Python's statistics is a built-in Python library for descriptive statistics. You can use it if your datasets are not too large or if you can't rely on importing other libraries.Start HereLearnPythonPythonTutorials→In-deptharticlesandtutorialsVideoCourses→Step-by-stepvideolessonsQuizzes→CheckyourlearningprogressLearningPaths→GuidedstudyplansforacceleratedlearningCommunity→LearnwithotherPythonistasTopics→FocusonaspecificareaorskilllevelUnlockAllContentStoreRPMembershipPythonBasicsBookPythonTricksBookCPythonInternalsBookTheRealPythonCourseManagingPythonDependenciesSublimeText+PythonSetupPythonicWallpapersPackPythonMugs,T-Shirts,andMorePythonistaCafeCommunityBrowseAll»MorePythonNewsletterPythonPodcastPythonJobBoardMeettheTeamBecomeaTutorialAuthorBecomeaVideoInstructorSearchJoinSign‑In😷Stuckathome?Enjoyfreecourses,on us →PythonStatisticsFundamentals:HowtoDescribeYourDatabyMirkoStojiljkovićdata-scienceintermediateMarkasCompletedTweetShareEmailTableofContentsUnderstandingDescriptiveStatisticsTypesofMeasuresPopulationandSamplesOutliersChoosingPythonStatisticsLibrariesGettingStartedWithPythonStatisticsLibrariesCalculatingDescriptiveStatisticsMeasuresofCentralTendencyMeasuresofVariabilitySummaryofDescriptiveStatisticsMeasuresofCorrelationBetweenPairsofDataWorkingWith2DDataAxesDataFramesVisualizingDataBoxPlotsHistogramsPieChartsBarChartsX-YPlotsHeatmapsConclusionRemoveadsIntheeraofbigdataandartificialintelligence,datascienceandmachinelearninghavebecomeessentialinmanyfieldsofscienceandtechnology.Anecessaryaspectofworkingwithdataistheabilitytodescribe,summarize,andrepresentdatavisually.Pythonstatisticslibrariesarecomprehensive,popular,andwidelyusedtoolsthatwillassistyouinworkingwithdata.Inthistutorial,you’lllearn:WhatnumericalquantitiesyoucanusetodescribeandsummarizeyourdatasetsHowtocalculatedescriptivestatisticsinpurePythonHowtogetdescriptivestatisticswithavailablePythonlibrariesHowtovisualizeyourdatasetsFreeBonus:Clickheretodownload5Python+Matplotlibexampleswithfullsourcecodet