Category Archives: dataviz

Infographics in Python: Plot a Noun Project Icon on a Matplotlib Chart

I had to put an icon on a chart in Python last week, and I couldn’t find a good brief blog about how to do it. Here is what I cobbled together:

1. Find a free, appropriate image from The Noun Project.
2. Load it into Python with plt.imread
3. Draw it in the proper place on a figure with plt.imshow and some cryptic, hacky options.

Looks good, right?
1500

See this all in action here: https://gist.github.com/aflaxman/c171050384471636e8f23f322ba7e9c5

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Visualizing Uncertainty

http://faculty.washington.edu/jhullman/paper_BELIV_evaluating_uncertainty_vis.pdf

http://www.cs.princeton.edu/courses/archive/spr04/cos598B/bib/Harrower.pdf
http://www.ejwagenmakers.com/inpress/HoekstraEtAlPBR.pdf
http://www.smunson.com/portfolio/projects/uncertainty/uncertain-bus-chi2016.pdf

http://www.geovista.psu.edu/publications/MacEachren/MacEachren_Visualizing_98.pdf
http://www.geovista.psu.edu/publications/2012/MacEachren_IEEE_TVCG_PrePub_2012_reduced_res.pdf
http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=6654171

http://www.geovista.psu.edu/publications/2012/MacEachren_IEEE_TVCG_PrePub_2012_reduced_res.pdf

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New words of wisdom from S Few

The Visual Perception of Variation in Data Displays
http://www.perceptualedge.com/articles/visual_business_intelligence/the_visual_perception_of_variation.pdf

(well, it was new when I started this post)

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Big Data Science resources

• The Oregon Health & Science University (OHSU) Department of Medical Informatics & Clinical Epidemiology (DMICE) and Library are pleased to announce the release of open educational resources (OERs) in the area of Biomedical Big Data Science. Funded by a grant from the National Institutes of Health (NIH) Big Data to Knowledge (BD2K) Program, OERs have been produced that can be downloaded, used, and repurposed for a variety of educational audiences by both learners and educators. Development of the OERs is an ongoing process, but they have reached the point where a critical mass of the content is being made available for use and to obtain feedback. The OERs are intended to be flexible and customizable and their use or repurpose is encouraged. They can be used as “out of the box” courses for students or as materials for educators to use in courses, training programs, and other learning activities. The goal is to create 32 module topics. Currently, 20 of the modules are available for download and use. For additional information, contact Bill Hersh at: hersh@ohsu.edu.

Also all on GitHub: https://github.com/OHSUBD2K/

I want to see this one: BDK32 Displaying Confidence and Uncertainty

it doesn’t exist yet, so I have to remember to check back when it does.

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Ideas that did not make it into my recent Data Viz talk

D3js in any substantial way
Steve Few email list, and his example with isotype and patient risk charts
538.com viz stuff

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OHSU BD2K material on data visualization

https://github.com/OHSUBD2K/BDK18-Data-Visualization

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S Few on expressing proportions

Always makes me think: http://www.perceptualedge.com/articles/visual_business_intelligence/expressing_proportions.pdf

Not sure I agree so much with this edition, but I like that he is taking on those goofy unit charts (and I missed the Unit Charts are for Kids essay the first time around http://www.perceptualedge.com/articles/visual_business_intelligence/unit_charts_are_for_kids.pdf )

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