1. STAT 4030 – Jennifer Priestley, Ph.D. Programming in R
Data Visualization Tips
Kennesaw State University
Presentation by Jennifer Hunter 1

2. Data Visualization Tips - Introduction2 2 2

3. Data Visualization Tips - Storytelling3 3 3

4. Data Visualization Tips
Storytelling with Data
By Cole Knaflic
The top selling book on data visualization from Amazon in November of 2017
Ms. Knaflic has a BS in applied mathematics and an MBA both from the University of Washington.
While working in HR at Google, she developed a data visualization course which she taught to Google staff throughout the U.S. and Europe. 4 4 4

5. Data Visualization Tips - General
The purpose of data visualization is to support the story that you are telling.
Tables interact with our verbal system, and graphs interact with our visual system, which is faster at processing information.
Know your audience and direct the analysis to your audience.
Concentrate on the "pearls", the information your audience needs to know.
Don't be afraid to include business recommendations supported by your data in your write-up. You know the data best. Data professionals should take a more confident stand. 5

6. Data Visualization Tips - General
Exploratory visualizations are important but not needed in the final product. Don't be tempted to include a graph just to show that you did the work.
Choosing the right type of visualization to support your write-up is critical.
Let the design of the charts fade into the background letting the data stand out.
Use ample white space and simple design to achieve this. 6

7. Data Visualization Tips – Less is More
Simple and to the point is the goal.
Do not use complicated charts. Better to use three simple charts than one complicated chart.
Use a good amount of white space around and in charts in order to direct the reader's eye to the pertinent information.
Use color, case, bold, italics, typeface, case, and size to emphasize the point of the chart. 7

8. Data Visualization Tips – Less is More
Avoid these things. They compete for audience attention.
Background colors for the chart
Gridlines
Heavy borders
Shading
Bright colors
Many, many colors
3D charts
Secondary Y axis 8

9. Data Visualization Tips – Less is More Example9

10. Data Visualization Tips – Less is More Example
Before simplifying After simplifying 10

11. Data Visualization Tips – Using Color
Sometimes it is necessary to use the colors of an organization.
If that isn't the case, medium blue and gray are recommended.
Use color to draw the reader's eye to the focus of the chart.
e.g. Use one color for the most important line in multiple line graphs and gray for all else.
e.g. Use gray rather than black for axes, titles, etc.
e.g. Use red for crisis or negative funds.
e.g. Use black, bold, and size for strong emphasis.
Missing Values have not been reported. For each Category:
Outside = 344 (5.9% of total)
Inside = 665 (11.47%)
Out of bed = 659 (11.36%)
Eating = 402 (6.93%)
Bathing = 321 (5.54%)
Toileting = 649 (11.19%)
Dressing = 522 (9.00%) 11 11

12. Data Visualization Tips – Using Color Example
Missing Values have not been reported. For each Category:
Outside = 344 (5.9% of total)
Inside = 665 (11.47%)
Out of bed = 659 (11.36%)
Eating = 402 (6.93%)
Bathing = 321 (5.54%)
Toileting = 649 (11.19%)
Dressing = 522 (9.00%) 12 12

13. Data Visualization Tips – Using Color Example
Missing Values have not been reported. For each Category:
Outside = 344 (5.9% of total)
Inside = 665 (11.47%)
Out of bed = 659 (11.36%)
Eating = 402 (6.93%)
Bathing = 321 (5.54%)
Toileting = 649 (11.19%)
Dressing = 522 (9.00%) 13 13

14. Data Visualization Tips – Using Gradient Color
Use gradients of a color or color family to show variance in quantitative data.
e.g. heat maps
Missing Values have not been reported. For each Category:
Outside = 344 (5.9% of total)
Inside = 665 (11.47%)
Out of bed = 659 (11.36%)
Eating = 402 (6.93%)
Bathing = 321 (5.54%)
Toileting = 649 (11.19%)
Dressing = 522 (9.00%) 14 14

15. Data Visualization Tips – Using Gradient Color
Missing Values have not been reported. For each Category:
Outside = 344 (5.9% of total)
Inside = 665 (11.47%)
Out of bed = 659 (11.36%)
Eating = 402 (6.93%)
Bathing = 321 (5.54%)
Toileting = 649 (11.19%)
Dressing = 522 (9.00%) 15 15

16. Data Visualization Tips – Using Gradient Color
Missing Values have not been reported. For each Category:
Outside = 344 (5.9% of total)
Inside = 665 (11.47%)
Out of bed = 659 (11.36%)
Eating = 402 (6.93%)
Bathing = 321 (5.54%)
Toileting = 649 (11.19%)
Dressing = 522 (9.00%) 16 16

17. Data Visualization Tips – Do Not Mislead
Most people assume a starting point of zero on the Y-axis.
It is tempting to start above zero sometimes to better show the differences in the data points.
This can lead to the audience not noticing that the Y-axis doesn't start at zero and consequently thinking that the variations are larger than they really are. 17

18. Data Visualization Tips – Do Not Mislead Example18

19. Data Visualization Tips – Specifics
Sans serif fonts are easier to read in charts.
Use natural ordering of data if available.
e.g. time series
If no natural ordering is available, think about what makes the most sense.
e.g. ordering a horizontal bar chart of market share from the largest at the top to the smallest at the bottom
Always retain the following elements with the numbers:
percentage signs – 10%
dollar symbols - $100
commas in large numbers – 1,000 19

20. Data Visualization Tips – Specifics
If specific data points are important, label them directly in the graph.
Decide whether to label all data points directly or keep the axis.
If you want the audience to focus on big picture data, keep the axis.
If the specific points are labeled and are the emphasis, consider omitting the axis in order to reduce redundancy. 20

21. Data Visualization Tips – Bar Charts
Use horizontal bar charts when the category names are long or when there are many categories.
The category labels can be as long as needed.
The category labels will not be truncated.
People read from left to right. Horizontal bar charts are easier to read than vertical bar charts because the audience will know what the categories are before seeing the results. 21

22. Data Visualization Tips – Horizontal Bar Chart Example
Missing Values have not been reported. For each Category:
Outside = 344 (5.9% of total)
Inside = 665 (11.47%)
Out of bed = 659 (11.36%)
Eating = 402 (6.93%)
Bathing = 321 (5.54%)
Toileting = 649 (11.19%)
Dressing = 522 (9.00%) 22 22

23. Data Visualization Tips – Pie Charts
Use only for a very few simple percentages of whole.
Avoid generally because not best method to visualize differences in amounts, especially when the amounts are similar.
Order by greatest to least percent of whole.
Order clockwise starting at 12:00.
Include for example "n=20" and "30%" for each pie slice (from Dr. Priestley).
Never use 3-D pie charts because they make the percentages of the pie look distorted. 23

24. Data Visualization Tips – Pie Charts24

25. Data Visualization Tips – 100% Bar Charts
Put the most important variable on the bottom so that the audience can easily see the percentage and the comparison across groups.
Put the second most important variable on the top so that the audience can easily see the comparison across groups. 25

26. Data Visualization Tips – 100% Bar Charts26

27. Data Visualization Tips – Live Presentations
Know that you will briefly lose the attention of the audience when they see a new slide.
Therefore, make the slides simple.
If complicated charts are necessary, add to the chart incrementally with a new slide for each additional item. 27

28. Data Visualization Tips – Live Presentation Example
Know that you will briefly lose the attention of the audience when they see a new slide.
Therefore, make the slides simple.
If complicated charts are necessary, add to the chart incrementally with a new slide for each additional item. 28

29. Data Visualization Tips – Live Presentation Example
Know that you will briefly lose the attention of the audience when they see a new slide.
Therefore, make the slides simple.
If complicated charts are necessary, add to the chart incrementally with a new slide for each additional item. 29

30. Data Visualization Tips – Live Presentation Example
Know that you will briefly lose the attention of the audience when they see a new slide.
Therefore, make the slides simple.
If complicated charts are necessary, add to the chart incrementally with a new slide for each additional item. 30

31. Data Visualization Tips – Live Presentation Example
Know that you will briefly lose the attention of the audience when they see a new slide.
Therefore, make the slides simple.
If complicated charts are necessary, add to the chart incrementally with a new slide for each additional item. 31

32. Data Visualization Tips – Live Presentation Example
Know that you will briefly lose the attention of the audience when they see a new slide.
Therefore, make the slides simple.
If complicated charts are necessary, add to the chart incrementally with a new slide for each additional item. 32

33. Data Visualization Tips – Summary
Understand the context.
Choose an appropriate visual display.
Eliminate clutter.
Focus attention where you want it.
Think like a designer.
Tell a story. 33