Introduction to data An Andr drew Heiss, PhD Brigham Young - - PowerPoint PPT Presentation

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Introduction to data An Andr drew Heiss, PhD Brigham Young - - PowerPoint PPT Presentation

Jan 29, 2023 240 likes •740 views

Introduction to data An Andr drew Heiss, PhD Brigham Young University visualization with R SLC RUG July 11, 2018 @andrewheiss Plan for today Why visualize data? Types of visualizations Aesthetics and design ! Take a sad plot and make

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Introduction to data visualization with R

An Andr drew Heiss, PhD

Brigham Young University SLC RUG • July 11, 2018 @andrewheiss

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Why visualize data?

Plan for today

Aesthetics and design Types of visualizations

! Take a sad plot and make it CRAPier !

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talks.andrewheiss.com/utah-rug-dataviz/

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Why visualize data?

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Data alone cannot tell stories or prove theories

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Never trust summary statistics alone

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Humans are visual creatures

@FacesPics

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What makes a good visualization?

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Characteristics of graphical excellence

  • 1. “... the well-designed presentation of interesting

data—a matter of substance, statistics, and design.”

  • 2. Complex ideas communicated with

clarity, precision, and efficiency.

  • 3. That which gives the viewer the greatest

number of ideas in the shortest time with the least ink in the smallest space.

  • 4. Nearly always multivariate.
  • 5. Requires telling the truth about the data.
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What makes Minard’s graph so great?

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We forget this!

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Types of visualizations

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Exploratory visualizations

Academic-ish Quick scatterplots, histograms, other charts to help understand your data

Explanatory visualizations

Publishable Consumable by the general public; Vox, NYT, Washington Post, FiveThirtyEight, etc.

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Exploratory data analysis

Find analytical insight in data (even causal inference ! )

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Explanatory data analysis

Annotate and tell a story

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Exploratory Explanatory

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Which chart type do I use?

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Aesthetics and design

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Is he maybe a little right?

plot(mtcars$wt, mtcars$mpg)

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R can’t do everything

There’s still a place for Illustrator, InDesign, et al.

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But R can do a lot

And it can automate most of the hard work

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What constitutes good design?

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Four core design principles

Co Contrast Re Repetition Al Alignmen ent Pr Proximity

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Contrast

“If f two it items are not exactly ly th the same, , make th them diffe

  • ifferent. Really different.”

.”

Don’t be a wimp!

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Serif Sans Serif Slab Serif Script Decorative Lorem ipsum dolor sit amet Lo Lorem ipsum um do dolor sit am amet

Lorem ipsum dolor sit amet

Lo Lorem ip ipsu sum do dolor sit am amet

Lo Lorem ip ipsum do dolor sit am amet Light Lorem ipsum dolor sit amet Black Lorem ipsum dolor sit amet

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https://color.adobe.com/ http://colorbrewer2.org/ viridis Scientific Colour-Maps https://github.com/thomasp85/scico

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Repetition

“R “Repeat at some as aspect

  • f

f the desig ign throughout the entir ire pie iece.”

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Alignment

“Every it item should ld have a vis isual l connectio ion wit ith somethin ing els lse on the page.”

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Proximity

“Group rela lated it items together.”

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Contrast Repetition Alignment Proximity

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! Take a sad plot and make it CRAPier !

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By default, R graphics violate CRAP

plot(mtcars$wt, mtcars$mpg, main = "Here's a title") ggplot(mtcars, aes(x = wt, y = mpg)) + geom_point() + labs(title = "Here's a title")

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With ggplot’s theme() and other functions, we can make beautiful CRAPy figures automatically with R talks.andrewheiss.com/utah-rug-dataviz/

You can also do this in base R, but I find ggplot’s paradigm more intuitive

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Moral of the story

Graphics are essential for telling stories and gaining insight Design principles (CRAP) make graphics better understandable R + ggplot can follow CRAP and make beautiful, insightful graphics