{"categories":[{"label":"Software Development","url":"https://skillfed.io/packages/category/software-development/15"},{"label":"Scientific/Engineering","url":"https://skillfed.io/packages/category/scientific-engineering/7"},{"label":"Information Analysis","url":"https://skillfed.io/packages/category/scientific-engineering-information-analysis/3"},{"label":"Visualization","url":"https://skillfed.io/packages/category/scientific-engineering-visualization"}],"enrichment":{"capability":"ridgeplot creates interactive ridgeline plots using Plotly, allowing you to visualize distributions across multiple categories or time periods with a simple interface.","skillfed_tags":["data-visualization","plotly-wrapper","statistical-graphics"],"use_cases":["Visualize temperature or weather patterns across months or years as overlapping density curves.","Compare probability distributions across survey response categories or demographic groups.","Display time-series density evolution (e.g., stock price distributions by year or month).","Create publication-ready ridgeline plots for scientific papers or reports with minimal code.","Explore multimodal or skewed distributions across many conditions in a single, readable plot."],"what_it_does":"ridgeplot is a Python visualization library that wraps Plotly to simplify creation of ridgeline plots\u2014a technique for displaying multiple probability distributions or time-series densities in a single, compact figure. It handles kernel density estimation (KDE) and layout automatically, letting you focus on data rather than plotting mechanics.\n\nThe package is built on numpy for numerical work, statsmodels for KDE computation, and Plotly for rendering. You pass in arrays of samples (one per row or category), and ridgeplot generates an interactive figure with sensible defaults for bandwidth, spacing, and color. The result is a Plotly Figure object, so you can extend it with standard Plotly methods for customization. It's designed for exploratory data analysis, scientific visualization, and publication-quality graphics.","worth_installing":"Yes. ridgeplot is actively maintained, has no known vulnerabilities, installs with low friction, and solves a specific visualization task well. The MIT license is unrestricted. Use it if you need ridgeline plots; it's more convenient than hand-coding KDE and layout in raw Plotly."},"id":"ridgeplot","links":{"html":"https://skillfed.io/packages/ridgeplot","md":"https://skillfed.io/packages/ridgeplot.md","pypi":"https://pypi.org/project/ridgeplot/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-04-07","license_spdx":null,"license_treatment":"permissive","name":"ridgeplot","python_support":"supports_current","summary":"Beautiful ridgeline plots in python"},"popularity":{"monthly_downloads":135169,"position":11452,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.6.0"}