Lux: Always-on Visualization Recommendations for Exploratory Data Science
Lux: Always-on Visualization Recommendations for Exploratory Data Science
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2021
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通讯作者：
D. Lee;Dixin Tang;Kunal Agarwal;Thyne Boonmark;Caitlyn Chen;J. Kang;U. Mukhopadhyay;Jerry Song;Micah Yong;Marti A. Hearst;Aditya G. Parameswaran
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作者：
D. Lee;Dixin Tang;Kunal Agarwal;Thyne Boonmark;Caitlyn Chen;J. Kang;U. Mukhopadhyay;Jerry Song;Micah Yong;Marti A. Hearst;Aditya G. Parameswaran
探索性数据科学在很大程度上发生在带有数据框架API（例如熊猫）的计算笔记本中，这些数据框架支持灵活的方法可以转换，清洁和分析数据。但是，在视觉范围内探索数据范围中的数据仍然很乏味，需要大量的编程工作来可视化和心理努力，以确定下一步要执行的分析。我们提出了Lux，这是一个始终在数据科学工作流程中的视觉见解发现的框架。当用户在笔记本中打印数据框时，Lux建议可视化量以简化模式和趋势概述，并建议有希望的分析方向。 LUX具有一种高级语言，可在按需生成可视化，以鼓励使用数据快速进行视觉实验。我们证明，通过使用仔细的设计和三个系统优化，Lux在UCI存储库中的98％的数据集中在Pandas的顶部增加了不超过两秒钟的开销。我们通过对可用性的可用性评估Lux，并通过对早期采用者的访谈来评估Lux有助于满足数据框架工作范围内可视化支持的需求。 Lux已经被数据科学从业人员所接受，在最初的15个月内，Github在Github上拥有超过1.9k的明星。
Exploratory data science largely happens in computational note-books with dataframe API, such as pandas , that support flexible means to transform, clean, and analyze data. Yet, visually exploring data in dataframes remains tedious, requiring substantial programming effort for visualization and mental effort to determine what analysis to perform next. We propose Lux, an always-on framework for accelerating visual insight discovery in data science workflows. When users print a dataframe in their notebooks, Lux recommends visualizations to provide a quick overview of the patterns and trends and suggests promising analysis directions. Lux features a high-level language for generating visualizations on-demand to encourage rapid visual experimentation with data. We demonstrate that through the use of a careful design and three system optimizations, Lux adds no more than two seconds of overhead on top of pandas for over 98% of datasets in the UCI repository. We evaluate Lux in terms of usability via a controlled first-use study and interviews with early adopters, finding that Lux helps fulfill the needs of data scientists for visualization support within their dataframe work-flows. Lux has already been embraced by data science practitioners, with over 1.9k stars on Github within its first 15 months.