基于开源工具的数据分析

2011-5  

东南大学  

Philipp K. Janert  

509  

无  

数据收集相对比较简单，而要把原始信息转化为有用的数据则需要知道如何精确地抽取你想要的内容。通过这本书(作者Philipp
K．Janert)的深入讲解，那些对数据分析感兴趣的中等或者富有经验的程序员将可以学习到在商业环境中与数据打交道的技术。你将了解到如何观察数据来找出它所包含的信息，如何在概念模型里捕捉到这些想法，然后把你的理解通过商业计划、度量标准的精确报告和其他方式反馈给你所在的机构。
你将会通过本书每章结束部分的动手实践来慢慢体验各种概念。最重要的是，你将了解到如何思考你所希望获取的数据——而不是依赖于工具来替你思考。

Philipp
K．Janert目前提供数据分析和数学模型的咨询服务，他曾经是物理学家和软件工程师。他是《Gnuplot in
Action：Understanding Data with Graphs》(Manning出版)的作者，他为O’Reillv
Network．IBM
deVeloperWorks和IEEEsoftware写过文章。他拥有Washington大学理论物理学的博士学位。

PREFACE
1 INTRODUCTION
Data Analysis
What's in This Book
What's with the Workshops?
What's with the Math?
What You'll Need
What's Missing
PART I Graphics: Looking at Data
2 A SINGLE VARIABLE: SHAPE AND DISTRIBUTION
Dot andJitter Plots
Histograms and Kernel Density Estimates
The Cumu/atiue Distribution Function
Rank-Order Plots and Lilt Charts
Only When Appropriate: Summary Statistics and Box Plots
Workshop: NumPy
Further Reading
3 TWO VARIABLES: ESTABLISHING RELATIONSHIPS
Scatter Plots
Conquering Noise: 5moothing
Logarithmic Plots
Banking
Linear ReRression and All That
Shouwing What's Important
Graphical Analysis and Presentation Graphics
Workshop: matplotlib
Further Reading
TIME AS A VARIABLE: TIME-SERIES ANALYSIS
Examples
The Task
Smoothing
Don't Ouerlook the Obuious!
The Correlation Function
Optional: Filters and Conuolutions
Workshop: scipy.signal
Further ReadinR
5 MORE THAN TWO VARIABLES: GRAPHICAL MULTIVARIATE ANALYSIS
False-Color Plots
A Lot at a Glance: Multiplots
Composition Problems
Nouel Plot Types
Interactiue Explorations
Workshop: Tools for Multiuariate Graphics
Further ReadinR
6 INTERMEZZO: A DATA ANALYSIS SESSION
A Data Analysis Session
Workshop: gnuplot
Further ReadinR
PART II Analyticg: Modeling Data
7 GUESSTIMATION AND THE BACK OF THE ENVELOPE
Principles of Guesstimation
How Good Are Those Numbers?
Optional: A Closer Look at Perturbation Theory and
Error PropaRation
Workshop: The Gnu Scientific Library (GSL)
Further Reading
8 MODELS FROM SCALING ARGUMENTS
Models
ArRuments from Scale
Mean-Field Approximations
Common Time-Euolution Scenarios
Case Study: How Many Seruers Are Best?
Why Modeling?
Workshop: Sage
Further Reading
9 ARGUMENTS FROM PROBABILITY MODELS
The. Binomial Distribution and Bernoulli Trials
The Gaussian Distribution and the Central Limit Theorem
Power-Law Distributions and Non-Normal Statistics
Other Distributions
Optional: Case Study--Unique Visitors ouer Time
Workshop: Power-Law Distributions
Further Reading
10 WHAT YOU REALLY NEED TO KNOW ABOUT CLASSICAL STATISTICS
Genesis
Statistics Defined
Statistics Explained
Controlled Experiments Versus Obseruationa} Studies
Optional: Bayesian Statistics--The Other Point of View
Workshop: R
Further Reading
11 INTERMEZZO:MYTHBUSTING--BIGFOOT, LEAST SQUARES, AND ALL
THAT
How to Auerage Auerages
The Standard Deuiation
Least Squares
Further Reading
PART III Computation: Mininhg Data
12 SIMULATIONS
A Warm-Up Question
Monte Carlo Simulations
Resampling Methods
Workshop: Discrete Euent Simulations with Simpy
Further Reading
13 FINDING CLUSTERS
What Constitutes a Cluster?
Distance and Similarity Measures
Clustering Methods
Pre-and Postprocessing
Other ThouRhts
A Special Case: Market BasketAnalysis
A Word of WarninR
Workshop: P/cluster and the C Clustering Library
Further Reading
14 SEEING THE FOREST FOR THE TREES: FINDING
IMPORTANT ATTRIBUTES
Principal Component Analysis
Visual Techniques
Kohonen Maps
Workshop: PCA with R
Further Readin2
15 INTERMEZZO:WHEN MORE IS DIFFERENT
A Horror Story
Some Suggestions
What About Map/Reduce?
Workshop: Generating Permutations
Further Reading
PART IV Applications: Using Data
16 REPORTING, BUSINESS INTELLIGENCE, AND DASHBOARDS
Business Intelligence
Corporate Metrics and Dashboards
Data Quality Issues
Workshop: Berkeley DB and SQLite
Further Reading
17 FINANCIAL CALCULATIONS AND MODELING
The Time Value o[ Money
Uncertainty in Planning and Opportunity Costs
Cost Concepts and Depreciation
Should You Care?
Is This All That Matters?
Workshop: The Newsuendor Problem
Further Reading
18 PREDICTIVE ANALYTICS
Introduction
Some Classification Terminology
Algorithms for Classification
The Process
The Secret Sauce
The Nature o[ Statistical Learning
Workshop: Two Do-lt-Yoursel Classifiers
Further Reading
19 EPILOGUE: FACTS ARE NOT REALITY
A PROGRAMMING ENVIRONMENTS FOR SCIENTIFIC COMPUTATION
AND DATA ANALYSIS
Software Tools
A Catalog of Scientific Software
Writing Your Own
Further Reading
B RESULTS FROM CALCULUS
Common Functions
Calculus
Useful Tricks
Notation and Basic Math
Where to Go from Here
Further Readin9
WORKING WITH DATA
Sources for Data
Cleanin9 and ConditioninR
Sarnplin9
Data File Formats
The Care and Feeding of Your Data Zoo
Skills
Terminology
Further Fleadin9
INDEX

《基于开源工具的数据分析(影印版)》(作者Philipp K．Janert)使用图形来描述带有一个、两个或者十多个变量的数据；使用粗略计算以及维度和概率参数来开发概念模型；使用诸如模拟和聚类的集约计算方法来挖掘数据；通过报告、信息板和其他度量程序来让你的结论更容易理解；理解财务计算，包括货币时间价值；利用降维技术或者预测分析来克服数据分析过程中面临的挑战；熟悉数据分析的不同开源编程环境。

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我很讨厌评价一本书不按书的内容来进行，例如什么给同事买的，说很好；什么快递太慢。。。。。毫无价值的评论。。。。我的评论也大约和书内容无关，只是有关书的外观的：书不像新的（难道我买的是二手的？），封面左上角粘胶处有裂开，封面右下角很褶皱。。。。不过，里面的书页很好，字体也很清晰，应该是正版。至于内容，自然是极好的～冲这书买的自然都知道～

速度快，质量很好，虽然不怎么懂，以后慢慢看

数学比较简单是个遗憾但是考虑到英文事实上是很好的。可以完整的学习到数据挖掘的基本概念和实战经验。