Tufte
Visual Display of Quantitative Information
Tufte defines visualization: "data graphics visually display
measured quantities by means of the combined use of points, lines,
a coordinate system, numbers, symbols, words, shading, and color. " p.
9
"statistical graphics  length and area to show quantity,
timeseries, scatterplots, and multivariate displays" p. 9
**"at their best, graphics are instruments for reasoning
about quantitative information. Often the most effective
way to describe, explore, and summarize a set of numbers  even
a very large set  is to look at pictures of those numbers." p.
9
In this book, emphasis on [1] maximizing principles, [2] empirical
measures of graphical performance, and [3] the sequential improvement
of graphics through revision and editing
"Insights are to be gained, I believe, from theories of what makes for
excellence in art, architecture, and prose." p. 9
Tufte's rules:
"Graphical displays should:
 show the data
 induce the viewer to think
about the substance rather than about methodology, graphic design, the technology
of graphic production, or something else
 avoid distorting what the
data have to say
 present many numbers in
a small space
 make large data sets coherent
 encourage the eye to compare
different pieces of data
 reveal the data at several
levels of detail, from a broad overview to the fine structure
 serve a reasonably clear
purpose: description, exploration, tabulation, or decoration
 be closely integrated with
the statistical and verbal descriptions of a data set
[1] Principles of Graphical Excellence
 Graphical excellence is
the welldesigned presentation of interesting data  a matter of substance,
of statistics, and of design
 Graphical excellence consists
of complex ideas communicated with clarity, precision, and efficiency.
 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
 Graphical excellence is
nearly always multivariate
 And graphical excellence
requires telling the truth about the data.
Preoccupations that keep us from taking graphics seriously:
 assumption that it is easy
to lie
 assumption "that data
graphics were mainly devices for showing the obvious to the ignorant"
John Tukey's work in 197072  "graphics were used
as instruments for reasoning about quantitative information" p.
53.
Graphical Integrity
 The representation of numbers,
as physically measured on the surface of the graphic itself, should be directly
proportional to the numerical quantities represented.
 Clear, detailed, and thorough
labeling should be used to defeat graphical distortion and ambiguity. Write
out explanations of the data on the graphic itself. Label important
events in the data.
 Show data variation, not
design variation.
 In timeseries displays
of money, deflated and standardized units of monetary measurement are nearly
always better than nominal units.
 The number of informationcarrying
(variable) dimensions depicted should not exceed the number of dimensions in
the data
 Graphics must not quote
data out of context.
"Five principles in the theroy of data graphics produce substantial
changes in graphical design. .."
 Above all else show the
data
 Maximize the dataink ratio
 Erase nondataink
 Erase redundant dataink
 Revise and edit" p.
105
Chapter 5: Chartjunk: Vibrations, Grids, and Ducks
 Forgo chartjunk
including: moire vibration, the grid, and the duck
Chapter 6: DataInk Maximization and Graphical Design
Chapter 7: Multifunctioning Graphical Elements
Chapter 8: Data Density and Small Multiples
"Welldesigned small multiples are
 inevitably comparative
 deftly multivariate
 shrunken, highdensity graphics
 usually based on a large
data matrix
 drawn almost entirely with
dataink
 efficient in interpretation
 often narrative in content,
showing shifts in the relationship between variables as the index variable
changes (thereby revealing interaction or multiplicative effects).
Small multiples reflect much of the theory of data graphics:
 For nondataink, less is
more
 For dataink, less is a
bore
Chapter 9: Aesthetics and Technique in Data Graphical Design
 "Graphical
elegance is often found in simplicity of design and complexity
of data" p. 177
"...some guides for enhancing the visual quality of routine,
workaday designs. Attractive displays of statistical information
 have a properly chosen format
and design
 use words, numbers, and
drawing together
 reflect a balance, a proportion,
a sense of relevant scale
 display an accessible complexity
of detail
 often have a narrative quality,
a story to tell about the data
 are drawn in a professional
manner, with the technical details of production done with care
 avoid contentfree decoration,
including chartjunk
