Interactive data visualization in Jupyter notebooks

Jorge Piazentin Ono; Juliana Freire; Claudio T. Silva

doi:10.1109/MCSE.2021.3052619

Interactive data visualization in Jupyter notebooks

Jorge Piazentin Ono, Juliana Freire, Claudio T. Silva

Urban Initiative

Research output: Contribution to journal › Article › peer-review

Abstract

Interactive visualizations are at the core of the exploratory data analysis process, enabling users to directly manipulate and gain insights from data. In this article, we present three different ways in which interactive visualizations can be included in Jupyter Notebooks: 1) matplotlib callbacks; 2) visualization toolkits; and 3) embedding HTML visualizations. We hope that this article will help developers to select the best tools to build their interactive charts in Jupyter Notebooks.

Original language	English (US)
Article number	9391750
Pages (from-to)	99-106
Number of pages	8
Journal	Computing in Science and Engineering
Volume	23
Issue number	2
DOIs	https://doi.org/10.1109/MCSE.2021.3052619
State	Published - Mar 1 2021

ASJC Scopus subject areas

General Computer Science
General Engineering

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10.1109/MCSE.2021.3052619

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Interactive data visualization in Jupyter notebooks

Abstract

ASJC Scopus subject areas

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