Python Data Science Handbook: Essential Tools for Working with Data (Record no. 58566)

MARC details
000 -LEADER
fixed length control field 01967nam a2200253 a 4500
001 - CONTROL NUMBER
control field 58566
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20260219124007.0
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781491912058
040 ## - CATALOGING SOURCE
Original cataloging agency AIS
Modifying agency AIS
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.312
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Jake Vanderplas
245 ## - TITLE STATEMENT
Title Python Data Science Handbook: Essential Tools for Working with Data
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. Sebastopol, CA
Name of publisher, distributor, etc. O'Reilly
Date of publication, distribution, etc. 2017
520 ## - SUMMARY, ETC.
Summary, etc. For many researchers, Python is a first-class tool mainly 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 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 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. With this handbook, you'll learn how to use: * IPython and Jupyter: provide computational environments for data scientists using Python * NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python * Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python * Matplotlib: includes capabilities for a flexible range of data visualizations in Python * Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms
655 ## - INDEX TERM--GENRE/FORM
Genre/form data or focus term Programming
655 ## - INDEX TERM--GENRE/FORM
Genre/form data or focus term Computer Science
655 ## - INDEX TERM--GENRE/FORM
Genre/form data or focus term Computers
655 ## - INDEX TERM--GENRE/FORM
Genre/form data or focus term Coding
655 ## - INDEX TERM--GENRE/FORM
Genre/form data or focus term Technology
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Genre/form data or focus term Technical
655 ## - INDEX TERM--GENRE/FORM
Genre/form data or focus term Artificial Intelligence
655 ## - INDEX TERM--GENRE/FORM
Genre/form data or focus term Nonfiction
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element (ICE-2702) Applied Data Science with Python
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