What kind of stories are best told with data? How do you take raw numbers and turn them into an engaging, meaningful story? Thinking Machines' content strategist Pia Faustino delivered this presentation on the data storytelling process at the "Humans + Machines: Using Artificial Intelligence to Power Your People" conference on February 19, 2016 in Bonifacio Global City, Taguig, Philippines.
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From Information to Insight: Data Storytelling for Organizations
1. Thinking
Machines
Data Science
Title Text
✦ Body Level One
✦ Body Level Two
✦ Body Level Three
✦ Body Level Four
✦ Body Level Five
From Info to Insight:
Data Storytelling
for Organizations
Thinking
Machines
Data Science
Pia Faustino
Content Strategist, Thinking Machines
@piafaustino
3. Thinking
Machines
Data Science
About Thinking Machines
We are a team of
data scientists engineers
statisticians storytellers
+ +
+
Data StrategyWe do
Data Engineering
Data Science
Data Storytelling
18. Thinking
Machines
Data Science
Types of data stories
01
02
03
04
05
Change over time
Macro to Micro (and vice versa)
Correlation and Causation
Comparisons and Contrasts
Outliers
19. Thinking
Machines
Data Science
“This is How Fast America
Changes Its Mind”
Bloomberg, June 2015
http://www.bloomberg.com/graphics/
2015-pace-of-social-change/
US states legalising same-sex marriage
2004-2016
Change over Time
20. Thinking
Machines
Data Science
Change over Time
What’s really warming the world?
Bloomberg News, June 2015
http://www.bloomberg.com/graphics/2015-whats-warming-the-world/
23. Thinking
Machines
Data Science
Comparison and Contrast
“How that Map You Saw on 538 Underrepresents Minorities”
by Joshua Tauberer, posted on Medium
https://medium.com/@joshuatauberer
24. Thinking
Machines
Data Science
Macro to Micro (and VV)
Are you in the Global Middle Class?
Pew Research, July 2015
http://www.pewglobal.org/2015/07/08/a-global-middle-class-is-more-promise-than-reality/
25. Thinking
Machines
Data Science
Micro to Macro (and VV)
1052 mass shootings in 1066 days | The Guardian, Dec 2015
http://www.theguardian.com/us-news/ng-interactive/2015/oct/02/mass-shootings-america-gun-violence
31. Thinking
Machines
Data Science
Our Data Storytelling Process
01
02
03
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Get the data
Choose your questions
Interview the data
Curate your findings
Communicate and visualize
33. Thinking
Machines
Data Science
Thinking Machines collaborated with
Philippine Center for Investigative Journalism
to analyze voter registration and turnout data for a
series of stories on the Philippine elections.
34. Thinking
Machines
Data Science
6,928 rows x 9 columns
Voter registration & turnout
4 national elections
1,644 Towns + Cities
Source: COMELEC / PCIJ
Filetype: CSV
About the data:
37. Thinking
Machines
Data Science
Where could unusual/outlier voting patterns be
found?
Where were voter turnout rates unusually high?
Are poorer places more likely to have high voter
turnout?
Questions
38. Thinking
Machines
Data Science
Interviewing the Data
Where were voter turnout rates unusually high?
Our tools: iPython Notebook, Pandas Library
voter_stats[‘turnout_rate’] =
voter_stats[‘voter_turnout’] /
voter_stats[‘registered_voters']
39. Thinking
Machines
Data Science
What’s the
voter turnout
rate per town? Has it always
been this
way?
What’s
normal?
Has it always
been this way
in Luzon?… in the
Visayas?
… Mindanao?
… in Basilan?
… in Antique?
… in San
Juan?
What’s
considered
high / low?
???
???
???
???
???