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Titlebook: Introduction to Data Systems; Building from Python Thomas Bressoud,David White Textbook 2020 Springer Nature Switzerland AG 2020 Data syste

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發(fā)表于 2025-3-21 17:10:40 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Introduction to Data Systems
副標(biāo)題Building from Python
編輯Thomas Bressoud,David White
視頻videohttp://file.papertrans.cn/474/473598/473598.mp4
概述With minimal prerequisites (Intro CS or Foundations of Python Programming), students in computer science or data science/data analytics are introduced to data systems, and develop data-aptitude early
圖書封面Titlebook: Introduction to Data Systems; Building from Python Thomas Bressoud,David White Textbook 2020 Springer Nature Switzerland AG 2020 Data syste
描述.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,
出版日期Textbook 2020
關(guān)鍵詞Data systems; Data model; REST API; client-server; HTTP; relational database system; Data science; Hierarch
版次1
doihttps://doi.org/10.1007/978-3-030-54371-6
isbn_softcover978-3-030-54373-0
isbn_ebook978-3-030-54371-6
copyrightSpringer Nature Switzerland AG 2020
The information of publication is updating

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File Systems and File Processingng and closing files, for both reading and writing, using Python. Lastly, we describe iterating through the lines of a file (both textual and comma-separated value) to extract data, and JSON file processing tools.
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Python Native Data Structures two-dimensional data. We discuss the pros and cons of each representation, and common patterns for creating them, filtering and mutating them, and extracting data from them. This discussion includes list comprehensions, accumulation, lambda functions, and mapping functions onto lists and dictionari
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Regular Expressionsing, wildcard characters, matching a particular number of repetitions, disjunction, capture groups, and the use of anchors to control where a match occurs. We illustrate each concept with a Python example and describe applications where regular expressions are commonly used.
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Data Systems Modelsh model: via its structure, operations, and constraints. For each of the three models, we give a high-level summary of its design, common operations (e.g., to access, mutate, or aggregate data), and rules that data in the model must satisfy.
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Tabular Model: Structure and Formatsriables to dependent variables, and file formats. We introduce the “pandas” module and the concept of a “DataFrame.” We illustrate how to read data from a comma-separated value file using Python programming, and using “pandas.” Lastly, we introduce basic “pandas” methods that operate on an entire “D
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Tabular Model: Access Operations and ,ow and column projection, column-vector operations, aggregation operations, updating columns, and adding and deleting data. We then illustrate these operations using “pandas” methods, “DataFrame” objects, and “Series” objects.
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Relational Model: Database Programmingdatabase, be it in a local SQLite file, or over a network interacting with a DBMS such as MySQL. Topics include establishing connections with the database, issuing SQL queries and retrieving results, and incorporating local variables in the construction of queries. The programming also ties back to
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