Or `yarn deploy` to Observable and configure sharing there (though it wouldn’t let you charge others).
3. Yup. Which is part of the appeal of model of running data loaders at build time: you can query some private data and viewers would only be able to see the final result set. (The lack of something like this has always been a huge problem for Observable notebooks. You’d make some great query-driven charts and then couldn’t make it public without some awkward manual dance of downloading and re-uploading a file to a fork of the notebook.)
4. I wish I knew! It’s being tracked here https://github.com/observablehq/plot/issues/1711. Lately there’s been a lot more work on Framework naturally but now that that’s out…
5. Another good question. We’re definitely interested in tailoring it more to this sort of use case but lots is TBD!
We’re working on zooming and panning for Observable Plot (https://github.com/observablehq/plot/pull/1738) and other interactions such as brushing (https://github.com/observablehq/plot/pull/721) — all of this is already possible, we just haven’t packaged it up in a convenient way yet (https://github.com/observablehq/plot/pull/1871).
We’ve been focused primarily on the static display of visualizations because that’s what viewers see first, and often that’s often the only thing they see. Relying too heavily on interaction places an onus on the user to find the insights; a good display of data should be opinionated about what it shows and guide the user to what is interesting.
We’re not trying to convince you to switch to JavaScript here — a main value prop of Observable Framework is that you can write data loaders in any language (Python, R, Go, Julia, etc.). So do all your data preparation and analysis in whatever language you like, and then do your front-end in JavaScript to leverage the graphics and interactive compute capabilities of modern browsers. It’s pipes and child_process.spawn under the hood. And you still get instant reactivity when you save changes to your data loaders (when you edit Python) because Framework watches files and pushes new data to the client with reactive hot data & module replacement.
And you can compress (aggregate or filter) the data as much as you like, so it’s up to you how much data you send to the client. For example your data loader could be a minimal CSV file that’s just the numbers you need for a bar chart. Or it could be a Parquet file and you use DuckDB (https://observablehq.com/framework/lib/duckdb) on the client to generate dynamic visualizations.
Yep, Evidence is doing good work. We were most directly inspired by VitePress; we spent months rewriting both D3’s docs (https://d3js.org) and Observable Plot’s docs (https://observablehq.com/plot) in VitePress, and absolutely loved the experience. But we wanted a tool focused on data apps, dashboards, reports — observability and business intelligence use cases rather than documentation. Compared to Evidence, I’d say we’re trying to target data app developers more than data analysts; we offer a lot of power and expressiveness, and emphasize custom visualizations and interaction (leaning on Observable Plot or D3), as well as polyglot programming with data loaders written in any language (Python, R, not just SQL).
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Using Deno with Jupyter Notebook to build a data dashboard
Observable Plot: A library built on top of D3.js used to visualize data and iterate more quickly on different plot chart
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What website frameworks are used to build these websites?
https://observablehq.com/
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Yandex open sourced it's BI tool DataLens
Observable Plot [0] is also nice. AFAIU it's the same library powering the visualizations within Observable itself.
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Observable Plot: The JavaScript library for exploratory data visualization
I expect we’ll release tooltips in a few weeks; I linked that newer PR in another comment. We’ve been exploring interaction while working on many other things (https://github.com/observablehq/plot/blob/main/CHANGELOG.md). Now that we’re feeling good about the foundation for static charts we are starting to address interaction.
If you’re primarily interested in static charts (or your interactivity is driven by external controls, such as drop-downs and sliders, where you can regenerate the chart as needed for interaction), then Plot is ready for use. On the other hand if you need direct manipulation interaction, such as brushing or painting dots in a scatterplot, then you might stick with Vega-Lite for now.
We’re working on tooltips now, and interaction next. There’s a PR here with an early sketch and demo video: https://github.com/observablehq/plot/pull/721
It’s not easy to do radial stuff right now; you can upvote this issue: https://github.com/observablehq/plot/issues/133
One bizarre workaround right now is to abuse the geographic projections: https://observablehq.com/@observablehq/pie-to-donut-chart
In general, you can do a lot of customization, including plugins (though that’s not well-documented yet), so you could make it work… see https://observablehq.com/@fil/radial-transform, https://observablehq.com/@observablehq/plot-radial-line for other approaches to hacking radial stuff into Plot.
You can do Cartesian tree diagrams in Plot, e.g. https://observablehq.com/@observablehq/plot-tree-flare, https://observablehq.com/@observablehq/plot-custom-tree-layo...
If you want to make a chord diagram like that “Müsli Ingredient Network” example, you could try one of these D3 examples: https://observablehq.com/@d3/chord-diagram, https://observablehq.com/@d3/hierarchical-edge-bundling/2
What are some alternatives?
superset - Apache Superset is a Data Visualization and Data Exploration Platform
graphic-walker - An open source alternative to Tableau. Embeddable visual analytic
pygwalker - PyGWalker: Turn your pandas dataframe into an interactive UI for visual analysis
plot-react - React wrapper for @observablehq/plot
PaLM-rlhf-pytorch - Implementation of RLHF (Reinforcement Learning with Human Feedback) on top of the PaLM architecture. Basically ChatGPT but with PaLM
lux - Automatically visualize your pandas dataframe via a single print! 📊 💡
blazor-samples - Explore and learn Syncfusion Blazor components using large collection of demos, example applications and tutorial samples
echarts - Apache ECharts is a powerful, interactive charting and data visualization library for browser
go-echarts - 🎨 The adorable charts library for Golang
d3 - Bring data to life with SVG, Canvas and HTML. :bar_chart::chart_with_upwards_trend::tada:
gonum - Gonum is a set of numeric libraries for the Go programming language. It contains libraries for matrices, statistics, optimization, and more
cli-d3 - Generate d3 plots from the command-line.