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Telling Stories with Data Phil Charron [email protected] | @pfilbert | linkedin.com/in/philcharron | thinkbrownstone.com/blog

Telling Stories With Data

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Page 1: Telling Stories With Data

Telling Stories with Data

Phil [email protected] | @pfilbert | linkedin.com/in/philcharron | thinkbrownstone.com/blog

Page 2: Telling Stories With Data

We are all made of storiesand stories are made of data

Page 3: Telling Stories With Data

The Science of Storytelling

storytelling with data

Page 4: Telling Stories With Data

Tragedy Aristotle (335 BCE)

Mythos (plot)

Ethos (character)

Dianoia (thought)

Lexis (diction)

Melos (melody)

Opsis (spectacle)

what is a story?

Page 5: Telling Stories With Data

Plot

Literature Data VisualizationCharacters

Vladmir, Estragon, Pozzo, Lucky, Godot?

Metrics Phil’s Spending

Settings A country road, a tree

Categories Phil’s Budget Areas

elements of a story

Time Act 1, Act 2

Time October 2014 - September 2015

Page 6: Telling Stories With Data

Seven Basic Conflicts Arthur Quiller-Couch (1863-1944)

Man vs. Man

Man vs. Nature

Man vs. God

Man vs. Society

Man in the Middle

Man and Woman

Man vs. Himself

defining plot

Page 7: Telling Stories With Data

Seven Basic Plots Christopher Booker (2004)

Overcoming the Monster

Rags to Riches

The Quest

Voyage and Return

Comedy

Tragedy

Rebirth

defining plot

Page 8: Telling Stories With Data

Plot Man in the Middle

or Man vs. God

The Question How does Phil spend his money?

Literature Data VisualizationCharacters

Vladmir, Estragon, Pozzo, Lucky, Godot?

Metrics Phil’s Spending

Settings A country road, a tree

Categories Phil’s Budget Areas

basic plots of data viz

Time Evening

Time October 2014 - September 2015

Page 9: Telling Stories With Data

puttytime!

Raise your hand if you know the artist

Page 10: Telling Stories With Data

puttytime!

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plots in data viz

$178.44

0 10

Page 12: Telling Stories With Data

ANSWER THE FREAKING QUESTION

TELL THE FREAKING STORY

mantra

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How much do I owe on my credit card?

What is the value of a metric right now?

basic plots of data viz

Credit Card Balance: $178.44

Page 14: Telling Stories With Data

How has my credit card spending changed over the past twelve

months?

How has a metric changed over time?

$0

$1,750

$3,500

$5,250

$7,000

Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep

basic plots of data viz

Page 15: Telling Stories With Data

Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep

How has my credit card spending changed over the past twelve

months?

How has a metric changed over time?

basic plots of data viz

Page 16: Telling Stories With Data

AVOID COGNITIVE FRICTION

mantra

Page 17: Telling Stories With Data

How does my credit card spending from this year compare to last year?

How does a metric compare across multiple time periods?

basic plots of data viz

Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep

2014 2015

Page 18: Telling Stories With Data

How does my credit card spending from this year compare to last year?

How does a metric compare across multiple time periods?

basic plots of data viz

Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep

2014 2015

Page 19: Telling Stories With Data

How do all these categories make up this metric?

How does my spending break down by budget area?

basic plots of data viz

OtherHome

Entertainment

Donations

Shopping

Travel

Auto & TransportFood & Dining

Business Services

Page 20: Telling Stories With Data

How do all these categories make up this metric?

How does my spending break down by budget area?

Did I spend more on Travel or Shopping?

basic plots of data viz

OtherHome

Entertainment

Donations

Shopping

Travel

Auto & TransportFood & Dining

Business Services

Page 21: Telling Stories With Data

How does my spending in each budget area compare

to each other?

How do all these categories compare to each other?

basic plots of data viz

Business Services

Food & Dining

Auto & Transport

Travel

Shopping

Donations

Entertainment

Home

Other

Page 22: Telling Stories With Data

How does my budget spending this year compare to last year?

How do all these categories compare across time periods?

basic plots of data viz

Business Services

Food & Dining

Auto & Transport

Travel

Shopping

Donations

Entertainment

Home

Other

2014 2015

Page 23: Telling Stories With Data

DES“I”

GN

THERE IS NO

IN I

mantra

Page 24: Telling Stories With Data

How do the information sources preferred by different generations compare to each other?

whyy: the question

Page 25: Telling Stories With Data

Age Group

Paper /magazine

AM/FM Radio Television

Text or email

Word of mouth

Website / blog Facebook

Mobile App

Internet search Other Twitter

Satellite Radio

19-28 3% 16% 17% 7% 14% 13% 13% 8% 1% 2% 5% 0%

29-38 5% 22% 12% 8% 9% 12% 13% 8% 3% 3% 5% 0%

39-48 13% 19% 7% 5% 13% 13% 12% 8% 6% 4% 2% 0%

49-58 27% 21% 15% 8% 7% 5% 5% 4% 5% 3% 1% 0%

59-68 32% 11% 13% 13% 5% 6% 6% 7% 2% 4% 1% 1%

69-78 47% 8% 19% 10% 6% 1% 0% 3% 3% 3% 0% 0%

79-88 67% 0% 19% 10% 5% 0% 0% 0% 0% 0% 0% 0%

How did you become aware of the last local story that interested you?

whyy: the answer

Page 26: Telling Stories With Data

19-28

29-38

39-48

49-58

59-68

69-78

79-88

0% 17.5% 35% 52.5% 70%

Newspaper/magAM/FM RadioTelevisionText or emailWord of mouthWebsite or blogFacebookMobile appInternet searchOtherTwitterSatellite Radio

How did you become aware of the last local story that interested you?

whyy: the answer

Page 27: Telling Stories With Data

How did you become aware of the last local story that interested you?

Newspaper/mag

AM/FM Radio

Television

Text or email

Word of mouth

Website or blog

Facebook

Mobile app

Internet search

Other

Twitter

Satellite Radio

0% 17.5% 35% 52.5% 70%

19-2829-3839-4849-5859-6869-7879-88

whyy: the answer

Page 28: Telling Stories With Data

19-28 29-38 39-48 49-58

59-68 69-78

Newspaper/mag AM/FM Radio Television Text or emailWord of mouth Website or blog Facebook Mobile AppInternet search Other Twitter Satellite Radio

79-88

How did you become aware of the last local story that interested you?

whyy: the answer

Page 29: Telling Stories With Data

WHAT WAS THE FREAKING QUESTION?

whyy: the answer

Page 30: Telling Stories With Data

How do the information sources used by different generations compare?compare

whyy: the answer

Page 31: Telling Stories With Data

How do the categories within these similar groups compare?

How do the information sources used by different generations compare?

whyy: the answer

Page 32: Telling Stories With Data

25%

50%

75%

100%

19-28 29-38 39-48 49-58 59-68 69-78 79-88

Newspaper/magAM/FM RadioTelevisionWord of mouthText or emailWebsite or blogFacebookMobile AppInternet searchSatellite RadioTwitterOther

How do the categories within these similar groups compare?

whyy: the answer

Page 33: Telling Stories With Data

How did you become aware of the last local story that interested you?

whyy: the answer

25%

50%

75%

100%

19-28 29-38 39-48 49-58 59-68 69-78 79-88

Newspaper/magAM/FM RadioTelevisionWord of mouthText or emailWebsite or blogFacebookMobile AppInternet searchSatellite RadioTwitterOther

Page 34: Telling Stories With Data

How did you become aware of the last local story that interested you?

whyy: the answer

25%

50%

75%

100%

19-28 29-38 39-48 49-58 59-68 69-78 79-88

Newspaper/magAM/FM RadioTelevisionWord of mouth

Traditional Sources

Page 35: Telling Stories With Data

25%

50%

75%

100%

19-28 29-38 39-48 49-58 59-68 69-78 79-88

Newspaper/magAM/FM RadioTelevisionWord of mouthText or emailWebsite or blogFacebookMobile AppInternet searchSatellite RadioTwitterOther

How did you become aware of the last local story that interested you?

whyy: the answer

Non-traditional Sources

Page 36: Telling Stories With Data

puttytime

Two common English words contain “uum"

Vacuum & _________

Page 37: Telling Stories With Data

Vacuum &

puttytime

Two common English words contain “uum"

Continuum

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the continuum

100

Page 39: Telling Stories With Data

the continuum

100Motivation

Is it worth trying to save Phil?

Page 40: Telling Stories With Data

100

Motivation

the continuum

50Performance

Is it worth trying to save Phil?

Page 41: Telling Stories With Data

the scatterplot

Performance

100

Motivation

5

Performance

Am I at risk for losing talented people?

Page 42: Telling Stories With Data

Am I at risk for losing talented people?

the scatterplot

100

Motivation

5

Performance

Page 43: Telling Stories With Data

the scatterplot

Oxford Comma

Puppies

Kittens

Standard Comma

Who should I vote for?

Page 44: Telling Stories With Data

the scatterplot

Oxford Comma

Puppies

Kittens

Standard Comma

Who should I vote for?

Hillary

The Donald

Cruz

Jindal

Fiorina

Carson

Christy

Sanders

Santorum

Page 45: Telling Stories With Data

google public data explorer

How does income disparity compare from territory to territory in the US?

Page 46: Telling Stories With Data

google public data explorer

How does each state’s per capita personal income compare to its personal disposable income over time?

Oh, and show me each state’s population to give some context.

How do two separate metrics for these related groups of different sizes compare to each other over time?

Page 47: Telling Stories With Data

How does each state’s per capita personal income compare to its personal disposable income over time?

Oh, and show me each state’s population to give some context.

How do two separate metrics for these related groups of different sizes compare to each other over time?

google public data explorer

Page 49: Telling Stories With Data

How much of something is there?

Something is changing over time

Something is changing over multiple time periods

Something is composed of many parts

Many parts compare to each other

Many parts compare to each other, over time

Similar things, made of similar parts, compare to each other

Party in DC!!!!

recap: some plots in data viz

$-523.66

Page 50: Telling Stories With Data

Thank You!

[email protected] | @pfilbert | linkedin.com/in/philcharron | thinkbrownstone.com/blog