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1、NumPyArraysAfterinstallingNumPyandotherkeyPython-programminglibrariesandgettingsomecodetowork,it'stimetopassoverNumPyarrays.ThischapteracquaintsyouwiththefundamentalsofNumPyandarrays.Attheendofthischapter,youwillhaveabasicunderstandingofNumPyarraysandtheirrelated
2、functions.Thetopicswewilladdressinthischapterareasfollows:•Datatypes•Arraytypes•Typeconversions•Creatingarrays•Indexing•Fancyindexing•Slicing•ManipulatingshapesTheNumPyarrayobjectNumPyhasamultidimensionalarrayobjectcalledndarray.Itconsistsoftwoparts,whichareasfol
3、lows:•Theactualdata•SomemetadatadescribingthedataThebulkofarrayproceduresleavestherawinformationunaffected;thesolefacetthatvariesisthemetadata.NumPyArraysWehavealreadydiscoveredintheprecedingchapterhowtoproduceanarraybyapplyingthearange()function.Actually,wemadea
4、one-dimensionalarraythatheldasetofnumbers.Thendarraycanhavemorethanasingledimension.TheadvantagesofNumPyarraysTheNumPyarrayis,ingeneral,homogeneous(thereisaparticularrecordarraytypethatisheterogeneous)—theitemsinthearrayhavetobeofthesametype.Theadvantageisthatifw
5、eknowthattheitemsinanarrayareofthesametype,itiseasytoascertainthestoragesizeneededforthearray.NumPyarrayscanexecutevectorizedoperations,processingacompletearray,incontrasttoPythonlists,whereyouusuallyhavetoloopthroughthelistandexecutetheoperationoneachelement.Als
6、o,NumPyutilizesanoptimizedCAPItomakethemparticularlyquick.NumPyarraysareindexedjustlikeinPython,commencingfrom0.Datatypesarerepresentedbyspecialobjects.Theseobjectswillbediscussedcomprehensivelyfurtherinthischapter.Wewillmakeanarraywiththearange()subroutineagain(
7、examinearrayattributes.pyfromthisbook'scode).Inthischapter,youwillseesnippetsfromIPythonsessionswhereNumPyisalreadyimported.Here'showtogetthedatatypeofanarray:In:a=arange(5)In:a.dtypeOut:dtype('int64')Thedatatypeofthearrayaisint64(atleastonmycomputer),butyoumayge
8、tint32astheoutputifyouareusing32-bitPython.Inboththecases,wearedealingwithintegers(64bitor32bit).Besidesthedatatypeofanarray,itiscrucialtoknowitsshape.Theexamp
