Sandra Becker
Data visualization implies an enormous power of democratizing relevant information.
SANDRAVIZ.COM | 2023
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INTRO
B. SCHNEIDERMANN
H. ROSLING
H. THOREAU
01
A. CAIRO
E. TUFTE
WHAT IS DATA VIZ?
01 | THE OBJECTIVE
Graphical excellence is that which gives to the viewer the greatest number of ideas in the shortest time with the least ink in the smallest space.
E. TUFTE
E.VELSON, 2011, PARA,. 6
01
01 BIG DATA ALLOWS FOR PATTERN DETECTION
01
01 | VISUAL ENCODINGS
01 | EXAMPLE
01 | OBSERVATION VS. PREDICTION PLOT
01 | OBSERVATION VS. PREDICTION PLOT
01 | VISUAL ENCODINGS
01 | VISUAL ANIMATION TO PRESENT SIMULATION
01 | SCROLL-Y-TELLING TO EXPLAIN MACHINE LEARNING
01 | ANIMATED VISUALIZATION AS THE FLOW OF THE STORY
01 | FINAL CONCLUSION
M. BOSTOCK
01
01 | COMPLEX CONCEPTS VISUALLY EXPLAINED
01 | STATISTICAL CONCEPTS EXPLAINED THROUGH INTERACTIIVE VIZ
01 | DATA ART
WIKIPEDIA
01 | CONSTELLATION MAPS
01 | VISUAL EONCODINGS
PRACTICE
DEFINE
OBJECTIVES
DATA
EXPLORE
02 | THE COMMON FLOW
M. STEFANER
DEFINE
OBJECTIVES
DATA
IDEA
RESULT
TOOL
EXPLORE
DESIGN
CREATE
REVIEW
02 | THE COMMON FLOW
02 | APPLIES TO A DATAVIZ PROJECT TOO
DATAVIZ TYPE
02 | DATAVIZ CATALOG
02 | 25 VISUALIZATIONS 1 DATASET
02 | EXAMPLES WITH CODE
THE SPAGHETTI PLOT
02 | STANDARD LINE CHARTS FOM THE 90s
02 | CHART EVALUATION
02 | LINE CHART WITH HIGHLIGHT OPTION
02 | CHART EVALUATION
02 | LINE CHART WITH FILTER OPTION
02 | CHART EVALUATION
02 | SMALL MULTIPLE AREA CHART
02 | SMALL MULTIPLE AREA CHART
02 | SMALL MULTIPLE PLUS FILTER & LINKED HIGHLIGHT OPTION
02 | SMALL MULTIPLE PLUS FILTER & LINKED HIGHLIGHT OPTION
02 | SMALL MULTIPLE PLUS FILTER & HIGHLIGHT OPTION
02 | SMALL MULTIPLE PLUS FILTER & HIGHLIGHT OPTION
DATAVIZ TOOLS
02 | ALL RESOURCES - TOOLS
02 | WEB BASED TOOLS FOR QUICK EXPLORATION
02 | VISUALIZATION FOR DATA SCIENTISTS
02 | INDUSTRY STANDARDS
02 | EXPLORATIVE ANALYSIS
02 | DYNAMIC VISUALIZATION FOR THE WEB
02 | LOCATION BASED DATA MAPPING
02 | WebGL
GOOD & BAD VIZ
02
02 | WHAT MAKES A GODO VIZ
02
02 | OVERPLOTTING PROBLEM
02 | SHOW THE DATA
02 | AWARD WINNERS
02 | TIPS & TRICKS
02 | GOOD PRACTICE
VIZ
02 | LEARNING FROM THE BAD
VISUAL ENCODING
03 | SEEING = UNDERSTANDING
03 | DIFFERENT TYPES OF VISUAL ENCODING
03 | DEFINITION
When a graph is constructed, quantitative and categorical information is encoded, chiefly through position, shape, size, symbols, and color.
When a person looks at a graph, the information is visually decoded by the person’s visual system. A graphical method is successful only if the decoding is effective.
No matter how clever and how technologically impressive the encoding, it fails if the decoding process fails.
Informed decisions about how to encode data can be achieved only through an understanding of this visual decoding process, which we call graphical perception.
CLEVELAND & MCGILL
03 | EXPLANATION
How do we make sure the audience is able to decode the information?
Legends (e.g. size bubble legend to endorse comparison)
Labels (if there is enough space you can add labels directly)
Keys (e.g. color scale: provide a key for each one)
COLOR
03 | COLOUR WHEEL
03 | RULES
03 | DON'T USE COLOURS TO SHOW INTENSITY
03 | SUPPORT TOOLS | COLOUR BREWER
03 | ADVANCED TOOLS
03 | ADVANCED TOOLS
03 | COLOR CHECK
03
ENVIRONMENT | NATURE | PERMISSION
03
03
SUN | HAPPINESS | PLAYFUL
03
03
DANGER | PASSION | BLOOD | LOVE | AGGRESSION
03
03
WATER | COOL | QUIETNESS | HOPE
03
03
DEATH | LUXURY | SOPHISTICATION
03
03
WEDDING | PURE | INNOCENT
03
03 | NEON COLOUR WITH DARK BACKGROUND
03 | ENDORSEMENT OF DIRECT COMPARISON
03 | OVERLAPPING PATTERN STRUCTURES
03 | PATTERN STRUCTURES THROUGH COLORS
03 | INTUITIVE CATEGORIZATION THROUGH COLORS
POSITION
03 | POSITIONING IN THE COORDINATE SYSTEM
03 | LEFT RIGHT RELATIONSHIP | COMPARISON
03 | ORDERING FROM TOP LEFT TO BUTTOM RIGHT
03 | USING COLORS TO INDICATE GOOD VS. BAD
REDUNDANCY
03 | LABELING & LEGEND ARE SHOWING THE SAME INFORMATION
03 | COLOR SUPPORTS THE POSITION ENCODING
HUMAN PERCEPTION
USERS ARE
HUMANS
04 | SAME MEAN, VARIANCE AND CORRELATION - SAME DATA?
04 | SCATTER PLOT SHOWS THE DIFFERENCES
04 | HOW MANY MORE POINTS ARE IN THE QUADRANT BELOW?
04 | HOW MANY MORE POINTS ARE IN THE QUADRANT BELOW?
04 | THE ABSOLUTE DIFFERENCE IS THE SAME
04 | WHICH BAR IS LARGER?
04 | WHICH BAR IS LARGER?
04 | IS THE COLOR OF THE QUADRANT BEHIND THE LETTER A & B THE SAME?
04 | IS THE COLOR OF THE QUADRANT BEHIND THE LETTER A & B THE SAME?
USERS
04 WHO ARE THE USERS?
04 | AVOID CHARTJUNK
04 | PRESENTING TRUTH
04 | PRESENTING TRUTH
04 | SHOWING REAL PROPORTIONS
04 | HANDELING OUTLIERS
04 | HANDELING OUTLIERS THROUGH RE-SCALING
04 | GENERAL WAYS OF VISUALIZING OUTLIERS
VISUAL COMPLEXITY
Even publications, such as NY times assume that people are intelligent enough to read complex prose, but too stupid to read complex graphics.
E. TUFTE
04
04 | NUMBER OF VISUAL ENCODINGS
04 | LEVEL OF INNOVATION
04 | LEVEL OF INNOVATION
04 | GUIDANCE
By Sandra Becker
Data visualization implies an enormous power of democratizing relevant information.