1. Data Visualization

2. Overview Why use visualization? Types of visualizations.
Design guidelines.
Infographics.
Tableau example.
Visualize This
Much of this is drawn from materials at the Duke University Library Data Visualization site:

3. Why not Statistics?
Consider the following four sets of 11 (x,y) coordinates: 1 2 3 4 x y 10
8.04 8
6.95 13
7.58 9
8.81 11
8.33 14
9.96 6
7.24 4
4.26 12
10.84 7
4.82 5
5.68 x y 10
9.14 8
8.14 13
8.74 9
8.77 11
9.26 14
8.1 6
6.13 4
3.1 12
9.13 7
7.26 5
4.74 x y 10
7.46 8
6.77 13
12.74 9
7.11 11
7.81 14
8.84 6
6.08 4
5.39 12
8.15 7
6.42 5
5.73 x y 8
6.58
5.76
7.71
8.84
8.47
7.04
5.25 19
12.5
5.56
7.91
6.89
Are they similar?

4. Summary Statistics 1 2 3 4 Statistically, they seem pretty similar…x y 10
8.04 8
6.95 13
7.58 9
8.81 11
8.33 14
9.96 6
7.24 4
4.26 12
10.84 7
4.82 5
5.68 x y 10
9.14 8
8.14 13
8.74 9
8.77 11
9.26 14
8.1 6
6.13 4
3.1 12
9.13 7
7.26 5
4.74 x y 10
7.46 8
6.77 13
12.74 9
7.11 11
7.81 14
8.84 6
6.08 4
5.39 12
8.15 7
6.42 5
5.73 x y 8
6.58
5.76
7.71
8.84
8.47
7.04
5.25 19
12.5
5.56
7.91
6.89
Mean:
Variance:
Correlation:
Linear regression line = X for all 4!
Statistically, they seem pretty similar…

5. Similar? 1 2 x y 10
7.46 8
6.77 13
12.74 9
7.11 11
7.81 14
8.84 6
6.08 4
5.39 12
8.15 7
6.42 5
5.73 x y 8
6.58
5.76
7.71
8.84
8.47
7.04
5.25 19
12.5
5.56
7.91
6.89 3 4

6. Why Visualization? To discover new things about your data.
The most effective way for humans to understand complex data (and large amounts of data) is visually!
To tell a story using data.
To provoke and answer questions.
To facilitate analysis.
To better communicate.
Visualization leverages human visual capabilities for data analysis.

7. Stages Identify the topic of interest and relevant questions.
Obtain useful and relevant data.
Explore the data to identify interesting relationships:
Look for trends, patterns and differences across categories, space and time.
Represent the data (maps, charts, etc.).
Refine the presentation with your audience in mind.
Provide tools to manipulate or interact with the data.

8. Visualizing Wind
Live:

9. Design
Design is not just what it looks like and feels like. Design is how it works.
Steve Jobs, 2003
Clarity
Aesthetics
Confusing
Ugly
Beautiful
Clear ?
Yes No ?

10. Visualization Design Guidelines
The visualization must have a purpose!
All elements should work together to achieve the purpose.
What questions can or does it answer?
What questions should it answer?
Be simple and succinct.
Show the main points – do not make the audience try to figure it out.
Do not present too much information! (Limit a dashboard to 2-4 elements/views).
Any interactivity should be obvious to the viewer.

11. Visualization Design Guidelines
Many visualizations combine several elements (views, charts, etc.) in a “dashboard”.
Place the most important view at the top, or top left.
Be sure the legends are associated with the correct view.
Position legends to the right of the view, if possible.
If elements are linked interactively, arrange them top to bottom and left to right, with the linking and filtering starting at the top.

12. Choosing a Good Chart

13. Color Vary the saturation level (lightness), not the hue (color).
Consider that your visualization may be printed in black and white.

14. 100 Points What do you see here?
Most points are blue, one is red and four are green.
The points are spread out “evenly” over the space.
What do you see here?
Differences are more difficult to distinguish with symbols alone.

15. 100 Points Again… What do you see here?
Most points are blue, one is red and some are green.
Some are squares, but most are dots; one is a +.
The points are spread out “evenly” over the space.
You may not appreciate that one point is very unusual point - both an uncommon color and an uncommon shape (the green square)
Combining color and shape does not work well!

16. Fonts Use only a few fonts: Verdana or Trebuchet for numbers.
Arial, Georgia, Tahoma, Times New Roman, Lucida Sans.
Use a few appropriate font sizes.
Change adjacent fonts by only one attribute (bold or underline, not both):
A good change A Bad change

17. Infographics
A common type of visualization specific to a particular context.
Usually created for a single dataset for a particular purpose.
Not designed for the user to explore the data.
Most view infographics as a type of visualization; but some see it the opposite way.

18. Infographic 1

19. Infographic 2

20. Infographic 3

21. Summary Use the real estate wisely.
Show the main points – do not make the audience try to figure it out.
Do not present too much information!
Do the squint test:
What stands out? What do you see?
Show it to someone else and ask what they see.
Include the source of the data.

22. Basic Information A great site for visualization basics.
A great site for Tableau information.
More design guidance…

23. Baby Names in Tableau
Consider the top baby name in each US state for each year…
What to call on 4th down?

24. Data for Baby Names in Tableau
AK,F,1910,Mary,14
AK,F,1910,Annie,12
AK,F,1910,Anna,10
AK,F,1910,Margaret,8
AK,F,1910,Helen,7
AK,F,1910,Elsie,6
AK,F,1910,Lucy,6
AK,F,1910,Dorothy,5
AK,F,1911,Mary,12
AK,F,1911,Margaret,7
AK,F,1911,Ruth,7
AK,F,1911,Annie,6
AK,F,1911,Elizabeth,6
AK,F,1911,Helen,6
AK,F,1912,Mary,9
AK,F,1912,Elsie,8
AK,F,1912,Agnes,7
AK,F,1912,Anna,7
AK,F,1912,Helen,7
AK,F,1912,Louise,7
AK,F,1912,Jean,6
AK,F,1912,Ruth,6
AK,F,1912,Alice,5
AK,F,1912,Esther,5
Original Data:
Every baby name used >5 times, by state and by year since 1910.
State, Gender, Year, Name, # of occurrences
From this, extract the top male and female name for each state for each year.

25. Tableau Dashboard
Number of different top male (blue) and female (pink) names in the 50 states since 1910
YEAR
Top name in each state for chosen year
Gender
Frequency of name (for top names)
Trend of name as the top name in states over time