01092nam0-2200349---450-99000946080040332120111025103131.01-4020-0228-9000946080FED01000946080(Aleph)000946080FED0100094608020111021d2002----km-y0itay50------baengZZa-------001yyHandbook on life cycle assessmentoperational guide to the ISO standardsJeroen B. Guineée (final editor)[et al.]Hans de Bruijn [et al.]Dordrecht [et al.]Kluwer Academic Publishersc2002XI, 692 p.ill.27 cmEco-efficiency in industry and science7ProduzioneControlloIndustria e ecologia658.56Guineée,J. B.Bruijn,Hans : deITUNINARICAUNIMARCBK99000946080040332160 658.56 B 113524FAGBCFAGBCHandbook on life cycle assessment853231UNINA01186nam a2200265 i 450099100051763970753620020509171717.0000220s1968 it ||| | ita b11370312-39ule_instPARLA210026ExLDip.to Filosofiaita190.9Di Vona, Piero159296Studi sulla scolastica della controriforma :l'esistenza e la sua distinzione metafisica dall'essenza /Piero Di VonaFirenze :Vallecchi,1968XII, 317 p. ;24 cmPubblicazioni della Facoltà di Lettere e filosofia dell'Università di Milano ;48Pubblicazioni della Facoltà di Lettere e filosofia dell'Università di Milano. Sezione a cura dell'Istituto di storia della filosofia ;14Filosofia occidentale modernaStoria.b1137031201-03-1701-07-02991000517639707536LE005IF II E 512005000068133le005-E0.00-l- 00000.i1155242601-07-02Studi sulla scolastica della controriforma478444UNISALENTOle00501-01-00ma -itait 0104039nam 22006255 450 991033801660332120230310143943.01-4842-4511-310.1007/978-1-4842-4511-8(CKB)4100000007992519(MiAaPQ)EBC5755001(DE-He213)978-1-4842-4511-8(CaSebORM)9781484245118(PPN)235671649(EXLCZ)99410000000799251920190417d2019 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierLearn RStudio IDE Quick, Effective, and Productive Data Science /by Matthew Campbell1st ed. 2019.Berkeley, CA :Apress :Imprint: Apress,2019.1 online resource (157 pages)1. Installing RStudio -- 2. Hello World -- 3. RStudio Views -- 4. RStudio Projects -- 5. Repeatable Analysis -- 6. Essential R Packages: Tidyverse -- 7. Data Visualization -- 8. R Markdown -- 9. Shiny R Dashboards -- 10. Custom R Packages -- 11. Code Tools -- 12. R Programming.Discover how to use the popular RStudio IDE as a professional tool that includes code refactoring support, debugging, and Git version control integration. This book gives you a tour of RStudio and shows you how it helps you do exploratory data analysis; build data visualizations with ggplot; and create custom R packages and web-based interactive visualizations with Shiny. In addition, you will cover common data analysis tasks including importing data from diverse sources such as SAS files, CSV files, and JSON. You will map out the features in RStudio so that you will be able to customize RStudio to fit your own style of coding. Finally, you will see how to save a ton of time by adopting best practices and using packages to extend RStudio. Learn RStudio IDE is a quick, no-nonsense tutorial of RStudio that will give you a head start to develop the insights you need in your data science projects. You will: Quickly, effectively, and productively use RStudio IDE for building data science applications Install RStudio and program your first Hello World application Adopt the RStudio workflow Make your code reusable using RStudio Use RStudio and Shiny for data visualization projects Debug your code with RStudio Import CSV, SPSS, SAS, JSON, and other data.Programming languages (Electronic computers)Computer programmingEngineering—Data processingData miningMathematical statisticsR (Computer program language)Programming Languages, Compilers, Interpretershttps://scigraph.springernature.com/ontologies/product-market-codes/I14037Programming Techniqueshttps://scigraph.springernature.com/ontologies/product-market-codes/I14010Data Engineeringhttps://scigraph.springernature.com/ontologies/product-market-codes/T11040Data Mining and Knowledge Discoveryhttps://scigraph.springernature.com/ontologies/product-market-codes/I18030Probability and Statistics in Computer Sciencehttps://scigraph.springernature.com/ontologies/product-market-codes/I17036Programming languages (Electronic computers)Computer programming.Engineering—Data processing.Data mining.Mathematical statistics.R (Computer program language)Programming Languages, Compilers, Interpreters.Programming Techniques.Data Engineering.Data Mining and Knowledge Discovery.Probability and Statistics in Computer Science.006.312Campbell Matthewauthttp://id.loc.gov/vocabulary/relators/aut686643BOOK9910338016603321Learn RStudio IDE2106915UNINA