Animated chart presentations in Jupyter notebooks
After releasing our open-source tool to build animated charts in Jupyter and other computational notebooks (https://news.ycombinator.com/item?id=30895975), we got two requests from data scientists: 1. They lacked the opportunity to use these charts to present their findings and control the animation better than just (re)running notebook cells. 2. They had challenges using our generic chart-building engine - they are more acquainted with picking a chart type and using the parameters specific to that type. So we decided to build a new extension that enables our users to add the…
In plain words
This tool creates animated chart presentations within Jupyter notebooks, allowing data scientists to build and present interactive visualizations directly from their computational environment. Users can organize charts into slides and control animations using on-screen buttons, keyboard shortcuts, or a presentation clicker. The extension provides chart-type-specific parameters designed for users familiar with traditional charting tools, making it easier to build visualizations without learning a generic chart engine.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
After releasing our open-source tool to build animated charts in Jupyter and other computational notebooks (https://news.ycombinator.com/item?id=30895975), we got two requests from data scientists: 1. They lacked the opportunity to use these charts to present their findings and control the animation better than just (re)running notebook cells. 2. They had challenges using our generic chart-building engine - they are more acquainted with picking a chart type and using the parameters specific to that type. So we decided to build a new extension that enables our users to add the charts to slides and thus create interactive, animated presentations they can present right from the notebook. The presentation can be controlled with buttons beneath the charts, keyboard shortcuts (arrows, PgUp, PgDn, Home, End), or a clicker. We also added the capability to export these presentations to HTML to share them with others who don't use notebooks. Example - scroll to the bottom for the presentation: https://vizzuhq.github.io/ipyvizzu-story/examples/demo/ipyvi.... We tackled the other challenge by introducing chart presets: users can now pick from the 40+ pre-defined chart types. https://ipyvizzu.vizzuhq.com/examples/examples.html#Preset-c... Everything is released under the Apache 2.0 license and is available for JavaScript developers as an open-source data storytelling solution. Technically, in the Jupyter version, it's the JS lib being called from the notebook with a Python interface - similarly to what Plotly does. More info: https://github.com/vizzuhq/vizzu-ext-js-story & https://lib.vizzuhq.com/latest/ We'd love to know more about how our technology can be put to good use, so if you have any feedback or suggestions, we're here to listen.
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