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Fritz Lekschas - Interactive Exploration of Large-Scale Datasets with Jupyter-Scatter | SciPy 2023
Interactive exploration of large-scale datasets with Jupyter-Scatter, a tool for scatter plots, scalable and customizable with API for categorical data and integration with Jupyter and other libraries.
- Jscatter is a tool for interactive exploration of large-scale datasets via scatter plots.
- It can handle datasets of up to several million points and provides a simple API for encoding categorical data.
- The API can be customized to use different encoding methods, including colorblind-safe options.
- Jscatter can be used to synchronize multiple scatter plots and provide a zoomable and panable interface.
- The tool can be used in conjunction with other data visualization libraries, such as Seaborn and D3.js.
- Jscatter is built on top of Jupyter and uses the IPY widget ecosystem to provide a seamless interface for users.
- The tool can be used to explore a wide range of datasets, including single-cell data, geospatial data, and more.
- Jscatter provides a flexible and customizable interface for exploratory data analysis and visualization.
- The tool can be used to perform faceted analysis and filtering of large datasets.
- Jscatter can be integrated with other libraries and tools, such as Jupyter Notebooks and PyCharm.
- The tool can be used to visualize and explore large datasets in a scalable and interactive way.