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Open Collective


Fiscal Host: NumFOCUS

HoloViz provides a set of Python packages that make viz easier, more accurate, and more powerful


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$1,004 USD since Apr 2023

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Credit from NumFOCUS to HoloViz

Added funds #706843
-$763.23 USD
Reimbursement #152829

Credit from NumFOCUS to HoloViz

Added funds #666059
Today’s balance

$240.77 USD

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$1,004.00 USD

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$763.23 USD

Estimated annual budget

$1,004.00 USD


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Join the HoloViz community

Published on June 9, 2023 by James A. Bednar

Welcome to HoloViz! The HoloViz community hosts short chats on Discord and longer and more detailed posts at...


HoloViz is a set of high-level tools that make it easier to use Python plotting libraries with your data. HoloViz tools include:
  • Panel: easily build powerful web apps using any plotting library or other visual content
  • hvPlot: Use the .plot() interface you already know from Pandas to generate powerful interactive plots
  • HoloViews: hvPlot is a data-science wrapper building on HoloViews, and if you need more features, more customizability, or want to build plotting support into your simulator or analytics package, use HoloViews
  • GeoViews: HoloViz tools are all general purpose, domain independent, except that GeoViews provides special support for anyone needing to project data in Earth-centered coordinates onto a flat screen for display
  • Datashader: Accurate server-side rendering for even the largest datasets, making it simple to work with enormous remote datasets from any web browser
  • Param: Everything in HoloViz builds on Param's support for configurable, modular Python; if you are running a big project like Panel or HoloViews, be sure to consider building on Param so you can stay sane!
  • Colorcet: Perceptually accurate monotonic or categorical colormaps for use with any plotting tool
  • Lumen: Python-extensible low-code and no-code data exploration and building web apps, so that everyone on your team can share in the wealth of Python tools for visualization and dashboarding!
All of these tools build on Python's rich ecosystem of data and analytics libraries, making it easy for you to apply them to your own work.