![]() ![]() Read about pyDeck at pydeck.gl/ and explore its gallery pydeck gallery.Learn more about its core deck.gl webGL based library a deck.gl.The pyDeck library is a set of Python bindings for making spatial visualizations with deck.gl, optimized for a Jupyter environment.Read more about Panel at / and explore its gallery /reference/.Panel works well within the Python visualization ecosystem and is what powers the interactive tools on this page.Panel -like holoViews, hvPlot, and datashader- is part of the HoloViz Ecosystem.Panel is a Python library that lets you create custom interactive web apps and dashboards by connecting user-defined widgets to plots, images, tables, or text.Run an interactive example and cpu / gpu code comparison below: Read about Holoviews at and explore its gallery /gallery/.With HoloViews, you can usually express what you want to do in very few lines of code, letting you focus on what you are trying to explore and convey, not on the process of plotting.See this diagram for an excellent architecture overview. HoloViews is an open-source Python library designed to make data analysis and visualization seamless and simple.To run a true interactive version, host through the active instance found on our cuxfilter GitHub Notebooks. When interacting with this page through a website, the interactive examples below are all static and use pre-computed data. Note: Web Hosted vs Local Hosted Chart Interaction Holoviews with Linked Brushing User Guide.The below libraries directly use RAPIDS cuDF/Dask-cuDF and/or cuSpatial to create charts that support accelerated crossfiltering or rendering: node RAPIDS: RAPIDS bindings in nodeJS, a high performance JS/TypeScript visualization alternative to using Python.cuxfilter: RAPIDS developed cross filtering dashboarding tool that integrates many of the libraries above.PyDeck: Python bindings for interactive spatial visualizations with webGL powered deck.gl, optimized for a Jupyter environment.Panel: A high-level app and dashboarding solution for the Python ecosystem.Seaborn: Static single charting library that extends matplotlib.Bokeh: Charting library for building complex interactive visualizations.Plotly: Charting library that supports Plotly Dash for building complex analytics applications.Datashader: Rasterizing huge datasets quickly as scatter, line, geospatial, or graph charts.hvPlot: Quickly return interactive plots from cuDF, Pandas, Xarray, or other data structures.HoloViews: Declarative objects for quickly building complex interactive plots from high-level specifications.This catalog of featured libraries offer direct cuDF support or easy integration.ģ30 million+ datapoints rendered in under 1.5s via RAPIDS + Plotly Dash 2020 Census Demo Featured Libraries RAPIDS libraries can easily fit in visualization workflows. ![]()
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