Wow! eBook
Python for Information Professionals:How to Design Practical Applications to Capitalize on the Data Explosion
by: Brady Lund (Author),Daniel Agbaji(Author),Kossi Dodzi Bissadu(Author),Haihua Chen(Author)&1more
Publisher: Rowman & Littlefield Publishers
Publication Date: 2023/11/1
Language: English
Print Length: 172 pages
ISBN-10: 1538178249
ISBN-13: 9781538178249
Book Description
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. As opposed to the many Python books available today that focus on the language only from a general sense, this book is designed specifically for information professionals who are seeking to advance their career prospects or challenge themselves in new ways by acquiring skills within the rapidly expanding field of data science. Readers of Python for Information Professionals will lea to:Develop Python applications for the retrieval, cleaning, and analysis of large datasets. Design applications to support traditional library functions and create new opportunities to maximize library value. Consider data security and privacy relevant to data analysis when using the Python language.
About the Author
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. As opposed to the many Python books available today that focus on the language only from a general sense, this book is designed specifically for information professionals who are seeking to advance their career prospects or challenge themselves in new ways by acquiring skills within the rapidly expanding field of data science. Readers of Python for Information Professionals will lea to:Develop Python applications for the retrieval, cleaning, and analysis of large datasets. Design applications to support traditional library functions and create new opportunities to maximize library value. Consider data security and privacy relevant to data analysis when using the Python language.
