عنوان
پدید آورنده
موضوع
رده
QA76.73 .P98 M42 2018
QA76
.
73
.
P98
M42
2018
کتابخانه
محل استقرار
INTERNATIONAL STANDARD BOOK NUMBER
Qualification
paperback
Qualification
paperback
(Number (ISBN
1491957662
(Number (ISBN
9781491957660
NATIONAL BIBLIOGRAPHY NUMBER
Number
۲۰۱۱۱۶۲۲
OTHER SYSTEM CONTROL NUMBERS
System Control Number
(OCoLC)ocn959595088
LANGUAGE OF THE ITEM
.Language of Text, Soundtrack etc
انگلیسی
TITLE AND STATEMENT OF RESPONSIBILITY
Title Proper
Python for data analysis
General Material Designation
[book]
Other Title Information
:data wrangling with pandas, NumPy, and IPython
First Statement of Responsibility
/Wes McKinney.
EDITION STATEMENT
Edition Statement
Second edition.
.PUBLICATION, DISTRIBUTION, ETC
Place of Publication, Distribution, etc.
Sebastopol, California
Name of Publisher, Distributor, etc.
:O'Reilly Media, Inc.
Date of Publication, Distribution, etc.
, 2018.
PHYSICAL DESCRIPTION
Specific Material Designation and Extent of Item
xvi, 524 pages
Other Physical Details
:illustrations
Dimensions
;28cm
GENERAL NOTES
Text of Note
"Revision history for the Second Edition: 2017-09-25: First Release"--Title page verso.
Text of Note
First edition: October 2012.
INTERNAL BIBLIOGRAPHIES/INDEXES NOTE
Text of Note
Includes index.
CONTENTS NOTE
Text of Note
Preliminaries -- Python language basics, IPython, and Jupyter notebooks -- Built-in data structures, functions, and files -- NumPy basics: arrays and vectorized computation -- Getting started with pandas -- Data loading, storage, and file formats -- Data cleaning and preparation -- Data wrangling: join, combine, and reshape -- Plotting and visualization -- Data aggregation and group operations -- Time series -- Advanced pandas -- Introduction to modeling libraies in Python -- Data analysis examples -- Advanced NumPy -- More on the IPython system.
0
SUMMARY OR ABSTRACT
Text of Note
"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"--Page 4 of cover.
TOPICAL NAME USED AS SUBJECT
Entry Element
Python (Computer program language)
Entry Element
Programming languages (Electronic computers)
Entry Element
Data mining.
Entry Element
Programming languages (Electronic computers)
Entry Element
Data mining.
Entry Element
Python (Computer program language)
Entry Element
Python 3.6
Entry Element
Datenanalyse
Entry Element
Datenmanagement
Entry Element
Data Mining
LIBRARY OF CONGRESS CLASSIFICATION
Class number
QA76
.
73
.
P98
Book number
M42
2018
PERSONAL NAME - PRIMARY RESPONSIBILITY
Entry Element
McKinney, Wes,
ORIGINATING SOURCE
Country
ایران
Agency
Central Library of the Kurdistan University
Date of Transaction
20220627110856.0
Cataloguing Rules (Descriptive Conventions))
rda
p
BL
270410
Y
