Difference between revisions of "Visualizing process data"

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* [http://learnche.org/pid/data-visualization/index Textbook, chapter 1]
* [http://learnche.org/pid/data-visualization/index Textbook, chapter 1]
* Check your knowledge with these quizzes:
* Check your knowledge with these quizzes:
** [[Media:Viz-quiz-01.pdf|Quiz 1]]  
** [[Media:Viz-quiz-01.pdf|Quiz 1]]  and [[Media:Viz-quiz-01-solution.pdf|Solution 1]]
** [[Media:Viz-quiz-02.pdf|Quiz 2]]
** [[Media:Viz-quiz-02.pdf|Quiz 2]] and [[Media:Viz-quiz-02-solution.pdf|Solution 2]]
** [https://docs.google.com/document/d/1rZXJY7aybeng7H_ZngzHDsbBxn-uipvRPF6r9JdH-9g Quiz 3] and [https://docs.google.com/document/d/1ew6UwKP8SBM19jvdYfMxgSnRVIvUNuwnOSNlJoZ3Tg4 Solution 3]
** [https://docs.google.com/document/d/1rZXJY7aybeng7H_ZngzHDsbBxn-uipvRPF6r9JdH-9g Quiz 3] and [https://docs.google.com/document/d/1ew6UwKP8SBM19jvdYfMxgSnRVIvUNuwnOSNlJoZ3Tg4 Solution 3]
* Complete steps 1, 2 ... 9 of the [http://learnche.mcmaster.ca/4C3/Software_tutorial software tutorial]
* Complete steps 1, 2 ... 9 of the [[Software_tutorial| software tutorial]]


== Extended readings ==
== Extended readings ==
* [http://en.wikipedia.org/wiki/Sankey_diagram 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 [http://bost.ocks.org/mike/sankey/ great example applied to the UK energy supply and demand].
* [http://en.wikipedia.org/wiki/Sankey_diagram 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 [http://bost.ocks.org/mike/sankey/ great example applied to the UK energy supply and demand].
* [http://www.investopedia.com/articles/financial-theory/11/lie-with-financial-statistics.asp How To Lie With Financial Statistics], Investopedia, November 2011
* [http://vita.had.co.nz/papers/boxplots.pdf 40 years of boxplots]  
* [http://vita.had.co.nz/papers/boxplots.pdf 40 years of boxplots]  
* Why you should [http://www.perceptualedge.com/articles/08-21-07.pdf never have to use pie charts], an article by Stephen Few.
* Why you should [http://www.perceptualedge.com/articles/08-21-07.pdf never have to use pie charts], an article by Stephen Few.
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===Videos from 2014===
===Videos from 2014===
{{#widget:Vimeo|id=83723241}}
{{#widget:YouTube|id=ZDGhrLsprkU}}
{{#widget:Vimeo|id=83855005}}
{{#widget:YouTube|id=ervdpbipMjE}}
 


===Videos from 2013===
===Videos from 2013===
{{#widget:Vimeo|id=57084831}}
{{#widget:YouTube|id=FHt6fgwbT_c}}
{{#widget:Vimeo|id=57241437}}
{{#widget:YouTube|id=E7LM9fqY1cI}}


== Software codes for this section ==
== Software codes for this section ==


=== Code to show how to superimpose plots  ===
=== Code to show how to superimpose plots  ===
[http://www.r-fiddle.org/#/fiddle?id=19PyJkpa&version=1 Try this code in a web-browser]
[http://www.r-fiddle.org/#/fiddle?id=19PyJkpa&version=1 Run this code in a web-browser]
 
<html><div data-datacamp-exercise data-lang="r">
<code data-type="sample-code">


<syntaxhighlight lang="rsplus">
# Run this code line-by-line (copy & paste) to understand the demonstration
# Run this code line-by-line (copy & paste) to understand the demonstration
 
f <- 'http://openmv.net/file/raw-material-properties.csv'
data <- read.csv('http://openmv.net/file/raw-material-properties.csv')
data <- read.csv(f)
summary(data)
summary(data)


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# Superimpose them?
# Superimpose them?
plot(data$density1, type='b', col="blue")
plot(data$density1, type='b', col="blue")
lines(data$density2, type='b', col="red")  # where's density2 ?
 
# Where's density2 ?
lines(data$density2, type='b', col="red")   


# Superimpose them: limits
# Superimpose them: limits
plot(data$density1, type='b', col="blue", ylim=c(10, 45))
plot(data$density1,  
lines(data$density2, type='b', col="red") # now density2 shows up
    type='b',  
</syntaxhighlight>
    col="blue",  
    ylim=c(10, 45))
 
# Now density2 shows up
lines(data$density2,  
      type='b',  
      col="red")  
 
</code>
</div></html>

Latest revision as of 19:11, 14 January 2019

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 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")