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Kanaries
Rath
TypeScript2022–2024
Kanaries / Rath

Rath

Next generation of automated data exploratory analysis and visualization platform.

AI & Machine LearningData & DatabasesLearning & ReferenceAutomation & Workflows
Explore on GitHubRead Hacker News discussions
5Distinct people
13Mentions
0Explicit recommenders
4.7KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Next generation of automated data exploratory analysis and visualization platform.

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

Mentioned in the same Hacker News threads. That is not proof they are substitutes.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 3:56:07 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by month13 dated mentions

Observed mentions: 2022-12-21 16:01:20 UTC to 2024-09-03 02:15:06 UTC.

0123452022-12-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 2 mentions; 1 submissions, 1 commentsDec 20222023-01-01 00:00:00 UTC to 2023-02-01 00:00:00 UTC (exclusive): 3 mentions; 1 submissions, 2 comments2023-02-01 00:00:00 UTC to 2023-03-01 00:00:00 UTC (exclusive): 5 mentions; 1 submissions, 4 comments2023-03-01 00:00:00 UTC to 2023-04-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-04-01 00:00:00 UTC to 2023-05-01 00:00:00 UTC (exclusive): 2 mentions; 1 submissions, 1 comments2023-05-01 00:00:00 UTC to 2023-06-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-06-01 00:00:00 UTC to 2023-07-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-07-01 00:00:00 UTC to 2023-08-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-08-01 00:00:00 UTC to 2023-09-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-09-01 00:00:00 UTC to 2023-10-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-10-01 00:00:00 UTC to 2023-11-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 commentsOct 20232023-11-01 00:00:00 UTC to 2023-12-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-12-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-01-01 00:00:00 UTC to 2024-02-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-02-01 00:00:00 UTC to 2024-03-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-03-01 00:00:00 UTC to 2024-04-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-04-01 00:00:00 UTC to 2024-05-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-05-01 00:00:00 UTC to 2024-06-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-06-01 00:00:00 UTC to 2024-07-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-07-01 00:00:00 UTC to 2024-08-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-08-01 00:00:00 UTC to 2024-09-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-09-01 00:00:00 UTC to 2024-10-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsSep 2024

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
Dec 20222022-12-01 00:00:00 UTC2023-01-01 00:00:00 UTC211
Jan 20232023-01-01 00:00:00 UTC2023-02-01 00:00:00 UTC312
Feb 20232023-02-01 00:00:00 UTC2023-03-01 00:00:00 UTC514
Mar 20232023-03-01 00:00:00 UTC2023-04-01 00:00:00 UTC000
Apr 20232023-04-01 00:00:00 UTC2023-05-01 00:00:00 UTC211
May 20232023-05-01 00:00:00 UTC2023-06-01 00:00:00 UTC000
Jun 20232023-06-01 00:00:00 UTC2023-07-01 00:00:00 UTC000
Jul 20232023-07-01 00:00:00 UTC2023-08-01 00:00:00 UTC000
Aug 20232023-08-01 00:00:00 UTC2023-09-01 00:00:00 UTC000
Sep 20232023-09-01 00:00:00 UTC2023-10-01 00:00:00 UTC000
Oct 20232023-10-01 00:00:00 UTC2023-11-01 00:00:00 UTC000
Nov 20232023-11-01 00:00:00 UTC2023-12-01 00:00:00 UTC000
Dec 20232023-12-01 00:00:00 UTC2024-01-01 00:00:00 UTC000
Jan 20242024-01-01 00:00:00 UTC2024-02-01 00:00:00 UTC000
Feb 20242024-02-01 00:00:00 UTC2024-03-01 00:00:00 UTC000
Mar 20242024-03-01 00:00:00 UTC2024-04-01 00:00:00 UTC000
Apr 20242024-04-01 00:00:00 UTC2024-05-01 00:00:00 UTC000
May 20242024-05-01 00:00:00 UTC2024-06-01 00:00:00 UTC000
Jun 20242024-06-01 00:00:00 UTC2024-07-01 00:00:00 UTC000
Jul 20242024-07-01 00:00:00 UTC2024-08-01 00:00:00 UTC000
Aug 20242024-08-01 00:00:00 UTC2024-09-01 00:00:00 UTC000
Sep 20242024-09-01 00:00:00 UTC2024-10-01 00:00:00 UTC101

What Hacker News says

13 sources
loa_observer·Sep 3, 2024
Wow, Vega is here! All our projects for data analytic and visualization are based on vega/vega-lite, really impressive by vega's signals design when i learned it first time(it's like rxjs, which i also love). Share some work based on vega/vega-lite: - PyGWalker: turn dataframe to tableau alternative UI in jupyter: https://github.com/Kanaries/pygwalker - RATH: Automation of data exploration workflow with one click. https://github.com/Kanaries/Rath - GWalkR: drag-and-drop based visualization in RStudio, https://kanaries.net/gwalkr
In Vega – A declarative language for interactive visualization designs
loa_observer·Apr 28, 2023
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?
In Observable Plot: A JavaScript library for exploratory data visualization
loa_observer·Apr 24, 2023Submission

Show HN: Copilot for Data Analysis, beyond an open-source alternative to Tableau

RATH is an open-source software for data exploration and visualization. It automates your workflow in data analysis. You can give RATH a CSV file and it will generates visualizations with insights and patterns automatically. It also has a data painter tool for more casual interaction with charts (https://youtu.be/djqePNyhz7w). It also has a lot of cool features like autovis, causal discovery, GPT integration, predictive interaction for text feature extraction, etc. Some of RATH’s components are also independent open-source project you might be interested: Like + Graphic Walker (https://github.com/Kanaries/graphic-walker): A lite embeddable component for visual analysis. + PyGWalker (https://github.com/Kanaries/pygwalker): turning your pandas dataframe into a Tableau-style User Interface for visual exploration. RATH is a collection of
Read the rest
interesting ideas that we think the next generation of data analysis software should be, so there might be many features that not well organized to be a united app. Tell me which feature you prefer and which is not. Looking forward for your ideas and advice.
61 points · Open discussion
loa_observer·Feb 14, 2023Submission

Show HN: Data Painter – A Different Way to Interact with Your Data

Data Painter is RATH's new feature to interact with your data. It helps you to specify complex visual patterns and find explanations and potential causals. It allows you to do on-flight data labeling, cleaning or even create new features does not exited in 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 automations. Feedbacks and suggestions are appreciated. RATH's Github: https://github.com/Kanaries/Rath RATH's HomePage: https://kanaries.net/
179 points · Open discussion
loa_observer·Jan 20, 2023
I have been working on an open-source project called RATH, an automated visualization tool for data exploration. However, I have encountered some performance issues when working with large datasets (> 1 million rows). 1. High memory usage: When loading large datasets, the memory usage can become quite high. (50MB csv will use 700MB memory in RATH) 2. Slow computation tasks: Group-by, filter, bin, or even Cube operations can be slow and sometimes block the main thread. 3. Slow chart rendering: Chart rendering can also be slow and sometimes block the main thread. (Currently using VegaLite) I have implemented some solutions to address these issues: 1. For high memory usage, I am storing large raw data in indexedDB and reading it as needed. This reduces memory usage but can still consume a lot of memory when the data is loaded into the main t
Read the rest
hread. 2. To improve the performance of computation tasks, I am using web workers for some data computations (such as group-by, bin, transform, and filters). I am also testing duckDB-wasm, but lack of some knowledge of its best practice. 3. For slow chart rendering, I have tried using offscreen canvas to render the chart in a web worker. However, this approach creates a static canvas without any interactive features (such as tooltips, zooming, or callbacks for data selections). I am looking for methods on how to make the chart rendered in the web worker interactive. Any suggestions or experiences shared would be greatly appreciated. RATH Github Repo: https://github.com/Kanaries/Rath RATH basic background: RATH is beyond an open-source alternative to Data Analysis and Visualization tools such as Tableau. It automates your Exploratory Data Analysis workflow with an Augmented Analytic engine by discovering patterns, insights, causals and presents those insights with powerful auto-generated multi-dimensional data visualization.
In Ask HN: How to handle large datasets in front end of data apps?
loa_observer·Jan 10, 2023
It's a cool project, thanks for sharing. graphic-walker focuses more on a Grammar of Graphics based graphic system, not a chart-based system. But for performance in the browser, I am also researching ways to handle large datasets in the browser, such as duckdb-wasm. Another project I am working on, called RATH is facing more challenging performance issues because it is designed to automate the exploration of data to find insights and causal relations by machine. It currently is using web worker and indexedDB to implement a lite cube service in the browser, but it is not enough. https://github.com/kanaries/rath Thanks for your advice, I will continue to improve the both computation and render performance in browser.
In Show HN: Graphic-Walker – A different type of open-source alternative to Tableau

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