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Python數(shù)據(jù)分析（影印版）
Python數(shù)據(jù)分析（影印版）
Wes McKinney 著
出版時(shí)間：2013年06月
頁數(shù)：472
“科學(xué)和數(shù)據(jù)分析領(lǐng)域已經(jīng)等了這本書好幾年了：具有具體的實(shí)用建議以及如何聚沙成塔的見解。它應(yīng)該會成為接下來若干年里Python科學(xué)計(jì)算方面的經(jīng)典參考資料。”
——Fernando Perez
UC Berkeley大學(xué)的助理研究員，也是IPython的原創(chuàng)作者之一

你是否在尋找一本完整介紹Python操縱、處理、提取和壓縮結(jié)構(gòu)化數(shù)據(jù)的指南？本書包含了許多實(shí)例分析，通過若干個(gè)Python庫——包括NumPy，pandas，matplotlib和IPython——為你展示了如何高效地解決大量數(shù)據(jù)分析的問題。
《Python數(shù)據(jù)分析》由Wes McKinney撰寫，他是pandas庫的主要作者。本書也是一本具有實(shí)踐性的指南，指導(dǎo)那些使用Python進(jìn)行科學(xué)計(jì)算的數(shù)據(jù)密集型應(yīng)用。它適用于剛剛開始使用Python的分析師，或者是進(jìn)入科學(xué)計(jì)算領(lǐng)域的Python程序員。

· 使用IPython交互式shell作為你的主要開發(fā)環(huán)境
· 學(xué)習(xí)NumPy（Numerical Python）的基礎(chǔ)和高級特性
· 接觸pandas庫中的數(shù)據(jù)分析工具
· 使用高性能工具來加載、抽取、轉(zhuǎn)換、合并和改造數(shù)據(jù)
· 使用matplotlib來創(chuàng)建散點(diǎn)圖和靜態(tài)或者交互式可視化數(shù)據(jù)
· 運(yùn)用pandas的groupby功能來對數(shù)據(jù)集進(jìn)行切片、切塊和匯總
· 通過具體實(shí)例來學(xué)習(xí)如何解決web分析、社交科學(xué)、金融和經(jīng)濟(jì)領(lǐng)域的問題

Wes McKinney是pandas的主要作者，pandas是Python中流行的數(shù)據(jù)分析開源庫。他一開始是AQR資產(chǎn)管理公司的量化分析師，后來創(chuàng)辦了Lambda Foundry——一家企業(yè)數(shù)據(jù)分析公司。Wes是Python和開源社區(qū)的活躍講師和參與者。
  1. Chapter 1: Preliminaries
  2. What Is This Book About?
  3. Why Python for Data Analysis?
  4. Essential Python Libraries
  5. Installation and Setup
  6. Community and Conferences
  7. Navigating This Book
  8. Acknowledgements
  9. Chapter 2: Introductory Examples
  10. 1.usa.gov data from bit.ly
  11. MovieLens 1M Data Set
  12. US Baby Names 1880-2010
  13. Conclusions and The Path Ahead
  14. Chapter 3: IPython: An Interactive Computing and Development Environment
  15. IPython Basics
  16. Using the Command History
  17. Interacting with the Operating System
  18. Software Development Tools
  19. IPython HTML Notebook
  20. Tips for Productive Code Development Using IPython
  21. Advanced IPython Features
  22. Credits
  23. Chapter 4: NumPy Basics: Arrays and Vectorized Computation
  24. The NumPy ndarray: A Multidimensional Array Object
  25. Universal Functions: Fast Element-wise Array Functions
  26. Data Processing Using Arrays
  27. File Input and Output with Arrays
  28. Linear Algebra
  29. Random Number Generation
  30. Example: Random Walks
  31. Chapter 5: Getting Started with pandas
  32. Introduction to pandas Data Structures
  33. Essential Functionality
  34. Summarizing and Computing Descriptive Statistics
  35. Handling Missing Data
  36. Hierarchical Indexing
  37. Other pandas Topics
  38. Chapter 6: Data Loading, Storage, and File Formats
  39. Reading and Writing Data in Text Format
  40. Binary Data Formats
  41. Interacting with HTML and Web APIs
  42. Interacting with Databases
  43. Chapter 7: Data Wrangling: Clean, Transform, Merge, Reshape
  44. Combining and Merging Data Sets
  45. Reshaping and Pivoting
  46. Data Transformation
  47. String Manipulation
  48. Example: USDA Food Database
  49. Chapter 8: Plotting and Visualization
  50. A Brief matplotlib API Primer
  51. Plotting Functions in pandas
  52. Plotting Maps: Visualizing Haiti Earthquake Crisis Data
  53. Python Visualization Tool Ecosystem
  54. Chapter 9: Data Aggregation and Group Operations
  55. GroupBy Mechanics
  56. Data Aggregation
  57. Group-wise Operations and Transformations
  58. Pivot Tables and Cross-Tabulation
  59. Example: 2012 Federal Election Commission Database
  60. Chapter 10: Time Series
  61. Date and Time Data Types and Tools
  62. Time Series Basics
  63. Date Ranges, Frequencies, and Shifting
  64. Time Zone Handling
  65. Periods and Period Arithmetic
  66. Resampling and Frequency Conversion
  67. Time Series Plotting
  68. Moving Window Functions
  69. Performance and Memory Usage Notes
  70. Chapter 11: Financial and Economic Data Applications
  71. Data Munging Topics
  72. Group Transforms and Analysis
  73. More Example Applications
  74. Chapter 12: Advanced NumPy
  75. ndarray Object Internals
  76. Advanced Array Manipulation
  77. Broadcasting
  78. Advanced ufunc Usage
  79. Structured and Record Arrays
  80. More About Sorting
  81. NumPy Matrix Class
  82. Advanced Array Input and Output
  83. Performance Tips
  84. Appendix: Python Language Essentials
  85. The Python Interpreter
  86. The Basics
  87. Data Structures and Sequences
  88. Functions
  89. Files and the operating system
書名：Python數(shù)據(jù)分析（影印版）
作者：Wes McKinney 著
國內(nèi)出版社：東南大學(xué)出版社
出版時(shí)間：2013年06月
頁數(shù)：472
書號：978-7-5641-4204-9
原版書書名：Python for Data Analysis
原版書出版商：O'Reilly Media
Wes McKinney
 
Wes McKinney是紐約的一名數(shù)據(jù)分析高手和企業(yè)主。在2007年獲得MIT的數(shù)學(xué)學(xué)士學(xué)位之后，他到位于康涅狄格州格林威治市（Greenwich，CT）的AQR Capital Management公司從事定量金融方面的工作。由于不滿那些數(shù)據(jù)分析工具的各種不好用，他開始學(xué)習(xí)Python，并于2008年開始構(gòu)建pandas項(xiàng)目。他目前是Python科學(xué)計(jì)算社區(qū)的活躍分子，而且積極倡導(dǎo)在數(shù)據(jù)分析、金融以及統(tǒng)計(jì)應(yīng)用中使用Python。
 
 
The animal on the cover of Python for Data Analysis is a golden-tailed, or pen-tailed, tree shrew (Ptilocercus lowii). The golden-tailed tree shrew is the only one of its species in the genus Ptilocercus and family Ptilocercidae; all the other tree shrews are of the family Tupaiidae. Tree shrews are identified by their long tails and soft red-brown fur. As nicknamed, the golden-tailed tree shrew has a tail that resembles the feather on a quill pen. Tree shrews are omnivores, feeding primarily on insects, fruit, seeds, and small vertebrates.Found predominantly in Indonesia, Malaysia, and Thailand, these wild mammals are known for their chronic consumption of alcohol. Malaysian tree shrews were found to spend several hours consuming the naturally fermented nectar of the bertam palm, equalling about 10 to 12 glasses of wine with 3.8% alcohol content. Despite this, no golden-tailed tree shrew has ever been intoxicated, thanks largely to their impressive ethanol breakdown, which includes metabolizing the alcohol in a way not used by humans. Also more impressive than any of their mammal counterparts, including humans? Brain to body mass ratio.

Despite these mammals’ name, the golden-tailed shrew is not a true shrew, instead more closely related to primates. Because of their close relation, tree shrews have become an alternative to primates in medical experimentation for myopia, psychosocial stress, and hepatitis.
購買選項(xiàng)
定價(jià)：74.00元
書號：978-7-5641-4204-9
出版社：東南大學(xué)出版社