Hands-On Data Science for Librarians (Chapman & Hall/CRC Data Science Series). Questo articolo non è disponibile.
Lingua: inglese
Editore: Chapman and Hall/CRC, 2023
- Rilegato
- Nuovo

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Descrizione dell’articolo da parte del venditore
In English.
Codice articolo ria9781032109992_new
- Titolo
- Hands-On Data Science for Librarians (Chapman & Hall/CRC Data Science Series)
- Autore
- Lin, Sarah; Scott, Dorris
- Editore
- Chapman and Hall/CRC
- Anno di pubblicazione
- 2023
- Condizione
- New
- Rilegatura
- Rilegato
- Lingua
- inglese
- ISBN 10
- 1032109998
- ISBN 13
- 9781032109992
- Peso dell'articolo
- 496 grammi
- Serie
- Libro 24 di 36: Chapman & Hall/CRC Data Science
Librarians understand the need to store, use and analyze data related to their collection, patrons and institution, and there has been consistent interest over the last 10 years to improve data management, analysis, and visualization skills within the profession. However, librarians find it difficult to move from out-of-the-box proprietary software applications to the skills necessary to perform the range of data science actions in code. This book will focus on teaching R through relevant examples and skills that librarians need in their day-to-day lives that includes visualizations but goes much further to include web scraping, working with maps, creating interactive reports, machine learning, and others. While there’s a place for theory, ethics, and statistical methods, librarians need a tool to help them acquire enough facility with R to utilize data science skills in their daily work, no matter what type of library they work at (academic, public or special). By walking through each skill and its application to library work before walking the reader through each line of code, this book will support librarians who want to apply data science in their daily work. Hands-On Data Science for Librarians is intended for librarians (and other information professionals) in any library type (public, academic or special) as well as graduate students in library and information science (LIS).
Key Features:
- Only data science book available geared toward librarians that includes step-by-step code examples
- Examples include all library types (public, academic, special)
- Relevant datasets
- Accessible to non-technical professionals
- Focused on job skills and their applications
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Informazioni sull’autore
Sarah Lin is the Senior Information & Content Architect at MongoDB.
Dorris Scott, PhD is the Academic Director of Data Studies at Washington University in St. Louis.
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