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DATA VISUALIZATION TOOLS
November 17th, 2017
Teaching Assistant: Anum Masood
SEIEE
Data can help in telling a great story, but data alone will never tell the whole story.
Example of Visualizing Data
• Following graph shows various combinations of usage and CPU for each category
– acceptable – problematic – low value – unacceptable
Question #1
How do UNC-curated titles scatter across these categories across TRLN?
Question #2
How do all the titles in the collection scatter across these categories for TRLN?
Pies Question: • How do all the titles in the
collection scatter across these categories for TRLN?
Issues: • Everything is treated as a
proportion • Values only available via labels • Hard to compare areas/angles • Gets confusing past 4-5 categories
Stephen Few on Pie Charts: Save the Pies for Dessert
817, 66%
159, 13%
113, 9%
95, 8%
55, 4%
Value of All TRLN Titles to TRLN
Good
Acceptable
Problematic
Low
Unacceptable
The World’s Most Accurate Pie Chart
http://visual.ly/literal-pie-chart
Idea: Accuracy and Human Perception
• We can use these rankings to assess whether a given graphical form is more or less effective than another at communicating accurately perceived values to the reader.
• However, context and audience as judged by the designer, can overrule these rankings.
• Maximizing visual accuracy doesn’t have to be your primary goal.
Mackinlay, J. (1986) Automating the design of graphical presentations of relational information.ACM Trans. Graph. 5, 2 (April)
Pie Alternatives
Quality Titles Percentage
Good 817 65.9%
Acceptable 159 12.8%
Problematic 113 9.1%
Low 95 7.7% Unacceptable 55 4.4%
817
159 113 95
55
0
100
200
300
400
500
600
700
800
900Value of UNC-UNL curated titles to TRLN
Question #3
How did the titles scatter across these benchmarks in 2010 vs. 2014?
0
200
400
600
800
1000
1200
1400
1600
Good Acceptable Problematic Low Unacceptable
2010 vs. 2014 Benchmark Distribution
2010 # of titles 2014 # of titles
Stacked Charts Question: • How did the titles scatter across
these benchmarks in 2010 vs. 2014?
Issues: • What does the overall height
mean? • How many titles were
unacceptable in 2014? • Visual Math
Before:
0
200
400
600
800
1000
1200
1400
1600
Good Acceptable Problematic Low Unacceptable
2010 vs. 2014 Benchmark Distribution
2010 # of titles 2014 # of titles
Alternatives:
• Height always encodes single year
• Slope of each line emphasizes different rates of change
0
100
200
300
400
500
600
700
800
900
Good Acceptable Problematic Low Unacceptable
2010 vs. 2014 Benchmark Distribution
2010 # of titles 2014 # of titles
0
100
200
300
400
500
600
700
800
900
2010 # of titles 2014 # of titles
2010 vs. 2014 Benchmark Distribution
Good Acceptable Problematic
Low Unacceptable
Question #4
How many e-books were used year over year?
Question #5
How does the ratio of books used vs available change over time?
Backgrounds Question: • How does the ratio of books used
vs available change over time? Issues: • Hard to read values on dots • Data doesn’t contrast highly with
background
39%
22%
29%
38% 37%
2010 2011 2012 2013 2014
Ratio of Books Used/Available, 2010-2014
Data-Ink (Edward Tufte)
Maximize (within reason): 𝐼𝐼𝐼𝐼𝐼𝐼 𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢 𝑡𝑡𝑡𝑡 𝑢𝑢𝐼𝐼𝑒𝑒𝑡𝑡𝑢𝑢𝑢𝑢 𝑢𝑢𝑑𝑑𝑡𝑡𝑑𝑑 𝑣𝑣𝑑𝑑𝑣𝑣𝑢𝑢𝑢𝑢𝑢𝑢
𝑇𝑇𝑡𝑡𝑡𝑡𝑑𝑑𝑣𝑣 𝑖𝑖𝐼𝐼𝐼𝐼 𝑖𝑖𝐼𝐼 𝑣𝑣𝑖𝑖𝑢𝑢𝑢𝑢𝑑𝑑𝑣𝑣𝑖𝑖𝑣𝑣𝑑𝑑𝑡𝑡𝑖𝑖𝑡𝑡𝐼𝐼
39%
22%
29%
38% 37%
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
2010 2011 2012 2013 2014
Ratio of Books Used/Available, 2010-2014
39%
22%
29%
38% 37%
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
2010 2011 2012 2013 2014
Ratio of Books Used/Available, 2010-2014
39%
22%
29%
38% 37%
2010 2011 2012 2013 2014
Ratio of Books Used/Available, 2010-2014
TOOL LANDSCAPE
• Spreadsheets • In-browser tools • Business Intelligence
Tools • Coding • Design
Spreadsheets e.g. Microsoft Excel, LibreOffice, Open Office • Pros:
• You probably already have it • Your data probably passes
through it already • Secure • Already integrated in workflows
• Cons: • Software not primarily designed
for visualization • Static and local
In-Browser General: Plot.ly, Datawrapper, Raw, Timeline.js Mapping: ArcGIS Online, CartoDB • Pros:
• Often easiest, most accessible, quickest
• Often free or cheap • Many tools available • Specialized tools like ArcGIS Online
• Cons: • Most subject to change (or
disappearance) • Inflexibility
• Specialized functionality • Strict data format needs • Dependence on other software
• Too many options • Full benefits require a more
advanced tool • ArcMap • QGIS
Plot.ly
ArcGIS Online
Business Intelligence e.g. Tableau, Qlik, SAS Visual Analytics • Pros:
• Flexible, but don’t require much if any coding
• Point and click interfaces • Good support/frequent updates • Some free public options
• Cons: • Most expensive
• IT support for large implementations
• Business-oriented user communities
https://public.tableau.com/s/gallery/fatal-drug-overdose-rates-united-states
Tableau
Coding e.g. JavaScript(D3.js), R(ggplot2), Python • Pros:
• Generally Free • If you have the time to learn it
• Most flexible and powerful
• Cons: • Multiple languages necessary • Need to hire developer(s) • Time-intensive
http://bl.ocks.org/mbostock/4060954
D3.js
Design e.g. Adobe Creative Suite, Inkscape • Pros:
• Most aesthetically oriented • Can be combined with other
tools
• Cons: • Expensive • Not data-oriented
• ‘Infographic effect’
• Static
http://icharts.net/blogs/2013/spotlight-interview-unique-approach-infographics-journalism-alberto-cairo
Adobe Illustrator
Learn more: Theory Practice
Edward Tufte: The Visual Display of
Quantitative Information (2001)
Visual Explanations (1997) Envisioning Information
(1990) Colin Ware: Information Visualization:
Perception for Design (2004)
Stephen Few: Show Me the Numbers (2004) Information Dashboard
Design (2006) Now You See It (2009) Alberto Cairo: The Functional Art (2012)
Learn more: Tools
• Tool lists: – http://dirtdirectory.org/ – http://selection.datavisualiz
ation.ch/ • Map Galleries
– CartoDB: https://cartodb.com/gallery/ – ArcGIS Online: http://www.arcgis.com/home/gallery.html#c=esri&t=maps&o=avgrating
• Sample Galleries – D3: https://github.com/mbostock/d3/wiki/Gallery – Tableau: https://public.tableau.com/s/gallery – Plot.ly https://plot.ly/feed/