introduction to graphical presentation andy wang cis 5930-03 computer systems performance analysis

Introduction toGraphical Presentation

Andy WangCIS 5930-03

Computer SystemsPerformance Analysis

2

The Art of Graphical Presentation

• Reference Works• Types of Variables• Guidelines for Good Graphics Charts• Common Mistakes in Graphics• Pictorial Games• Special-Purpose Charts

3

Useful Reference Works

• Edward R. Tufte, The Visual Display of Quantitative Information, Graphics Press, Cheshire, Connecticut, 1983.

• Edward R. Tufte, Envisioning Information, Graphics Press, Cheshire, Connecticut, 1990.

• Edward R. Tufte, Visual Explanations, Graphics Press, Cheshire, Connecticut, 1997.

• Darrell Huff, How to Lie With Statistics, W.W. Norton & Co., New York, 1954

4

Types of Variables

• Qualitative– Ordered (e.g., modem, Ethernet, satellite)– Unordered (e.g., CS, math, literature)

• Quantitative– Discrete (e.g., number of terminals)– Continuous (e.g., time)

5

Charting Basedon Variable Types

• Qualitative variables usually work best with bar charts or Kiviat graphs– If ordered, use bar charts to show order

• Quantitative variables work well in X-Y graphs– Use points if discrete, lines if continuous– Bar charts sometimes work well for

discrete

6

Guidelines for Good Graphics Charts

• Principles of graphical excellence• Principles of good graphics• Specific hints for specific situations• Aesthetics• Friendliness

7

Principlesof Graphical Excellence

• Graphical excellence is the well-designed presentation of interesting data:– Substance– Statistics– Design

8

Graphical Excellence (2)

• Complex ideas get communicated with:– Clarity– Precision– Efficiency

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• Viewer gets:– Greatest number of ideas– In the shortest time– With the least ink– In the smallest space

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• Is nearly always multivariate• Requires telling truth about data

11

Principles of Good Graphics

• Above all else show the data• Maximize the data-ink ratio• Erase non-data ink• Erase redundant data ink• Revise and edit

12

Above All ElseShow the Data

y = 1E-05x + 1.3641

R2 = 0.0033

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0 5000 10000 15000File size (bytes)

Time to fetch (seconds)

Linear model

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Above All ElseShow the Data

y = 1E-05x + 1.3641

R2 = 0.0033

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1

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0 5000 10000 15000File size (bytes)

Time to fetch (seconds)

Linear model

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Maximize theData-Ink Ratio

1st Qtr

3rd Qtr

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80

90

East

West

North

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Maximize theData-Ink Ratio

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1st Qtr 2nd Qtr 3rd Qtr 4th Qtr

East West

North

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Erase Non-Data Ink

05

101520253035404550556065707580859095


East

West

North

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Erase Non-Data Ink

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80


Ea

st

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st

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rth

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Erase Redundant Data Ink

20.4

27.4

90

20.4

38.634.6

31.6

46.9 45 43.9

30.6

45.9

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80


Ea

st

We

st

No

rth

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Erase Redundant Data Ink

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Ea

st

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st

No

rth

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Revise and Edit

0102030405060708090

Qua

rter

ly S

ales


Default Microsoft Powerpoint Chart

EastWestNorth

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Revise and Edit

Remove Decorative Effects

0102030405060708090

100


Qua

rter

ly S

ales

EastWestNorth

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Revise and Edit

Remove Clutter

0102030405060708090

100


Qua

rter

ly S

ales

EastWestNorth

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Revise and Edit

Make Legends and Titles Simple to Interpret

0102030405060708090

100


Sales

East

West

North

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Revise and Edit

Eliminate Superfluous Ink

0102030405060708090

100


Sales

East

West

North

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Revise and Edit

Eliminate Red/Green Distinctions

0102030405060708090

100


Sales

East

West

North

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Revise and Edit

Choose Better Fonts

0102030405060708090

100


Sales

East

West

North

27

Specific Things to Do

• Give information the reader needs• Limit complexity and confusion• Have a point• Show statistics graphically• Don’t always use graphics• Discuss it in the text

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Give Informationthe Reader Needs

• Show informative axes– Use axes to indicate range

• Label things fully and intelligently• Highlight important points on the graph

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Giving Informationthe Reader Needs

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1 2 3 4

E

W

N

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Giving Informationthe Reader Needs

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Sales

in

Millions

MicrosoftContractSigned

East

North

West

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Limit Complexityand Confusion

• Not too many curves• Single scale for all curves• No “extra” curves• No pointless decoration (“ducks”)

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0

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60


0

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120 West

North

Northeast

Southwest

Mexico

Europe

Japan

East

South

International

Limiting Complexityand Confusion

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International Sales

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Millions

of

Dollars

Japan

MexicoEurope

Limiting Complexityand Confusion

34

Have a Point

• Graphs should add information not otherwise available to reader

• Don’t plot data just because you collected it

• Know what you’re trying to show, and make sure the graph shows it

35

Having a Point

• Sales were up 15% this quarter:

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140

1st Qtr 2nd Qtr

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Having a Point

User Time of Copy Benchmarks (Seconds)

0

0.01

0.02

0.03

0.04

1 Replica 2 Replicas 3 Replicas 4 Replicas

cp rcp

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Having a Point

0

1000000

2000000

3000000

4000000

5000000

Modem Ethernet ATM Satellite

Throughput

Latency

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Having a Point

0.001

0.01

0.1

1

10

100

1000

0.01 0.1 1 10 100 1000

Throughput (Mbits/sec)

Latency(ms) Ethernet

Modem

ATM

Satellite

39

Show Statistics Graphically

• Put bars in a reasonable order– Geographical– Best to worst– Even alphabetic

• Make bar widths reflect interval widths– Hard to do with most graphing software

• Show confidence intervals on the graph– Examples will be shown later

40

Don’t AlwaysUse Graphics

• Tables are best for small sets of numbers– Tufte says 20 or fewer

• Also best for certain arrangements of data– E.g., 10 graphs of 3 points each

• Sometimes a simple sentence will do• Always ask whether the chart is the best

way to present the information– And whether it brings out your message

41

Text Would HaveBeen Better

Dem Rep Indep

Carter

Reagan

Anderson

Lib Mod Cons

LibDems

ModDems

ConsDems Lib Ind Mod Ind Cons Ind

42

Discuss It in the Text

• Figures should be self-explanatory– Many people scan papers, just look at

graphs– Good graphs build interest, “hook” readers

• But text should highlight and aid figures– Tell readers when to look at figures– Point out what figure is telling them– Expand on what figure has to say

43

Aesthetics

• Not everyone is an artist– But figures should be visually pleasing

• Elegance is found in– Simplicity of design– Complexity of data

44

Principles of Aesthetics

• Use appropriate format and design• Use words, numbers, drawings together• Reflect balance, proportion, relevant scale• Keep detail and complexity accessible• Have story about the data (narrative

quality)• Do professional job of drawing• Avoid decoration and chartjunk

45

Use AppropriateFormat and Design

• Don’t automatically draw a graph– Mentioned before

• Choose graphical format carefully• Sometimes “text graphic” works best

– Use text placement to communicate numbers

– Very close to being a table

46

GNP: +3.8 IPG: +5.8 CPI: +7.7 Profits: +13.3

CEA: +4.7

DR: +4.5

NABE: +4.5

WEF: +4.5

CBO: +4.4

CB: +4.2

IBM: +4.1

CE: +2.9

NABE: +6.2

IBM: +5.9

CB: +5.5

DR: +5.2

WEF: +4.8

IBM: +6.6

NABE: +6.5

CB: +6.2

WEF: +21

DR: +10.5

IBM: +10.4

CE: +6.5

WEF: 6.8

CB: 6.7

NABE: 6.7

IBM: 6.6

DR: 6.5

CBO: 6.3

CEA: 6.3

Unempl: 6.0

About a year ago, eight forecasters were asked for

their predictions on some key economic indicators.

Here’s how the forecasts stack up against the

probable 1978 results (shown in the black panel).

(New York Times,

Jan. 2, 1979)

Using Text as a Graphic

47

The Stem-and-Leaf Plot

• From Tukey, via Tufte, heights of volcanoes in feet:

0|987665621|977196302|999877665444222110098503|8766554120995514264|99988443319294333611075|976666665544222100977316|8986654410777610657|988554311006521080738|653322122937

48

Choosinga Graphical Format

• Many options, more being invented all the time– Examples will be given later– See Jain for some commonly useful ones– Tufte shows ways to get creative

• Choose a format that reflects your data– Or that helps you analyze it yourself

49

Use Words, Numbers, Drawings Together

• Put graphics near or in text that discusses them– Even if you have to murder your word

processor

• Integrate text into graphics• Tufte: “Data graphics are paragraphs

about data and should be treated as such”

50

Reflect Balance, Proportion, Relevant

Scale• Much of this boils down to “artistic sense”• Make sure things are big enough to read

– Tiny type is OK only for young people!

• Keep lines thin– But use heavier lines to indicate important

information

• Keep horizontal larger than vertical– About 50% larger works well

51

Poor Balanceand Proportion

• Sales in the North and West districts were steady through all quarters

• East sales varied widely, significantly outperforming the other districts in the third quarter

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Better Proportion

• Sales in North and West districts were steady through all quarters

• East sales varied widely, significantly outperforming other districts in third quarter

0

50

100

Q1 Q2 Q3 Q4

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Keep Detail and Complexity Accessible

• Make your graphics friendly:– Avoid abbreviations and encodings– Run words left-to-right– Explain data with little messages– Label graphic, don’t use elaborate

shadings and a complex legend– Avoid red/green distinctions– Use clean, serif fonts in mixed case

54

An Unfriendly Graph

050

100150200250300350400450

Time

CP

FIND

FINDGREP

GREP

LS

MAB

RCP

RM

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A Friendly Version

0

100

200

300

400

1 2 3 4 5 6 7 8

Number of Replicas

Time in Seconds

Copy

Compile

Remove

Note almost no growth incompile/remove times

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Even Friendlier

0

100

200

300

400

Copy Compile Remove

Benchmark and Number of Replicas

Time in Seconds

Note slower growth incompile and remove times

1 Replica

8 Replicas(note departurefrom linearity)

57

Have a Story About the Data (Narrative

Quality)• May be difficult in technical papers• But think about why you are drawing graph• Example:

– Performance is controlled by network speed– But it tops out at high end– And that’s because we hit a CPU bottleneck

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Showing a StoryAbout the Data

0

20

40

60

0 2 4 6 8 10 12

Network Bandwidth (Mbps)

Transactionsper

SecondCPU bottleneck

reached

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Do a Professional Jobof Drawing

• This is easy with modern tools– But take the time to do it right

• Align things carefully• Check final version in format you will use

– I.e., print Postscript one last time before submission

– Or look at your slides on projection screen• Preferably in presentation room• Color balance varies by projector

60

Avoid Decorationand Chartjunk

• Powerpoint, etc. make chartjunk easy• Avoid clip art, automatic backgrounds, etc.• Remember: data is the story

– Statistics aren’t boring– Uninterested readers aren’t drawn by

cartoons– Interested readers are distracted

• Does removing it change message?– If not, leave it out

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Examples of Chartjunk

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Gridlines!Vibration

Pointless

Fake 3-D Effects

Filled “Floor” Clip Art

In or out?

Filled

“Walls”

Borders and

Fills Galore

Unintentional

Heavy or Double Lines

Filled Labels

Serif Font with

Thin & Thick Lines

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Common Mistakesin Graphics

• Excess information• Multiple scales• Using symbols in place of text• Poor scales• Using lines incorrectly

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Excess Information

• Sneaky trick to meet length limits• Rules of thumb:

– 6 curves on line chart– 10 bars on bar chart– 8 slices on pie chart

• But note that Tufte hates pie charts

• Extract essence, don’t cram things in

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Way Too Much Information

0

100

200

300

400

500

Time

cp

find

findgrep

grep

ls

mab

rcp

rm

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What’s ImportantAbout That Chart?

• Times for cp and rcp rise with number of replicas

• Most other benchmarks are near constant• Exactly constant for rm

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The Right Amountof Information

0

100

200

300

400

500

0 1 2 3 4 5 6 7 8 9Replicas

Timecp

mab

rm

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Multiple Scales

• Another way to meet length limits• Basically, two graphs overlaid on each

other• Confuses reader (which line goes with

which scale?)• Misstates relationships

– Implies equality of magnitude that doesn’t exist

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Some Especially Bad Multiple Scales

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5

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30

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40

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1 2 3 4

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Throughput

Response Time

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Using Symbolsin Place of Text

• Graphics should be self-explanatory– Remember that the graphs often draw the

reader in

• So use explanatory text, not symbols• This means no Greek letters!

– Unless your conference is in Athens...

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It’s All Greek To Me...

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12

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9

r

w

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Explanation is Easy

Waiting Time asa Function of Offered Load

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10

12

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9

Offered Load

WaitingTime

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Poor Scales

• Plotting programs love non-zero origins– But people are used to zero

• Fiddle with axis ranges (and logarithms) to get your message across– But don’t lie or cheat

• Sometimes trimming off high ends makes things clearer– Brings out low-end detail

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A Poor Axis Range

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A Logarithmic Range

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1 2 3 4

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A Truncated Range

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1 2 3 4

10000

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Using Lines Incorrectly

• Don’t connect points unless interpolation is meaningful

• Don’t smooth lines that are based on samples– Exception: fitted non-linear curves

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Incorrect Line Usage

0

100

200

300

400

500

0 1 2 3 4 5 6 7 8 9Replicas

Timecp

mab

rm

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Pictorial Games

• Non-zero origins and broken scales• Double-whammy graphs• Omitting confidence intervals• Scaling by height, not area• Poor histogram cell size

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Non-Zero Originsand Broken Scales

• People expect (0,0) origins– Subconsciously

• So non-zero origins are great way to lie• More common than not in popular press• Also very common to cheat by omitting

part of scale– “Really, Your Honor, I included (0,0)”

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Non-Zero Origins

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Us

Them

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Them

Us

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The Three-Quarters Rule

• Highest point should be 3/4 of scale or more

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Them

Us

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Double-Whammy Graphs

• Put two related measures on same graph– One is (almost) function of other

• Hits reader twice with same information– And thus overstates impact

0

20

40

60


Sales ($)

Units Shipped

85

OmittingConfidence Intervals

• Statistical data is inherently fuzzy• But means appear precise• Giving confidence intervals can make it

clear there’s no real difference– So liars and fools leave them out

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Graph WithoutConfidence Intervals

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Graph WithConfidence Intervals

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Scaling by HeightInstead of Area

• Clip art is popular with illustrators:

Women in the Workforce

1960 1980

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The Troublewith Height Scaling

• Previous graph had heights of 2:1• But people perceive areas, not heights

– So areas should be what’s proportional to data• Tufte defines lie factor: size of effect in

graphic divided by size of effect in data– Not limited to area scaling– But especially insidious there (quadratic effect)

90

Scaling by Area

• Same graph with 2:1 area:

Women in the Workforce

1960 1980

91

Poor Histogram Cell Size

• Picking bucket size is always problem• Prefer 5 or more observations per

bucket• Choice of bucket size can affect results:

02468

1012

5 10 15 20 25 30

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Principles ofGraphics Integrity

(Tufte)• Proportional representation of numbers• Clear, detailed, thorough labeling• Show data variation, not design variation• Use deflated money units• Don’t have more dimensions than data has• Don’t quote data out of context

93

Proportional Representation

of Numbers• Maintain lie factor of 1.0• Use areas, not heights, with clip art• Avoiding “decorative” graphs will do

wonders– Not too hard for most engineers!

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Clear, Detailed,Thorough Labeling

• Goal is to defeat distortion and ambiguity

• Write explanations on graphic itself• Label important events in the data

95

Show Data Variation,Not Design Variation

• Use one design for entire graphic• In papers, try to use one design for all

graphs• Again, artistic license is big culprit

96

Use Deflated Money Units

• Often necessary to show money over time– Even in computer science– E.g., price/performance over time– Or expected future cost of a disk

• Nominal dollars are meaningless• Derate by some standard inflation

measure– That’s what the WWW is for!

97

Don’t Have More Dimensions Than Data

Has• This gets back to the Lie Factor• 1-D data (e.g., money) should occupy

one dimension on the graph: not• Clip art is prohibited by this rule

– But if you have to, use an area measure

$1.00$2.00

98

Don’t Quote DataOut of Context

• Tufte’s example:

Traffic Deaths andEnforcement of Speed Limits

250

275

300

325

350

1954 1955 1956 1957

Before stricterenforcement

After stricterenforcement

99

The Same Data in Context

Connecticut Traffic Deaths, 1951-1959

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350

1950 1951 1952 1953 1954 1955 1956 1957 1958 1959 1960

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Special-Purpose Charts

• Tukey’s box plot• Histograms• Scatter plots• Gantt charts• Kiviat graphs

101

Tukey’s Box Plot

• Shows range, median, quartiles all in one:

• Tufte can’t resist improvements:

or

or even

minimum

maximum

quartile

quartile

median

102

Histograms

• Tufte improves everything about them:

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1st 2nd 3rd 4th

Quarter

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Scatter Plots

• Useful in statistical analysis• Also excellent for huge quantities of

data– Can show patterns otherwise invisible

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Better Scatter Plots

• Again, Tufte improves the standard– But it can be a pain with automated tools

• Can use modified Tukey box plot for axes

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3040

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105

Gantt Charts

• Shows relative duration of Boolean conditions

• Arranged to make lines continuous– Each level after first follows FTTF pattern

0 20 40 60 80 100

CPU

I/O

Network

106

Kiviat Graphs

• Also called “star charts” or “radar plots”• Useful for looking at balance between

HB and LB metrics

107

A Few Examples

• A bad graph• Two good graphs

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A Very Bad Graph

109

A Good Graph: Sunspots

110

A Superb Graph:DEC Traces

White Slide

introduction to graphical presentation andy wang cis 5930-03 computer systems performance analysis

Documents

readerdont plot data

graphics press

thedataink ratio

dogive information

envisioning information

continuousbar charts

reader needslimit complexity

specific things