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eazyml-data-quality from EazyML family for comprehensive data quality assessment, including bias detection, outlier identification, and data drift analysis.
pip install eazyml-data-quality
PyPI declares 24 unique dependency rules for this release. Environment markers are shown when supplied by the project.
==1.3.* when python_version <= "3.7"==1.0.* when python_version <= "3.7"==1.21.* when python_version <= "3.7">=2.2.3 when python_version == "3.10"==1.3.* when python_version == "3.10"==1.24.* when python_version == "3.10">=2.2.3 when python_version == "3.11"==1.3.* when python_version == "3.11"==1.24.* when python_version == "3.11">=2.0.3 when python_version == "3.8"==1.3.* when python_version == "3.8"==1.24.* when python_version == "3.8">=2.2.3 when python_version == "3.9"==1.3.* when python_version == "3.9"==1.24.* when python_version == "3.9">=2.2.3 when python_version > "3.11"==1.3.* when python_version > "3.11"eazyml-data-quality publishes 1 wheel and 1 source archive for version 0.0.39. Wheel platform tags: any.
Declared Python classifiers: 3.10, 3.11, 3.12, 3.8, 3.9.
PyPI lists 7 releases with files. The first dated release is ; 7 releases fall within the 365 days preceding the latest dated release. The current release files were uploaded on . The preceding dated release was .