data visualization - a brief overview

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Data Visualization A (Very) Brief Overview

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Page 1: Data Visualization - A Brief Overview

Data VisualizationA (Very) Brief Overview

Page 2: Data Visualization - A Brief Overview

What’s your graphic IQ?

O http://www.perceptualedge.com/files/Grap

hDesignIQ.html

Page 3: Data Visualization - A Brief Overview

What is data viz?

O Data visualization helps us translate numbers

into a picture that we can interpret more

easily.

O Two of the biggest reasons to use data

visualization are to…

O Make sense of data (i.e., help you see patterns)

O Communicate data to others (i.e., executive

presentations)

O Good visualizations allow our eyes to do

some of the heavy lifting in data processing

Page 4: Data Visualization - A Brief Overview

What is data viz?

O The low profit in Q2 is more apparent in

the graph than in the table.

Profit ($M)

Q 1 $4.18

Q 2 $3.24

Q 3 $4.12

Q 4 $3.91

$0 $1 $2 $3 $4 $5

Q1

Q2

Q3

Q4

Profit ($M)

Page 5: Data Visualization - A Brief Overview

Audience matters!

O Visualizations can be useful, even if you’re the only one to see them.

O For presentations, consider if everyone will have a printed copy, or if they need to be able to see fine details on a screen.

Q1 Q2 Q3

Group 1 4.19 4.25 4.50

Group 2 4.00 4.32 4.31

Group 3 4.22 4.18 4.54

Group 4 4.35 4.41 4.62

Q1 Q2 Q3

Group 1 4.19 4.25 4.50

Group 2 4.00 4.32 4.31

Group 3 4.22 4.18 4.54

Group 4 4.35 4.41 4.62

Page 6: Data Visualization - A Brief Overview

Purpose matters!

O Presentations are often expected to

function as both the visual aid during the

meeting, and a reference for those unable

to attend.

O Alternatives:

O 2 documents with difference purposes

O Use “speaker notes”

Page 7: Data Visualization - A Brief Overview

Content matters!

O Different chart types have different

strengths and weaknesses.

O Of the two options below, which do you

think is easier to interpret? Why?

0% 20% 40% 60% 80%

White/Caucasian

Hispanic

Black/African American

Asian

Two or More Races

Prefer not to answer

% of Population% of PopulationWhite/Caucasian

Hispanic

Black/AfricanAmericanAsian

Two or MoreRacesPrefer not toanswer

Page 8: Data Visualization - A Brief Overview

Types of Data: Comparisons

O Column charts are likely the best option if you have few groups (< 8), but title length can be a problem

O Bar charts work better if you have more groups or longer titles

O Heat maps are good if you’re comparing more than one group on more than one metric

Page 9: Data Visualization - A Brief Overview

Types of Data: Comparisons, continued

O Bullet graphs have become popular in dashboards, since they’re a compact option to show a value against a specific metric as well as a showing what’s considered good, fair, and bad.

4.1

8

3.2

4

4.1

2

3.9

1

Q1

Q2

Q3

Q4

Poor Fair Good

2016 2015

Page 10: Data Visualization - A Brief Overview

Types of Data: Composition

75%

67%

82%

73%

13%

11%

12%

18%

12%

22%

Question 1

Question 2

Question 3

Question 4

Fav Neu Unf

O Stacked bar or

column charts are

frequently used for

survey results

O Pie charts can be

used, but be careful

to avoid common

issues with pies

IC71%

Mgr26%

Sr Ldr3% Manager

Status

Page 11: Data Visualization - A Brief Overview

Types of Data: Trend

O Line charts are commonly used to

display long-term trend data.

55%

60%

65%

70%

75%

2014 2015 2016 2017

Group 1

Group 2

Group 3

Page 12: Data Visualization - A Brief Overview

Types of Data: Relationship

O Scatterplots are the most common graphic to show relationship data, but bubble charts can be used if you need to look at a third variable

O You can also use line charts to see relationships by comparing the shape of the graphs

O Network graphs can be used to show relationships between individuals

60%

70%

80%

90%

60% 70% 80% 90%

2017

2016

Page 13: Data Visualization - A Brief Overview

Tips for Useful Charts & Graphs

O Use the full axis, particularly on column and bar charts

O Highlight the most important information

O Consider if legends and labels detract from your point

O This isn’t to say you shouldn’t label your data, but sometimes it’s redundant or could be placed in a better way

O Consider the “data-to-ink” ratio

O Pass the “squint” test

O Think about sort order

O Ask for a second opinion

Page 14: Data Visualization - A Brief Overview

Common Problems in Presentations

O Too much information

O Poor color choices

O Variety for the sake of variety

O Inconsistent axes from one slide to the

next

O Neglecting to label charts

O Not following common conventions

Page 15: Data Visualization - A Brief Overview

Making Bad Charts Better

Page 16: Data Visualization - A Brief Overview

Pretty vs. Useful

Example from: http://viz.wtf/post/147196565281/alphabet-on-the-x-axis-for-reals#notes

O While this chart is pretty and at least

labeled, it’s hard to read quickly. Using an

alphabetic scale on the x-axis doesn’t do

anything to enhance interpretation.

Page 17: Data Visualization - A Brief Overview

Pretty vs. Useful, continued

O This bar chart is a better option for

conveying the same data.

Example from: http://viz.wtf/post/147196565281/alphabet-on-the-x-axis-for-reals#notes

Page 18: Data Visualization - A Brief Overview

Poor Axis Choice

Example from: http://junkcharts.typepad.com/junk_charts/2016/06/what-doesnt-help-readers-on-the-chart-and-what-does-help-off-the-chart.html

The graph below uses a line to show

trend (a common convention), but the

upside-down, truncated y-axis makes it

hard to read. A bar chart version would

be easier to follow, but you could just fix

the y-axis.

Page 19: Data Visualization - A Brief Overview

Republicans are bad at graphs…

O Media sources with a clear bias are

notorious for using a truncated axis to

their advantage.

6

7.066

0

2

4

6

8

As of 3/27 3/31 Goal

Mil

lio

ns

Obamacare Enrollment

Page 20: Data Visualization - A Brief Overview

… but so are Democrats

O In addition to

truncating the

axis, this one

also fails to

show that the

upward trend

started before

Obama took

office.

Example from: https://qz.com/580859/the-most-misleading-charts-of-2015-fixed/

Page 21: Data Visualization - A Brief Overview

Yet Another Poor Axis Choice

Example from: https://qz.com/580859/the-most-misleading-charts-of-2015-fixed/

O This is one of those times that it doesn’t

make sense to start the y-axis at 0.

Page 22: Data Visualization - A Brief Overview

Yet Another Poor Axis Choice, continued

Example from: https://qz.com/580859/the-most-misleading-charts-of-2015-fixed/

O The trend is more apparent when we use

a more realistic axis.

Page 23: Data Visualization - A Brief Overview

How Not to Make a Pie Chart

O Pie charts should never be

used to show values on a

multiple-select item. Use a

bar or column chart instead.

Example from: http://viz.wtf/post/162169270900/what-is-the-recidivism-rate-for-pie-chart

Overall

0%

20%

40%

60%

80%

Rec

idiv

ism

Ra

te

Offense Type

Page 24: Data Visualization - A Brief Overview

How Not to Make a Pie Chart, continued

O While this pie does add

up to 100%, the design

of the graphic makes it

nearly impossible to

read.

Example from: http://viz.wtf/post/60203066686/the-spiral-staircase-courtesy-of-janwillemtulp

0%

10%

20%

30%

40%

50%

60%

Con

tra

rian

Th

esis

Pe

rso

nal F

ailu

re

Sn

ap

py R

efr

ain

Sta

tem

en

t of

Utte

r C

ert

ain

ty

Sp

on

tane

ou

sM

om

en

t

Op

enin

g J

oke

So

ph

istica

ted

Vis

ua

l A

ids

Page 25: Data Visualization - A Brief Overview

Telling Your Story

O The headline to go with this chart was “Price has declined for all products on the market since the launch of Product C in 2010.”

Example from: http://www.storytellingwithdata.com/blog/2014/05/the-story-you-want-to-telland-one-your

Page 26: Data Visualization - A Brief Overview

Telling Your Story, continued

O Since we’re looking at trend data, a line chart would make it easier to see where the points are for each year/product.

Example from: http://www.storytellingwithdata.com/blog/2014/05/the-story-you-want-to-telland-one-your

Page 27: Data Visualization - A Brief Overview

Telling Your Story, continued

O Alternate headline: “As of 2014, retail prices

have converged across products, with an

average retail price of $223, ranging from a low

of $180 (Product C) to a high of $260 (Product

A).

Example from: http://www.storytellingwithdata.com/blog/2014/05/the-story-you-want-to-telland-one-your

Page 28: Data Visualization - A Brief Overview

Use of Color & Number of Groups

1

1.5

2

2.5

3

3.5

4

4.5

5

Page 29: Data Visualization - A Brief Overview

Use of Color & Number of Groups, continued

1

1.5

2

2.5

3

3.5

4

4.5

5

1

1.5

2

2.5

3

3.5

4

4.5

5

Page 30: Data Visualization - A Brief Overview

Appendix

Page 31: Data Visualization - A Brief Overview

Chart Chooser

Chart Chooser from: http://extremepresentation.typepad.com/blog/2006/09/choosing_a_good.html

Page 32: Data Visualization - A Brief Overview

Why Are Pie Charts Disliked?

O In each of these charts, can you identify

the largest slice? How does it compare to

the second largest?

Example from: http://prsync.com/oracle/pie-charts-just-dont-work-when-comparing-data---number--of-top--reasons-to-never-ever-use-a-pie-chart--23294/

Page 33: Data Visualization - A Brief Overview

Why Are Pie Charts Disliked?

O Here’s the same data as column charts-

it’s much easier to see differences

between groups.

Example from: http://prsync.com/oracle/pie-charts-just-dont-work-when-comparing-data---number--of-top--reasons-to-never-ever-use-a-pie-chart--23294/

Page 34: Data Visualization - A Brief Overview

If You Really Need to Use a Pie Chart…

O There are some do’s and don’t’s that are specific to pies if you really feel you need to use them.

O Arrange the slices in a way that makes sense.

O Don’t use them for more than 2-3 categories.

O Don’t use 3D. Ever.

O Add numeric values as labels so that the end user doesn’t have to guess. It’s also usually helpful to put the category in the label instead of using a legend.

O Don’t “explode” your pies.

O Don’t use pies for questions that allow more than one response.

Page 35: Data Visualization - A Brief Overview

Excel Tricks

O Trying to get Excel to do something it’s not

really designed to do? Check the Peltier

Tech site.

O https://peltiertech.com/Excel/Charts/ChartI

ndex.html

Page 36: Data Visualization - A Brief Overview

More on Color Choices

O Semantically resonant colors

O https://hbr.org/2014/04/the-right-colors-

make-data-easier-to-read

Page 37: Data Visualization - A Brief Overview

More on Color Choices

O If you know someone in the audience is

color-blind or will be printing the

presentation, there are specific palettes

that are “friendly”.

O http://www.vischeck.com has examples of

what various images look like to individuals

with color-blindness

O http://colorbrewer2.org gives sample

“friendly” palettes

Page 38: Data Visualization - A Brief Overview

Other ResourcesThere are several great data viz practitioners with

excellent books and websites. Some to look for:

O Stephen Few

O Edward Tufte

O Nathan Yau

O Albert Cairo

O Cole Nussbaumer

Knaflic

O Junk Chartshttp://junkcharts.typepad.com/

O WTF Visualizationshttp://viz.wtf/