Hands-on data science for librarians / Sarah Lin, Dorris Scott.
By: Lin, Sarah [author.].
Contributor(s): Scott, Dorris [author.].
Series: Data Science Series. Publisher: Boca Raton CRC Press 2023Description: xlx, 180p.ISBN: 9781032080826.Subject(s): R (Computer program language) | Libraries -- Data processingDDC classification: 025.00285| Item type | Current location | Call number | Status | Date due | Barcode |
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NASSDOC Library | 025.00285 LIN-H (Browse shelf) | Available | 54318 |
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| 025.00285 HAR-D Digital curation: a how to do it manual | 025.00285 JOI-E Emerging Library Technologies | 025.00285 KOC-L Library information systems : from library automation to distributed information access solutions | 025.00285 LIN-H Hands-on data science for librarians / | 025.00285 MAN- Managing technologies and automated library systems in developing countries: open source vs commercial options | 025.00285 MAR-; Information technology and the role of the librarian | 025.00285 PHA-R Reinventing Libraries with Future Technologies |
Includes bibliographical references and index.
Using RStudio's IDE -- Tidying data with dplyr -- Visualizing your project with ggplot2 -- Webscraping with rvest -- Mapping with tmap -- Textual analysis with tidytext -- Creating dynamic documents with rmarkdown -- Creating a flexdashboard -- Creating an interactive dashboard with shiny -- Using tidymodels to understand machine learning.
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).
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