Can I create geographic maps with this skill?

Yes, it includes specific patterns for geographic plotting using GeoPandas integration and HoloViz map tools.

What is the primary benefit of the Plotting Fundamentals skill?

It allows you to create complex, interactive visualizations with minimal code by using high-level HoloViz abstractions rather than low-level plotting commands.

Is it compatible with standard pandas DataFrames?

Absolutely; it is designed to extend pandas objects with the .hvplot() API, enabling a seamless workflow from data processing to visualization.

Which libraries are required for this skill?

This skill requires hvPlot (>=0.9.0), HoloViews (>=1.18.0), Pandas, NumPy, and Bokeh (>=3.0.0) for rendering.

Does it support large datasets?

Yes, it provides patterns for handling large datasets using techniques like hexbinning and offers guidance on integrating with Datashader for millions of points.

HoloViz Plotting Fundamentals

Name: HoloViz Plotting Fundamentals
Author: cdcore09

bycdcore09

•

데이터 과학 및 ML

Simplifies the creation of interactive, publication-quality visualizations using hvPlot and HoloViews within the HoloViz ecosystem.

소개

This skill empowers developers to generate complex interactive charts and dashboards with minimal code by leveraging high-level hvPlot and HoloViews libraries. It provides optimized implementation patterns for common visualization tasks—including time series, geographic maps, and statistical distributions—while ensuring all outputs are interactive, responsive, and visually polished for both exploratory data analysis and professional reporting.

주요 기능

Rapid interactive plotting with a pandas-integrated API via hvPlot
Advanced styling controls for publication-quality aesthetic consistency
Intuitive composition of multiple plots using layout and overlay operators
Interactive features including hover tools, linked selections, and responsive sizing
Built-in support for geographic data and map-based visualizations
2 GitHub stars

사용 사례

Building interactive dashboards for time-series and geographic trends
Performing rapid exploratory data analysis (EDA) on pandas DataFrames
Generating statistical summaries like KDEs, box plots, and histograms with minimal boilerplate

소개

주요 기능

Rapid interactive plotting with a pandas-integrated API via hvPlot
Advanced styling controls for publication-quality aesthetic consistency
Intuitive composition of multiple plots using layout and overlay operators
Interactive features including hover tools, linked selections, and responsive sizing
Built-in support for geographic data and map-based visualizations
2 GitHub stars

사용 사례

Building interactive dashboards for time-series and geographic trends
Performing rapid exploratory data analysis (EDA) on pandas DataFrames
Generating statistical summaries like KDEs, box plots, and histograms with minimal boilerplate