Souti Chattopadhyay: What's Wrong with Computational Notebooks? Pain Points, Needs, and Design Opportunities
タイトル
著者
ソース
Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems
ページ
1-12
年
2020
月
Volume
Number
概要
Computational notebooks - such as Azure, Databricks, and Jupyter - are a popular, interactive paradigm for data scientists to author code, analyze data, and interleave visualizations, all within a single document. Nevertheless, as data scientists incorporate more of their activities into notebooks, they encounter unexpected difficulties, or pain points, that impact their productivity and disrupt their workflow. Through a systematic, mixed-methods study using semi-structured interviews (n=20) and survey (n=156) with data scientists, we catalog nine pain points when working with notebooks. Our findings suggest that data scientists face numerous pain points throughout the entire workflow - from setting up notebooks to deploying to production - across many notebook environments. Our data scientists report essential notebook requirements, such as supporting data exploration and visualization. The results of our study inform and inspire the design of computational notebooks. コメント
増井俊之.icon
タマタマ現状のJupyterその他の辛い部分に文句を言ってるだけに聞こえるが
データ読み込みが面倒、とかどんなシステムでも同じだろう
https://gyazo.com/51c5d8b25b5db796582ed0bee904a076
URL
ISBN
9781450367080
DOI