DS Lab Notebook: A new tool for data science applications

Abstract

The main focus of the technical application of this research relies on a web and mobile-based solution identified as Data Science Notebook named as DS Lab Notebook. Specifically, the main focus will be on tackling already present challenges in data science education and a solution presented around DS Lab, an interactive computational notebook. The core ideas are represented by the concept of extending the traditional computing notebooks, especially from the Jupyter family, with live visualizations, debugging, widgets, and interactivity during the educational process across all the major platforms: web, Android, and IOS. The features are outlined in several use cases that can be useful in the data-science teaching process, with a primary focus in matrix manipulations, scatter plots, and image filters. Python 3 was used as the main programming runtime and the back-end for providing access to variable values and type information is being described in the form of a runtime-independent pipeline relying on code parsing and injection.