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New dataset captures real-world Pandas workflows from 139k notebooks

By PulseAugur Editorial · [1 sources] ·

Researchers have introduced PandasCorpus, a new dataset designed to systematically investigate real-world Pandas workflows and usage patterns. This dataset, extracted from GitHub repositories, contains 139,000 Jupyter notebooks and captures over 4 million Pandas API calls. The study analyzes code executability, notebook size, and common sequences of Pandas operations, offering empirical insights into how the library is utilized in practice. PandasCorpus is intended as a reusable resource for studying data analysis workflows and library-aware code composition. AI

IMPACT Provides a resource for studying data analysis workflows and library-aware code composition.

RANK_REASON The cluster contains an academic paper describing a new dataset. [lever_c_demoted from research: ic=1 ai=0.4]

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New dataset captures real-world Pandas workflows from 139k notebooks

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The cluster contains an academic paper describing a new dataset. [lever_c_demoted from research: ic=1 ai=0.4]
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COVERAGE [1]

  1. arXiv cs.LG TIER_1 English(EN) · Syrym Abdikhan, Mazhar Hameed ·

    PandasCorpus: A Resource of Real-World Pandas Workflows and Usage Patterns

    arXiv:2608.14742v1 Announce Type: cross Abstract: Pandas has emerged as the de facto library for data processing and machine learning, widely used for tasks, such as data loading, transformation, and analysis. Despite its ubiquity, there has been limited systematic investigation …

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