21 Essential Tools for Python
Pythonisoneofthemostpopularprogramminglanguages.Itissimple,powerful,anddrivenbya communitythatcontributestoopen-sourceprojects.ThemanyPythonusesarewhythe languageissopopular;youcanbuildsoftware,developwebservices,performdataanalyticsand visualization,andtrainmachinelearningmodelsforfree.
ThelistofPythontoolsmentionedinthispostwillhelpbeginnersstarttheirPythondevelopment journey.ItwillalsohelpdataprofessionalsandPythondevelopersbecomeproductive.So, whateverstageofyourPythonjourneyyou’reat,thesetoolscanhelpyoumakethemostofthe language.
PythonDevelopmentTools
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21 Essential Tools for Python
21 Essential Tools for Python Learn about the essential Python tools for software development, web scraping and development, data analysis a
Creating Synthetic Data with Python Faker Tutorial Creating Synthetic Data with Python Faker Tutorial Generating synthetic data using Python Faker to supplement real world data for applicatio
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DevelopmenttoolshelpustobuildfastandreliablePythonsolutions.ItincludesIntegrated DevelopmentEnvironment(IDE),Pythonpackagemanager,andproductiveextensions.These toolshavemadeiteasytotestthesoftware,debug,anddeploysolutionsinproduction.
1.JupyterNotebook
JupyterNotebookisaweb-basedIDEforexperimentingwithcodeanddisplayingtheresults.It isfairlypopularamongdatascientistsandmachinelearningpractitioners.Itallowsthemtorun andtestsmallsetsofcodeandviewresultsinsteadofrunningthewholefile.
TheJupyterNotebookletsusaddadescriptionandheadingusingmarkdownandexportthe resultintheformofPDFand.ipynbfiles.
WhenyoumixscientificcomputationwithPythondevelopment,yougetaJupyterNotebook. Nowadays,teachersareusingitforteachingdatasciencecourses,dataanalystsareusingitto createreports,andmachinelearningengineersareusingexperimentationandbuildinghighperformingmodelarchitecture.
YoucancheckoutafreecloudJupyternotebookontheWorkspacetobuildandshareanalytical reportsanddiscoverourJupytertutorialtolearnhowtouseit.
Itisnotgoinganywhereinthefuture,peoplearebuildingproduction-readysolutionsonit,and techgiantslikeAWSarealsoincorporatingitintothecloudcomputingecosystems.
2.Pip
PipisatoolthatusesPythonPackageIndextoinstallandmanagePythonsoftware.Thereare 393,343projectsforyoutodownloadandinstallwithlightningspeed.ThePythonecosystem worksonit.
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Code pipinstall<package_name> POWERED BY DATACAMP WORKSPACE COPY CODE 15 days of Power BI Complete Microsoft Power BI Bootcamp 15 days of Power BI Complete Microsoft Power BI Bootcamp What you'll learn Get Udemy courses 95 % DI SCOUNT UDEMY COURSES Home earning with social media EARN MONEY FROM SOCI AL MEDI A A millionaire's Secret J OHN CRESTANI T HI S SECRET FRUI T RAPI DLY MELT S FAT
Pipisnotjustaninstaller.YoucancreateandmanagePythonenvironments,install dependencies,andinstallpackagesfromthird-partyrepositoriesusingURLs.Learnmoreabout pipbyfollowingthePIPPythonTutorialtutorial.
VSCode
VisualStudioCodeisfree,lightweight,andapowerfulcodeeditor.Youcanbuild,test,deploy, andmaintainalltypesofapplicationswithoutleavingthesoftwarewindow.Itcomeswithsyntax highlighting,codeauto-completing,language,Git,andin-linedebugsupport.Youcanuse extensionstopre-buildsystemsanddeployapplicationstothecloud.
VSCodeisthemostpopularIDEintheworld,anditspopularityismainlyduetofreeextensions thatimproveuserexperience.Theextensionsallowdatascientiststorunexperimentsonthe Jupyternotebook,editmarkdownfiles,integrateSQLserver,collaborateonprojects, autocompletecode,andin-linecodehelp.Insteadofusingmultiplesoftware,youcanuse extensionsandruneverythingfromVSCodesoftwarelikebashterminalandbrowser
PythonWebScrapingTools
Webscrapingallowsdatascientistsandanalyticstocollectdatafromwebsites.Thehardpartof webscrapingistocleandataandconvertitintoareadableandstructuredformat.Inthissection, wewilllearnaboutthemostusedtoolstoperformwebscrapinganddatacleaning.
RequestsmakeiteasyforyoutosendHTTPrequests.Insteadofmanuallyadding authentication,arguments,andconfigurationquerystringstoyourURLs,youcansimplyuse requestsAPIandusethegetJSONmethod.TheRequestsisquiteapopularlibraryamongdata professionalsforscrapingmultiple-pagewebsites.
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Code python mpipinstall rrequirementstxt POWERED BY DATACAMP WORKSPACE COPY CODE 3.
4.Requests 5.BeautifulSoup There is a secret ingredient in that that makes people thin no matter what they eat? Social media jobs are really hot right now !! GET PAI D ON SOCI AL MEDI A September (24) BLOG ARCHI VE ▼ 2022 (129) ▼ September (24) Data Science Interview Questions And Answers Python package Fuzzy project Gender Prediction us 15 days of Power BI Complete Microsoft Power BI Learn SQL LIKE Pattern Matching Tutorial 21 Essential Tools for Python Learn Power BI Calculate function Tutorial What is R? The Statistical Computing base for da How to Become a Data Scientist with No Experience ? SQL Joins Cheat Sheet Learn SQL Commands —25 Most Popular SQL Commands Creating Synthetic Data with Python Faker Tutorial How to Create and Sell Pro table Online Courses: BLOG ARCHI VE
BeautifulSoupisusedtocleanandextractthedatafromHTMLandXLM.Itisusedtoparse HTMLtextandallowsdatascientiststoconverttextdataintoastructuredtableorpandas dataframe.
Withafewlinesofcode,youcanextractcomplexHTMLdata.Insomecases,youonlyneeda tabletag,andyoucanaccesswholedatawithoutparsingthetext.
LearnmoreaboutBeautifulSoupbyreadingWebScrapingUsingPython BeautifulSouptutorial.
6.Scrapy
Scrapyisanopen-sourceandcollaborativeframeworkforwebscrapingandwebcrawling.Itis fast,simple,andextensibleincrawlingwebsitesofmultiplepagestoextractdatainastructured format.Itisgenerallyusedfordatamining,monitoring,andautomatedtesting.
LearnmoreaboutScrapybyreadingourMakeWebCrawlerinPythontutorial.
PythonWebDevelopmentTools
Pythonhasoneofthebestwebdevelopmentframeworks.Youcancreateawebpage,web application,orwebAPIbytypingafewlinesofcode.Thesetoolsarebeginnerfriendlyanddon't requireyoutomasterlanguageslikeHTML,CSS,andJS.
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7.Flask
Flaskisanopen-sourcewebframeworkforbuildingwebapplicationsandRESTAPI.Itiseasier tolearnthanDjango’sframework,andwithafewlinesofcode,youcanassembleasimpleweb APIthatyoucanrunlocally.
FlaskisbasedontheWSGI(WebServerGatewayInterface)toolkitandJinja2templateengine.It canbeusedtocreatesimpleaswellaslarge-scalewebapplicationssuchasbloggingwebsites, socialmediaapps,portfoliowebpages,machinelearningapplications,andanalyticsDashboard.
LearnmoreaboutFlaskbyreadingourMachineLearningModelsintoAPIswiththePython Flasktutorial.
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Streamlitisthefastestandeasiestwayofbuildingandsharingwebapplications.Youcancreate adatascienceportfolio,analyticsdashboard,machinelearningwebapplication,educational tutorial,andgeospatialandcomputervisionapplicationswithinafewminutes.Youjustneedto addawidgetthesameasdeclaringvariablesinPython.Noneedtolearnback-enddevelopment, defineroutes,andhandleHTTPrequests,HTML,CSS,andJavaScript.
Foradatascientistandanalyst,itisthegatewaytotheworldofwebdevelopment.Thatiswhy mostdatascientistusesStreamlittodemonstratefinancialreports,research,andmachine learningconcepts.CheckouttheStreamlittutorialtobuildyourfirstwebapplicationinafew minutes.
FastAPI
FastAPIisawebframeworkforcreatinghigh-performancewebAPIs.SimilartoStreamlit,it requiresafewlinesofcodetobuildproduction-readywebapplications.Afterdeployingtheweb app,youcanaccessitusingtheGUIinterfaceorsendHTTPrequests.
Itisfast,Intuitive,androbust.Youcandeploythemachinelearningmodelhassle-free.Itisalso usedforInternalcrisismanagementandauthenticationmanagementforwebapplications.
PythonDataAnalysisTools
Dataanalysistoolsallowuserstoingest,clean,andmanipulatedataforstatisticalanalysis. Everydataprofessionalmustunderstandthecorefunctionalityofthesetoolstoperformdata analysis,machinelearning,dataengineering,andbusinessintelligencetasks.
10.pandas
pandasisagatewayintotheworldofdatascience.Thefirstthingyoulearnasabeginneristo loadaCSVfileusingread_csv().pandasisanessentialtoolforalldataprofessionals.
Youcanloadadataset,cleanit,manipulateit,calculatestatistics,createvisualizations,andsave thedataintovariousfileformats.ThepandasAPIissimpleandintuitive.Youcanloadandsave CSVandtextfiles,MicrosoftExcel,SQLdatabases,andthefastHDF5fileformat.
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LearnmoreaboutpandasbytakingourDataManipulationwithpandascourse.
Numpy
NumPyisafundamentalPythonpackageforscientificcomputations,andmostmoderntoolsare builtuponit.Asadatascientist,youwillusetheNumpyarrayformathematicalcalculationsand datawrangling.Itprovidesmultidimensionalarrayobjectstoperformfastoperationssuchas logical,shapemanipulation,sorting,selection,basicstaticsoperation,andrandomsimulation.
Numpywillhelpyouunderstandthefundamentalsofmathematicsindatascienceandhowto convertcomplexequationsintoPythoncode.Youcanuseittocreatemachinelearningmodels, customizedstaticalformulas,scientificsimulations,andperformadvanceddataanalyticstasks.
LearnmoreaboutNumPybytakingourIntroductiontoNumPycourse.
SQLAlchemy
SQLAlchemyisaPythonSQLtoolkitforyoutoaccessandmanagerelationaldatabases.Ituses ObjectRelationalMappertoprovidepowerfulfeaturesandflexibilityofSQL.
Thistoolisnecessaryfordatascientistsandanalyticswhoareusedtoperformdataprocessing andanalyticsinPython.YoucaneitheruseSQLscriptstoperformdataanalysisoruseanobjectbasedapproachwhereyoucanuseanintuitivePythonAPItoperformsimilartasksineffective ways.
LearnmoreaboutSQLAlchemybytakinganIntroductiontoDatabasescourseonDataCamp.
Daskisanessentialtoolforprocessingbigdataorfiles.Itusesparallelcomputingtoperform similartasksbylibrarieslikeNumPy,pandas,andscikit-learn.
Runningasimplelogicalfunctiononalargedatasetof4GBwilltakeatleast10minutes.Even withbettermachines,youcannotimproveprocessingtimestoafewseconds.Daskusesdynamic taskschedulingandparalleldatacollectiontoachievefastresultswiththesamemachine.
TheAPIissimilartopandasandscikit-learn.Itisflexible,nativetoPython,itcanscaleup(1000 core)anddown(singlecore),andprovidesrapidfeedbackanddiagnosticstoaidhumans.
LearnmoreaboutDaskbytakingourParallelProgrammingwithDaskcourse.
PythonDataVisualizationTools
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Datavisualizationgiveslifetodataanalysis.Ifyouwanttoexplainthingstonon-technical executives,youneedtotelladatastorybydisplayingabarchart,lineplot,scatterplot,heat maps,andhistograms.Thevisualizationtoolshelpdataanalyticscreateinteractive,colorful,and cleanvisualizationwithfewlinesofcode.
14.Matplotlib
Matplotlibisagatewaytotheworldofdatavisualization.Youwilllearnaboutitinmanydata visualizationintroductions.
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WithMatplotlib,youcancreatefullycustomizablestatic,animated,andinteractivevisualizations. It’sintuitive,andyoucanuseittoplot3D,multilevel,anddetailedvisualization.Thereare hundredsofexamplesofdifferentvisualizationsavailableinthegallery.
YoucanlearnmoreaboutMatplotlibinourDataVisualizationwithMatplotlibcourse..
15.Seaborn
Seabornisahigh-levelinterfacebasedonMatplotlibforcreatingattractivestatisticalgraphics. SimilartoMatplotlib,youcanproduceinteractivevisualizationbytypingasinglelineofcode.
Itishighlyadaptableandworkswonderswhenyouarenewtodatavisualization.Forcustomizing, youcanalwaysusematplotlibtocreatemultiplegraphs,editaxis,title,orevencolors.Insome cases,seabornwillcalculateeverythingforyouanddisplaydistplot,violinplot,residplot,implot, jointplot,andboxplot.
LearnmoreaboutSeabornbytakingaDataVisualizationwithSeaborncourseonDataCamp.
16.Plotly
WhenyouwantthefeaturesofTableauorPowerBI,youusethePlotlyPythonlibrarytodisplay interactiveandpublication-qualitygraphs.Youcanzoomintoagraph,isolateasinglebar,filter things,andevenanimateittoyourneeds.
Itcomeswithcustomcontrolsandallowsyoutoanimateyourvisualizationsandworkondata transformation.PlotlyalsocontainsJupyterwidgets,3Dcharts,AIcharts,financialcharts,and scientificcharts.
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PlotlyisthebesttooltocreatedataanalyticsJupyter-basedreports.Insteadofcreatingmultiple staticplots,youcanmakeoneandaddcustomcontrolstoexploreandexplaindatainsights.
YoucandiscoverhowtoutilizePlotlywithourDataVisualizationwithPlotlycourse.
Pandas-profiling
Pandas-profilingisanAutoEDAtoolforcreatingexploratorydataanalyticsreportswithasingle lineofcode.Thereportincludescolumntypes,missingvalues,uniquevalues,quantilestatistics, descriptivestatistics,histogram,correlation,textanalysis,andfileandimageanalysis.
Itisquiteahelpfultoolwhenyouhavelesstimetoexplore.Forexample,duringtechnicaltests, preparationforteammeetings,andparticipatinginthecompetition.
PythonMachineLearningTools
Machinelearningtoolsareusedfordataprocessing,dataaugmentation,andbuilding,training, andvalidationofmachinelearningmodels.Thesetoolsprovideacompleteecosystemtoperform anytaskfromimageclassificationtotimesseriesforecasting.
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18.Scikit-learn
Scikit-learnisanopen-sourcetoolforperformingpredictiveanalysis.ItisbuiltonNumpy,Scipy, andmatplotlib.Scikit-learnhasmademachinelearningaccessibletoeveryone.Itisbeginner friendly,andtheinterfaceisdesignedtomatchtheneedsofprofessionals.
Scikit-learnallowsyoutoperformclassification,regression,clustering,dimensionalityreduction, datapreprocessing,andfeatureextractions.Itismostlyusedfortabulardataandexecutingdata augmentationfordeeplearningmodels.Italsoallowsyoutostreamlinemultipleprocesseswith thehelpofmachinelearningpipelines.
Learnmoreaboutscikit-learnbytakingourSupervisedLearningwithscikit-learncourse.
Keras
Kerasisadeeplearningframeworkforprocessingunstructureddataandtrainingitonneural networks.ItisbuiltontopofTensorFlow2toprovideGPUandTPUacceleration.WithKeras,you candeployyourmodelsontheserver,browser,android,andembeddedsystems.
KerasAPIoffersyouamodelinterface,neuralnetworklayers,callbacksAPI,optimizers,metrics, dataloaders,pre-trainedmodels,modeltuning,andAPIforcomputervisionandnaturallanguage processing.Theinterfaceissimple,fast,andpowerful.Itisbeginnerfriendlyandagatewaytothe worldofdeepneuralnetworks.
LearnmoreaboutKerasbytakingourDeepLearningwithKerascourseorcheckingout ourKerasdeeplearningtutorial.
PyTorch
PyTorchisanopen-sourcedeeplearningframeworkforresearchersandmachinelearning practitioners.ItprovidesamoredirectdebuggingexperiencethanKeras,whileallowingyouto createyourcustomtrainer,lossfunction,andmetrics.
ThekeyfeaturesofPyTorcharemodelservingandproductionsupport,distributedtraining,a robustecosystem,andcloudsupport.
PyTorchprovidesdedicatedsupportforNLP,computervision,audio,andtabulardata.Withafew linesofcode,youcanloadpre-trainedmodelsandfinetunethemonanewbutsimilardataset.
Itisthefutureofdeeplearningapplications,andmodernmachinelearningresearchisdrivenby theTorchecosystem.
CheckoutourDeepLearningwithPyTorchcoursetolearnmoreabouttheapplicationsof PyTorch.
OpenCV
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OpenCVisacomputervisionframeworkfordevelopingreal-timeapplications.Youcanuseitto processimages,visualizethemwithlabelsandsegmentation,augmentimagesandvideosfor improvingmachinelearningperformance,andviewreal-timeresultswithlabels.Itisanessential toolforperformingimageprocessingandtrainingdeeplearningmodelsforcomputervisiontasks.
LearnmoreaboutOpenCVbytakinganImageProcessingcourseonDataCamp.
Conclusion
These21essentialPythontoolsarenecessaryforsoftwareandwebdevelopment,webscraping, dataanalyticsandvisualization,andmachinelearning.Evenifyouarenotadataprofessional, youmustunderstandthefunctionalitiesofthesetoolstomakethemostoutofthedevelopment experience.
IfyouarenewtoPythonandbecomeaprofessionalPythondeveloperinnotime,checkout thePythonProgrammercareertrack.Andifyouareinterestedinstartingadatasciencecareer, checkoutDataScientistwithPythoncareertrack.
CoursesforPython
Levelupyourdatascience skillsbycreatingvisualizations usingMatplotliband manipulatingDataFrameswith pandas.
IntermediatePython 4Hours
HugoBowne-Anderson CourseInstructorContinuetobuildyourmodern DataScienceskillsbylearning aboutiteratorsandlist comprehensions.
PythonDataScience Toolbox(Part2) 4Hours
HugoBowne-Anderson CourseInstructor
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