Code Code Evolution: Understanding How People Change Data Science Notebooks Over Time-Reference-Cited by-同舟云学术

Code Code Evolution: Understanding How People Change Data Science Notebooks Over Time

Published:2023-04-19 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems
language:
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Author:

Raghunandan Deepthi¹^ORCID,Roy Aayushi¹^ORCID,Shi Shenzhi¹^ORCID,Elmqvist Niklas²^ORCID,Battle Leilani³^ORCID

Affiliation:

1. Department of Computer Science, University of Maryland, United States and Department of Computer Science, University of Maryland, United States

2. College of Information Studies, University of Maryland, United States and College of Information Studies, University of Maryland, United States

3. Paul G. Allen School of Computer Science & Engineering, University of Washington, United States and Paul G. Allen School of Computer Science & Engineering, University of Washington, United States

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3544548.3580997

Reference46 articles.

1. Futzing and Moseying: Interviews with Professional Data Analysts on Exploration Practices

2. Regression to the mean: what it is and how to deal with it

3. Characterizing Exploratory Visual Analysis: A Literature Review and Evaluation of Analytic Provenance in Tableau

4. What's Wrong with Computational Notebooks? Pain Points, Needs, and Design Opportunities

5. Splitting, Renaming, Removing: A Study of Common Cleaning Activities in Jupyter Notebooks

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