{"library":"datasieve","type":"library","category":null,"description":"The `datasieve` package provides a flexible data pipeline inspired by scikit-learn's Pipeline, but with enhanced capabilities to manipulate `y` (target) and `sample_weight` arrays alongside `X` (features). This is particularly useful for tasks such as removing outliers across all associated data, removing feature columns based on arbitrary criteria, and handling dynamic feature renaming within the pipeline. The current version is 0.1.9, with releases occurring on an irregular, as-needed basis.","language":"python","status":"active","version":"0.1.9","tags":["data-pipeline","outlier-detection","feature-engineering","sklearn-compatible","data-preprocessing"],"last_verified":"Mon May 25","install":[{"cmd":"pip install datasieve","imports":["from datasieve.pipeline import Pipeline","import datasieve.transforms as dst","from datasieve.transforms import SKlearnWrapper"]}],"homepage":null,"github":null,"docs":null,"changelog":null,"pypi":"https://pypi.org/project/datasieve/","npm":null,"openapi_spec":null,"status_page":null,"smithery":null,"compatibility":{"summary":{"python_range":"3.10–3.9","success_rate":50,"avg_install_s":13.3,"avg_import_s":4.41,"wheel_type":"wheel"},"url":"https://checklist.day/v1/registry/datasieve/compatibility"}}