• Journal: Towards data science
  • Date: Aug. 19, 2018
  • Category: Visualization & Software


Ross Burton, a biomedical scientist and technology enthusiast, wrote an article on Medium about creating interactive plots of Project Tycho measles data using Python and Bokeh. He also made a video of the visualization tool and posted his code on Github.


Ross Burton

Related Project Tycho Datasets

United States of America - Measles


In the United States, in the year 1912, Measles became a nationally notifiable disease. As a result, all U.S. healthcare providers and laboratories had to report diagnosed cases to the federal government. Today I’m going to be looking at measles data collected in the United States from 1928 to 2002. This is made available from Project Tycho, a project which aims to advance the availability of large scale public health data to the worldwide community of researchers, data scientists, students, and general public. The data originates from the weekly National Notifiable Disease Surveillance System reports and includes standardised counts at the state level and incidence rates per 100,000 people based on historical population estimates.

The purpose of this project was to explore different methods of data visualisation and the capabilities of BokehJS. I am overwhelmed with the results from BokehJS and I would highly recommend exploring this package. BokehJS provides a powerful Python API that allows you to create interactive plots in the style of D3.js. I learnt about BokehJS mostly from the documentation and the great tutorials that they provide on their website.

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