bokeh
Apache Superset
Our great sponsors
| bokeh | Apache Superset | |
|---|---|---|
| 24 | 3 | |
| 18,792 | 34,745 | |
| 0.9% | - | |
| 9.5 | 9.9 | |
| 7 days ago | about 3 years ago | |
| Python | Python | |
| BSD 3-clause "New" or "Revised" License | 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.
bokeh
-
Mastering Matplotlib: A Step-by-Step Tutorial for Beginners
Bokeh - Interactive Web Plotting for Python.
-
Top 10 growing data visualization libraries in Python in 2023
Github: https://github.com/bokeh/bokeh
- Bokeh Python Library for Interactive Visualizations
-
Best data visualisation library
If you don’t mind passing html around this library allows you to share full interactive plot:
-
Emerging Rust GUI libraries in a WASM world
It sounds like you want BokehJS. It was one of the alternatives I was recommended while I was exploring, but for various reasons my particular use case is not so easy to integrate (plus my backend was already in Rust).
https://github.com/bokeh/bokeh
I did do a basic test, and the raw rects-on-screen performance is roughly comparable to my final solution.
-
What Python modules can I use to create my own indicators? Like the indicator below, I very new to Python so please don’t be rude
I just came across this: https://bokeh.org/
-
Interactive plots
Take a look at Bokeh. https://bokeh.org/
- December goals
-
[OC] The Criminal Podcast's intros have gotten longer over time
I recorded all 200 "I'm Phoebe Judge, this is Criminal" intros from the Criminal podcast, measured the length, and plotted using python's Bokeh package.
- What's the most scalable visualization library?
Apache Superset
-
Using KeyCloak(OpenID Connect) with Apache SuperSet
The first difference is that after pull request 4565 was merged, you can no longer do:
-
Open Source Analytics Stack: Bringing Control, Flexibility, and Data-Privacy to Your Analytics
Open-source BI platforms such as Metabase (website, GitHub) and Apache SuperSet (website, GitHub) are easy to deploy without IT involvement. Metabase lets you build dashboards from the data in your warehouse easily, with no SQL, or, if you have data engineering or science know-how, inside more powerful and flexible notebooks or with SQL itself. Similarly, Apache SuperSet helps businesses explore and visualize data from simple line charts to detailed geospatial charts.
-
Ask HN: What low-code “dashboarding“ SaaS would you recommend in 2021?
Check out Superset. https://github.com/apache/incubator-superset
It’s modern, easy to extend. From the same author of apache airflow.
What are some alternatives?
plotly - The interactive graphing library for Python :sparkles: This project now includes Plotly Express!
seaborn - Statistical data visualization in Python
Grafana - The open and composable observability and data visualization platform. Visualize metrics, logs, and traces from multiple sources like Prometheus, Loki, Elasticsearch, InfluxDB, Postgres and many more.
Altair - Declarative statistical visualization library for Python
Metabase - The simplest, fastest way to get business intelligence and analytics to everyone in your company :yum:
matplotlib - matplotlib: plotting with Python
Redash - Make Your Company Data Driven. Connect to any data source, easily visualize, dashboard and share your data.
PyQtGraph - Fast data visualization and GUI tools for scientific / engineering applications
Elasticsearch - Free and Open, Distributed, RESTful Search Engine
folium - Python Data. Leaflet.js Maps.
cube.js - 📊 Cube — The Semantic Layer for Building Data Applications