mlsanityData to 14 Oct 2026

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

arXiv 2406.11637 ↗First posted 17 Jun 2024cs.HCcited by 2

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Abstract (arXiv)

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.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). First posted on arXiv 17 Jun 2024.

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Citing papers per year: 2024: 1; 2025: 1.

2 papers.