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Matplotlib 2.x By Example

You're reading from  Matplotlib 2.x By Example

Product type Book
Published in Aug 2017
Publisher Packt
ISBN-13 9781788295260
Pages 334 pages
Edition 1st Edition
Languages
Authors (3):
Allen Yu Allen Yu
Profile icon Allen Yu
Claire Chung Claire Chung
Profile icon Claire Chung
Aldrin Yim Aldrin Yim
Profile icon Aldrin Yim
View More author details

Visualizing population health information


The following section will be dedicated to combining both geographical and population health information of the US. Since this is a tutorial on Python, we focus more on ways to visualize the data, rather than to draw solid conclusions from it. However, many of the findings below actually concur with the population health research and news reports that one may find online.

To begin, let us first download the following information:

  • Top 10 leading causes of death in the United States from 1999 to 2013 from Healthdata.gov
  • 2016 TIGER GeoDatabase from US Census Bureau
  • Survival data of various type of cancers from The Cancer Genome Atlas (TCGA) project (https://cancergenome.nih.gov/)

Since some of the information does not allow direct download through links, we have included the raw data in our code repository:

  • Top 10 leading causes of death in the United States from 1999-2013: https://www.healthdata.gov/dataset/nchs-age-adjusted-death-rates-top-10-leading-causes...
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