Computational notebooks are a popular tool for data analysis. However, the 1D linear structure used by many computational notebooks can lead to challenges and pain points in data analysis, including messiness, tedious navigation, inefficient use of screen space, and presentation of non-linear narratives. To address these problems, we designed a prototype Jupyter Notebooks extension called 2D Jupyter that enables a 2D organization of code cells in a multi-column layout, as well as freeform cell placement. We conducted a user study using this extension to evaluate the usability of 2D computational notebooks and understand the advantages and disadvantages that it provides over a 1D layout. As a result of this study, we found evidence that the 2D layout provides enhanced usability and efficiency in computational notebooks. Additionally, we gathered feedback on the design of the prototype that can be used to inform future work. Overall, 2D Jupyter was positively received and users not only enjoyed using the extension, but also expressed a desire to use 2D notebook environments in the future. / Master of Science / Computational notebooks are a tool commonly used by data analysts that allows them to construct computational narratives through a combination of code, text and visualizations. Many computational notebooks use a 1D linear layout; however data analysis work is often conducted in a non-linear fashion due to the need to debug code, test new theories, and evaluate and compare results. In this work, we present a prototype extension for Jupyter Notebooks called 2D Jupyter that enables the user to arrange their notebook in a 2D multi-column layout. A user study was conducted to evaluate the usability of this extension and understand the benefits that a 2D layout may provide. Feedback on the extension's design was also collected to inform future design opportunities. The prototype received a positive reaction overall and users expressed a desire to use 2D computational notebooks in their future work.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/115412 |
| Date | 12 June 2023 |
| Creators | Christman, Elizabeth |
| Contributors | Computer Science and Applications, North, Christopher L., Gulzar, Muhammad Ali, Belcaid, Mahdi |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | ETD, application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
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