Radar chart - Wikipedia

A radar chart is a graphical method of displaying multivariate data in the form of a two-dimensional chart of three or more quantitative variables ... Radarchart FromWikipedia,thefreeencyclopedia Jumptonavigation Jumptosearch Typeofchart "Spiderchart"redirectshere.FortheextensionofEulerdiagrams,seeSpiderdiagram. ExamplestarplotfromNASA,withsomeofthemostdesirabledesignresultsrepresentedinthecenterThisspiderchartrepresentstheallocatedbudgetversusactualspendingforagivenorganization. Aradarchartisagraphicalmethodofdisplayingmultivariatedataintheformofatwo-dimensionalchartofthreeormorequantitativevariablesrepresentedonaxesstartingfromthesamepoint.Therelativepositionandangleoftheaxesistypicallyuninformative,butvariousheuristics,suchasalgorithmsthatplotdataasthemaximaltotalarea,canbeappliedtosortthevariables(axes)intorelativepositionsthatrevealdistinctcorrelations,trade-offs,andamultitudeofothercomparativemeasures.[1] Theradarchartisalsoknownaswebchart,spiderchart,spidergraph,spiderwebchart,starchart,[2]starplot,cobwebchart,irregularpolygon,polarchart,orKiviatdiagram.[3][4]Itisequivalenttoaparallelcoordinatesplot,withtheaxesarrangedradially. Contents 1Overview 2Applications 3SoftwareImplementation 3.1CodeExample 4Usage 5Limitations 5.1Artificialstructure 5.2Datasetsize 6Example 7Alternatives 8Seealso 9References 10Externallinks Overview[edit] Theradarchartisachartand/orplotthatconsistsofasequenceofequi-angularspokes,calledradii,witheachspokerepresentingoneofthevariables.Thedatalengthofaspokeisproportionaltothemagnitudeofthevariableforthedatapointrelativetothemaximummagnitudeofthevariableacrossalldatapoints.Alineisdrawnconnectingthedatavaluesforeachspoke.Thisgivestheplotastar-likeappearanceandtheoriginofoneofthepopularnamesforthisplot.Thestarplotcanbeusedtoanswerthefollowingquestions:[5] Whichobservationsaremostsimilar,i.e.,arethereclustersofobservations?(Radarchartsareusedtoexaminetherelativevaluesforasingledatapoint(e.g.,point3islargeforvariables2and4,smallforvariables1,3,5,and6)andtolocatesimilarpointsordissimilarpoints.)[5] Arethereoutliers? Radarchartsareausefulwaytodisplaymultivariateobservationswithanarbitrarynumberofvariables.[6]Eachstarrepresentsasingleobservation.Typically,radarchartsaregeneratedinamulti-plotformatwithmanystarsoneachpageandeachstarrepresentingoneobservation.[5]ThestarplotwasfirstusedbyGeorgvonMayrin1877.[7][8]Radarchartsdifferfromglyphplotsinthatallvariablesareusedtoconstructtheplottedstarfigure.Thereisnoseparationintoforegroundandbackgroundvariables.Instead,thestar-shapedfiguresareusuallyarrangedinarectangulararrayonthepage.Itissomewhateasiertoseepatternsinthedataiftheobservationsarearrangedinsomenon-arbitraryorder(ifthevariablesareassignedtotheraysofthestarinsomemeaningfulorder).[9] Applications[edit] Themainapplicationofradarchartsistomeasuremultivariabledatabeingsharedamongsimilargroups,people,orobjects.Thismeansradarchartshaveanincrediblywidevarietyofusesinfieldsincludingathletics,performancemetrics,lifesciences,education,andbusinessamongmanyothers.[10]Theseapplicationsallowresearcherstovisualizedataandhelpthemcompare,analyze,andeffectivelymakedecisionsaboutdatasetstheyarelookingatbasedontheinsightsprovidedbythechartedvariables.[11] Figure3.Aradarchartdepictingstandardbattingstatisticsfromthe2021MLBSeason.2021MVPShoehiOhtani,green,canbeseenperformingfarbetterthantheDH,red,andMLB,blue,averagesforthatseason,contributingtohiswin.Noticethoughthathealsostrikesoutmoreoften,likelybeingtradeoffforhisincreasedsluggingpercentage.Thedatacomesfromhttps://www.baseball-reference.com/. Radarchartscommonlyusedinsportstochartplayers'strengthsandweaknesses.[12]Thisisdonebycalculatingvariousstatisticsrelatedtotheplayerthatcantrackedalongthecentralaxisofthechart.Examplesincludeabasketplayersshotsmade,rebounds,assists,etc.,orthebattingorpitchingstatsofabaseballplayer.Thiscreatesacentralizedvisualizationofthestrengthsandweaknessesofaplayer,andifoverlappedwiththestatisticsofotherplayersorleagueaverages,candisplaywhereaplayerexcelsandwheretheycouldimprove.[13]Theseinsightsintoplayerstrengthsandweaknesscouldprovecrucialtoplayerdevelopmentasitallowscoachesandtrainerstoadjustaplayer'strainingregimenttohelpimproveontheirweaknesses.Theresultsoftheradarchartcanalsobeusefulinsituationalplay.Ifabatterisshowntohitpoorlyagainstleft-handedpitching,thenhisteamknowstolimithisplateappearancesagainstleft-handedpitchers,whiletheopposingteammaytrytoforceasituationwherethebatterisforcedtohitagainstthepitcher.Whenusedforcomparison,theycanalsoillustratehowgoodanathleteis,suchasbyahalloffamecandidatetootherhalloffamecandidates. Anotherapplicationofradarchartsisthecontrolofqualityimprovementtodisplaytheperformancemetricsvariousobjectsincludingcomputerprograms,[14]computers,phones,vehicles,andmore.Computerprogrammeroftenuseanalyticstotesttheperformanceoftheirprogramsversusothers.Anexampleofthiswhereradarchartsmaybeusefulistheperformanceanalysisofvarioussortingalgorithms.Aprogrammercouldgatherupseveraldifferentsortingalgorithmssuchasselection,bubble,andquick,thenanalyzetheperformanceofthesealgorithmsbymeasuringtheirspeed,memoryusage,andpowerusage,thengraphtheseonaradarcharttoseehoweachsortperformsundervarioussizesofdata.Anotherperformanceapplicationismeasuringtheperformanceofsimilarcarsagainsteachother.Aconsumercouldlookatvariablessuchasthecars’topspeed,milespergallon,horsepower,andtorque.Thenafterusingaradarcharttovisualizethedata,theycoulddecideonwhatcarisbestforthembasedontheresults. Figure4.Aradarchartillustratingthedifferencesinperformancemetricsofasedan,sportscar,andpickuptruck.Theradarchartcouldbeusefultoshopperlookingtofindthebestcartofittheirneeds,withthedifferentverticesofthechartshowingwhereeachcarperformswellandwhereeachperformspoorly.Thedataisgeneralizedanddoesnotcomefromaspecificsource. Onemoremajorusageofradarchartsisinlifesciences.Radarchartscanbeusedforwideawayofrelateddatasetssuchasstrengthsandweaknessofdrugsandothermedications.[15]Usingtheexampleoftwoanti-depressants,aresearchercanrankvariablessuchasefficacy,sideeffects,cost,etc.onascaleofonetoten.Theycouldthengraphtheresultsusingaradarcharttoseethespreadofvariablesandfindhowthediffer,suchasoneanti-depressantbeingcheaperandquickeracting,butnothavinggreatreliefovertime.Meanwhile,theotheranti-depressantprovidesstrongerreliefandholdsupbetterovertimebutismoreexpensive.Anotherlifescienceapplicationisinpatientanalysis.Radarchartscanbeusedtographthevariablesoflifeaffectingaperson'swellness,andthenbeanalyzedtohelpthem.Amorespecificexampleisinthecaseofathletes,who’svariouswellnesshabitssuchassleep,diet,andstressaremonitoredtomakesuretheystayinpeakphysicalcondition.[16]Ifanyareaswouldbeshowndipping,doctorsandtrainerscouldstepintoassisttheathleteandimprovetheirwellness. Theradarchartisanincrediblyusefulandpowerfultoolfordatavisualization.Thewidearrayoffieldstheycanbeappliedto,andthemultitudeofwaystheycanusedinthosefieldsmakesthemamustlearnaspectofdatamininganddataanalytics.Theyareincrediblyusefulforthefindingperformanceofdifferentdatasetsrelatedbythesamemultivariablesetofdata,andmakingdecisionsbasedtheanalysisofthosedatasets.Additionally,theyhaverelativelyeasytoreaddesignsthatcanchangecolorstohelpdifferentiatetheobjectsbeinglookedat,userelativelylessspacecomparedtoothergraphs,andoverallhaveasmoothandpresentablelooktothem.Radarchartshavesomedrawbacks,suchastryingtousethemwhenthevariablesaremeasuredonscalesthatarenotclosetoeachother,andtheytendtoworkbestwithlessthaneighttotenvariablesandgroupsofthreeorfewerobjects.[17]Despitethesedrawbacks,radarchartsareoneofthebesttoolsinadataanalyticstoolbagforbothprofessionalsandenthusiast. SoftwareImplementation[edit] SoftwarecanbeusedtogenerateRadarChartsinanefficientmanner.Pythonisoneexample.WithinPythondifferentlibrariesofcodecanbeaccessedwithdifferentfunctionalities.PlotlyisausefulgraphinglibraryforRadarChartsinPython.PlotlysupportsmultipletypesofRadarCharts. TocreateabasicRadarChartusingPlotlyyouwillneedtodefineafigurewhichconsistsoftwolistsofdata,theradiiandthecorrespondingmagnitudevalues.NextPlotlyrequiresyoutoupdatethefigure'slayoutwhichincludesaspectssuchasradialaxisvisibilityandwhetherornotthereisalegendtothegraph.Oncethisiscompleted,allthatislefttodoistocalltheshowfunctiononyourfigureobjectwhichwillproducetheRadarChart.[18] TocreateamultipletraceRadarChartusingPlotlytheprocessismostlythesameasabovewiththebasicRadarChartbutwithonedifference.Similartothestepsaboveyoufirstcreateafigureobject,butnowinsteadofimmediatelyfillingthisfigurewithdatayouinsteadneedtocalltheadd_tracefunctionforeachtraceyouwanttoadd.Withintheadd_tracefunctiontheRadarChart'sradiiandmagnitudevaluesareinputtedfortheirrespectivetrace.[18] PlotlyisnottheonlylibraryavailabletoPythontoproduceaRadarChart,andPythonisnottheonlyprogramminglanguagetheycanbeproducedin.PlotlystandsoutasagreatoptionforproducingRadarChart'sbecauseitiseasytouseandflexible.Thelogicissimpletofollowandwelldocumentedontheirwebsitewhichisreferencedabove.Theoptiontoaddtracesortojustuseonemakeitflexible.Pythonisagoodchoiceforprogrammingwithdataanalysis.Newlibrariesarealwaysbeingcreatedtogowiththeplethorathatalreadyexistandthelearningcurveforthelanguageisverylowmakingitagoodchoiceforeventhosewithlimitedprogrammingexperience. CodeExample[edit] #ExampleRadarChartwithMultipleTrace #Requiredimportstatementtousethelibrary importplotly.graph_objectsasgo #Defineafigure fig=go.figure() #Calltheadd_tracefunction fig.add_trace(go.Scatterpolar( r=[] theta= fill='toself' name='' )) #Repeatthelastfunctioncallforeachtraceyouwanttoadd fig.add_trace(go.Scatterpolar( r=[] theta= fill='toself' name='' )) #Updatethefigure'slayout fig.update_layout( polar=dict( radialaxis=dict( visible=True, ), ), ) #DisplaytheRadarChart fig.show() Usage[edit] Figure5. Theradarchartshows2setsofcommunities(seealsoCommunityStructure)thatconsistofconnectedgenomicwindowswhichseethesameNP(thenamesofthespokeswithinthepentagram).Inavisualanalysis,wecandeterminethatthetwocommunitiesarecloseinthattheyseesimilaramountsofthegivenNP's.ThedatapointsarerepresentedasapercentageofthecommunitythatseetheNP. Asmentionedpreviouslytheusageofradarchartsisforabettervisualanalysisoftwoormoresetsofdatapoints.Oftensomeusagesofaradarchartaretoshowtheattributesofthingssuchasvideogamecharacters,sportsplayers,andsoon.Conversely,radarchartsarealsousedwidelyinacademicandresearchcategoriestoallowvisualanalysisofdatasetstothenfurtherexploremorerigorously.Weareabletoseeoutliers,clusters(seealsoClusterAnalysis),andothertrendanalysiswithinthedatathatmayotherwisebehardertointerpretwhilevisuallyviewingthedatapointsetitself.[19]AnexampleasshowninFigure5isonesuchusageofaradarchart.Inthisinstance,weutilizetheradarcharttovisualizetwogenomicwindowstoNP's(seealsoGenomearchitecturemappingandPurinenucleosidephosphorylase)thattheymayormaynotpossess.[20]OurdatasetconsistsoffourteennumbersthatrepresentthepercentageofNP'sthatourgenomicwindowshaveseen.ThatistosaythatthewindowscontainthoseNPsequences. Thedirectimplementationfortheresultofthisradarchartisasfollows: PythonCode: #Createalistofnamesforthespokesofthechart,theseourtheNP’sasmentionedabove labels=['Hist1','LAD','Vmn','RNAPII-S2P','RNAPII-S5P','RNAPII-S7P','Enhancer','H3K9me3','H3K20me3','H3K36me3','NANOG','pou5f1','sox2','CTCF-7BWU'] #Gethowmanyspokestherewillbeonthechart,whichishowmanylabelswehave N=len(labels) #Callthemainfunctiontocreatetheradarchart theta=radar_factory(N,frame='polygon') #Initializeourgivendata.Thiswillbealistofnumbersthatwillrepresentthepointsonthechart case_data=[(7.27,61.81,49.09,20.0,45.45,34.54,25.454545454545453,16.36,29.09090909090909,29.09,20.0,23.63,18.18,16.36),(10.52,59.64,49.12,24.561,49.12,36.84,21.05,10.52,24.56,26.31,19.29,22.80,21.052631578947366,22.80)] #Givethesizeofthechart fig,ax=plt.subplots(figsize=(6,6),subplot_kw=dict(projection='radar')) fig.subplots_adjust(top=0.85,bottom=0.05) #Theintervalsoftheringswithintheradarchart ax.set_rgrids([0,5,10,15,20,25,30,35,40,45,50,55,60,65,70]) #Thetitleoftheradarchart title='WikiArticleRadarChartExample' ax.set_title(title,position=(0.5,1.1),ha='center') #Fillinthegraphwithfromoutdata fordincase_data: line=ax.plot(theta,d) ax.fill(theta,d,alpha=0.15) #Setthenameswithinthechartfromourlistofnames ax.set_varlabels(labels) #Addlegendtotop-leftplot legend=plt.legend(['Community1','Community2'],loc=(0.9,.95),labelspacing=0.1,fontsize='small') #Showgraph plt.show() Note:Thecodeimplementationaboveisutilizingradar_factory’sradarchartimplementationalongwithmatplotlibandotherpackages.Thisisfunctionalcodethatwillworkifyoucopyandpastetheradar_factoryimplementationandthecodeasseenabove.[21] Withinthisusageoftheradarchartourgivendatapointswereverycloseinproximitytoeachother.Duetothis,wecouldhavevisuallydeterminedthatthewindowswerecloseinvaluetoeachother.Thusinthisrepresentation,theimportancecomesfromitsvisualaspecttoshowthedatapointsinaneasyandagreeableformatasshown.NowpreviewingtheradarchartitselfwecanvisuallydeterminethatmostofthevaluesinrelationtotheNPwereveryclose.Thatistosaythatthevalueswereusuallywithintheonetofivepointdifferencemark.Nowthatwehavedeterminedthatfactwecouldthenfurtherexplorewhythatisthecaseandadjustourdatasetstoseesomepossiblechangesinoutcomesasmentionedwithintheseealsoabove. Limitations[edit] Radarchartsareprimarilysuitedforstrikinglyshowingoutliersandcommonality,orwhenonechartisgreaterineveryvariablethananother,andprimarilyusedforordinalmeasurements–whereeachvariablecorrespondsto"better"insomerespect,andallvariablesonthesamescale. Conversely,radarchartshavebeencriticizedaspoorlysuitedformakingtrade-offdecisions–whenonechartisgreaterthananotheronsomevariables,butlessonothers.[22] Further,itishardtovisuallycomparelengthsofdifferentspokes,becauseradialdistancesarehardtojudge,thoughconcentriccircleshelpasgridlines.Instead,onemayuseasimplelinegraph,particularlyfortimeseries.[23] Radarchartscandistortdatatosomeextent,especiallywhenareasarefilledin,becausetheareacontainedbecomesproportionaltothesquareofthelinearmeasures.Forexample,inachartwith5variablesthatrangefrom1to100,theareacontainedbythepolygonboundedby5pointswhenallmeasuresare90,ismorethan10%largerthanthesameforachartwithallvaluesof82. Radarchartscanalsobecomehardtovisuallycomparebetweendifferentsamplesonthechartwhentheirvaluesarecloseastheirlinesorareasbleedintoeachother,asshowninFigure5below. Artificialstructure[edit] Radarchartsimposeseveralstructuresondata,whichareoftenartificial: Relatednessofneighbors–radarchartsareoftenusedwhenneighboringvariablesareunrelated,creatingspuriousconnections. Cyclicstructure–thefirstandlastvariablesareplacednexttoeachother. Length–variablesareoftenmostnaturallyordinal:betterorworse,thoughthedegreeofdifferencemaybeartificial. Area–areascalesasthesquareofvalues,exaggeratingtheeffectoflargenumbers.Forexample,2,2takesup4timestheareaof1,1.Thisisageneralissuewithareagraphs,andareaishardtojudge–see"Cleveland'shierarchy".[24] Forexample,thealternatingdata9,1,9,1,9,1yieldsaspikingradarchart(whichgoesinandout),whilereorderingthedataas9,9,9,1,1,1insteadyieldstwodistinctwedges(sectors). Insomecasesthereisanaturalstructure,andradarchartscanbewell-suited.Forexample,fordiagramsofdatathatvaryovera24-hourcycle,thehourlydataisnaturallyrelatedtoitsneighbor,andhasacyclicstructure,soitcannaturallybedisplayedasaradarchart.[23][25][26] Onesetofguidelinesontheuseofradarcharts(orratherthecloselyrelated"polarareagraph")is:[26] youdon'tmindreadingstackedareasinsteadofpositionalongacommonscale(seeCleveland'sHierarchy), thedatasetistrulycyclic,notlinear,and therearetwoseriestocompare,onemuchsmallerthantheother Datasetsize[edit] Radarchartsarehelpfulforsmall-to-moderate-sizedmultivariatedatasets.Theirprimaryweaknessisthattheireffectivenessislimitedtodatasetswithlessthanafewhundredpoints.Afterthat,theytendtobeoverwhelming.[5] Further,whenusingradarchartswithmultipledimensionsorsamples,theradarchartmaybecomeclutteredandhardertointerpretasthenumberofsamplesgrows. Forexample,takethebattingstatstablecomparingMLB2021MVPShoheiOhtani,vsthestatsoftheleaguesaveragedesignatedhittersandsomeHallofFameplayers.Thesestatsrepresentthepercentageofhits,homeruns,strikeouts,etcperatbatofaplayer.Formoreinformationonwhateachstatusedinthetablerepresents,youcanrefertothisreferencebytheMLB.[27]WewillusethistablebelowtocreateRadarchartscomparingthe2021MVPbattingstatstotheleagueaveragesforDesignatedHittersandregularbatters,inanattempttovisualizeperformancemetricsandvisuallycometoaconclusionthatShoheioutperformedtheaverageplayer.NextwewillincludeadditionalsamplesintotheRadarchart,usingHallofFameplayersJackieRobinson,JimThome,andFrankThomastocompareShoheitoafewofthegreatestbattersofalltime.ThisRadarchartnotonlycangiveusintuitionofhowShoheicomparestothetophistoricalplayers,butwillalsoserveapurposeinshowingthelimitationsofhavingtoomanysamplesinaRadarchart. Target BA OBP SLG OPS HR% SO% BB% MLB 0.244 0.317 0.411 0.728 0.037 0.232 0.087 DH 0.239 0.316 0.434 0.75 0.047 0.256 0.093 ShoheiOhtani 0.257 0.372 0.592 0.965 0.086 0.296 0.15 JackieRobinson 0.313 0.41 0.477 0.887 0.0282 0.0582 0.151 JimThome 0.276 0.402 0.554 0.956 0.072 0.302 0.207 FrankThomas 0.301 0.419 0.555 0.974 0.063 0.17 0.203 WecanseeinFigure10howaradarchartcanbeeasilyinterpretedwhenthenumberofspokesandsamplesisrelativelysmall.WhenwecomparemoresamplesinFigure11,evenwithoutanareafillontheradarchart,itbecomesapparenthowdifficultitcanbecometointerpretormaketrade-offdecisions. Figure10.RadarchartdepictingMLB2021MVPShoheiOhtanibattingstatsvsleagueaverage Figure11.Comparingbattingstatsof2021MVPShoheiOhtanitotheleagueaverageandaselectfewHallofFamers.Herewecanseehowitbecomesmoredifficulttointerprettheradarchartwhenmoresamplesareadded Example[edit] DetailforthestarplotoftheCadillacSeville Thechartontheright[5]containsthestarplotsof15cars.Thevariablelistforthesamplestarplotis: Price Mileage(MPG) 1978RepairRecord(1=Worst,5=Best) 1977RepairRecord(1=Worst,5=Best) Headroom RearSeatRoom TrunkSpace Weight Length Wecanlookattheseplotsindividuallyorwecanusethemtoidentifyclustersofcarswithsimilarfeatures.Forexample,wecanlookatthestarplotoftheCadillacSeville(thelastoneontheimage)andseethatitisoneofthemostexpensivecars,getsbelowaverage(butnotamongtheworst)gasmileage,hasanaveragerepairrecord,andhasaverage-to-above-averageroominessandsize.WecanthencomparetheCadillacmodels(thelastthreeplots)withtheAMCmodels(thefirstthreeplots).Thiscomparisonshowsdistinctpatterns.TheAMCmodelstendtobeinexpensive,havebelowaveragegasmileage,andaresmallinbothheightandweightandinroominess.TheCadillacmodelsareexpensive,havepoorgasmileage,andarelargeinbothsizeandroominess.[5] Alternatives[edit] Mostsimply,onemayuseasimplelinegraph,particularlyfortimeseries.[23] Forgraphicalqualitativecomparisonof2-dimensionaltabulardatainseveralvariables,acommonalternativeareHarveyballs,whichareusedextensivelybyConsumerReports.[28]ComparisoninHarveyballs(andradarcharts)maybesignificantlyaidedbyorderingthevariablesalgorithmicallytoaddorder.[29] Anexcellentwayforvisualisingstructureswithinmultivariatedataisofferedbyprincipalcomponentanalysis(PCA). Anotheralternativeistousesmall,inlinebarcharts,whichmaybecomparedtosparklines.[29] Althoughradarandpolarchartsareoftendescribedasthesamecharttypes,[4]somesourcesmakeadifferencebetweenthemandevenconsidertheradarcharttobeapolarchart'svariationthatdoesnotdisplaydataintermsofpolarcoordinate.[30] Seealso[edit] Plot(graphics) Polarareadiagram Parallelcoordinates References[edit]  Thisarticleincorporates publicdomainmaterialfromtheNationalInstituteofStandardsandTechnologywebsitehttps://www.nist.gov. ^Porter,MichaelM;Niksiar,Pooya(2018)."Multidimensionalmechanics:Performancemappingofnaturalbiologicalsystemsusingpermutatedradarcharts".PLOSONE.13(9):e0204309.Bibcode:2018PLoSO..1304309P.doi:10.1371/journal.pone.0204309.PMC 6161877.PMID 30265707. ^NancyR.Tague(2005)Thequalitytoolbox.page437. ^Kolence,KennethW.(1973)."TheSoftwareEmpiricist".ACMSIGMETRICSPerformanceEvaluationReview.2(2):31–36.doi:10.1145/1113644.1113647.S2CID 18600391.Dr.PhilipJ.KiviatsuggestedatarecentNBS/ACMworkshoponperformancemeasurementthatacirculargraph,usingradiiasthevariableaxesmightbeausefulform.[…]Irecommendtheybecalled"KiviatPlots"or"KiviatGraphs"torecognizehisinsightastotheirimportance. ^ab"FindContentGapsUsingRadarCharts".ContentStrategyWorkshops.March3,2015.RetrievedDecember17,2015. ^abcdefNIST/SEMATECH(2003).StarPlotin:e-HandbookofStatisticalMethods.6/01/2003(Datecreated) ^Chambers,John,WilliamCleveland,BeatKleiner,andPaulTukey,(1983).GraphicalMethodsforDataAnalysis.Wadsworth.pp.158–162 ^Mayr,Georgvon(1877),DieGesetzmäßigkeitimGesellschaftsleben(inGerman),Munich:Oldenbourg,OL 23294909M,p.78.Linien-DiagrammeimKreise:Linechartsincircles. ^MichaelFriendly(2008)."Milestonesinthehistoryofthematiccartography,statisticalgraphics,anddatavisualization". ^MichaelFriendly(1991)."StatisticalGraphicsforMultivariateData".PaperpresentedattheSASSUGI16Conference,Apr,1991. ^Nowicki,HannahandMerenstein,Carter."RadarChartCS465:InformationVisualization-Spring2016".MiddleburyCollege.{{citeweb}}:CS1maint:multiplenames:authorslist(link) ^WondershareEdrawMax."WhatisaRadarChart?ExplainedwithExamples".WondershareEdrawMax. ^SpiderGraphs:ChartingBasketballStatistics ^SeeingData."Makingsenseofdatavisualizations".SeeingData. ^RonBasu(2004).ImplementingQuality:APracticalGuidetoToolsandTechniques.p.131. ^ModelSystemsKnowledgeTranslationCenter."EffectiveUseofRadarCharts"(PDF).ModelSystemsKnowledgeTranslationCenter. ^JohnMaguire."De-normalizedSpiderandRadarGraphs".KitmanLabs. ^Sowmya(29April2019)."WhyAndWhenToUseASpiderAndRadarChart?".Pluscharts. ^ab"Radar". ^WhatisaspiderChart? ^GenomeWideCharacterizationofGenomeOrganizationinMouseEScells,SupplementaryFile:GSE64881_segmentation_at_30000bp.passqc.multibam.txt.gz ^radar_factoryimplementation ^YouareNOTspiderman,sowhydoyouuseradarcharts?,byChandoo,September18th,2008 ^abcPeltier,Jon(2008-08-14)."RockAroundTheClock-PeltierTechBlog".Peltiertech.com.Retrieved2013-09-11. ^(Cleveland1984)harverror:notarget:CITEREFCleveland1984(help),summarizedathttp://processtrends.com/toc_data_visualization.htmArchivedMarch25,2010,attheWaybackMachine ^"ChartingaroundtheclockTheExcelChartsBlog".Excelcharts.com.2008-08-15.Retrieved2013-09-11. ^abClockThis ^"StandardStats".www.mlb.com.Retrieved2022-04-26. ^"QualitativeComparison".SupportAnalyticsBlog.11December2007.Archivedfromtheoriginalon2012-04-08. ^ab"InformationOcean:ReorderabletablesII:BertinversustheSpiders".I-ocean.blogspot.com.2008-09-24.Retrieved2013-09-11. ^"PolarCharts(ReportBuilderandSSRS)".MicrosoftDeveloperNetwork.RetrievedDecember17,2015. Externallinks[edit] WikimediaCommonshasmediarelatedtoRadarcharts. StarPlot–NIST/SEMATECHe-HandbookofStatisticalMethods vteStatistics Outline Index DescriptivestatisticsContinuousdataCenter Mean Arithmetic Cubic Generalized/power Geometric Harmonic Heinz Median Mode Dispersion Averageabsolutedeviation Coefficientofvariation Interquartilerange Percentile Range Standarddeviation Variance Shape Centrallimittheorem Moments Kurtosis L-moments Skewness Countdata Indexofdispersion Summarytables Contingencytable Frequencydistribution Groupeddata Dependence Partialcorrelation Pearsonproduct-momentcorrelation Rankcorrelation Kendall'sτ Spearman'sρ Scatterplot Graphics Barchart Biplot Boxplot Controlchart Correlogram Fanchart Forestplot Histogram Piechart Q–Qplot Radarchart Runchart Scatterplot Stem-and-leafdisplay Violinplot DatacollectionStudydesign Effectsize Missingdata Optimaldesign Population Replication Samplesizedetermination Statistic Statisticalpower Surveymethodology Sampling Cluster Stratified Opinionpoll Questionnaire Standarderror 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