hvplot course

[Haleshot]

hvPlot

We're seeking contributors for a course on hvPlot! Contributors will be credited as authors in the course's directory, and in the notebooks they contribute.

hvPlot provides a high-level plotting API that makes data visualization intuitive and powerful, while seamlessly integrating with the PyData ecosystem.

Claiming a notebook.

Any notebook without an assigned author needs a contributor. To get started, leave a comment to claim a notebook you'd like to contribute, and then create a PR with your draft.

Notebook	Description	Status	Author
Getting Started with hvPlot	Understanding hvPlot's philosophy and advantages for data visualization	🚧
Plotting Fundamentals	Essential plot types and common patterns with different data structures	🚧
Data Exploration	Interactive data exploration techniques and plot customization	🚧
Statistical Visualization	Creating statistical plots, distributions, and advanced analytics visualizations	🚧
Working with Time	Specialized features and best practices for time series visualization	🚧
Geospatial Visualization	Plotting geographic data using GeoViews integration	🚧
Network Graphs	Using hvplot.networkx as a drop-in replacement for networkx.draw with interactive features	🚧
Advanced Layouts	Creating sophisticated subplot arrangements and composite visualizations	🚧
Interactive Features	Adding widgets and interactive elements to plots	🚧
Large Scale Visualization	Strategies for visualizing large datasets with datashader	🚧
Streaming & Real-time	Building visualizations for streaming and real-time data	🚧
Backend Deep Dive	Understanding and leveraging Bokeh, Matplotlib and Plotly backends	🚧
Advanced Topics	Extensions, custom plots, and advanced customization techniques	🚧

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