ipyvizzu-story VS plotly

Jupyter/Python extension: https://github.com/vizzuhq/ipyvizzu-story

Depending on the nature of your reporting requirements, you could output a formatted Excel document with Python and a library such as openpyxl, and shove that into your SharePoint environment. This would be less dynamic than PBI reports can be, but may be sufficient. If you want viz as well, you can use something like ggplot or Plotly. Again, less dynamic than PBI for the same effort.

Because the confusion matrix is implemented in plotly, it is interactive! To interact visually with your data via the confusion matrix, attach the plot to a session launched with the dataset:

I've created a notebook in this Github repo to demo some of Plotly basic capabilities and I highly recommend checking out the official documentations for examples of each plot type and to discover lots of cool stuff that you can put in your notebook/site 🙂.

- plotly (https://plotly.com/python/);

Sure! One of the big ones that really powers the whole web application is Python Dash. This framework lets you build an entire web application in pure python, similar to something like Flask or Django, but its geared more towards data science applications. You get to use all of the Plotly charts in a streamlined way. 🙌 Dash actually uses React under the hood to render the web page, and there's a lot of useful 3rd party libraries with ready-to-use web components.

They have a lot of detailed examples on https://plotly.com/python/

(I don't know how to run it if it's installed as a package, but this works great and is much easier to customize. Plotly has pretty graph/chart options by the way https://plotly.com/python/ )

Focus on Documentation We get more traffic to our documentation than our main website. A well-documented project is always loved by the community. Open-source projects like Docusaurus make it super easy to build documentation portals that look great just out of the box. Adding links to the repository from the documentation can drive more visitors to your repository. What to include in documentation How to install/deploy the project If the project has a compiled software as the final product, make sure to add installation instructions. If the project is the codebase for a library such as an npm package or a Ruby gem, include details on how to import and use the library. If the project needs to be or can be deployed on platforms like Kubernetes, Docker, Heroku, and others, include separate guides for each of the options. Contributing guide Apart from the contributing guide doc in the codebase, add one to the documentation, too. It should include guides for setting up a local environment on different platforms like Docker, Mac OS, Ubuntu, Windows, and so on. Tutorials and code examples If this is applicable, it can be really helpful. How to guides on using using the project will show other devs how they can actually get started. It can be code examples if the project is a library. Architecture reference It will be helpful for the contributors if the documentation has details on different components of the project. For example, if the project has server and client components, include a diagram on how everything works together. Here are some projects with great documentation: https://docs.nestjs.com/ https://docs.n8n.io/ https://guides.rubyonrails.org/ https://plotly.com/python/ https://docs.mapbox.com/ https://www.github-stars.com or Github24.