datapane
powerbi-jupyter
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datapane | powerbi-jupyter | |
---|---|---|
30 | 2 | |
1,349 | 436 | |
0.4% | 2.3% | |
7.3 | 6.8 | |
7 months ago | 7 months ago | |
Python | Python | |
Apache License 2.0 | MIT License |
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.
datapane
- Datapane: Build and share data reports in 100% Python
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Polars: Company Formation Announcement
If you're looking for an easy way to build an HTML report using Python, you might find Datapane (https://github.com/datapane/datapane) helpful. I'm one of the people building it! We don't support polars (yet, on the roadmap) but we do support pandas so you can convert to a pandas DataFrame and include your data and any plots, etc.
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JupyterLab 4.0
If you're interested in an easier way to create reports using Python and Plotly/Pandas, you should check out our open-source library, Datapane: https://github.com/datapane/datapane - you can create a standalone, redistributable HTML file in a few lines of Python.
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Evidence – Business Intelligence as Code
You might be interested in what we're hacking on at Datapane (I'm one of the founders): https://github.com/datapane/datapane.
You can create standalone HTML data reports from Python/Jupyter in ~3 lines of code: https://docs.datapane.com/reports/overview/
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Ask HN: Fastest way to turn a Jupyter notebook into a website these days?
You can build web apps from Jupyter using Datapane [0]. I'm one of the founders, so let me know if I can help at all.
You can either export a static site [1] (and host on GH pages or S3), or, if you need backend logic, you can add Python functions [2] and serve on your favourite host (we use Fly).
We have specific Jupyter integration to automatically convert your notebook into an app [3].
[0] https://github.com/datapane/datapane
[1] https://docs.datapane.com/reference/reports/#datapane.proces...
[2] https://docs.datapane.com/apps/overview/
[3] https://docs.datapane.com/reports/jupyter-integration/#conve...
- Datapane – Build full-stack data apps in 100% Python
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Datapane - Build full-stack data apps in 100% Python
Our GitHub is https://github.com/datapane/datapane and you can get started here: https://docs.datapane.com/quickstart/
- Datapane: Build internal analytics products in minutes using Python
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Datapane - Build internal data products in 100% Python
Thanks a lot! Yes, absolutely, a few people have brought this up and working working on removing the header right now. If I can help at all, feel free to reach us on GH Discussions: https://github.com/datapane/datapane/discussions
- Datapane/datapane: Build full-stack data analytics apps in Python
powerbi-jupyter
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Automated testing of Power BI reports using Selenium
Consider using the PowerBI-Jupyter package in python and bolt it to your favorite testing framework.
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Jupyter notebooks for dashboarding?
I haven't tried this yet but I'm going to experiment with it later this week to connect Jupyter to PowerBI. https://github.com/microsoft/powerbi-jupyter
What are some alternatives?
streamlit - Streamlit — A faster way to build and share data apps.
dash - Data Apps & Dashboards for Python. No JavaScript Required.
jupyter-dash - OBSOLETE - Dash v2.11+ has Jupyter support built in!
superset - Apache Superset is a Data Visualization and Data Exploration Platform
perspective - A data visualization and analytics component, especially well-suited for large and/or streaming datasets.
plotly - The interactive graphing library for Python :sparkles: This project now includes Plotly Express!
csv-metabase-driver - A CSV metabase driver
xlwings - xlwings is a Python library that makes it easy to call Python from Excel and vice versa. It works with Excel on Windows and macOS as well as with Google Sheets and Excel on the web.
cube.js - 📊 Cube — The Semantic Layer for Building Data Applications