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

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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Publication Details

Published
2024-10-13
DOI
https://doi.org/10.1109/vis55277.2024.00009
Citations
8
Primary Topic
Video Analysis and Summarization
Type
article
Field-Weighted Citation Impact
1.99
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article

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

Hao Chen, Leixian Shen, Yue Yu, Fei Long et al.
8 citations
Video Analysis and Summarization
1.99
article

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

Hao Chen, Leixian Shen, Yue Yu, Fei Long, Huamin Qu
article en
8 citations

Abstract

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.

Canarie (CA), Hong Kong University of Science and Technology (HK)
Openalex Percentile: Top 12%
Video Analysis and Summarization
1.99
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PyGWalker: On-the-fly Assistant for Exploratory Visual Data Analysis — Hao Chen, Leixian Shen, et al. · (2024) | TGRS Research Map | TGRS