南開科技大學圖書館 |

Language: 繁體中文

說明(常見問題)

南開科技大學

圖書館首頁

編目中圖書申請

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Humanities data analysis :case studies with Python /

紀錄類型:	書目-語言資料,印刷品 : 單行本
正題名/作者:	Humanities data analysis :/ Folgert Karsdorp, Mike Kestemont & Allen Riddell.
其他題名:	case studies with Python /
作者:	Karsdorp, Folgert,
其他作者:	Kestemont, Mike,
出版者:	Princeton :Princeton University Press,c2021.
面頁冊數:	xiii, 337 p. :ill. (some col.), maps (some col.) ;27 cm.
標題:	Humanities - Research -
ISBN:	9780691172361 (hbk.) :

Humanities data analysis :case studies with Python /
Karsdorp, Folgert,

Humanities data analysis :case studies with Python /Folgert Karsdorp, Mike Kestemont & Allen Riddell. - Princeton :Princeton University Press,c2021. - xiii, 337 p. :ill. (some col.), maps (some col.) ;27 cm.

Includes bibliographical references and index.

"The use of quantitative methods in the humanities and related social sciences has increased considerably in recent years, allowing researchers todiscover patterns in a vast range of source materials. Despite this growth,there are few resources addressed to students and scholars who wish to takeadvantage of these powerful tools. Humanities Data Analysis offers the firstintermediate-level guide to quantitative data analysis for humanitiesstudents and scholars using the Python programming language. This practicaltextbook, which assumes a basic knowledge of Python, teaches readers thenecessary skills for conducting humanities research in the rapidlydeveloping digital environment. The book begins with an overview of theplace of data science in the humanities, and proceeds to cover datacarpentry: the essential techniques for gathering, cleaning, representing,and transforming textual and tabular data. Then, drawing from real-world,publicly available data sets that cover a variety of scholarly domains, thebook delves into detailed case studies. Focusing on textual data analysis,the authors explore such diverse topics as network analysis, genre theory,onomastics, literacy, author attribution, mapping, stylometry, topicmodeling, and time series analysis. Exercises and resources for furtherreading are provided at the end of each chapter. An ideal resource forhumanities students and scholars aiming to take their Python skills to thenext level, Humanities Data Analysis illustrates the benefits thatquantitative methods can bring to complex research questions. Appropriatefor advanced undergraduates, graduate students, and scholars with a basicknowledge of Python. Applicable to many humanities disciplines, includinghistory, literature, and sociology. Offers real-world case studies usingpublicly available data sets. Provides exercises at the end of each chapterfor students to test acquired skills. Emphasizes visual storytelling viadata visualizations"--

ISBN: 9780691172361 (hbk.) :NT1220

LCCN: 2020034614Subjects--Topical Terms:

1000140798
Humanities
--Research

LC Class. No.: AZ186 / .K37 2021

Dewey Class. No.: 001.3072/1

Humanities data analysis :case studies with Python /
LDR:02669cam a2200205 a 450 001 1000117006
005 20200818173358.0
008 200814s2021 njuab b 001 0 eng
010 $a 2020034614
020 $a 9780691172361 (hbk.) : $c NT1220
020 $z 9780691200330 (ebook)
035 $a 669902
040 $a DLC $b eng $c DLC
042 $a pcc
050 0 0 $a AZ186 $b .K37 2021
082 0 0 $a 001.3072/1 $2 23
100 1 $a Karsdorp, Folgert, $e author. $3 1000140795
245 1 0 $a Humanities data analysis : $b case studies with Python / $c Folgert Karsdorp, Mike Kestemont & Allen Riddell.
260 # $a Princeton : $b Princeton University Press, $c c2021.
300 $a xiii, 337 p. : $b ill. (some col.), maps (some col.) ; $c 27 cm.
504 $a Includes bibliographical references and index.
520 # $a "The use of quantitative methods in the humanities and related social sciences has increased considerably in recent years, allowing researchers todiscover patterns in a vast range of source materials. Despite this growth,there are few resources addressed to students and scholars who wish to takeadvantage of these powerful tools. Humanities Data Analysis offers the firstintermediate-level guide to quantitative data analysis for humanitiesstudents and scholars using the Python programming language. This practicaltextbook, which assumes a basic knowledge of Python, teaches readers thenecessary skills for conducting humanities research in the rapidlydeveloping digital environment. The book begins with an overview of theplace of data science in the humanities, and proceeds to cover datacarpentry: the essential techniques for gathering, cleaning, representing,and transforming textual and tabular data. Then, drawing from real-world,publicly available data sets that cover a variety of scholarly domains, thebook delves into detailed case studies. Focusing on textual data analysis,the authors explore such diverse topics as network analysis, genre theory,onomastics, literacy, author attribution, mapping, stylometry, topicmodeling, and time series analysis. Exercises and resources for furtherreading are provided at the end of each chapter. An ideal resource forhumanities students and scholars aiming to take their Python skills to thenext level, Humanities Data Analysis illustrates the benefits thatquantitative methods can bring to complex research questions. Appropriatefor advanced undergraduates, graduate students, and scholars with a basicknowledge of Python. Applicable to many humanities disciplines, includinghistory, literature, and sociology. Offers real-world case studies usingpublicly available data sets. Provides exercises at the end of each chapterfor students to test acquired skills. Emphasizes visual storytelling viadata visualizations"-- $c Provided by publisher.
650 # 0 $a Humanities $x Research $x Methodology. $3 1000140798
650 # 0 $a Python (Computer program language) $3 163241
650 # 0 $a Quantitative research $x Data processing. $3 1000140799
650 # 0 $a Social sciences $x Research $x Methodology. $3 164817
700 1 # $a Kestemont, Mike, $d 1985- $e author. $3 1000140796
700 1 # $a Riddell, Allen, $e author. $3 1000140797