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July 13, 2023 Interactive Exploration of Large-Scale Datasets with Jupyter-Scatter Fritz Lekschas @flekschas lekschas.de 1 SciPy '23

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2 WORK Head of Visualization Research at Ozette EDUCATION PhD '21 in CS from Harvard University RESEARCH Visualization Human-Centered ML Design

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3 PASSION Embeddings & Scatter plots!

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3 PASSION Embeddings & Scatter plots!

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4 PASSION Embeddings & Scatter plots!

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7 USEFUL FOR Overview of Data Explore & Compare Clusters

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7 USEFUL FOR Overview of Data Explore & Compare Clusters Data from Mair et al., 2022. Nature.

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7 USEFUL FOR Overview of Data Explore & Compare Clusters Data from Mair et al., 2022. Nature.

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7 USEFUL FOR Overview of Data Explore & Compare Clusters Data from Mair et al., 2022. Nature.

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Jupyter Scatter A widget for interactive exploration of large-scale scatter plots. 8 github.com/flekschas/jupyter-scatter pip install jupyter-scatter

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GOALS 1. Scale to millions of points 2. Support interactive pan+zoom and selections 3. Offer perceptually-effective defaults 4. Allow linking multiple scatter plots 5. Expose via an easy-to-use API 9

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GOALS 1. Scale to millions of points 2. Support interactive pan+zoom and selections 3. Offer perceptually-effective defaults 4. Allow linking multiple scatter plots 5. Expose via an easy-to-use API 10

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GOALS 1. Scale to millions of points 2. Support interactive pan+zoom and selections 3. Offer perceptually-effective defaults 4. Allow linking multiple scatter plots 5. Expose via an easy-to-use API 11

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GOALS 1. Scale to millions of points 2. Support interactive pan+zoom and selections 3. Offer perceptually-effective defaults 4. Allow linking multiple scatter plots 5. Expose via an easy-to-use API 12

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GOALS 1. Scale to millions of points 2. Support interactive pan+zoom and selections 3. Offer perceptually-effective defaults 4. Allow linking multiple scatter plots 5. Expose via an easy-to-use API 13

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GOALS 1. Scale to millions of points 2. Support interactive pan+zoom and selections 3. Offer perceptually-effective defaults 4. Allow linking of multiple scatter plots 5. Expose via an easy-to-use API 14

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Live Demos! https://github.com/flekschas/jupyter-scatter-tutorial 15

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ARCHITECTURE 1. WebGL Rendering via regl-scatterplot1 for fast plotting 2. Python API layer for integrating with Pandas and configuring regl-scatterplot1 3. Ipywidgets for communication with Jupyter via anywidget2 16 1) https://github.com/flekschas/regl-scatterplot/ 2) https://github.com/manzt/anywidget/

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! MASSIVE SHOUT OUTS! Trevor Manz for the codec design, anywidget integration, & tutorial setup Nezar Abdennur for feedback–––––––– on the API design–––––––– Ricky Reusser for his inspirational work on selecting the right point opacity Rye Terrell for his beautiful multi-instance–––––––– WebGL rendering approach–––––––– 17

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Thanks! pip install jupyter-scatter github.com/flekschas/jupyter-scatter github.com/flekschas/jupyter-scatter-tutorial @flekschas lekschas.de July 13, 2023 SciPy '23