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VISUALISING DATA

NOTE: THE NOTES IN THIS PRESENTATION WERE WRITTEN BY TOM SMITH WITH ADDITIONS BY STEPH JESPER (same goes for the slides themselves, for that matter!)

Data is everywhere. We have too much data. We can’t possibly understand it.

Visualisation takes something we can’t possibly understand, such as large collections of inter-related numbers, and presents them in a new language, a visual language that we maybe can understand.

Visualisation can also reveal something new about the data we are looking at. Visualisations can help us explore what the data might be, or see data in a personal context like the UK Government Daily spend and UK Government departmental spending.

See also: The Data day of Digital Creativity Week: https://docs.google.com/presentation/d/1lOWETR8ZaWTuIqBO3_t3onZ6c06j1JlgstCoWcG6tMI/edit#slide=id.p

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Tip of the hat to one of my favourite artists, Barbara Kruger: https://www.google.co.uk/search?q=barbara+kruger&num=50&hl=en&source=lnms&tbm=isch&sa=X&ved=0ahUKEwiNme6QwpPZAhXRMywKHabDCIIQ_AUICigB&biw=1459&bih=863

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Giving life to numbers

X	A	B	C
1	20
1.1	0
1.2	7
1.5	10
1.8	7
2	0
2.2	1	5	5
2.5	2.5	10	1
2.8	4	9	0
3	5	5	0
3.1			0
3.2			2
3.3			20
3.4			4
3.5			1
3.6			0
3.7			2
3.8			20
3.9			4
4			1
4.1			0
4.2	5	5	6
4.3	3	7	8
4.4	2	8	9
4.8	0	10	10
5.3	1		8
5.5	5		5
5.6
6	0	5
6.1	1	20

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Look around you...

We’ll start with some inspiration. It won’t all be relevant, but it might get you thinking.

We’re in the middle of a pandemic. And that means loads of graphs. Some of them are a bit grizzly but easy to follow. Some are less straightforward.

FT https://www.ft.com/coronavirus-latest

A simple plot of daily deaths against date (each country gets its own line)… but it’s not that simple when you start to pay attention to the axes

@EdConwaySky https://twitter.com/EdConwaySky/status/1255147479466565636

A similar plot, but again, do you understand the axes?

Information is Beautiful - https://informationisbeautiful.net/visualizations/covid-19-coronavirus-infographic-datapack/

An isotype plot can be a very clear way of showing comparative data

DannyDorling.org – Kirsten McClure http://www.dannydorling.org/?p=7758

Wow.

@thomasforth https://twitter.com/thomasforth/status/1255458040528191488

Private Eye clipping: https://twitter.com/jnicho02/status/1256985303119810560

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Look around you...

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You know something, John Snow…

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UoY Development Plan

K 8.42741 YOR

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Not just bar charts

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Isotypes

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Isotypes

CC BY Nallerton via Wikipedia

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Information

is

Beautiful

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Would a pie-chart have done?

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Pie charts

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Node maps of Shakespearean tragedies

READ THIS

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Node maps of Shakespearean tragedies

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Weirder stuff

READ THIS

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READ THIS

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READ THIS

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READ THIS

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READ THIS

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Lots of data in a small space!

READ THIS

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Maps and time

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Time

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“Timelines Revisited”

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Visual shortcuts

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39 studies about human perception in 30 minutes

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Useful graphics

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Layers of information

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The Periodic Table crams a lot of information into a small space

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Tangible Visualisations

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Tangible Visualisations

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The Forest of Data

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More Tangible Visualisations

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Visualising with sound

youtube.com/playlist?list=PLbLdd1fdNg5ymNYshv2xWtJTTo0cA7_1H

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Visualising with video

Black Sea high frequency radar data over the course of one year – Refik Anadol

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Visualising with video

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The Other Extra Dimension: Interactivity

karun.in/blog/expected-threat.html

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FIRST, GET SOME DATA

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The Internet!

York Open Data

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The Internet!

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APIs

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=ImportHTML()

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ALSO, HARD WORK

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THE n DEADLY SINS

OF VISUALISATION

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Validation...

NUMBERS: What could be easier than 1, 2, 3?

How many siblings...?

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Vali-date-tion...

2001

n.d.

c.1977

ca.1982

1957-2019

1800s

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Valley-daton...

Birmingham

Near Huddersfield

Northern Europe

Yugoslavia

54.3049287,-2.3369909

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Tip: data validation is your grumpy friend

...otherwise your data on Rock’n’Roll stars might include…

Elvis, Elvis Presley, The King, elvis, Elvis Aaron Presley, The King of Rock n Roll...

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48

FORMATS

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FORMATS

First Name Surname Age DOB

Tom Smith 52 3/9/1966

Spike Milligan - 16/04/18

First Name,Surname,Age,DOB

Tom,Smith,52,3/9/1966

Spike,Milligan,-,16/04/18

<firstname>Tom</firstname><surname>Smith</surname><age>51</age><dob>1966-09-03</dob>

</person>

{firstname:”Tom”, surname:”Smith”, age:51, dob:”1966-09-03”}

.csv or .tsv - what a spreadsheet can give you when you export a spreadsheet but NOT an .xls file and not any good if you have entered dates like this “Next Tuesday” or numbers like this “430 ish” or date like this 14thC.

http://convertcsv.com/

First Name Surname Age DOB

Tom Smith 51 3/9/1966

Xml - Invented to get around the problem of csv because you can write rules (Document Type Definitions) that mean you can verify IF the data is in the format it should be. But because you didn’t have to, and because it was difficult, nobody did, and so it ended up as bad as csv, only with much bigger files.

<person><firstname>Tom</firstname><surname>Smith</surname><age>51</age><dob>1966-09-03</dob></person>

JSON - Essentially just code serialised.

{firstname:”Tom”, surname:”Smith”, age:51, dob:”1966-09-03”}

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DEALING WITH MESSY DATA

More often than not, when working with data, you discover either that your data is messy, and maybe some columns might contain words and numerical data, or some rows have missing data, or you are trying to mashup two separate spreadsheets and the columns names don’t quite match, or people have used a label in slightly different ways throughout the data.

This is when you need to clean your data, or what is sometimes called data munging, or data wrangling

and is the process of cleansing

it and/or getting it into the shape

your visualisation needs.

It’s all about understanding formats and your data adhering to those formats.

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Seven Free Data Wrangling Tools: https://blog.varonis.com/free-data-wrangling-tools/

7 Steps to Mastering Data Preparation with Python https://www.kdnuggets.com/2017/06/7-steps-mastering-data-preparation-python.html

7 command-line tools for data science http://jeroenjanssens.com/2013/09/19/seven-command-line-tools-for-data-science.html

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DEALING WITH MESSY DATA

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	2023	2024	2025
Steph	8	6	9
Shaz	9	3	11

Your data is often ‘pivoted’:

that is, similar data in multiple columns

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Person	Year	Biscuits Eaten
Steph	2023	8
Steph	2024	6
Steph	2025	9
Shaz	2023	9
Shaz	2024	3
Shaz	2025	11

But that data is the same thing.

Having it separate makes it harder to count and play with in other ways.

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TOOLS

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Excel and Google Sheets

For most simple visualisation needs, you really only need something simple. The tools in Google Forms ( to create surveys ) and Google Spreadsheets ( to store and manipulate your data ) and Google Charts ( to display your data in interesting ways ) are enough for most people.

As well as bar, column and line charts, Google Spreadsheets can display the more esoteric Tree maps, Trendlines, Maps and Bubble charts once you have your data organised into the correct format. Go explore the Google Chart Gallery and start visualising today. https://developers.google.com/chart/interactive/docs/gallery

Hackney carriages EXPLORE tab https://docs.google.com/spreadsheets/d/12Jp_P8riMWkq0pcFpa-SaOS6euKpAz9NJ9eh6l46KEo/edit#gid=694658972

76 trees https://docs.google.com/spreadsheets/d/1tIa72_sW-LV1ZndFw8XLJs_QguY-y6eBOfH6Hbz_Oyk/edit#gid=1084460216 (Let’s create a pivot table)

https://docs.google.com/spreadsheets/d/1tIa72_sW-LV1ZndFw8XLJs_QguY-y6eBOfH6Hbz_Oyk/edit#gid=1084460216

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Rawgraphs.io

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Charticulator

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Digital Creativity Tools:� �Visualisation

digitalcreativitytools.everythingability.com/activities/tag/visualisation

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EXAMPLES

We’ll start with some inspiration. It won’t all be relevant, but it might get you thinking.

We’re in the middle of a pandemic. And that means loads of graphs. Some of them are a bit grizzly but easy to follow. Some are less straightforward.

FT https://www.ft.com/coronavirus-latest

A simple plot of daily deaths against date (each country gets its own line)… but it’s not that simple when you start to pay attention to the axes

@EdConwaySky https://twitter.com/EdConwaySky/status/1255147479466565636

A similar plot, but again, do you understand the axes?

Information is Beautiful - https://informationisbeautiful.net/visualizations/covid-19-coronavirus-infographic-datapack/

An isotype plot can be a very clear way of showing comparative data

DannyDorling.org – Kirsten McClure http://www.dannydorling.org/?p=7758

Wow.

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ESC ’82�voting�

RAWGraphs

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ESC ‘82 box plot

RAWGraphs

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ESC ’82 voting

Palladio

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ESC ’82 voting

Charticulator

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Electorate share (40yrs)

RAWGraphs

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North-south spread of words in the �Yorkshire Historic Dictionary

Google Sheets

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Geographic spread of words in the �Yorkshire Historic Dictionary

Google Sheets

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MAKING INFOGRAPHICS

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Designing good infographics

Be clear and concise.
Use relevant imagery.
Choose fonts, colours, shapes, and other design elements with a focus on the overall effect and style.
Guide the viewer around the infographic.
Make sure the information can be accessed in different ways.

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Fonts

Font choices impact readability, style, and tone.

Font size and spacing are also very important to consider.

If a viewer can't read your text, there's no point in it being there!

Music

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Colours

Pick a (simple) colour scheme and stick to it. You might match colours to an image or use a colour that matches the tone of the infographic.

Ensure you have good colour contrast between colours e.g. between text colour and background colour (whocanuse.com is a good checker).

Don't convey information just using colour.

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Plan your layout

Plan on paper

Try multiple layouts

Consider

reading

order

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Some online tools

Piktochart and Infogram are Freemium tools that let you enter tabulated data tables for some decent charts graphics…

But the free versions are pretty limited.

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Canva

Canva is an online design tool focused on visuals like graphics and videos.

It has a free version and also a lot of paid-for 'Pro' features (we don't have a University of York Pro licence).

Canva has a range of templates, some free and some paid-for, including infographic templates.

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PowerPoint

subjectguides.york.ac.uk/posters

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Think in pictures...

Be concise with words...

“Let’s have a brew!”

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Free-to-use stock images

Many websites offer images you can use for free either with or without attribution (check information on the site), e.g. Unsplash, Pixabay, Pexels, Nappy, Wikimedia Commons

Be warned: most of these sites make their money by also having paid-for images appear, so check carefully when choosing your images!

Some options for free-to-use stock images (and video and audio)

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Sourcing images

Your own images?

Stock images?

AI..?

Searching for information: Sourcing and reusing media

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Choose your images wisely

Think about which image(s) you use to communicate things…

…images aren't neutral!

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The Noun Project

Free icons!

Iconfinder

PowerPoint

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Designing an infographic in PPT

Set the page size (A4’s probably fine)
Draft some ideas out on paper: think about reading layout (columns like a newspaper? rows like a comic strip? boxes? does it flow logically?)
Consider the important details you need to convey. If it’s not essential, you probably should leave it off the page
Set up guidelines on your page to help create a balanced structure

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Designing an infographic in PPT

Draw your graphics. PPT has tools or you could just import things from elsewhere. You can always draw over the top of something too
Add your content; add your text (use shapes, not text boxes; space text out – empty space helps readability)
Think about your choice of colour – remember, minimalist simplicity is often best for infographics (you don’t want to distract from the message)
Export to PDF.

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Data visualisation�Skills Guide

subjectguides.york.ac.uk/skills/data-visualisation

There’s more slides on Data Viz in our

Visualisation 2019 deck

X	A	B	C
1	20
1.1	0
1.2	7
1.5	10
1.8	7
2	0
2.2	1	5	5
2.5	2.5	10	1
2.8	4	9	0
3	5	5	0
3.1			0
3.2			2
3.3			20
3.4			4
3.5			1
3.6			0
3.7			2
3.8			20
3.9			4
4			1
4.1			0
4.2	5	5	6
4.3	3	7	8
4.4	2	8	9
4.8	0	10	10
5.3	1		8
5.5	5		5
5.6
6	0	5
6.1	1	20

X	A	B	C
1	20
1.1	0
1.2	7
1.5	10
1.8	7
2	0
2.2	1	5	5
2.5	2.5	10	1
2.8	4	9	0
3	5	5	0
3.1			0
3.2			2
3.3			20
3.4			4
3.5			1
3.6			0
3.7			2
3.8			20
3.9			4
4			1
4.1			0
4.2	5	5	6
4.3	3	7	8
4.4	2	8	9
4.8	0	10	10
5.3	1		8
5.5	5		5
5.6
6	0	5
6.1	1	20

X	A	B	C
1	20
1.1	0
1.2	7
1.5	10
1.8	7
2	0
2.2	1	5	5
2.5	2.5	10	1
2.8	4	9	0
3	5	5	0
3.1			0
3.2			2
3.3			20
3.4			4
3.5			1
3.6			0
3.7			2
3.8			20
3.9			4
4			1
4.1			0
4.2	5	5	6
4.3	3	7	8
4.4	2	8	9
4.8	0	10	10
5.3	1		8
5.5	5		5
5.6
6	0	5
6.1	1	20