The statistics module comes with an assortment of goodies: Mean, median, mode, standard deviation, and variance. These are all fairly straight forward to use, ...searchHome+=1SupporttheContentCommunityLoginSignupHome+=1SupporttheContentCommunityLoginSignupStatisticsModulePythonTutorialSincePythonissuchapopularprogramminglanguagefordataanalysis,itonlymakessensethatitcomeswithastatisticsmodule.Sadly,thisisnotavailableinPython2.7,butthat'sokaybecausewe'reinPython3!Thestatisticsmodulecomeswithanassortmentofgoodies:Mean,median,mode,standarddeviation,andvariance.Theseareallfairlystraightforwardtouse,hereandsomesimpleexamples: importstatisticsexample_list=[5,2,5,6,1,2,6,7,2,6,3,5,5]x=statistics.mean(example_list)print(x)y=statistics.median(example_list)print(y)z=statistics.mode(example_list)print(z)a=statistics.stdev(example_list)print(a)b=statistics.variance(example_list)print(b)We'venotgonemuchoverimportingthingsinPython,soI'vekeptthisbasic.Asyoucansee,youjustsimplypassalistthroughthemodule'sfunction,andyou'reoutputistheanswer.Here,we'resavingtheoutputtoavariable,andthenwe'rejustprintingoutthevariable.Innormalcircumstances,you'dprobablycontinuedoingthingswithit.Here,we'veseenhowsimpleimportingandusingmodulescanbe,buttherearealotofotheroptionswhenitcomestohowweimportthings.Thenexttutorial:ModuleimportSyntaxPythonTutorialPythonIntroductionGoPrintFunctionandStringsGoMathwithPythonGoVariablesPythonTutorialGoWhileLoopPythonTutorialGoForLoopPythonTutorialGoIfStatementPythonTutorialGoIfElsePythonTutorialGoIfElifElsePythonTutorialGoFunctionsPythonTutorialGoFunctionParametersPythonTutorialGoFunctionParameterDefaultsPythonTutorialGoGlobalandLocalVariablesPythonTutorialGoInstallingModulesPythonTutorialGoHowtodownloadandinstallPythonPackagesandModuleswithPipGoCommonErrorsPythonTutorialGoWritingtoaFilePythonTutorialGoAppendingFilesPythonTutorialGoReadingfromFilesPythonTutorialGoClassesPythonTutorialGoFrequentlyaskedQuestionsPythonTutorialGoGettingUserInputPythonTutorialGoStatisticsMo

This module contains a large number of probability distributions, summary and frequency statistics, correlation functions and statistical tests, ...GettingstartedUserGuideAPIreferenceDevelopmentReleasenotesGitHubClusteringpackage(scipy.cluster)K-meansclusteringandvectorquantization(scipy.cluster.vq)Hierarchicalclustering(scipy.cluster.hierarchy)Constants(scipy.constants)DiscreteFouriertransforms(scipy.fft)LegacydiscreteFouriertransforms(scipy.fftpack)IntegrationandODEs(scipy.integrate)Interpolation(scipy.interpolate)Inputandoutput(scipy.io)Linearalgebra(scipy.linalg)Low-levelBLASfunctions(scipy.linalg.blas)Low-levelLAPACKfunctions(scipy.linalg.lapack)BLASFunctionsforCythonLAPACKfunctionsforCythonInterpolativematrixdecomposition(scipy.linalg.interpolative)Miscellaneousroutines(scipy.misc)Multidimensionalimageprocessing(scipy.ndimage)Orthogonaldistanceregression(scipy.odr)Optimizationandrootfinding(scipy.optimize)NonlinearsolversCythonoptimizezerosAPISignalprocessing(scipy.signal)Sparsematrices(scipy.sparse)Sparselinearalgebra(scipy.sparse.linalg)Compressedsparsegraphroutines(scipy.sparse.csgraph)Spatialalgorithmsanddatastructures(scipy.spatial)Distancecomputations(scipy.spatial.distance)Specialfunctions(scipy.special)Statisticalfunctions(scipy.stats)ResultclassesStatisticalfunctionsformaskedarrays(scipy.stats.mstats)Quasi-MonteCarlosubmodule(scipy.stats.qmc)Low-levelcallbackfunctionsOnthispageProbabilitydistributionsContinuousdistributionsMultivariatedistributionsDiscretedistributionsSummarystatisticsFrequencystatisticsCorrelationfunctionsStatisticaltestsQuasi-MonteCarloMaskedstatisticsfunctionsOtherstatisticalfunctionalityTransformationsStatisticaldistancesRandomvariategeneration/CDFInversionCircularstatisticalfunctionsContingencytablefunctionsPlot-testsUnivariateandmultivariatekerneldensityestimationWarningsusedinscipy.statsStatisticalfunctions(scipy.stats)¶Thismodulecontainsalargenumberofprobabilitydistributions,summaryandfrequencystatistics,correlationfunctionsan

SkiptocontentTutorialsPracticeDS&Algo.DSATopic-wiseDSACompany-wiseAlgorithmsAnalysisofAlgorithmsAsymptoticAnalysisWorst,AverageandBestCasesAsymptoticNotationsLittleoandlittleomeganotationsLowerandUpperBoundTheoryAnalysisofLoopsSolvingRecurrencesAmortizedAnalysisWhatdoes'SpaceComplexity'mean?Pseudo-polynomialAlgorithmsPolynomialTimeApproximationSchemeATimeComplexityQuestionSearchingAlgorithmsSortingAlgorithmsGraphAlgorithmsPatternSearchingGeometricAlgorithmsMathematicalBitwiseAlgorithmsRandomizedAlgorithmsGreedyAlgorithmsDynamicProgrammingDivideandConquerBacktrackingBranchandBoundAllAlgorithmsDataStructuresArraysLinkedListStackQueueBinaryTreeBinarySearchTreeHeapHashingGraphAdvancedDataStructureMatrixStringsAllDataStructuresInterviewCornerCompanyPreparationTopTopicsPracticeCompanyQuestionsInterviewExperiencesExperiencedInterviewsInternshipInterviewsCompetititveProgrammingDesignPatternsSystemDesignTutorialMultipleChoiceQuizzesLanguagesCC++JavaPythonC#JavaScriptjQuerySQLPHPScalaPerlGoLanguageHTMLCSSKotlinISROCSISROCSSolvedPapersISROCSOriginalPapersandOfficialKeysISROCSSyllabusforScientist/EngineerExamGATEGATEComputerScienceNotesLastMinuteNotesGATECSSolvedPapersGATECSOriginalPapersandOfficialKeysGATE2021DatesGATECS2021SyllabusImportantTopicsforGATECSCSSubjectsMathematicsOperatingSystemDBMSComputerNetworksComputerOrganizationandArchitectureTheoryofComputationCompilerDesignDigitalLogicSoftwareEngineeringWebTechnologiesHTMLCSSJavaScriptAngularJSReactJSNodeJSBootstrapjQueryPHPSchoolLearningSchoolProgrammingMathematicsAlgebraTrigonometryStatisticsProbabilityGeometryMensurationCalculusMathsNotes(Class8-11)Class8NotesClass9NotesClass10NotesClass11NotesNCERTSolutionsClass8MathsSolutionClass9MathsSolutionClass10MathsSolutionClass11MathsSolutionClass12MathsSolutionRDSharmaSolutionsClass8MathsSolutionClass9MathsSolutionClass10MathsSolutionClass11MathsSolutionClass12MathsSolutionUGCNETCSUGCNETCSNotesPaperIIUGCNETCSNotesPaperIIIUGCNETCSSolvedPapersStudentCampusAmbassadorProgramSchool

GetstartedOpeninappSigninGetstartedFollow567KFollowers·Editors'PicksFeaturesDeepDivesGrowContributeAboutGetstartedOpeninapp3TopPythonPackagestoLearnStatisticforDataScientistEnhanceyourstatisticskillswiththesepackagesCornelliusYudhaWijayaMay14·7minreadPhotobyRuthsonZimmermanonUnsplashDataScientistsareknownforhavingbetterprogrammingskillsthanastatisticianandbetterstatisticknowledgethanaprogrammer.Whilelearningprogrammingskillisnotaneasyfeat,sometimesnewdatapeopleforgetaboutthestatisticskill.Iknowstatisticishardtolearn,especiallyforpeoplewhoarenotformallyeducatedinthestatistic.However,itispossibletolearnstatisticsfromscratch—withthehelpofmoderntechnology.Learningstatisticsbecomeseasierthanbeforewithallthesedevelopedstatisticpackagesintheprogramminglanguage.Iknowthatmanywouldargueifyouwanttolearnstatistics.YoushouldusetheRlanguageinsteadofPython;but,IwanttoofferanalternativebyusingthePythonpackagebecausemanypeoplestarttheirDataSciencejourneybylearningthePythonlanguage.Inthisarticle,Iwanttoshowyouthe3topPythonPackagestolearnStatisticandtheexampleofhowtousethepackage—remember,forlearning.Let’sgetintoit!1.Scipy.StatsSciPy(pronounced“SighPie”)isanopen-sourcepackagecomputingtoolforperformingascientificmethodinthePythonenvironment.TheScipyitselfisalsoacollectionofnumericalalgorithmsanddomain-specifictoolboxesusedinmanymathematical,engineering,anddataresearch.OneoftheAPIsavailablewithinScipyisthestatisticalAPIcalledStats.AccordingtotheScipyhomepage,Scipy.Statsisamodulethatcontainsalargenumberofprobabilitydistributionsandagrowinglibraryofstatisticalfunctions,especiallyforprobabilityfunctionstudy.OntheScipy.Statsmodule,therearemanystatisticalfunctionAPIyoucouldrefertoforfurtherlearning.Theyare:ContinuousdistributionsMultivariatedistributionsDiscretedistributionsSummarystatisticsFrequencystatisticsCorrelationfunctionsStatisticaltestsTransformationsStatisticaldistancesRandomvariategenerationCircularstatisticalfunctionsContingencytablefunctionsPlot-testsMaskedstatisticsfunctionsUni

It's hard to ignore the wealth of statistical packages available in R/CRAN. That said, I spend a lot of time in Python land and would never dissuade anyone ...CrossValidatedisaquestionandanswersiteforpeopleinterestedinstatistics,machinelearning,dataanalysis,datamining,anddatavisualization.Itonlytakesaminutetosignup.SignuptojointhiscommunityAnybodycanaskaquestionAnybodycananswerThebestanswersarevotedupandrisetothetopHomePublicQuestionsTagsUsersUnansweredTeamsStackOverflowforTeams–Collaborateandshareknowledgewithaprivategroup.CreateafreeTeamWhatisTeams?TeamsCreatefreeTeamTeamsQ&AforworkConnectandshareknowledgewithinasinglelocationthatisstructuredandeasytosearch.LearnmorePythonasastatisticsworkbenchAskQuestionAsked10years,11monthsagoActive7monthsagoViewed134ktimes375421$\begingroup$LotsofpeopleuseamaintoollikeExceloranotherspreadsheet,SPSS,Stata,orRfortheirstatisticsneeds.Theymightturntosomespecificpackageforveryspecialneeds,butalotofthingscanbedonewithasimplespreadsheetorageneralstatspackageorstatsprogrammingenvironment.I'vealwayslikedPythonasaprogramminglanguage,andforsimpleneeds,it'seasytowriteashortprogramthatcalculateswhatIneed.Matplotliballowsmetoplotit.Hasanyoneswitchedcompletelyfrom,sayR,toPython?R(oranyotherstatisticspackage)hasalotoffunctionalityspecifictostatistics,andithasdatastructuresthatallowyoutothinkaboutthestatisticsyouwanttoperformandlessabouttheinternalrepresentationofyourdata.Python(orsomeotherdynamiclanguage)hasthebenefitofallowingmetoprograminafamiliar,high-levellanguage,anditletsmeprogrammaticallyinteractwithreal-worldsystemsinwhichthedataresidesorfromwhichIcantakemeasurements.ButIhaven'tfoundanyPythonpackagethatwouldallowmetoexpressthingswith"statisticalterminology"–fromsimpledescriptivestatisticstomorecomplicatedmultivariatemethods.WhatcanyourecommendifIwantedtousePythonasa"statisticsworkbench"toreplaceR,SPSS,etc.?WhatwouldIgainandlose,basedonyourexperience?rspssstatapythonShareCiteImprovethisquestionFolloweditedJul4'13at17:03communitywiki3rev

TogglenavigationPythonforUndergraduateEngineersAboutBookGearNowArchivesstatisticsStatisticsinPythonusingthestatisticsmoduleInthispost,we'lllookatacoupleofstatisticsfunctionsinPython.ThesestatisticsfunctionsarepartofthePythonStandardLibraryinthestatisticsmodule.Thefourfunctionswe'lluseinthispostarecommoninstatistics:mean-averagevaluemedian-middlevaluemode-mostoftenvaluestandarddeviation-spreadofvaluesToaccessPython'sstatisticsfunctions,weneedtoimportthefunctionsfromthestatisticsmoduleusingthestatement:fromstatisticsimportmean,median,mode,stdevAftertheimportstatement,thefunctionsmean(),median(),mode()andstdev()(standarddeviation)canbeused.SincethestatisticsmoduleispartofthePythonStandardLibrary,noexternalpackagesneedtobeinstalled.Let'simaginewehaveadatasetof5testscores.Thetestscoresare60,83,91and100.ThesetestscorescanbestoredinaPythonlist.Pythonlistsaredefinedwithsquarebrackets[].ElementsinPythonlistsareseparatedwithcommas.In [1]:fromstatisticsimportmean,median,mode,stdevtest_scores=[60,83,83,91,100]Calculatethemean¶Tocalculatethemean,oraverageofourtestscores,usethestatisticsmodule'smean()function.In [2]:mean(test_scores)Out[2]:83.4Calculatethemedian¶Tocalculatethemedian,ormiddlevalueofourtestscores,usethestatisticsmodule'smedian()function.Ifthereareanoddnumberofvalues,median()returnsthemiddlevalue.Ifthereareanevennumberofvaluesmedian()returnsanaverageofthetwomiddlevalues.In [3]:median(test_scores)83Out[3]:83Calculatethemode¶Tocalculatethemode,ormostoftenvalueofourtestscores,usethestatisticsmodule'smode()function.Ifthereismorethanonenumberwhichoccursmostoften,mode()returnsanerror.>>>mode([1,1,2,2,3])StatisticsError:nouniquemode;found2equallycommonvaluesIfthereisnovaluethatoccursmostoften(allthevaluesareuniqueoroccurthesamenumberoftimes),mode()alsoreturnsanerror.>>>mode([1,2,3])StatisticsError:nouniquemode;found3equallycommonvaluesIn [4]:mode(test_scores)Out[4]:83Calculatethestandarddeviation¶Tocalculatethestandarddeviation,orspreadofthetestscores,usethestatisticsmodul

Navigationindexmodules|next|previous|Python»3.9.6Documentation»ThePythonStandardLibrary»NumericandMathematicalModules»|statistics—Mathematicalstatisticsfunctions¶Newinversion3.4.Sourcecode:Lib/statistics.pyThismoduleprovidesfunctionsforcalculatingmathematicalstatisticsofnumeric(Real-valued)data.Themoduleisnotintendedtobeacompetitortothird-partylibrariessuchasNumPy,SciPy,orproprietaryfull-featuredstatisticspackagesaimedatprofessionalstatisticianssuchasMinitab,SASandMatlab.Itisaimedatthelevelofgraphingandscientificcalculators.Unlessexplicitlynoted,thesefunctionssupportint,float,DecimalandFraction.Behaviourwithothertypes(whetherinthenumerictowerornot)iscurrentlyunsupported.Collectionswithamixoftypesarealsoundefinedandimplementation-dependent.Ifyourinputdataconsistsofmixedtypes,youmaybeabletousemap()toensureaconsistentresult,forexample:map(float,input_data).Averagesandmeasuresofcentrallocation¶Thesefunctionscalculateanaverageortypicalvaluefromapopulationorsample.mean()Arithmeticmean(“average”)ofdata.fmean()Fast,floatingpointarithmeticmean.geometric_mean()Geometricmeanofdata.harmonic_mean()Harmonicmeanofdata.median()Median(middlevalue)ofdata.median_low()Lowmedianofdata.median_high()Highmedianofdata.median_grouped()Median,or50thpercentile,ofgroupeddata.mode()Singlemode(mostcommonvalue)ofdiscreteornominaldata.multimode()Listofmodes(mostcommonvalues)ofdiscreteornomimaldata.quantiles()Dividedataintointervalswithequalprobability.Measuresofspread¶Thesefunctionscalculateameasureofhowmuchthepopulationorsampletendstodeviatefromthetypicaloraveragevalues.pstdev()Populationstandarddeviationofdata.pvariance()Populationvarianceofdata.stdev()Samplestandarddeviationofdata.variance()Samplevarianceofdata.Functiondetails¶Note:Thefunctionsdonotrequirethedatagiventothemtobesorted.However,forreadingconvenience,mostoftheexamplesshowsortedsequences.statistics.mean(data)¶Returnthesamplearithmeticmeanofdatawhichcanbeasequenceoriterable.Thearithmeticmeanisthesumofthedatadividedbythenumberofdatapoi

Let's try to learn some statistics with Scipy.Stats. If you are using Python from Anaconda distribution, the Scipy package is already inbuilt within the ...GetstartedOpeninappSigninGetstartedFollow567KFollowers·Editors'PicksFeaturesDeepDivesGrowContributeAboutGetstartedOpeninapp3TopPythonPackagestoLearnStatisticforDataScientistEnhanceyourstatisticskillswiththesepackagesCornelliusYudhaWijayaMay14·7minreadPhotobyRuthsonZimmermanonUnsplashDataScientistsareknownforhavingbetterprogrammingskillsthanastatisticianandbetterstatisticknowledgethanaprogrammer.Whilelearningprogrammingskillisnotaneasyfeat,sometimesnewdatapeopleforgetaboutthestatisticskill.Iknowstatisticishardtolearn,especiallyforpeoplewhoarenotformallyeducatedinthestatistic.However,itispossibletolearnstatisticsfromscratch—withthehelpofmoderntechnology.Learningstatisticsbecomeseasierthanbeforewithallthesedevelopedstatisticpackagesintheprogramminglanguage.Iknowthatmanywouldargueifyouwanttolearnstatistics.YoushouldusetheRlanguageinsteadofPython;but,IwanttoofferanalternativebyusingthePythonpackagebecausemanypeoplestarttheirDataSciencejourneybylearningthePythonlanguage.Inthisarticle,Iwanttoshowyouthe3topPythonPackagestolearnStatisticandtheexampleofhowtousethepackage—remember,forlearning.Let’sgetintoit!1.Scipy.StatsSciPy(pronounced“SighPie”)isanopen-sourcepackagecomputingtoolforperformingascientificmethodinthePythonenvironment.TheScipyitselfisalsoacollectionofnumericalalgorithmsanddomain-specifictoolboxesusedinmanymathematical,engineering,anddataresearch.OneoftheAPIsavailablewithinScipyisthestatisticalAPIcalledStats.AccordingtotheScipyhomepage,Scipy.Statsisamodulethatcontainsalargenumberofprobabilitydistributionsandagrowinglibraryofstatisticalfunctions,especiallyforprobabilityfunctionstudy.OntheScipy.Statsmodule,therearemanystatisticalfunctionAPIyoucouldrefertoforfurtherlearning.Theyare:ContinuousdistributionsMultivariatedistributionsDiscretedistributionsSummarystatisticsFrequencystatisticsCorrelationfunctionsStatistic