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conda-forge.org : static-frame
Among the many Python DataFrame libraries, StaticFrame is an alternative that prioritizes correctness, maintainability, and reducing opportunities for error. Key features include: * ðĄïļ Immutable Data: Provides memory efficiency, excellent performance, and prohibits side effects. * ðïļ Static Typing: Use Python type-hints to statically type index, columns, and columnar types. * ðĶ Runtime Validation: Use type hints and specialized validators for runtime type and data checks. * ð§ Consistent Interface: An easy-to-learn, hierarchical, and intuitive API that avoids the many inconsistencies of Pandas. * 𧎠Comprehensive ``dtype`` Support: Full compatibility with all NumPy dtypes and datetime64 units. * ð Broad Interoperability: Translate between Pandas, Arrow, Parquet, CSV, TSV, JSON, MessagePack, Excel XLSX, SQLite, HDF5, and NumPy; output to xarray, VisiData, HTML, RST, Markdown, LaTeX, and Jupyter notebooks. * ð Optimized Serialization & Memory Mapping: Fast disk I/O with custom NPZ and NPY encodings. * ðž Multi-Table Containers: The ``Bus`` and ``Yarn`` provide interfaces to collections of tables with lazy data loading, well-suited for large datasets. * âģ Deferred Processing: The ``Batch`` provides a common interface for deferred processing of groups, windows, or any iterator. * ðŠķ Lean Dependencies: Core functionality relies only on NumPy and team-maintained C-extensions. * ð Comprehensive Documentation: All API endpoints documented with thousands of easily runnable examples.
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purl: pkg:conda/static-frame
Keywords: arrays, dataframes, immutable-collections, immutable-data-structures, python
License: MIT
Latest release: over 1 year ago
First release: about 5 years ago
Stars: 354 on GitHub
Forks: 32 on GitHub
Total Commits: 5499
Committers: 26
Average commits per author: 211.5
Development Distribution Score (DDS): 0.1
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Last synced: 2 days ago