Python Data Science Handbook : (Record no. 60195)

MARC details
000 -LEADER
fixed length control field 04300cam a2200433 i 4500
001 - CONTROL NUMBER
control field on1351696593
003 - CONTROL NUMBER IDENTIFIER
control field OCoLC
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240920115510.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 221104t20222023caua bf 001 0 eng d
015 ## - NATIONAL BIBLIOGRAPHY NUMBER
National bibliography number GBC2K4887
Source bnb
016 7# - NATIONAL BIBLIOGRAPHIC AGENCY CONTROL NUMBER
Record control number 020807698
Source Uk
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781098121228
Qualifying information paperback
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 1098121228
Qualifying information paperback
029 0# - OTHER SYSTEM CONTROL NUMBER (OCLC)
OCLC library identifier UKMGB
System control number 020807698
035 ## - SYSTEM CONTROL NUMBER
System control number (OCoLC)1351696593
040 ## - CATALOGING SOURCE
Original cataloging agency UKMGB
Language of cataloging eng
Description conventions rda
Transcribing agency UKMGB
Modifying agency OCLCF
-- IG$
-- UKMGB
-- GPRCL
-- OQX
-- IWA
-- YDX
-- CNR
049 ## - LOCAL HOLDINGS (OCLC)
Holding library CNRM
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number QA76.73.P98
Item number V365 2022
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.3/12
Edition number 23
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Vanderplas, Jacob T.,
Relator term author.
245 10 - TITLE STATEMENT
Title Python Data Science Handbook :
Remainder of title Essential Tools for Working with Data.
250 ## - EDITION STATEMENT
Edition statement Second edition.
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture Sebastopol, CA :
Name of producer, publisher, distributor, manufacturer O'Reilly Media,
Date of production, publication, distribution, manufacture, or copyright notice 2022.
264 #4 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Date of production, publication, distribution, manufacture, or copyright notice 2023
300 ## - PHYSICAL DESCRIPTION
Extent xxiv, 563 pages :
Other physical details illustrations ;
Dimensions 24 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
500 ## - GENERAL NOTE
General note Previous edition: 2016.
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc Includes bibliographical references and index.
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Part I: Jupyter: Beyond normal Python -- 1. Getting started in in IPython and Jupyter -- 2. Enhanced interactive features -- 3. Debugging and profiling -- Part II: Introduction to NumPy -- 4. Understanding data types in Python -- 5. The basics of NumPy arrays -- 6. Computation on NumPy arrays: Universal functions -- 7. Aggregations: min, max, and everything in between -- 8. Computation on arrays: broadcasting -- 9. Comparisons, masks, and boolean logic -- 10. Fancy indexing -- 11. Sorting arrays -- 12. Structured data: NumPy's structured arrays -- Part III: Data manipulation with Pandas -- 13. Introducing Pandas objects -- 14. Data indexing and selection -- 15. Operating on data in Pandas -- 16. Handling missing data -- 17. Hierarchial indexing -- 18. Combining datasets: concat and append -- 19. Combining datasets: merge and join -- 20. Aggregation and grouping -- 21. Pivot tables -- 22. Vectorized string operations -- 23. Working with time series -- 24. High-performace Pandas: eval and query -- Part IV: Visualization with Matplotlib -- 25. General Matplotlib tips -- 26. Simple line plots -- 27. Simple scatter plots -- 28. Density and contour plots -- 29. Customizing plot legends -- 30. Customizing colorbars -- 31. Multiple subplots -- 32. Text and annitatuin -- 33. Customizing ticks -- 34. Customizing Matplotlib: Configurations and stylesheets -- 35. Three-dimensional plottin in Matplotlib -- 36. Visualization with Seaborn -- Part V: Machine learning -- 37. What is machine learning? -- 38. Introducing Scitit-Learn -- 39. Hyperparameters and model validation -- 40. Feature engineering -- 41. In depth: Naive beyes classification -- 42. In depth: Linear regression -- 43> In depth: Support vector machines -- 44. In depth: Decision trees and random forests -- 45> In depth: Principal component analysis -- 46> In depth: Manifold learning -- 47. In depth: k-means clustering -- 48. In depth: Gaussian mixture models -- 49. In depth: Kernel density estimation -- 50. Application: a face detection pipeline.
520 ## - SUMMARY, ETC.
Summary, etc. "Python is a first-class tool for many researchers, primarily because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the new edition of Python Data Science Handbook do you get them all--IPython, NumPy, pandas, Matplotlib, scikit-learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find the second edition of this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python."--Publisher marketing.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Data mining
Form subdivision Handbooks, manuals, etc.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Python (Computer program language)
Form subdivision Handbooks, manuals, etc.
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Data mining.
Source of heading or term fast
Authority record control number (OCoLC)fst00887946
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Python (Computer program language)
Source of heading or term fast
Authority record control number (OCoLC)fst01084736
655 #7 - INDEX TERM--GENRE/FORM
Genre/form data or focus term Handbooks and manuals.
Source of term lcgft
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type BOOK
Source of classification or shelving scheme Library of Congress Classification
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Home library Current library Shelving location Date acquired Total Checkouts Total Renewals Full call number Barcode Checked out Date last seen Date last checked out Copy number Price effective from Koha item type
    Library of Congress Classification     NCAR Library NCAR Library Mesa Lab 07/27/2023 1 1 QA76.73 .P98 .V365 2022 50583020012658 12/28/2024 10/12/2023 10/12/2023 1 07/27/2023 BOOK

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