{"title":"Teaching Data Science by Visualizing Data Table Transformations: Pandas Tutor for Python, Tidy Data Tutor for R, and SQL Tutor","authors":"Sam Lau, Sean Kross, Eugene Wu, Philip J. Guo","doi":"10.1145/3596673.3596972","DOIUrl":null,"url":null,"abstract":"Data science instructors often find it hard to explain to students how a piece of code written in Python, R, or SQL executes in order to transform tabular data. They currently resort to hand-drawing diagrams or making presentation slides to illustrate the semantics of operations such as filtering, sorting, reshaping, pivoting, grouping, and joining. These diagrams are time-consuming to create and do not synchronize with real code or data that students are learning about. In this paper we show that a step-by-step visual representation of tabular data transforms can help instructors to explain these operations. To do so, we created a table visualization library that illustrates the row-, column-, and cell-wise relationships between an operation's input and output tables. On top of this library we built a trio of free web-based visualization tools - Pandas Tutor for Python, Tidy Data Tutor for R tidyverse, and SQL Tutor - that run users' code and automatically produce diagrams of how Python/R/SQL transforms data tables step-by-step from input to output. Since launching in Dec 2021, over 61,000 people from over 160 countries have visited our website to try out these tools.","PeriodicalId":409189,"journal":{"name":"Proceedings of the 2nd International Workshop on Data Systems Education: Bridging education practice with education research","volume":"51 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2nd International Workshop on Data Systems Education: Bridging education practice with education research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3596673.3596972","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Data science instructors often find it hard to explain to students how a piece of code written in Python, R, or SQL executes in order to transform tabular data. They currently resort to hand-drawing diagrams or making presentation slides to illustrate the semantics of operations such as filtering, sorting, reshaping, pivoting, grouping, and joining. These diagrams are time-consuming to create and do not synchronize with real code or data that students are learning about. In this paper we show that a step-by-step visual representation of tabular data transforms can help instructors to explain these operations. To do so, we created a table visualization library that illustrates the row-, column-, and cell-wise relationships between an operation's input and output tables. On top of this library we built a trio of free web-based visualization tools - Pandas Tutor for Python, Tidy Data Tutor for R tidyverse, and SQL Tutor - that run users' code and automatically produce diagrams of how Python/R/SQL transforms data tables step-by-step from input to output. Since launching in Dec 2021, over 61,000 people from over 160 countries have visited our website to try out these tools.
通过可视化数据表转换来教授数据科学:Pandas Python教程,Tidy Data R教程和SQL教程
数据科学教师经常发现很难向学生解释如何执行用Python、R或SQL编写的代码来转换表格数据。他们目前依靠手绘图表或制作演示幻灯片来说明过滤、排序、重塑、旋转、分组和连接等操作的语义。这些图的创建非常耗时,并且不与学生正在学习的实际代码或数据同步。在本文中,我们展示了表格数据转换的逐步可视化表示可以帮助教师解释这些操作。为此,我们创建了一个表可视化库,用于演示操作的输入和输出表之间的行、列和单元关系。在这个库的基础上,我们构建了三个免费的基于web的可视化工具——Pandas for Python、Tidy Data Tutor for R tidyverse和SQL Tutor——它们运行用户的代码,并自动生成图表,显示Python/R/SQL如何一步一步地将数据表从输入转换为输出。自2021年12月推出以来,来自160多个国家的61,000多人访问了我们的网站来试用这些工具。