In this readme and the repo, you'll find a collection of useful resources related to the workshop.
Moreover, you'll find some helpful links to the Streamlit apps and their source code, the ipyvizzu documentation, and the bidirectional component that integrates ipyvizzu into Streamlit.
- The tutorial app for using ipyvizzu in Streamlit: https://intro-to-vizzu-in.streamlit.app/
- Vizzu builder app: https://vizzu-builder.streamlit.app/
- Check out and get through the installation guide below
- Fork the repo of the tutorial app (locally if you will) - https://github.com/vizzu-streamlit/streamlit-vizzu-intro/
- Get some data! Check out the sample datasets in the tutorial repo (or within the data folder here; they are identical) and pick one you want to start working with. You can also use your own CSV or samples from the Vega datasets: https://github.com/altair-viz/vega_datasets
- Create a new py file and reuse snippets from the tutorial examples - remember, most of them are in the pages folder
- Use the builder app to generate ipyvizzu code: https://vizzu-builder.streamlit.app/ and reuse it within your app
- Be creative! :)
- Share your app using the Streamlit Community Cloud
For Those With Experience in Python and Local Development:
If you're accustomed to working with Python packages locally and prefer having everything set up on your machine, this pathway is for you.
- Environment Setup: Install Streamlit, streamlit-vizzu, and ipyvizzu-story (along with their dependencies) in a virtual environment. Both pip and conda are great options for this step.
pip install streamlit streamlit-vizzu ipyvizzu-story
- Download Sample Materials: Grab the sample apps and datasets using this link. Download and extract the zip file to a convenient location on your computer.
- Get Ready to Share: Planning to showcase your work publicly? Create a free account at Streamlit Community Cloud to share your apps with the world. Keep in mind that Streamlit requests access to all your public repositories. If this raises any concerns for you, a straightforward solution is to create a new GitHub account.
For Those New to Python Packages and Local Setup:
If you're newer to the world of Python or prefer a setup that doesn't require local installations, we've got you covered.
- GitHub Account: Ensure you have a GitHub account ready to go. If not, you can create one here.
- Streamlit Community Cloud: Set up your free account at Streamlit Community Cloud to run and share apps directly from your browser.
- Get Coding in the Cloud: Once registered, you can write code and work with sample apps directly in your browser through Codespace, with no local setup required. For more info on this last step, read this blogpost: https://blog.streamlit.io/edit-inbrowser-with-github-codespaces/
- Streamlit intro presentation: https://docs.google.com/presentation/d/1asGx8vMvvHjqLENL0G1J84wDOojBUp5jBo5CaE_CQlo/edit#slide=id.g29371e65c4e_0_0
- Streamlit-Vizzu bidirectional component code: https://github.com/vizzu-streamlit/streamlit-vizzu
- Streamlit Community Cloud sign-up and documentation: https://streamlit.io/cloud & https://docs.streamlit.io/streamlit-community-cloud
- ipyvizzu documentation, examples & tutorial: http://ipyvizzu.com/
- ipyvizzu repo: https://github.com/vizzuhq/ipyvizzu - 🌟's are very much appreciated.
We'd like to invite you to join our community on Slack. We're always eager to welcome new members and help them get started, answer any questions you may have, and provide feedback and support for your projects and contributions. Here's the invite link: https://join.slack.com/t/vizzu-community/shared_invite/zt-w2nqhq44-2CCWL4o7qn2Ns1EFSf9kEg
We love to see our community members actively engaged with us! There are a few ways you can help us out:
- Test our tool and let us know if you encounter any issues. We value your feedback and are always looking to improve our tool. Please feel free to share your thoughts with us on Slack or open an issue in the ipyvizzu repository.
- Create new examples of how to use the awesome capabilities of animated reports! Your creativity and expertise are invaluable to us and can inspire other users to take advantage of ipyvizzu's full potential.
Thank you for your time, and we look forward to hearing from you soon!
Peter & the Vizzu Team