This document summarizes common mistakes in data visualization based on a presentation by Cory Jez. It identifies unclear or difficult to understand visuals, low data-to-ink ratios, displaying too much data ("data deluge"), using too many pie charts, misleading or distorted data, truncating axes, improper use of geographic maps, and misleading cumulative graphs as common errors. Specific examples are provided for each type of error along with potential solutions to improve the visualizations.

1. DATA VIZ GONE WRONG
WHAT NOT TO DO
Cory Jez
#DataViz15
San Jose, California
April 29, 2015

2. About Me
Over 4 years working as a
BI Analyst, Consultant, and Trainer
Tableau Desktop Certified, Tableau
Certified Trainer
Winner: 2014 Tableau Viz as Art
Fantasy Football & Data Viz

3. Data Viz is all around

4. Why Data Viz?
- Arthur Schopenhaur

5. Why Data Viz?

6. Why Data Viz?

7. Have you ever seen a “bad” infographic?
Source: @wtfviz
Survey

8. Unclear, difficult to understand
Low Data / Ink Ratio
Data Deluge
Too much pie
Misleading or intentionally distorting our data
Truncate Y-Axis
Geographic Data
Cumulative Graphs
Data Viz Gone Wrong

9. Unclear, difficult to understand
Low Data / Ink Ratio
Data Deluge
Too much pie
Misleading or intentionally distorting our data
Truncate Y-Axis
Geographic Data
Cumulative Graphs
Data Viz Gone Wrong

10. ink used to print data points
Data-ink ratio =
total ink used to print graphic
Source: The Visual display of Quantitative Information, Edward Tufte
Low Data / Ink Ratio

11. Redundant coloring
Redundant labeling
Background colors
Grid lines
Color legend
Low Data / Ink Ratio

12. Color signifies team of
interest
Remove axis, one
label for shots
No background
No grid lines
No color legend
Low Data / Ink Ratio

13. Remove
to
Improve
The Data / Ink Ratio

14. Unclear, difficult to understand
Low Data / Ink Ratio
Data Deluge
Too much pie
Misleading or intentionally distorting our data
Truncate Y-Axis
Geographic Data
Cumulative Graphs
Data Viz Gone Wrong

16. A lot of data in a tight space
Color scheme used to be congruent with the flag, not to highlight data
Should data about Americans always be represented by a flag?
All metrics are presented in-line with each other (race, age, citizenship)
Male / Female splits are automatically in 2% buckets (50 stars)
Source: junkcharts.com
Data Deluge

17. Unclear, difficult to understand
Low Data / Ink Ratio
Data Deluge
Too much pie
Misleading or intentionally distorting our data
Truncate Y-Axis
Geographic Data
Cumulative Graphs
Data Viz Gone Wrong

18. Source: buzzfeed.com
Too Much Pie
Issues:
Uninformative title
Too many pies make comparisons
difficult
Sort ordering
Names in ALL CAPS
Dem and Rep labels are switched
Not all pies add up to 100%
**You just end up reading numbers**

19. Source: buzzfeed.com
Too Much Pie
Solutions:
Title is more clear
Stacked bars make comparison
easier
Ordered by positive sentiment
Labeling is aligned
Visually see some bars +/- 100%
**You can visualize the winners/losers
and the trends now**

20. Pie isn’t always bad….

21. Unclear, difficult to understand
Low Data / Ink Ratio
Data Deluge
Too much pie
Misleading or intentionally distorting our data
Truncate Y-Axis
Geographic Data
Cumulative Graphs
Data Viz Gone Wrong

22. How much did R.A. Dickey’s Knuckleball velocity decrease in 2013?
Source: Heap Analytics
Truncated Y-axis
How much has his velocity decreased?

23. How much did R.A. Dickey’s Knuckleball velocity decrease in 2013?
Source: Heap Analytics
Truncated Y-axis
6% ?

24. 2.6% ?
Source: Heap Analytics
Remove labels & tell the story…

25. 2.6% ?
Source: Robinhood
Remove labels & tell the story…

26. Unclear, difficult to understand
Low Data / Ink Ratio
Data Deluge
Too much pie
Misleading or intentionally distorting our data
Truncate Y-Axis
Geographic Data
Cumulative Graphs
Data Viz Gone Wrong

27. Blue or Red? Who won?
Source: wikipedia

28. Geo’s are not sized by population
Some of the largest places: NYC, Boston
appear very small on a map
Solutions
Use “size” to denote population density
Accompany maps with aggregate data
Interactivity – allow for zooming and filtering
Geo Maps

29. Blue or Red? Who won?
Source: NY Times

30. Unclear, difficult to understand
Low Data / Ink Ratio
Data Deluge
Too much pie
Misleading or intentionally distorting our data
Truncate Y-Axis
Geographic Data
Cumulative Graphs
Data Viz Gone Wrong

31. Source: Heap Analytics
Cumulative Graphs: helpful or
misleading?

32. Source: Heap Analytics
Cumulative Graphs: helpful or
misleading?

34. Thanks!
cory.jez1@gmail.com
@jezlax
Linkedin.com/in/coryjez