Making Data Pretty (and understandable)

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Michele Bannister @astrokiwi NRC-Herzberg Astronomy / University of Victoria, BC Making Data Pretty (and understandable)

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colour palettes what sort of data do you have? chart junk cleaning up plots packages that can make life easier

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colour palettes sequential diverging qualitative learn more: Cynthia Brewer’s colorbrewer http://colorbrewer2.org/ Try your plots in diﬀerent perception spaces http://www.vischeck.com/

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palettable by Matt Davis jiﬀyclub.github.io/palettable/ pip install palettable > from palettable.colorbrewer.qualitative import Dark2_7

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http://www.research.ibm.com/people/l/lloydt/color/color.HTM work with the colour response of human eyes

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work with the colour response of human eyes h"ps://mycarta.wordpress.com/2012/10/06/the-‐rainbow-‐is-‐deadlong-‐live-‐the-‐rainbow-‐part-‐3/

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matplotlib http://matplotlib.org/users/colormaps.html Defaults are there because something has to be there -ﬂowingdata.com

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matplotlib http://matplotlib.org/users/colormaps.html jet viridis @astrofrog

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chart junk “routinely added graphical paraphernalia” - E. Tufte detail impeding understanding

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https://stanford.edu/~mwaskom/ software/seaborn/tutorial/aesthetics.html

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heliocentric distance (AU) 0 10 20 30 40 50 inclination (degrees) 0 10 20 30 40 50 inclination (degrees) 1:1 2:1 3:2 5:2 7:3 7:4 5:3 11:4 8:5 15:8 13:5 25 30 35 40 45 50 55 60 65 70 75 80 85 semimajor axis (AU) 0.0 0.1 0.2 0.3 0.4 0.5 0.6 eccentricity 1:1 2:1 3:2 5:2 7:3 7:4 5:3 11:4 8:5 15:8 13:5 classical resonant scattering detached o3e45

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0 5 10 15 20 25 30 35 40 inclination (degrees) 38 39 40 41 42 43 44 45 46 47 48 49 semimajor axis (AU) 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 eccentricity 2:1 3:2 7:4 centaur classical resonant scattering detached

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packages for pleasing plots palettable seaborn (has superseded prettyplotlib) for web approaches: d3.js bokeh plotly https://plot.ly/python/#scientiﬁc-charts (mpld3 no longer under active development)

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The greatest value of a picture plot is when it forces us to notice what we never expected to see. J. Tukey, Exploratory Data Analysis, 1977