Python for Information Professionals: How to Design Practical Applications to Capitalize on the Data Explosion is an introduction to the Python programming language for library and information professionals with little or no prior experience.
Python for Information Professionals: How to Design Practical Applications to Capitalize on the Data Explosion is an introduction to the Python programming language for library and information professionals with little or no prior experience.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
By Brady Lund; Daniel Agbaji; Kossi Dodzi Bissadu and Haihua Chen
Inhaltsangabe
Preface Part I: Python: The Basics * Chapter 1 - The Python Workspace * Chapter 2 - Object Oriented Programming * Chapter 3 - Data Types, Structures, Sets and Algorithms * Chapter 4 - Functions: Code that Puts Our Data to Work * Chapter 5 - Importing, Creating, and Maintaining Data Files * Chapter 6 - Testing and Troubleshooting Part II: Further Applications of Python in Information Organizations * Chapter 7 - Library Management and Usage Data * Chapter 8 - Library Research Data Management * Chapter 9 - Text Analysis * Chapter 10 - Library and Information Science Research * Chapter 11 - Artificial Intelligence Applications Part III: Practical and Ethical Considerations for Using Python * Chapter 12 - Data Explosion, Big Data, and Data Literacy * Chapter 13 - Data Ethics * Chapter 14 - Knowledge and Data Economy * Chapter 15 - Further Resources for Advancing Your Python Mastery Glossary Index About the Author
Preface Part I: Python: The Basics * Chapter 1 - The Python Workspace * Chapter 2 - Object Oriented Programming * Chapter 3 - Data Types, Structures, Sets and Algorithms * Chapter 4 - Functions: Code that Puts Our Data to Work * Chapter 5 - Importing, Creating, and Maintaining Data Files * Chapter 6 - Testing and Troubleshooting Part II: Further Applications of Python in Information Organizations * Chapter 7 - Library Management and Usage Data * Chapter 8 - Library Research Data Management * Chapter 9 - Text Analysis * Chapter 10 - Library and Information Science Research * Chapter 11 - Artificial Intelligence Applications Part III: Practical and Ethical Considerations for Using Python * Chapter 12 - Data Explosion, Big Data, and Data Literacy * Chapter 13 - Data Ethics * Chapter 14 - Knowledge and Data Economy * Chapter 15 - Further Resources for Advancing Your Python Mastery Glossary Index About the Author
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