Does it support geographic maps?

Yes, the skill provides implementation patterns for geographic plotting using GeoPandas and hvPlot's geo-spatial capabilities.

Can I combine multiple charts into one view?

Yes, the skill covers HoloViews composition patterns for overlays (using *), layouts (using +), and complex grid views.

What libraries are required for this skill?

This skill requires hvplot, holoviews, pandas, numpy, and bokeh to generate high-quality interactive visualizations.

Is the output interactive?

Absolutely. Plots generated using this skill include native hover tools, pan, wheel zoom, and selection functionality powered by the Bokeh backend.

Can this skill handle large datasets?

Yes, it includes best practices for using Datashader and aggregation techniques to visualize datasets with over 100,000 points efficiently.

HoloViz Plotting Fundamentals

Name: HoloViz Plotting Fundamentals
Author: robertpelloni

byrobertpelloni

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데이터 과학 및 ML

Generates interactive, publication-quality data visualizations using the HoloViz ecosystem and hvPlot for rapid data analysis.

소개

This skill empowers Claude to create sophisticated and interactive visualizations using hvPlot and HoloViews with minimal boilerplate code. It bridges the gap between raw pandas DataFrames and high-level, web-ready plots, offering deep support for various chart types including line, scatter, bar, and geographic maps. Whether you are performing exploratory data analysis or building polished dashboards, this skill provides the patterns and best practices needed to implement responsive, interactive, and aesthetically pleasing data representations quickly.

주요 기능

Rapid hvPlot integration for pandas DataFrames with minimal code
Geographic data visualization using GeoPandas and hvPlot
Interactive tools including hover, zoom, and selection streams
Advanced styling and customization for publication-quality output
Interactive plot composition with overlays and side-by-side layouts
3 GitHub stars

사용 사례

Creating high-resolution visualizations for research papers and presentations
Exploratory Data Analysis (EDA) of complex datasets
Building interactive dashboards and data reports for stakeholders

소개

주요 기능

Rapid hvPlot integration for pandas DataFrames with minimal code
Geographic data visualization using GeoPandas and hvPlot
Interactive tools including hover, zoom, and selection streams
Advanced styling and customization for publication-quality output
Interactive plot composition with overlays and side-by-side layouts
3 GitHub stars

사용 사례

Creating high-resolution visualizations for research papers and presentations
Exploratory Data Analysis (EDA) of complex datasets
Building interactive dashboards and data reports for stakeholders