000 03874nam a2200517 i 4500
001 on1374196026
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006 m d
007 cr |||||||||||
008 230131s2023 flua ob 001 0 eng
010 _a 2022049051
040 _aEBZ
_beng
_cEBZ
020 _a9781003218012
_q(ebook)
020 _a1003218016
020 _a9781000863093
_q(electronic bk.)
020 _a1000863093
_q(electronic bk.)
020 _z9781032109992
_q(hardback)
020 _z9781032080826
_q(paperback)
042 _apcc
050 0 0 _aQA276.45.R3
049 _aMAIN
100 1 _aLin, Sarah,
_eauthor.
_965000
245 1 0 _aHands-on data science for librarians /
_cSarah Lin, Dorris Scott.
263 _a2304
264 1 _aBoca Raton :
_bCRC Press
_c2023.
300 _a1 online resource :
_billustrations.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
341 0 _atextual
_2sapdv
_3EBSCOhost
532 0 _3EBSCOhost
_a"EBSCO evaluates our products based on the Web Content Accessibility Guidelines (WCAG) and the related Section 508 and EN 301 549 regulations in the US and EU. Most EBSCO products are substantially conformant with WCAG 2.2 level AA." Source: https://connect.ebsco.com/s/article/EBSCO-VPATs?language=en_US. Last accessed April 22, 2025.
588 _aDescription based on print version record.
504 _aIncludes bibliographical references and index.
505 0 _aUsing 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.
520 _a"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)"--
_cProvided by publisher.
650 0 _aR (Computer program language)
_965001
650 0 _aLibraries
_xData processing.
_965002
700 1 _aScott, Dorris,
_eauthor.
_965003
776 0 8 _iPrint version:
_aLin, Sarah.
_tHands-on data science for librarians
_dBoca Raton : CRC Press 2023
_z9781032109992
_w(DLC) 2022049050
856 4 0 _3EBSCOhost
_uhttps://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=3590941
938 _aEBSCOhost
_bEBSC
_n3590941
994 _a92
_bN$T
999 _c56105
_d56105