bloxs
Apache Superset
bloxs | Apache Superset | |
---|---|---|
8 | 3 | |
213 | 34,745 | |
-0.5% | - | |
0.0 | 9.9 | |
almost 2 years ago | over 3 years ago | |
Python | Python | |
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.
bloxs
- Show HN: Build dashboards in Jupyter Notebook with numeric and chart boxes
- Show HN: Build dashboard boxes with charts and numbers in Jupyter Notebook
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Automated PDF Reports with Python Notebooks
Right now it is flowing the notebook html. It should be possible to add some layout library (Python library that will do HTML+CSS to get nice layout).
Recently I did similar for displaying numbers in the notebook as a good looking boxes. I created a small Python package that takes the number and creates a box with borders with HTML+CSS. It is pretty handy for building dashboards in Python. The package name is Bloxs https://github.com/mljar/bloxs
- Show HN: Build dashboards in Jupyter Notebook from bloxs
- Bloxs: Display your data as cards in your Python notebook!
- Show HN: Bloxs – display data as cards in your notebook
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Bloxs: display your data in an attractive way in your notebook
Hi, I would like to share with you a small python package that I've created to display data in a notebook in an attractive way. The package is called bloxs and is available on GitHub https://github.com/mljar/bloxs.
Apache Superset
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Using KeyCloak(OpenID Connect) with Apache SuperSet
The first difference is that after pull request 4565 was merged, you can no longer do:
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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.
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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!
Flight-Test-Data-Analytics-Module-01 - Code to support Module 01 of the Daedalus Aerospace Flight Test Data Analytics course.
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.
mercury - Convert Jupyter Notebooks to Web Apps
Metabase - The simplest, fastest way to get business intelligence and analytics to everyone in your company :yum:
Redash - Make Your Company Data Driven. Connect to any data source, easily visualize, dashboard and share your data.
Elasticsearch - Free and Open, Distributed, RESTful Search Engine
cube.js - 📊 Cube — The Semantic Layer for Building Data Applications
grafanalib - Python library for building Grafana dashboards
bokeh - Interactive Data Visualization in the browser, from Python
matplotlib - matplotlib: plotting with Python