IT training mathematica data visualization saquib 2014 09 17

MathematicaDataVisualization


TableofContents
MathematicaDataVisualization
Credits
AbouttheAuthor
AbouttheReviewers
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Preface
Whatthisbookcovers
Whatyouneedforthisbook
Whothisbookisfor
Conventions
Readerfeedback
Customersupport
Downloadingtheexamplecode
Downloadingthecolorimagesofthisbook
Errata
Piracy
Questions
1.VisualizationasaTooltoUnderstandData
Theimportanceofvisualization
Typesofdatasets
Tables
Scalarfields

Timeseries
Graphs
Text
Cartographicdata


Mathematicaasatoolforvisualization
GettingstartedwithMathematica
Creatingandselectingcells
Evaluatingacell
Suppressingoutputfromacell
Cellformatting
Commenting
Abortingevaluation
Upcomingchapters
Furtherreading
Summary
2.DissectingDataUsingMathematica
Datastructuresandcorelanguages
Introducinglists
Nestedlists
Matrices
Constructinglistsprogrammatically
Tableentrieswithmultipleelements
Accessingelementsfromalist
Applyingsetoperationsonlists
Functionsandconditionals
Declaringandusingfunctions
Conditionals
Furthercorelanguage

Dataimportingandbasicplots
ImportingdataintoMathematica
SetDirectory[]andNotebookDirectory[]
Loadingthedataset
Basicplottingfunctions
ListPlot
Stylingourplots


Plotlegends
3Dpointplots
Logplots
Furtherreading
Summary
3.TimeSeriesandScientificVisualization
Periodicpatternsintimeseries
Sectorcharts
SimulatingInternetactivity
SectorChartanditsoptions
Interactivevisualizationoffinancialdata
TheDateListPlotfunction
Addinginteractivity–preliminaries
Intermission–GraphicsandShow
Addinginteractivity–DynamicandRefresh
Isocontourandmolecularvisualization
Introductiontoisocontours
Exampleproject–proteinmoleculevisualization
Loadingandvisualizingtheproteinmolecule
Preparingtheisocontourplots
Addinginteractivity–manipulate

Isosurfaceandstyling
Thinkinglikeavisualizationscientist–isovalueanalysis
Furtherreading
Summary
4.StatisticalandInformationVisualization
Statisticalvisualization
Theswissbanknotesdataset
Histogramsandcharts
Histogram
PairedHistogram


Histogram3D
PieChart
BubbleChart
Choosingappropriateplots
Aglimpseofhigh-dimensionaldata
Similaritymaps
Projectinginformationtolowdimensions
Visualizinggenuineandcounterfeitclusters
Similaritymapforsmallerdatasets
Thingsthatcan(andwill)gowrong
Employingthewrongdistancemetric
Choosingamisleadingcolormap
Textvisualization
Amodifiedwordcloud
Cleaningthedata
Thebasicalgorithm
Codeandexplanation
Graphsandnetworks

Abasicgraphvisualization
RepresentinggraphsinMathematica
VisualizingtheLesMisérablesnetwork
Highlightingcentralitymeasures
Othergraphlayouts
3Dlayouts
Chorddiagrams
Codeandexplanation
Tweakingthevisualization
Furtherreading
Summary
5.MapsandAesthetics
Mapvisualization


TheGeoGraphicspackage
Amapofourcurrentlocation
Plottingapathonthemap
InteractivityinGeoGraphics
Anatomyofamapvisualizationengine
Thevisualinterface
Codeandexplanation
Aestheticsinvisualization
Choosingtherightcolormap
Therainbowcolormapismisleading
Understandinghueandluminance
Somebettercolormaps
Designingtherightinterface
DeployingMathematicavisualizations
Lookingforward

Furtherreading
Summary
Index



MathematicaDataVisualization



MathematicaDataVisualization
Copyright©2014PacktPublishing
Allrightsreserved.Nopartofthisbookmaybereproduced,storedinaretrievalsystem,
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Firstpublished:September2014
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Credits
Author
NazmusSaquib
Reviewers
RogerJ.Brown
WenjunDeng
KristjanKannike
CommissioningEditor
AkramHussain
AcquisitionEditor
MohammadRizvi
ContentDevelopmentEditor
AnilaVincent
TechnicalEditors
VenuManthena
AmanPreetSingh
CopyEditors
SayaneeMukherjee
AlfidaPaiva
ProjectCoordinator
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Proofreaders
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Indexers
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ProductionCoordinator
ManuJoseph
CoverWork
ManuJoseph




AbouttheAuthor
NazmusSaquibisaresearcherattheMITMediaLabinCambridge,MA,wherehe
worksondatavisualization,machinelearning,andsocialcomputingprojects.Hehasa
bachelor’sdegreeinPhysicsandamaster’sdegreeinComputationalEngineeringand
AppliedMathematics.Saquibhasbeenprogramming3Dgamessincemiddleschool.Asa
result,hehasdevelopedandmaintainsakeeninterestingameengines,graphics,and
visualization.Throughouthisacademicyears,heworkedonawiderangeofresearch
projects,includingacoustics,particlephysics,augmentedreality,socialdatamining,and
uncertaintyquantification.Saquibisalsointerestedintheapplicationsofcreative
computingineducationandsocialwelfare.



AbouttheReviewers
RogerJ.BrownisthePresidentofIMOJIM,Inc.,oneoftheoldestcommercial
investmentfirmsinSanDiego,whichisnowcompletingitsfifthdecade.Hisexperience
includesnumerousconsultingandexpertwitnessassignments,andownershipor
originationofloansonvariouspropertiesinsevenstatesoftheUS.HeobtainedhisPhD
inFinancefromPennsylvaniaStateUniversityin2000,writinghisdissertationonLevystable(non-normal,andheavy-tailed)returndistributions.HeistheauthorofPrivateReal
EstateInvestment,publishedbyAcademicPress,whichisnowinitssecondedition.
WenjunDengisaComputationalPhysicistatPrincetonUniversityandPrincetonPlasma

PhysicsLaboratory.HeobtainedhisBSfromtheUniversityofScienceandTechnologyof
Chinain2006,andhisPhDinPhysicsfromtheUniversityofCalifornia,Irvinein2012.
Hisresearchinterestsincludemodelingandsimulationsoffusionplasmasandlaserexcitedhigh-energy-densityplasmas.Tocomprehensivelyunderstandthesecomplex
plasmas,whicharecomposedofahugenumberofelectricallychargedionsandelectrons
aswellaselectromagneticfields,isoneofthemostdifficultchallengesinhumanhistory.
Toadvancethefrontierofthisfield,heworkswithhiscollaboratorstodevelop,debug,
optimize,andrunlarge-scalesimulationsonworld-leadinghigh-performancecomputing
facilities.Bycarefullyanalyzingandvisualizingthesimulationdata,heisabletodigout
theunderlyingphysicalprinciplesandthusabletopredictandoptimizethebehaviorsof
theseplasmasinexperiments.
IwouldliketothankmywifeLiangforhercontinuousencouragementandsupport.
KristjanKannikeisaTheoreticalParticlePhysicistattheNationalInstituteofChemical
PhysicsandBiophysicsinEstonia.HeusesMathematicadailytosimulateandvisualize
modelsofhigh-energyphysics.



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