Visualizing process data

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Learning outcomes

  • Understand when it is appropriate to use scatter plots, bar plots, pie charts (hint: almost never), and even tables.
  • Learn an interesting, potentially new plot: the box plot, to summarize and compare data.
  • How to effectively visualize up to 5 dimensions on a 2-D plot, as shown in a video by Hans Rosling.
  • Know the meaning of words like sparklines, data density, and chart junk.

Resources

Extended readings

Class videos from prior years

Videos from 2015

07:31 | Download video | Download captions | Script
03:16 | Download video | Download captions | Script
04:51 | Download video | Download captions | Script
07:23 | Download video | Download captions | Script

Videos from 2014

Videos from 2013

Software codes for this section

Code to show how to superimpose plots

Run this code in a web-browser

# Run this code line-by-line (copy & paste) to understand the demonstration
 
data <- read.csv('http://openmv.net/file/raw-material-properties.csv')
summary(data)
 
# Single plot
plot(data$density1)
 
# Connect the dots
plot(data$density1, type='b')
 
# Another variable
plot(data$density2, type='b', col="red")
 
# Superimpose them?
plot(data$density1, type='b', col="blue")
lines(data$density2, type='b', col="red")  # where's density2 ?
 
# Superimpose them: limits
plot(data$density1, type='b', col="blue", ylim=c(10, 45))
lines(data$density2, type='b', col="red")  # now density2 shows up