graphic-walker
superset
graphic-walker | superset | |
---|---|---|
20 | 137 | |
2,243 | 58,852 | |
2.1% | 1.5% | |
9.4 | 9.9 | |
5 days ago | 7 days ago | |
TypeScript | TypeScript | |
Apache License 2.0 | Apache License 2.0 |
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.
graphic-walker
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Show HN: Open-source, browser-local data exploration using DuckDB-WASM and PRQL
[2] https://github.com/Kanaries/graphic-walker/issues/330
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Show HN: GPT and tableau-style interface in R for data visualization
GWalkR is an open-source R library that allows you to turn your data frame into a tableau style user interface for data exploration and visualization. It also allows you to analysis your data with natural language questions.
GWalkR is the R binding of graphic-walker: https://github.com/Kanaries/graphic-walker
- FLaNK Stack for 4th of July
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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?
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Show HN: RATH – Open-Source Copilot and Autopilot for Data Analysis
+ 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 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.
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Hey /r/SQL! I created a tool for data analysts to save time and visualize data using DuckDB - looking for feedback
I know you said you *dont* want a tableau like interface, but in case you do this might be a cool open source project to check out: https://github.com/Kanaries/graphic-walker
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Show HN: Turn Your Pandas Dataframe to a Tableau-Style UI for Visual Analysis
> it seems like the heavy lifting is done by the web app here: https://github.com/Kanaries/graphic-walker
FWIW, both are made by the same entity, Kanaries.
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Tools for Integrating Interactive Dashboards on a Website without Licensing Problems?
You may try to use and modify based on the OpenSource Graphic Walker: https://github.com/Kanaries/graphic-walker
- Easier Data Visualization & Exploration in React: Graphic Walker
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Graphic Walker, A Different Type of Open Source Tableau Alternative
Graphic Walker is designed to be easy to embed in other applications as a React component. Check out the code here: https://github.com/Kanaries/graphic-walker
superset
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Apache Superset
Superset is absolutely phenomenal. I really hope Microsoft eventually releases all of their customizations they made to it internally to the OS community someday.
https://www.youtube.com/watch?v=RY0SSvSUkMA
https://github.com/apache/superset/discussions/20094
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A modern data stack for startups
I recently ran a little shootout between Superset, Metabase, and Lightdash. All have nontrivial weaknesses but I ended up picking Lightdash.
Superset the best of them at _data visualization_ but I honestly found it almost useless for self-serve _BI_ by business users. This issue on how to do joins in Superset (with stalebot making a mess XD) is everything difficult about Superset for BI in a nutshell. https://github.com/apache/superset/issues/8645
Metabase is pretty great and it's definitely the right choice for a startup looking to get low cost BI set up. It still has a very table centric view, but feels built for _BI_ rather than visualization alone.
Lightdash has significant warts (YAML, pivoting being done in the frontend, no symmetric aggregates) but the Looker inspiration is obvious and it makes it easy to present _groups of tables_ to business users ready to rock. I liked Looker before Google acquired it. My business users are comfortable with star and snowflake schemas (not that they know those words) and it was easy to drop Lightdash on top of our existing data warehouse.
- FLaNK Stack Weekly for 20 Nov 2023
- Hiding tokens retrieved via API from the html source?
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Yandex open sourced it's BI tool DataLens
Or like not being able to delete a user without running some SQL:
https://github.com/apache/superset/issues/13345
Almostl instantly run into this issue setting up a test instance of Superset. And the issue has been around for years.
- Apache Superset Is a Data Visualization and Data Exploration Platform
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Apache Superset: Installing locally is easy using the makefile
Are you interested in trying out Superset, but you're intimidated by the local setup process? Worry not! Superset needs some initial setup to install locally, but I've got a streamlined way to get started - using the makefile! This file contains a set of scripts to simplify the setup process.
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More public SQL-queryable databases?
Recently I discovered BigQuery public datasets - just over 200 datasets available for directly querying via SQL. I think this is a great thing! I can connect these direct to an analytics platform (we use Apache Superset which uses Python SQLAlchemy under the hood) for example and just start dashboarding.
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How useful is SQL for managers?
if they don't want to pay for powerbi, can try something like https://superset.apache.org/
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Real-time data analytics with Apache Superset, Redpanda, and RisingWave
In today's fast-paced data-driven world, organizations must analyze data in real-time to make timely and informed decisions. Real-time data analytics enables businesses to gain valuable insights, respond to real-time events, and stay ahead of the competition. Also, the analytics engine must be capable of running analytical queries and returning results in real-time. In this article, we will explore how you can build a real-time data analytics solution using the open-source tools Redpanda a distributed streaming platform, Apache Superset, a data visualization, and a business intelligence platform, combined with RisingWave a streaming database.
What are some alternatives?
Rath - Next generation of automated data exploratory analysis and visualization platform.
streamlit - Streamlit — A faster way to build and share data apps.
jupyter-dash - OBSOLETE - Dash v2.11+ has Jupyter support built in!
vega-embed - Publish Vega visualizations as embedded web components with interactive parameters.
Apache Hive - Apache Hive
pygwalker - PyGWalker: Turn your pandas dataframe into an interactive UI for visual analysis
lightdash - Self-serve BI to 10x your data team ⚡️
pivottable - Open-source Javascript Pivot Table (aka Pivot Grid, Pivot Chart, Cross-Tab) implementation with drag'n'drop.
Metabase - The simplest, fastest way to get business intelligence and analytics to everyone in your company :yum:
vega-lite - A concise grammar of interactive graphics, built on Vega.
django-project-template - The Django project template I use, for installation with django-admin.