ARCHBISHOP KAVUKATTU CENTRAL LIBRARY
ONLINE LIBRARY CATALOGUE (OPAC)

Python for Data Analysis: (Record no. 40042)

MARC details
000 -LEADER
fixed length control field 01918nam a22002657a 4500
003 - CONTROL NUMBER IDENTIFIER
control field OSt
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20241205134838.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
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020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9789355421906
040 ## - CATALOGING SOURCE
Transcribing agency AKCL
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 003.133
Item number MCK-P3
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name McKinney, Wes
245 ## - TITLE STATEMENT
Title Python for Data Analysis:
Remainder of title Data Wrangling with pandas NumPy and Jupyter /
Statement of responsibility, etc. by Wes McKinney
250 ## - EDITION STATEMENT
Edition statement 3rd Ed.
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. Mumbai:
Name of publisher, distributor, etc. Shroff publishers and Distributors,
Date of publication, distribution, etc. 2022
300 ## - PHYSICAL DESCRIPTION
Extent p.561
520 ## - SUMMARY, ETC.
Summary, etc. Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6, the second edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You’ll learn the latest versions of pandas, NumPy, IPython, and Jupyter in the process.<br/><br/>Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It’s ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub.<br/><br/>Use the IPython shell and Jupyter notebook for exploratory computing<br/>Learn basic and advanced features in NumPy (Numerical Python)<br/>Get started with data analysis tools in the pandas library<br/>Use flexible tools to load, clean, transform, merge, and reshape data<br/>Create informative visualizations with matplotlib<br/>Apply the pandas groupby facility to slice, dice, and summarize datasets<br/>Analyze and manipulate regular and irregular time series data<br/>Learn how to solve real-world data analysis problems with thorough, detailed examples
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Computer Science
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Systems Theory
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element System Identification
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Koha item type Books
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Source of classification or shelving scheme Dewey Decimal Classification
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
942 ## - ADDED ENTRY ELEMENTS (KOHA)
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    Dewey Decimal Classification     ARCHBISHOP KAVUKATTU CENTRAL LIBRARY ARCHBISHOP KAVUKATTU CENTRAL LIBRARY 11/26/2024 1800.00   003.133 MCK-P3 69192 11/26/2024 1800.00 11/26/2024 Books