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Add K3D-jupyter to Visualization - #241
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https://github.com/K3D-tools/K3D-jupyter 3D visualization in Jupyter notebooks from NumPy arrays: volumes, isosurfaces, point clouds and streamlines. Added at the bottom of the category and linking the repository, per the pull request template.
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Project name: K3D-jupyter
Project website/repository: https://github.com/K3D-tools/K3D-jupyter (docs: https://k3d-jupyter.org)
License: MIT
Submission type: New Software Project
Checklist for all pull requests:
certified awesome### Visualization, afterDigitize Heatmap.media/icon/folder if applicable. —.Checklist for new software projects:
pip install k3d/conda install -c conda-forge k3d.WebGL 3D plotting widget for Jupyter: volumes, isosurfaces, meshes, voxels, point clouds and streamlines, from plain NumPy arrays. MIT, ~1k stars, ~92k PyPI downloads/month, 237k on conda-forge.
Geoscience relevance: seismic and gridded volumes, terrain and LiDAR point clouds, and flow streamlines. It also reads VTK objects directly, so PyVista/VTK pipelines feed it without a conversion step, and since 3.0.0 the front end is an anywidget — the same package works in JupyterLab, Notebook, Colab and VS Code with no extension to enable.
Note on the diff: this README uses CRLF line endings, so the entry was written with CRLF to keep the diff to the single added line.
Disclosure: I maintain K3D-jupyter.