LEADER 00952nam0-22003011i-450- 001 990001869190403321 005 20021010 035 $a000186919 035 $aFED01000186919 035 $a(Aleph)000186919FED01 035 $a000186919 100 $a20021010d--------km-y0itay50------ba 101 0 $aita 200 1 $aSul valore delle osservazioni alla gestione infortuni agricoli della Cassa Nazionale Infortuni$fLucio TascaBordonaro. 210 $aRoma$cTip. del Senato$d1925. 215 $a22 p.$d26 cm 610 0 $aAssicurazioni agricole 610 0 $aInfortuni - assicurazioni 676 $a368.5 700 1$aTasca Bordonaro,$bLucio$082033 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990001869190403321 952 $a60 MISC. B 150/6$b$fFAGBC 959 $aFAGBC 996 $aSul valore delle osservazioni alla gestione infortuni agricoli della Cassa Nazionale Infortuni$9401056 997 $aUNINA DB $aING01 LEADER 04739nam 22007215 450 001 9910481953403321 005 20251113194637.0 010 $a3-030-54371-4 024 7 $a10.1007/978-3-030-54371-6 035 $a(CKB)4100000011631449 035 $a(DE-He213)978-3-030-54371-6 035 $a(MiAaPQ)EBC6455924 035 $a(PPN)252517326 035 $a(EXLCZ)994100000011631449 100 $a20201204d2020 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aIntroduction to Data Systems $eBuilding from Python /$fby Thomas Bressoud, David White 205 $a1st ed. 2020. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2020. 215 $a1 online resource (XXIX, 828 p. 81 illus., 65 illus. in color.) 311 08$a3-030-54370-6 327 $aPart I Foundation -- 1. Introduction -- 2. File Systems and File Processing -- 3. Python Native Data Structures -- 4. Regular Expressions -- Part II Data Systems: The Data Models -- 5. Data Systems Models -- 6. Tabular Model: Structure and Formats -- 7. Tabular Model: Access Operations and pandas -- 8. Tabular Model: Advanced Operations and pandas -- 9. Tabular Model: Transformations and Constraints -- 10. Relational Model: Structure and Architecture -- 11. Relational Operations: Single Table -- 12. Relational Operations: Multiple Tables -- 13. Relational Database Programming -- 14. Relational Model: Design, Constraints, and Creation -- 15. Hierarchical Model: Structure and Formats -- 16. Hierarchical Model: Operations and Programming -- 17. Hierarchical Model: Constraints -- Part III Data Systems: The Data Sources -- 18. Overview of Data Systems Sources -- 19. Networking and Client-Server -- 20. The HyperText Transfer Protocol -- 21. Interlude: Client Data Acquisition -- 22. Web Scraping -- 23. RESTful Application Programming Interfaces -- 24. Authentication and Authorization. 330 $aEncompassing a broad range of forms and sources of data, this textbook introduces data systems through a progressive presentation. Introduction to Data Systems covers data acquisition starting with local files, then progresses to data acquired from relational databases, from REST APIs and through web scraping. It teaches data forms/formats from tidy data to relationally defined sets of tables to hierarchical structure like XML and JSON using data models to convey the structure, operations, and constraints of each data form. The starting point of the book is a foundation in Python programming found in introductory computer science classes or short courses on the language, and so does not require prerequisites of data structures, algorithms, or other courses. This makes the material accessible to students early in their educational career and equips them with understanding and skills that can be applied in computer science, data science/data analytics, and information technology programs as well as for internships and research experiences. This book is accessible to a wide variety of students. By drawing together content normally spread across upper level computer science courses, it offers a single source providing the essentials for data science practitioners. In our increasingly data-centric world, students from all domains will benefit from the ?data-aptitude? built by the material in this book. 606 $aData mining 606 $aData structures (Computer science) 606 $aInformation theory 606 $aArtificial intelligence 606 $aComputer networks 606 $aBig data 606 $aPython (Computer program language) 606 $aData Mining and Knowledge Discovery 606 $aData Structures and Information Theory 606 $aArtificial Intelligence 606 $aComputer Communication Networks 606 $aBig Data 606 $aPython 615 0$aData mining. 615 0$aData structures (Computer science) 615 0$aInformation theory. 615 0$aArtificial intelligence. 615 0$aComputer networks. 615 0$aBig data. 615 0$aPython (Computer program language) 615 14$aData Mining and Knowledge Discovery. 615 24$aData Structures and Information Theory. 615 24$aArtificial Intelligence. 615 24$aComputer Communication Networks. 615 24$aBig Data. 615 24$aPython. 676 $a006.312 700 $aBressoud$b Thomas$0960004 702 $aWhite$b David 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910481953403321 996 $aIntroduction to data systems$92175815 997 $aUNINA