{"categories":[{"label":"Scientific/Engineering","url":"https://skillfed.io/packages/category/scientific-engineering/8"},{"label":"GIS","url":"https://skillfed.io/packages/category/scientific-engineering-gis"}],"enrichment":{"capability":"splot creates static and interactive visualizations for spatial analysis workflows, connecting PySAL objects to matplotlib and other visualization toolkits.","skillfed_tags":["spatial-analysis","geospatial-viz","pysal-ecosystem"],"use_cases":["Visualize univariate or multivariate spatial autocorrelation results from esda as Moran scatterplots and cluster maps.","Create choropleth maps with value-by-alpha styling to show spatial patterns with statistical confidence.","Plot space-time autocorrelation trends from giddy to assess how spatial relationships evolve over time.","Explore neighboring polygon relationships and non-planar spatial joins using libpysal visualization functions.","Generate publication-ready static maps and exploratory interactive plots for spatial regression diagnostics from spreg."],"what_it_does":"splot is a visualization layer for the PySAL spatial analysis ecosystem. It translates PySAL statistical objects\u2014like Moran's I results, classification schemes, and space-time autocorrelation measures\u2014into publication-ready static plots and exploratory interactive visualizations. The package wraps matplotlib, seaborn, and related tools to handle the domain-specific needs of spatial data, such as choropleth mapping, spatial autocorrelation scatterplots, and value-by-alpha visualizations.\n\nYou use splot when you've completed spatial statistical analysis in PySAL (esda, libpysal, spreg, giddy) and need to communicate or explore the results visually. It abstracts away boilerplate matplotlib configuration and provides sensible defaults for common spatial workflows, letting you focus on interpretation rather than plot construction.","worth_installing":"Yes, if you work with PySAL for spatial analysis and need to visualize results. The package is stable (Production/Stable status), has no known vulnerabilities, and installs cleanly. The aging maintenance status is a minor concern for active development, but the repository is not abandoned and the codebase is mature. Install it as part of your PySAL workflow or as a standalone visualization layer for spatial statistics."},"id":"splot","links":{"html":"https://skillfed.io/packages/splot","md":"https://skillfed.io/packages/splot.md","pypi":"https://pypi.org/project/splot/"},"maintenance":{"status":"aging"},"meta":{"latest_release":"2024-09-09","license_spdx":null,"license_treatment":"permissive","name":"splot","python_support":"unspecified","summary":"Visual analytics for spatial analysis with PySAL."},"popularity":{"monthly_downloads":99239,"position":13033,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"1.1.7"}