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عنوان
Python for data mining quick syntax reference /

پدید آورنده
Valentina Porcu.

موضوع
Data mining.,Python (Computer program language),COMPUTERS-- General.,Data mining.,Python (Computer program language)

رده
QA76
.
9
.
D343

کتابخانه
Center and Library of Islamic Studies in European Languages

محل استقرار
استان: Qom ـ شهر: Qom

Center and Library of Islamic Studies in European Languages

تماس با کتابخانه : 32910706-025

INTERNATIONAL STANDARD BOOK NUMBER

(Number (ISBN
1484241126
(Number (ISBN
1484241134
(Number (ISBN
9781484241127
(Number (ISBN
9781484241134
Erroneous ISBN
9781484241127

TITLE AND STATEMENT OF RESPONSIBILITY

Title Proper
Python for data mining quick syntax reference /
General Material Designation
[Book]
First Statement of Responsibility
Valentina Porcu.

.PUBLICATION, DISTRIBUTION, ETC

Place of Publication, Distribution, etc.
New York :
Name of Publisher, Distributor, etc.
Apress,
Date of Publication, Distribution, etc.
[2018]
Date of Publication, Distribution, etc.
©2018

PHYSICAL DESCRIPTION

Specific Material Designation and Extent of Item
1 online resource :
Other Physical Details
illustrations (some color)

GENERAL NOTES

Text of Note
Includes index.

CONTENTS NOTE

Text of Note
Intro; Table of Contents; About the Author; About the Technical Reviewer; Introduction; Chapter 1: Getting Started; Installing Python; Editor and IDEs; Differences between Python2 and Python3; Work Directory; Using a Terminal; Summary; Chapter 2: Introductory Notes; Objects in Python; Reserved Terms for the System; Entering Comments in the Code; Types of Data; File Format; Operators; Mathematical Operators; Comparison and Membership Operators; Bitwise Operators; Assignment Operators; Operator Order; Indentation; Quotation Marks; Summary; Chapter 3: Basic Objects and Structures; Numbers
Text of Note
Chapter 6: Other Basic ConceptsObject-oriented Programming; More on Objects; Classes; Inheritance; Modules; Methods; List Comprehension; Regular Expressions; User Input; Errors and Exceptions; Summary; Chapter 7: Importing Files; .csv Format; From the Web; In JSON; Other Formats; Summary; Chapter 8: pandas; Libraries for Data Mining; pandas; pandas: Series; pandas: Data Frames; pandas: Importing and Exporting Data; pandas: Data Manipulation; pandas: Missing Values; pandas: Merging Two Datasets; pandas: Basic Statistics; Summary; Chapter 9: SciPy and NumPy; SciPy; NumPy
Text of Note
Container ObjectsTuples; Lists; Dictionaries; Sets; Strings; Files; Immutability; Converting Formats; Summary; Chapter 4: Functions; Some words about functions in Python; Some Predefined Built-in Functions; Obtain Function Information; Create Your Own Functions; Save and run Your Own Modules and Files; Summary; Chapter 5: Conditional Instructions and Writing Functions; Conditional Instructions; if; if + else; elif; Loops; for; while; continue and break; Extend Functions with Conditional Instructions; map() and filter() Functions; The lambda Function; Scope; Summary
Text of Note
NumPy: Generating Random Numbers and SeedsSummary; Chapter 10: Matplotlib; Basic Plots; Pie Charts; Other Plots and Charts; Saving Plots and Charts; Selecting Plot and Chart Styles; More on Histograms; Summary; Chapter 11: Scikit-learn; What Is Machine Learning?; Import Datasets Included in Scikit-learn; Creation of Training and Testing Datasets; Preprocessing; Regression; K-Nearest Neighbors; Cross-validation; Support Vector Machine; Decision Trees; KMeans; Managing Dates; Data Sources; Index
0
8
8
8

SUMMARY OR ABSTRACT

Text of Note
Learn how to use Python and its structures, how to install Python, and which tools are best suited for data analyst work. This book provides you with a handy reference and tutorial on topics ranging from basic Python concepts through to data mining, manipulating and importing datasets, and data analysis. Python for Data Mining Quick Syntax Reference covers each concept concisely, with many illustrative examples. You'll be introduced to several data mining packages, with examples of how to use each of them. The first part covers core Python including objects, lists, functions, modules, and error handling. The second part covers Python's most important data mining packages: NumPy and SciPy for mathematical functions and random data generation, pandas for dataframe management and data import, Matplotlib for drawing charts, and scikitlearn for machine learning.

ACQUISITION INFORMATION NOTE

Source for Acquisition/Subscription Address
Springer Nature
Stock Number
com.springer.onix.9781484241134

OTHER EDITION IN ANOTHER MEDIUM

International Standard Book Number
9781484241127
International Standard Book Number
9781484241141

TOPICAL NAME USED AS SUBJECT

Data mining.
Python (Computer program language)
COMPUTERS-- General.
Data mining.
Python (Computer program language)

(SUBJECT CATEGORY (Provisional

COM-- 000000
UMX
UMX

DEWEY DECIMAL CLASSIFICATION

Number
006
.
3/12
Edition
23

LIBRARY OF CONGRESS CLASSIFICATION

Class number
QA76
.
9
.
D343

PERSONAL NAME - PRIMARY RESPONSIBILITY

Porcu, Valentina

ORIGINATING SOURCE

Date of Transaction
20200823032531.0
Cataloguing Rules (Descriptive Conventions))
pn

ELECTRONIC LOCATION AND ACCESS

Electronic name
 مطالعه متن کتاب 

[Book]

Y

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