Python.Data.Analytics

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Chapter 1: An Introduction to Data Analysis Chapter 2: Introduction to the Python’s World Chapter 3: The NumPy Library Chapter 4: The pandas Library—An Introduction Chapter 5: pandas: Reading and Writing Data Chapter 6: pandas in Depth: Data Manipulation Chapter 7: Data Visualization with matplot
Python Data analytics Copyright o 2015 by Fabio Nelli This work is subject to copyright All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information torage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. Exempted from this legal reservation are brief excerpts in connection with reviews or scholarly analysis or material supplied specifically for the purpose of being entered and executed on a computer system, for exclusive use by the purchaser of the work. Duplication of this publication or parts thereof is permitted only under the provisions of the Copyright Law of the Publisher's location, in its current version, and permission for use must always be obtained from Springer. Permissions for use may be obtained through Rightslink at the Copyright Clearance Center Violations are liable to prosecution under the respective Copyright Law. ISBN-13(pbk):978-1-484209592 ISBN-13( electronic:978-1-4842-0958-5 Trademarked names, logos, and images may appear in this book. Rather than use a trademark symbol with every occurrence of a trademarked name, logo, or image we use the names, logos, and images only in an editorial fashion and to the benefit of the trademark owner, with no intention of infringement of the trademark The use in this publication of trade names, trademarks, service marks, and similar terms, even if they are not identified as such, is not to be taken as an expression of opinion as to whether or not they are subject to proprietary rights While the advice and information in this book are believed to be true and accurate at the date of publication neither the authors nor the editors nor the publisher can accept any legal responsibility for any errors or omissions that may be made. The publisher makes no warranty, express or implied, with respect to the material contained herein Managing Director: Welmoed Spahr Lead Editor Steve anglin Technical Reviewer: Shubham Singh Tomar Editorial Board: Steve Anglin, Louise Corrigan, Morgan Ertel, Jonathan Gennick, Robert Hutchinson, Michelle lowman, James Markham, Susan McDermott, Matthew Moodie, Jeffrey Pepper, Douglas Pundick, Ben Renow-Clarke, Gwenan Spearing, Steve Weiss Coordinating Editor: Mark Powers Copy Editor: Brendan Frost Compositor SPi Global Indexer: SPi Global Artist: SPi global Distributed to the book trade worldwide by Springer Science+Business Media New York, 233 Spring Street, 6th Floor, New York, NY 10013. Phone 1-800-SPRINGER, fax(201)348-4505, e-mail orders-ny@springer-sbm.com,orvisitwww.springeronline.comApressMedia,LlcisaCaliforniaLlc and the sole member(owner)is Springer Science Business Media Finance Inc(SSBM Finance Inc) SSBM Finance Inc is a Delaware corporation. Forinformationontranslationspleasee-mailrights@apress.comorvisitwww.apress.com Apress and friends of ed books may be purchased in bulk for academic, corporate, or promotional us eBook versions and licenses are also available for most titles. For more information, reference our Special Bulksales-ebookLicensingwebpageatwww.apress.com/bulk-sales Any source code or other supplementary materials referenced by the author in this text is available to readersatwww.apress.com/9781484209592.Fordetailedinformationabouthowtolocateyourbookssource codegotowww.apress.com/source-code/.ReaderscanalsoaccesssourcecodeatSpringerlinkinthe Supplementary Material section for each chapter Contents at a glance About the author ■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■口■■■■■■■■■■■■■■■■■■■■■■■■■■ About the technical reviewer ■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■ XIX Acknowledgments ■■■■■■■ auauuauuuaaXX Chapter 1: An introduction to Data Analysis am 1 Chapter 2: Introduction to the Python's World ■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■ 13 Chapter 3: The NumPy library. u35 Chapter 4: The pandas library-An Introduction.ammmamamta, 63 Chapter 5: pandas: Reading and Writing Data mmmmmmamm 103 Chapter 6: pandas in Depth: Data Manipulation aammammammammna 131 Chapter7: Data Visualization with matplotlib-,…,,,,,,…,…,167 Chapter 8: Machine Learning with scikit-learn mmmm BIBIRIBRIRImInam 237 Chapter 9: An Example--Meteorological Data aaamaammmnmnmmmmanan 265 Chapter 10: Embedding the Javascript D3 Library in IPython Notebook amam. 289 Chapter 11: Recognizing handwritten Digits mmmammmmmmmn 311 Appendix A: Writing Mathematical Expressions with Latex mmmmmmmnn 317 Appendix B:0 pen Data Sources,,,,,,…,…,,,,,,,…,327 Index ■■■■■■■■ 331 Contents About the author About the technical reviewer Acknowledgments mIREI BIRRIEIEIIEIIIIEI XXi ■ Chapter1: An Introduction to Data Analysis,,,…,…1 Data analysis.eaten. Knowledge Domains of the data analyst 2 Computer Science… 2 Mathematics and statistics 日B日自日面日日日面口日自日面日日自日面日日自日面日日自日面日面日自日面日日自日自日面日自日 Machine Learning and artificial Intelligence 3 Professional Fields of Application Understanding the Nature of the Data When the data become When the Information Becomes Knowledge..................4 Types of data....,,,,,,,,……4 The Data analysis Process 5 Problem definition Data extraction Data Preparation..................................7 Data Exploration/i」 ualization.……7 Predictive Modeling…… 8 Model validation Deployment Quantitative and Qualitative Data analysis 9 CONTENTS Open data 10 Python and Data Analysis ,11 Conclusions ,12 Chapter 2: Introduction to the Python's World ■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■口■■■■■口■■ Python— The Programming Language....,,….…,13 Python- The Interpreter....……,14 Hythe 5 Python 15 PyPy 15 Python 2 and Python 3 15 Installing python.… 16 Python Distributions ,16 Anaconda 16 Enthought Canopy 17 Python(x,y)….....,,,…,,…,… 8 Using Python 18 Python She..……………18 Run an Entire program code 18 Implement the code Using an IdE ,日面a面面面a,日面面a日面面面面日面面a日面面面日面面量面画 19 Interact with Python 19 Writing python Code 19 Make calculations Import New Libraries and functions 002 Functional Programming(Only for Python 3. 4) Indentation 24 Python 24 IPython Shell. 24 IPython Qt-Console 26 CONTENTS PyPI--The Python package Index 28 The IDEs for Python DDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD 28 DLE( ntegrated DeveLopment Environment,,,,…………29 Spyder… Eclipse( pyDev)……… Sublime.…30 Liclipse NinjalDE Komodo ide SciP 32 NumPy Pandas matplotlib… Conclusions 34 Chapter 3: The NumPy library. 35 NumPy: A Little History DDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD 35 The NumPy Installation DDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD题 35 Ndarray: The Heart of the library……, 36 Create an array…...,..,,… Types of Data The dtype option 39 trinsic Creation of an Array…....,.,.,……39 Basic operations 40 Arithmetic Operators The matrix Product 日面口 Increment and decrement operators Universal Functions( func)...……… 344 Aggregate Functions CONTENTS dexing Slicing, and Iterating 45 Indexing 45 Slicing 46 Iterating an Array................... 48 onditions and Boolean Arrays. 50 Shape Manipulation . Array Manipulation 51 Joining arrays......,…………….51 Splitting Arrays 52 General Concepts. Copies or Views of objects Vectorization Broadcasting ,55 Structured Arrays 58 Reading and Writing array Data on Files 59 Loading and saving Data in Binary Files…......,.…,………59 Reading File with Tabular Data 60 Conclusions ,61 Chapter 4: The pandas library-An Introduction mm m RnI, 63 pandas: The Python Data Analysis Library 63 Installation 64 Installation from anaconda Installation from PyP 65 Installation on linux 面m 日面a面面面a,日面面a日面面面面日面面日面面面面日面面量a面画 nsta| ation from s0urCe… A Module Repository for Windows.............................. 66 Test Your pandas Installation 66 Getting Started with pandas 67 CONTENTS Introduction to pandas Data Structures 67 The series The data frame 75 The Index objects Other functionalities on indexes 83 Reindexing………8 Dropping Arithmetic and Data Alignment. Operations between Data Structures .87 Flexible Arithmetic Methods Operations between DataFrame and Series Function Application and Mapping 89 Functions by element,… 89 Functions by Row or Column Statistics Functions 91 Sorting and ranking 91 Correlation and covariance “ Not a number”Data…95 Assigning a Nan value....................................96 Filtering Out Nan value Filling in Nan occurrences……, Hierarchical Indexing and Leveling ... 97 Reordering and Sorting Levels 100 Summary statistic by Level...,….……….100 Conclusions… 101 CONTENTS Chapter 5: pandas: Reading and Writing data RRmEmmInatanan 103 10 API Tools ,103 CSV and Textual files 104 Reading Data in CSv or Text Files. ,104 Using regExp for Parsing TXT Files. Reading TXT Files into Parts or Partially ,日面a面面面a,日面面a日面面面面日面面a日面面面日面面量面面面面 108 Writing Data in CSV.… 109 Reading and Writing HTML Files 111 Writing Data in HTML ………11 Reading Data from an HTML File 113 Reading Data from XML 114 Reading and Writing Data on Microsoft Excel Files 116 JS0 NData…118 The format hde5…121 Pickle--Python object Serialization 122 Serialize a Python object with pIckle 122 Pickling with pandas 123 nteracting with Databases 124 Loading and writing data with sQlite 3 124 Loading and Writing Data with PostgreSQL. Reading and Writing Data with a NosQL Database: MongoDB 128 Conclusions 130 Chapter 6: pandas in Depth: Data Manipulation amam 131 Data Preparation… 131 Merging 132 Concatenating. Combining 139 Pivoting…,,,,,…,…,…,,…,…,…,…………………140 Removing ..........................................................................................................................142

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空灵竹 不错,跟描述的一样的,谢谢
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