{"library":"kmeans1d","type":"library","category":null,"description":"kmeans1d is a Python package providing an implementation of optimal k-means clustering specifically for one-dimensional data. It utilizes an O(kn + n log n) dynamic programming algorithm, based on research by Xiaolin (1991) and Gronlund et al. (2017), to find globally optimal k clusters. The core logic is written in C++ for performance and wrapped for Python usage. The library is actively maintained, with its current version being 0.5.0.","language":"python","status":"active","version":"0.5.0","tags":["kmeans","clustering","1d","optimal","data-science","machine-learning"],"last_verified":"Sun May 24","install":[{"cmd":"pip install kmeans1d","imports":["import kmeans1d\nclusters, centroids = kmeans1d.cluster(data, k)"]}],"homepage":null,"github":"https://github.com/dstein64/kmeans1d","docs":null,"changelog":null,"pypi":"https://pypi.org/project/kmeans1d/","npm":null,"openapi_spec":null,"status_page":null,"smithery":null,"compatibility":{"summary":{"python_range":"3.10–3.9","success_rate":50,"avg_install_s":1.6,"avg_import_s":0.03,"wheel_type":"wheel"},"url":"https://checklist.day/v1/registry/kmeans1d/compatibility"}}