{"categories":[{"label":"Information Analysis","url":"https://skillfed.io/packages/category/scientific-engineering-information-analysis"}],"enrichment":{"capability":"Swifter applies functions to DataFrames and Series using automatic vectorization or parallel processing to speed up operations beyond standard apply.","skillfed_tags":["pandas-acceleration","parallel-processing","data-transformation"],"use_cases":["Speed up element-wise transformations on large Series by automatically vectorizing or parallelizing the operation.","Apply complex row-wise functions without manually managing parallel backends.","Optimize groupby().apply() chains when the function cannot be vectorized.","Migrate existing code to parallel execution with minimal refactoring.","Benchmark apply performance across different execution strategies in a single call."],"what_it_does":"Swifter is an extension that intercepts apply operations on DataFrames and Series, then automatically chooses the fastest execution path: vectorization when possible, or parallel processing when not. It wraps the standard apply interface, so you call `.swifter.apply()` instead of `.apply()` and let the package decide whether to run on a single core, multiple cores, or a distributed backend.\n\nThe package is designed for data-processing workflows where apply operations are a bottleneck. It includes optional extras for notebook progress bars and groupby-apply support. However, it carries a significant caveat: sample applies are run during optimization, so functions with side effects (modifying external state) will produce incorrect results.","worth_installing":"Yes, if you have large DataFrames and apply-heavy workflows where standard apply is too slow. However, proceed with caution: maintenance is dormant (last release 2023-07-31), license status is unclear, and Python version support is unspecified. Test compatibility with your environment before relying on it in production. Not suitable for functions with side effects."},"id":"swifter","links":{"html":"https://skillfed.io/packages/swifter","md":"https://skillfed.io/packages/swifter.md","pypi":"https://pypi.org/project/swifter/"},"maintenance":{"status":"dormant"},"meta":{"latest_release":"2023-07-31","license_spdx":null,"license_treatment":"unclear","name":"swifter","python_support":"unspecified","summary":"A package which efficiently applies any function to a pandas dataframe or series in the fastest available manner"},"popularity":{"monthly_downloads":10262816,"position":1464,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"1.4.0"}