Foundations of data science with Python / (Record no. 30685)

MARC details
000 -LEADER
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001 - CONTROL NUMBER
control field 23579326
003 - CONTROL NUMBER IDENTIFIER
control field OSt
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20250830095446.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 240225s2024 flua b 001 0 eng
010 ## - LIBRARY OF CONGRESS CONTROL NUMBER
LC control number 2023037553
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781032346748
Qualifying information (hardback)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781032350424
Qualifying information (paperback)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
Canceled/invalid ISBN 9781003324997
Qualifying information (ebook)
035 ## - SYSTEM CONTROL NUMBER
System control number 23579326
040 ## - CATALOGING SOURCE
Original cataloging agency DLC
Language of cataloging eng
Description conventions rda
Transcribing agency TUPM
Modifying agency DLC
042 ## - AUTHENTICATION CODE
Authentication code pcc
050 00 - LIBRARY OF CONGRESS CALL NUMBER
Classification number QA 76.9
Item number S54 2024
082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 519.50285/5133
Edition number 23/eng/20240229
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Shea, John M.
Relator term author.
245 10 - TITLE STATEMENT
Title Foundations of data science with Python /
Statement of responsibility, etc. John M. Shea.
250 ## - EDITION STATEMENT
Edition statement First edition.
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture Boca Raton :
Name of producer, publisher, distributor, manufacturer CRC Press, Taylor & Francis Group,
Date of production, publication, distribution, manufacture, or copyright notice 2024.
300 ## - PHYSICAL DESCRIPTION
Extent 488 pages :
Other physical details illustrations (some color) ;
Dimensions 27 cm.
336 ## - CONTENT TYPE
Content type term text
Content type code txt
Source rdacontent
337 ## - MEDIA TYPE
Media type term unmediated
Media type code n
Source rdamedia
338 ## - CARRIER TYPE
Carrier type term volume
Carrier type code nc
Source rdacarrier
490 0# - SERIES STATEMENT
Series statement Chapman & Hall/CRC data science series
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc. note Includes bibliographical references and index.
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note First simulations, visualizations, and statistical tests -- First visualizations and statistical tests with real data -- Introduction to probability -- Null hypothesis tests -- Conditional probability, dependence, and independence -- Introduction to Bayesian methods -- Random variables -- Expected value, parameter estimation, and hypothesis tests on sample means -- Decision making with observations from continuous distributions -- Categorical data, tests for dependence, and goodness of fit for discrete distributions -- Multidimensional data : vector moments and linear regression -- Working with dependent data in multiple dimensions.
520 ## - SUMMARY, ETC.
Summary, etc. "Foundations of Data Science with Python introduces readers to the fundamentals of data science, including data manipulation and visualization, probability, statistics, and dimensionality reduction. This book is targeted toward engineers and scientists, but it should be readily understandable to anyone who knows basic calculus and the essentials of computer programming. It uses a computational-first approach to data science: the reader will learn how to use Python and the associated data-science libraries to visualize, transform, and model data, as well as how to conduct statistical tests using real data sets. Rather than relying on obscure formulas that only apply to very specific statistical tests, this book teaches readers how to perform statistical tests via resampling; this is a simple and general approach to conducting statistical tests using simulations that draw samples from the data being analyzed. The statistical techniques and tools are explained and demonstrated using a diverse collection of data sets to conduct statistical tests related to contemporary topics, from the effects of socioeconomic factors on the spread of the COVID-19 virus to the impact of state laws on firearms mortality. This book can be used as an undergraduate textbook for an Introduction to Data Science course or to provide a more contemporary approach in courses like Engineering Statistics. However, it is also intended to be accessible to practicing engineers and scientists who need to gain foundational knowledge of data science"--
Assigning source Provided by publisher.
590 ## - CITATION
Citation Shea, J. M. (2024). Foundations of data science with Python (1st ed.). CRC Press.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Statistics
General subdivision Data processing,
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Probabilities
General subdivision Data processing.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Information visualization.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Python (Computer program language)
906 ## - LOCAL DATA ELEMENT F, LDF (RLIN)
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b cbc
c orignew
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e ecip
f 20
g y-gencatlg
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Library of Congress Classification
Koha item type Book
Suppress in OPAC No
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Home library Current library Shelving location Date acquired Source of acquisition Cost, normal purchase price Inventory number Total checkouts Full call number Barcode Date last seen Cost, replacement price Price effective from Koha item type
    Library of Congress Classification     TUP Manila Library TUP Manila Library General Circulation Section-GF 05/26/2025 Forefront 7398.00 34241   QA 76.9 S54 2024 P00034241 08/30/2025 7398.00 05/26/2025 Book



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