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DATAVISUALIZATION
inanutshell
DAVIDALAYÓNCreativeTechnologist·SerialEntrepreneur
DesignThinker·UX&ProductDesigner
@davidalayon
SocialNoise
ChiefInnovationOfficer&Partner
Guud
DataScientistwannabe&Co-Founder
Google,IEBS,MiamiAdSchool...
Professor&Mentor
MoveWoman
ProductDesignAdvisor&Co-Founder
DataPointed
Viz by:
... and I’m here to talk about Data Visualization
... and I’m here to talk about Data Visualization
DataPointed
Viz by:
... and I’m here to talk about Data Visualization
DataPointed
Viz by:
... and I’m here to talk about Data Visualization
DataPointed
Viz by:
... and I’m here to talk about Data Visualization
DataPointed
Viz by:
... and I’m here to talk about Data Visualization
DataPointed
Viz by:
THEDEFINITION
Coolness Graphed
Viz by:
PLOS
Viz by:
VEGETATIVE STAGE BRAIN DAMAGE HEALTHY PERSON
IMAGEN:
Best American
Infographics 2013
Viz by:
Aaron Koblin
Viz by:
AIR TRAFFIC OVER NORTH AMERICA
IMAGEN:
IT ISN'T CLEAR...
IMAGEN:
Data
visualization
Information
visualization
VISUALIZE
RAW DATA
IMAGEN:
Data
visualization
Information
visualization
Information
Graphics
Data
Graphics
VISUAL ENCODINGS
(RAW) DATA
IMAGEN:
INFORMATION
GRAPHIC
IMAGEN:
INFOGRAPHIC
IMAGEN:
Data
visualization
Information
visualization
Information
Graphics
Data
Graphics
SUBJECTIVE
DESIGN-CENTERED
PERSUASION
OBJECTIVE
DATA-CENTERED
EXPLORATION
¿?
IMAGEN:
Super Graphic
Viz by:
Best American
Infographics 2013
Viz by:
IMAGEN:
The goal of Data visualization is to communicate
information clearly and efficiently to users via the
statistical graphics, plots, information graphics,
tables, and charts selected. Effective visualization
helps users in analyzing and reasoning about data
and evidence. It makes complex data more
accessible, understandable and usable.
WIKIPEDIA
IMAGEN:
DNA11
Viz by:
IMAGEN:
Data visualization is the mix of many
disciplines whose goal is to communicate
data-based information in a visual way with a
certain objective to a certain target audience.
COMPUTER SCIENCE
STATISTICS
GRAPHIC DESIGN
...
disciplines
visual way
objective target audience
INFORM
EXPLORE
ADMIRE
...
IMAGE
VIDEO
INTERACTIVE APP
...
MAINSTREAM
IN-COMPANY
JOURNALISTS
...
THEWHY
IMAGEN:
IMAGEN:
Tor Norretranders
Viz by:
IMAGEN:
EXPLORE INFORM ADMIRE
FRAGMENT FIRST
WORLD MAP - PIRI REIS
CARTOGRAPHY
EXPLORE
GMAPS - GOOGLE
CARTOGRAPHY
EXPLORE
INFORM
REAL MADRID VS ATLÉTICO
MADRID - CARTODB
CARTOGRAPHY
EXPLORE
INFORM
ADMIRE
FIRST TIME-SERIES -
10th century
OBSERVATION
OFOURWORLD
EXPLORE
TIDE TABLE
EXPLORE
INFORM
OBSERVATION
OFOURWORLD
THE LARGEST STARS IN
THE UNIVERSE 2015
EXPLORE
INFORM
ADMIRE
OBSERVATION
OFOURWORLD
CHOLERA MAP -
DR SNOW
PROBLEM
SOLVING
BETTER
COMMUNICATION
Videogames Market: $32 billions dollars
Internet Porn Industry: $97 billion dollars
US Defense Budget: $440 billion dollars
Global Pharmaceutical Market: $534 billions dollars
Save the Amazon: $21 billion dollars
Videogames Market: $32 billions dollars
Feed every child in the world for a year: $54 billion dollars
Internet Porn Industry: $97 billion dollars
Yearly amount given to charity by Americans: $300 billion dollars
US Defense Budget: $440 billion dollars
Feed and educate every child on Earth for 5 years: $465 billion dollars
Global Pharmaceutical Market: $534 billions dollars
BETTER
COMMUNICATION
THE BILLION
DOLLAR GRAM
BETTER
COMMUNICATION
DETECT
PATTERN
DETECT
PATTERN
THEPROCESS
IMAGEN:
IMAGEN:
“Obesity is, on average,
inversely proportional to the average
education of the population”
Can you show the evidence
for this assertion?
THE FUNCTIONAL ART -
ALBERTO CAIRO
THE FUNCTIONAL ART -
ALBERTO CAIRO
THE FUNCTIONAL ART -
ALBERTO CAIRO
THE FUNCTIONAL ART -
ALBERTO CAIRO
THE FUNCTIONAL ART -
ALBERTO CAIRO
IMAGEN:
Step 1: Accept that a graphic is a tool for
understanding
Step 2: Be curious and start making simple graphics
about topics you care about. Tons of them.
Step 3: Educate yourself in creating hierarchies,
narratives, stories, etc., that make your
presentations understandable.
Alberto Cairo
IMAGEN:
Represent Refine Interact
DATA VISUALIZATION
IMAGEN:
Represent Refine Interact
DATA VISUALIZATION
Mine FilterAcquire Parse
EXPLORATORY
DATA ANALYSYSDATA WRANGLING
IMAGEN:
- SHAPED
IMAGEN:
- SHAPED
BROAD
D
E

E

P
IMAGEN:
NoSQL
ETL
Statistics Machine LearningData Mining
Communication
Graphic Design
Web scrapping
API
Storytelling
IMAGEN:
Represent Refine Interact
VISUALIZING DATA
Mine FilterAcquire Parse
PREPARING DATACOLLECTING DATA DATA VISUALIZATIONEXPLORATORY
DATA ANALYSYSDATA WRANGLING
LIKE IF WE WERE COOKING!
IMAGEN:
WE HAVE THE DATA!
IT’S PREPARE TO COOK!
LET’S COOK!
HAVE A GREAT
STORY
William Doree
Photo by:
DETERMINE YOUR
MESSAGE
Carly Wong
Photo by:
KNOW YOUR
AUDIENCE
Victoria Hellner
Photo by:
KNOW YOUR
CONTENT
Victoria Hellner
Photo by:
RESPECT YOUR
AUDIENCE
IMAGEN:
DECIDE WHICH DATA TO
ILLUSTRATE
Pablo Peron
Photo by:
DECIDE HOW TO
ILLUSTRATE
Antonis Androulakis
Photo by:
Sabrina Secco
IMAGEN:
THEBASICS
TYPES OF DATA
Ordinal
(size: S, M...)
Quantitative
(counts: 1, 2, 3...)
Fields
(altitude temperature...)
Nominal
(shape, geo...)
Cyclic values
(directions, hues...)
DISCRETE
(no between values)
CONTINUOUS
(values between)
ORDERED
(values are comparable)
UNORDERED
(values not comparable)
LIFE EXPECTANCY
GEOGRAPHICAL REGION
GapMinder
Viz:
INCOME PER
PERSON
LIFE EXPECTANCY
Quantitative
Fields
GEOGRAPHICAL REGION
Nominal
GapMinder
Viz:
INCOME PER
PERSON
HOW MANY TIMES BIGGER?
HOW MANY TIMES BIGGER?
x7
SATURATION
BRIGHTNESS
DENSITY
HUE
COLOR
Observers can rapidly differentiate between
only five to ten hues (Healy)
Twelve colors (6+6) recommended (Ward)
Don’t forget white, black and gray
SATURATION &
CONTRAST
Use saturated colors for points,
strokes and symbols
Use desaturated colors for fills and
larger areas
Make sure that the elements have
sufficient luminance contrast
WHAT’S THE PROBLEM?
WHAT’S HAPPENING HERE?
WHAT’S HAPPENING HERE?
WHAT’S THE PROBLEM?
We organize what we see in particular ways to make sense of visual information.
There are six principles that influence the ways human see and understand visuals.
GESTALT PRINCIPLES
OF PERCEPTION
FONTS
Data visualization
Data visualization
Data visualization
Data visualization
Datavisualization
Helvetica
Arial
Gill Sans
ICONS
Easy to understand
(icon + measure)
Sentences are to speech what charts are to visual encodings
CHARTS
VISUAL
ENCODINGS
DATA
TYPES RELATIONSHIPS CHART
TYPES++ =
BAR CHART
Quantitative
dependent
variable
Discrete / nominal
independent variable
POSITION + LENGHT
LINE CHART
Quantitative
continuous
dependent
variable
Quantitative continuous
independent variable
POSITION
SCATTER PLOT
Quantitative
independent
variable
Quantitative independent
variable
POSITION + DENSITY
PIE CHART
Relative portions of
a quantitative
dependent variables
On single dimension (100%)
ANGLES
STACKED BAR CHART
Two accumulating
quantitative
dependent
variable
Independent variables
POSITION + LENGTH
ANATOMY OF A CHART
WHAT’S HAPPENING HERE?
CHERNOFF
FACES
DASHBOARD
Ducksboard
Ryan MacEachern
DESIGN X FOOD
DATA-INK
RATIO
ink used to
describe the data
ink used to describe
everything else
=
The highest
the better!
If it’s high you
have too much
chart junk!
THESTORY
HAVE A GREAT
STORY
William Doree
Photo by:
PRESENTATION
VISUALIZATION
INTERACTIVE
VISUALIZATION
INTERACTIVE
STORYTELLING
Used for communication
Doesn’t support user input
COMMUTING BARCELONA
Bestiario
Viz by:
TV & TWITTER ADS
BCNBEATS
Outliers
Viz:
PRESENTATION
VISUALIZATION
INTERACTIVE
VISUALIZATION
INTERACTIVE
STORYTELLING
Used for discovery
Rerenders based on input
AUTHOR-DRIVEN VIEWER-DRIVEN
- Strong ordering
- Heavy messaging
- Need for clarity and
for speed
- Ask questions
- Explore and interact
- Tell your own data
story
PRESENTATION
VISUALIZATION
INTERACTIVE
VISUALIZATION
INTERACTIVE
NARRATIVE
ending1
ending2
ending3
ending4
ending5
ending6
ending7
ending8
ending9
The Guardian
Viz:
Town Center
Car parks
Viz:
Bestiario
Viz:
Bloomberg
Viz:
Future of car
sharing
Viz:
DataViva
Viz:
PRESENTATION
VISUALIZATION
INTERACTIVE
VISUALIZATION
INTERACTIVE

STORYTELLING
Mix between presentation
and interaction
AUTHOR-DRIVEN
VIEWER-DRIVEN
Evolution of
the web
Viz:
Drones
Viz:
Periscopic
Viz:
THETOOLS
Evuan Murray
IMAGEN:
Flexibility
Productivity
ASSEMBLY
C / C++
Python / Ruby
Excel
Flexibility
Productivity
SVG, Canvas, WebGL
D3.js
Dimple.js
Tableau
SVG
@Enjalot
Tutorial:
SVG
@Enjalot
Tutorial:
SVG
<path d=‘
M 256,213 C 245,181 206,187 234,262 147,181
169,71.2 233,18 220,56 235,81 283,88 285,78.7
286,69.3 288,60 289,61.3 290,62.7 291,64 291,64
297,63 300,63 303,63 309,64 309,64 310,62.7
311,61.3 312,60 314,69.3 315,78.7 317,88 365,82
380,56 367,18 431,71 453,181 366,262 394,187
356,181 344,213 328,185 309,184 300,284
291,184 272,185 256,213 Z’>
</path>
Tavmjong
Animated:
D3.js
D3.js (Data-Driven Documents) is a JavaScript
library for producing dynamic and interactive data
visualizations in web browsers.
- D3 is Not a Charting Library (like Highcharts)
- D3 is Not a Graphics Layer (SVG, HTML + CSS)
- D3 is Not a SVG Polyfill (like RaphaelJS)
D3.js as a data visualization tool, in the sense that its
API has two parts: data (comes with lots of utilities for
processing data) and visualization (to bind and
transform DOM elements)
Ruoyu Sun
Source:
D3.js · Binding API
var svg = d3.select('svg')
svg.append('circle')
.attr({
cx: 100,
cy: 100,
r: 40,
fill:'#25B0B0'
})
svg.append('circle')
.attr({
cx: 350,
cy: 100,
r: 40,
fill:'#25B0B0'
})
@Enjalot
Tutorial:
D3.js · Non- Binding API
var quant = [0, 5, 10, 15, 20];
var qual = ["big", "small", "medium"];
var qScale = d3.scale.linear()
.domain(d3.extent(quant))
.range([10, 100])
quantValue = qScale(7);
@Enjalot
Tutorial:
D3.geo
function draw(geo_data) {
"use strict";
var margin = 75,
width = 1400 - margin,
height = 600 - margin;
var svg = d3.select("body")
.append("svg")
.attr("width", width + margin)
.attr("height", height + margin)
.append('g')
.attr('class', 'map');
var projection = d3.geo.mercator()
.scale(150)
.translate( [width / 2, height / 1.5]);
var path = d3.geo.path().projection(projection);
var map = svg.selectAll('path')
.data(geo_data.features)
.enter()
.append('path')
.attr('d', path)
.style('fill', 'lightBlue')
.style('stroke', 'black')
.style('stroke-width', 0.5);
};
dimple.js
D3.js
- Protovis (http://mbostock.github.io/protovis/)
- Vega (https://trifacta.github.io/vega/)
- Prefuse (http://prefuse.org/)
Dimple.js
- NVD3 (http://nvd3.org/)
- Rickshaw (http://code.shutterstock.com/rickshaw/)
- Highcharts (http://www.highcharts.com/)
Tableau
- RAW (http://raw.densitydesign.org/)
- Chartio (https://chartio.com/)
- Plot.ly (https://plot.ly/)
Books
- The functional art - Alberto Cairo
- Data + Design - Infoactive
- Raw Data: Infographic Designer - Steven Heller & Rick Landers
- Visual Storytelling with D3 - Ritchie S. King
Online
- Data Visualization & D3.js (Udacity)
- Data Visualization (Coursera)
- Front-end Masters - @Enjalot (GitHub)
- Mike Bostock (link)
- Flowing Data (link)
- Visualising Data (link)
RESOURCES
david.alayon@socialnoise.com
¡Gracias!
@davidalayon

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