{"library":"tabmat","type":"library","category":null,"description":"Tabmat provides efficient matrix representations for working with tabular data, designed to integrate seamlessly with various dataframe libraries. It offers specialized matrix types like DenseMatrix, CategoricalMatrix, and SplitMatrix for performance-critical statistical and machine learning tasks, especially useful for generalized linear models. The current version is 4.2.1, with an active development pace and frequent releases addressing bug fixes and new features.","language":"python","status":"active","version":"4.2.1","tags":["matrix","tabular data","numerical computing","statistics","machine learning","sparse matrix"],"last_verified":"Wed May 27","install":[{"cmd":"pip install tabmat","imports":["from tabmat import from_df","from tabmat import from_formula","from tabmat import DenseMatrix","from tabmat import CategoricalMatrix","from tabmat import SplitMatrix"]}],"homepage":null,"github":"https://github.com/Quantco/tabmat","docs":null,"changelog":null,"pypi":"https://pypi.org/project/tabmat/","npm":null,"openapi_spec":null,"status_page":null,"smithery":null,"compatibility":{"summary":{"python_range":"3.10–3.9","success_rate":50,"avg_install_s":12.6,"avg_import_s":1.88,"wheel_type":"wheel"},"url":"https://checklist.day/v1/registry/tabmat/compatibility"}}