cufflinks
datapane
| cufflinks | datapane | |
|---|---|---|
| 2 | 30 | |
| 2,980 | 1,348 | |
| - | 0.4% | |
| 10.0 | 7.3 | |
| over 2 years ago | 7 months ago | |
| Jupyter Notebook | Python | |
| MIT 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.
cufflinks
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JupyterLab 4.0
While I have no need for it's only functionality and the SAAS part of plotly, I really do like plotly python + cufflinks [1]. It lets you make interactive plots in html/js format. Which means you can save the notebook as html, and while people won't be able to rerun the code, they can still zoom in on graphs, hover to see annotations etc, which is a really nice way to share the outcome of your work in a more accessible way.
[1] https://github.com/santosjorge/cufflinks
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Plotly and Cufflinks : Advanced Python Data Visualization Libraries
If you are interested in financial analyst you can check out some functions here like moving averages, correlation between plots etc..: https://github.com/santosjorge/cufflinks/blob/b973f3a0f689816139de6c68855ab65ffec1556 7/cufflinks/ta.py
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
What are some alternatives?
nb_conda_kernels - Package for managing conda environment-based kernels inside of Jupyter
streamlit - Streamlit — A faster way to build and share data apps.
papermill - 📚 Parameterize, execute, and analyze notebooks
dash - Data Apps & Dashboards for Python. No JavaScript Required.
nbformat - Reference implementation of the Jupyter Notebook format
jupyter-dash - OBSOLETE - Dash v2.11+ has Jupyter support built in!
jupyenv - Declarative and reproducible Jupyter environments - powered by Nix
perspective - A data visualization and analytics component, especially well-suited for large and/or streaming datasets.
m1_huggingface_diffusers_demo - Demo of how to get HuggingFace Diffusers working on an M1 Mac
superset - Apache Superset is a Data Visualization and Data Exploration Platform
plotly - The interactive graphing library for Python :sparkles: This project now includes Plotly Express!
powerbi-jupyter - A Custom Jupyter Widget Library for Power BI