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PyGWalker: On-the-fly Assistant for Exploratory Visual Data Analysis

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arxiv 2406.11637 v1 pith:K5634EAK submitted 2024-06-17 cs.HC

classification cs.HC
keywords dataanalysisexploratoryvisualpygwalkercomputationalon-the-flyaccommodate
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Exploratory visual data analysis tools empower data analysts to efficiently and intuitively explore data insights throughout the entire analysis cycle. However, the gap between common programmatic analysis (e.g., within computational notebooks) and exploratory visual analysis leads to a disjointed and inefficient data analysis experience. To bridge this gap, we developed PyGWalker, a Python library that offers on-the-fly assistance for exploratory visual data analysis. It features a lightweight and intuitive GUI with a shelf builder modality. Its loosely coupled architecture supports multiple computational environments to accommodate varying data sizes. Since its release in February 2023, PyGWalker has gained much attention, with 612k downloads on PyPI and over 10.5k stars on GitHub as of June 2024. This demonstrates its value to the data science and visualization community, with researchers and developers integrating it into their own applications and studies.

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  1. DataLab: A Unified Platform for LLM-Powered Business Intelligence

    cs.DB 2024-12 conditional novelty 6.0 of 10

    DataLab is a unified notebook-based platform for LLM-powered BI tasks that shows strong efficiency gains and competitive accuracy, but its state-of-the-art claim is not supported on several benchmarks.

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