plot
superset
plot | superset | |
---|---|---|
40 | 138 | |
3,913 | 59,473 | |
2.5% | 2.5% | |
8.8 | 9.9 | |
27 days ago | 4 days ago | |
HTML | TypeScript | |
ISC License | Apache License 2.0 |
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plot
- Ask HN: What's the best charting library for customer-facing dashboards?
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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 !
[0] https://github.com/livebook-dev/vega_lite
[1] https://github.com/observablehq/plot
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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!
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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.
[0] https://observablehq.com/plot/
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Best React charting libraries for data visualizations
I liked observablehq plot library: https://github.com/observablehq/plot
- Bank Failures Visualized
- Observable Plot: A JavaScript library for exploratory data visualization
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?
plot-react - React wrapper for @observablehq/plot
streamlit - Streamlit — A faster way to build and share data apps.
blazor-samples - Explore and learn Syncfusion Blazor components using large collection of demos, example applications and tutorial samples
jupyter-dash - OBSOLETE - Dash v2.11+ has Jupyter support built in!
echarts - Apache ECharts is a powerful, interactive charting and data visualization library for browser
Apache Hive - Apache Hive
go-echarts - 🎨 The adorable charts library for Golang
lightdash - Self-serve BI to 10x your data team ⚡️
d3 - Bring data to life with SVG, Canvas and HTML. :bar_chart::chart_with_upwards_trend::tada:
Metabase - The simplest, fastest way to get business intelligence and analytics to everyone in your company :yum:
gonum - Gonum is a set of numeric libraries for the Go programming language. It contains libraries for matrices, statistics, optimization, and more
django-project-template - The Django project template I use, for installation with django-admin.