Intro to Visualization:

How to make more effective charts and graphs

Frank Elavsky, Data Visualization Specialist
Research Computing, Northwestern University

These slides:

nuitrcs.github.io/intro_to_viz_workshop

This repo:

github.com/nuitrcs/intro_to_viz_workshop

Chart literacy is important.

Not just for the audience, but for communicators too.

Visualization is a

Chainsaw

Use wisely.

This is the chart version of a chainsaw massacre.

Think about your data! How did this happen?

An honest mistake... or?

Poor designer put their own name on this one.

From Smashing Magazine's series: "Imagine a pie chart stomping on an infographic forever"

An "automated" visualization report.
Yikes.

Gestalt Principles:

Hacking the Mind

AKA: the “chainsaws of visual communication”

Proximity

(creates categories)

Similarity

(creates subcategories)

Contrast

(creates focus)

Commonality

(creates connections)

Continuity

(creates flow)

Closure

(creates suggestion)

Figure-Ground

(creates entry-point and layers)

Common Fate

(creates meta-categories)

Quick thanks to Pablo Stanley

Big Picture: Empathy and Awareness

Your skill in these will define whether your visualization is successful or not.

Data is painful.

So what do you do?

Hint: it's time to take notes!

Audience, Purpose, Context

The holy triumvirate: Who, why, and where

Audience

Who is your visualization for?
This is the first and most important consideration.

I'm not sure even astrophysists know what this means.
Disciplines intersecting over Equation of State. Ozel F, Freire P. 2016. Annu. Rev. Astron. Astrophys. 54:401-40

The geometry lies, but communicating data is the whole point here.
Infographics are the worst at this.

This color scale is very bad, but if meteorologists did things differently, the public would lose their minds.
Texas Storm Chasers

Purpose

Why are you visualizing data?
How can you measure your success if you don't define your purpose?

This is explaining data to a general audience - a little fluff is acceptable to keep their interest.
Brain response predicts movie sales.

This is learning data for your own analysis - not meant to be pretty.
Using ggplot to test data

This is exploring the dimensions of the data - meant for the audience to learn something (not you)
"How will Automation Affect Different US Cities?"

Context

Where does the visual end up?
You can do a lot differently depending on the answer to this question.

Editors: "Print. Small size. No color." (Given the context, this isn't too shabby!)
Lung Cancer Epidemiology

Small multiples are great for many static dimensions (if you have the room)
"Public support for vouchers"

Time+scope are part of context too!

How long do you have and how much do you do?
Don't wait until the end of your research or analysis before you consider this.

Let's check your skills real quick.

This is a monster.

Tell me why. What is wrong with this?

Which wedge is largest? Smallest?

This is a case of too much dimension for the data.

Default bar version from excel

What can we improve about this? Use empathy. What is hard?

Horizontal has more room for text

Text is often a big limitation for the context of your visual.

Cut axis, bump up font size

Sort and use color to emphasize

Much better.

Minimize the time your audience takes to understand your purpose.

Edward Tufte's 'Data to Ink Ratio'.

The golden rule of visualization.

Even your tables have 'ink'

These gifs courtesy of Dark Horse Analytics

Now you have a task!

Audience: Everyone here

Purpose: Compare two groups of congress members

Context: 15 minutes, using Excel

Go to the github for the file '3.xlsx' and get to work.

This was my 5 minute attempt

I want you to do better with just 10 minutes more.

My slightly improved version

Whew, what a rush.

You have all leveled up as Chart Wizards. Congrats.

Your take-aways:

Empathy is the key to effective visualization
 

Audience

Who is your reader? What about your data will be difficult for them?

Purpose

Why are you visualizing your data? How will you know when you have succeeded?

Context

Where/what/when are your limitations? Do you have the scope to do what you want?

 
Frank Elavsky, Research Computing, Northwestern IT