{"library":"loess","type":"library","category":null,"description":"LOESS (Locally Estimated Scatterplot Smoothing) is a non-parametric regression method that fits simple models to localized subsets of data to build up a function that describes the deterministic part of the variation. This Python library provides robust implementations for 1D and 2D LOESS smoothing. The current version is 2.1.2, and it typically sees releases for bug fixes and minor improvements, with a stable API.","language":"python","status":"active","version":"2.1.2","tags":["statistics","smoothing","regression","data science","non-parametric"],"install":[{"cmd":"pip install loess","imports":["from loess.loess_1d import loess_1d","from loess.loess_2d import loess_2d"]}],"homepage":"https://purl.org/cappellari/software","github":null,"docs":null,"changelog":null,"pypi":"https://pypi.org/project/loess/","npm":null,"openapi_spec":null,"status_page":null,"smithery":null,"compatibility":{"summary":{"python_range":"3.10–3.9","success_rate":100,"avg_install_s":11.6,"avg_import_s":0.25,"wheel_type":"wheel"},"url":"https://checklist.day/v1/registry/loess/compatibility"},"provenance":{"verified_status":"passing","verified_at":"Sun Jun 28","last_verified":"Sun Jun 28","next_check":"Tue Jul 28","install_tag":null}}