Introduction to data systems : building from Python (Record no. 30984)

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fixed length control field 220610b xxu||||| |||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783030543730
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.312
Item number BRE
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Bressoud, Thomas
245 ## - TITLE STATEMENT
Title Introduction to data systems : building from Python
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Name of publisher, distributor, etc Springer,
Date of publication, distribution, etc 2020
Place of publication, distribution, etc Cham :
300 ## - PHYSICAL DESCRIPTION
Extent xxix, 828 p. ;
Other physical details ill.,
Dimensions 24 cm
365 ## - TRADE PRICE
Price amount 49.99
Price type code EUR
Unit of pricing 86.00
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc Includes bibliographical references and index.
520 ## - SUMMARY, ETC.
Summary, etc Encompassing 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.
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Topical term or geographic name as entry element Python
Topical term or geographic name as entry element Computer program language
Topical term or geographic name as entry element Data mining
Topical term or geographic name as entry element Data structures
Topical term or geographic name as entry element Computer science
Topical term or geographic name as entry element Big data
Topical term or geographic name as entry element Artificial intelligence
Topical term or geographic name as entry element Computers
Topical term or geographic name as entry element Aggregation
Topical term or geographic name as entry element Byte-stream
Topical term or geographic name as entry element Client-secret
Topical term or geographic name as entry element Data structure
Topical term or geographic name as entry element Element treee parser
Topical term or geographic name as entry element Functional dependency
Topical term or geographic name as entry element Hierarchical data model
Topical term or geographic name as entry element JSON schema
Topical term or geographic name as entry element Lxml module
Topical term or geographic name as entry element Missing data
Topical term or geographic name as entry element Node
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Topical term or geographic name as entry element Authorization
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Personal name White, David
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Source of classification or shelving scheme
Item type Books
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Permanent location Current location Date acquired Cost, normal purchase price Full call number Barcode Date last seen Koha item type
          DAIICT DAIICT 2022-06-01 4299.14 006.312 BRE 033044 2022-06-10 Books

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