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
- Class notes 2015
- Class notes 2014
- Textbook, chapter 1
- Check your knowledge with these quizzes:
- Quiz 1 and Solution 1
- Quiz 2 and Solution 2
- Quiz 3 and Solution 3
- Complete steps 1, 2 ... 9 of the software tutorial
Extended readings
- Sankey diagrams for example, would make a great way to show energy utilization in your company, or even a mass balance superimposed on a flowsheet. Here's a great example applied to the UK energy supply and demand.
- 40 years of boxplots
- Why you should never have to use pie charts, an article by Stephen Few.
- This is one video you must watch for the course: Hans Rosling shows an incredible data visualization
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
f <- 'http://openmv.net/file/raw-material-properties.csv'
data <- read.csv(f)
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")
# Where's density2 ?
lines(data$density2, type='b', col="red")
# Superimpose them: limits
plot(data$density1,
type='b',
col="blue",
ylim=c(10, 45))
# Now density2 shows up
lines(data$density2,
type='b',
col="red")