June Recap: Data Visualiztion

Data visualization is paramount to both understanding and presenting your data, whatever your data may be. For our June Meetup, R-Ladies Philly member Jake Riley led an interactive workshop to elucidate aspects of the popular ggplot2 package and share helpful tips and best practices relevant to any R user.

The 2 g’s in ggplot2 - defined!

Jake explained that the architecture of visualizing data using ggplot2 is based on the grammar of graphics: In ggplot2, just like every sentence has a subject, verb, and noun, every plot has a coordinate system, geom, and aesthetics.

This is demonstrated in the example below using the mpg dataset:

myplot <- 
  ggplot(mpg) + #set the 'subject' or coordinate system
  geom_point(aes(x = cty, y = hwy)) #add the 'verb' or geom used to show the data, and 'nouns' or aesthetics on how the geom should appear

But what exactly does aes() control in plot aesthetics? Jake clarified this by explaining that dynamic, data driven variables go inside the aes(), while constant, static values go outside.

The following two plots show the difference between these aes() arguments:
myplot.v2 <- 
  ggplot(mpg) +
  geom_point(aes(x = cty, y = hwy, color = class)) +
  labs(title = "Setting color inside `aes()`")+
  theme(legend.position = "bottom")

myplot.v3 <- 
  ggplot(mpg) +
  geom_point(aes(x = cty, y = hwy), color = "blue") +
  labs(title = "Setting color outside `aes()`")

  ncol = 2

Helpful tips, and best practices for plotting

Jake shared some tips for plotting, including:

  • ordering barplots in descending (or ascending) order
  • using facet_grid() and facet_wrap()
  • controlling color and size more precisely using scale_*_identity()

To make your plot as visually appealing as possible, Jake additionally recommended:

  • approximating the golden ratio (1:1.6) for plot dimensions
  • using color to highlight the most important plot features
  • choosing a color palette amenable to colorblindness

Extensions and Addins

As a final activity, we explored ggplot extensions and ggplot addins and shared examples of our findings with the group

Alice shared how she added pikachu to her plot using cowplot

Check it Out

The slides and code from Jake’s workshop are available on his github!


We would like to thank WeWork for hosting us!

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This post was authored by Katerina Placek For more information contact philly@rladies.org