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獲得關於用Python語言操縱、處理、清洗和壓縮數據集的完整介紹。這本容易上手的指南第二版為Python 3.6而升級,其中包括一些實用的案例研究,展示瞭如何有效解決各種數據分析問題。你將從中學到新版pandas、NumPy、IPython和Jupyter的處理方法。
內容簡介
本書由Python pandas項目的創立者Wes McKinney撰寫,是一本實用、現代的Python數據科學工具讀物,適閤新入門的Python分析師和剛接觸數據科學及科學計算的Python程序員。數據文件和相關材料在Github上可以獲得。
* 將IPython shell和Jupyter Notebook用於探索式計算
* 學習NumPy(Numerical Python)的基礎和高級特性
* 通過pandas庫中的數據分析工具入門
* 使用靈活的工具裝載、清洗、轉換、閤並和整形數據
* 用matplotlib創建信息可視化
* 應用pandas groupby功能將數據集切片、切塊和匯總
* 分析和操縱規整和不規整時間序列數據
* 通過全麵詳細的實例學習如何解決真實世界的數據分析問題
“作為在Python數據生態中已成經典的著作,這本新版更新瞭能提升其獨特價值的多個領域,從Python 3.6到新的pandas特性。通過闡釋Python數據工具的原理和方法,本書幫助讀者以新穎而富有創造性的途徑學習如何有效利用它們。這是任何現代數據密集型計算庫的關鍵部分。
作者簡介
Wes McKinney是流行開源Python數據分析庫pandas的創立者。他是一位公共演講者和開源Python及C++開發者,活躍於Python數據科學社區和Apache軟件基金會。他在紐約從事軟件架構師工作。
目錄
Preface
1. Preliminaries
1.1 What Is This Book About?
What Kinds of Data?
1.2 Why Python for Data Analysis?
Python as Glue
Solving the "Two-Language" Problem
Why Not Python?
1.3 Essential Python Libraries
NumPy
pandas
matplotlib
IPython and Jupyter
SciPy
scikit-learn
statsmodels
1.4 Installation and Setup
Windows
Apple (OS X, macOS)
GNU/Linux
Installing or Updating Python Packages
Python 2 and Python 3
Integrated Development Environments (IDEs) and Text Editors
1.5 Community and Conferences
1.6 Navigating This Book
Code Examples
Data for Examples
Import Conventions
Jargon
2. Python Language Basics, IPython, and Jupyter Notebooks
2.1 The Python Interpreter
2.2 IPython Basics
Running the IPython Shell
Running the Jupyter Notebook
Tab Completion
Introspection
The %run Command
Executing Code from the Clipboard
Terminal Keyboard Shortcuts
About Magic Commands
Matplotlib Integration
2.3 Python Language Basics
Language Semantics
Scalar Types
Control Flow
3. Built-in Data Structures, Functions, and Files
3.1 Data Structures and Sequences
Tuple
List
Built-in Sequence Functions
dict
set
List, Set, and Dict Comprehensions
3.2 Functions
Namespaces, Scope, and Local Functions
Returning Multiple Values
Functions Are Objects
Anonymous (Lambda) Functions
Currying: Partial Argument Application
Generators
Errors and Exception Handling
3.3 Files and the Operating System
Bytes and Unicode with Files
3.4 Conclusion
4. NumPy Basics: Arrays and Vectorized Computation
4.1 The NumPy ndarray: A Multidimensional Array Object
5. Getting Started with pandas.
6. Data Loading, Storage, and File Formats
7. Data Cleanincl and Preparation.
8. Data Wrangling: Join, Combine, and Reshape.
9. Plotting and Visualization.
10. Data Aggregation and Group Operations.
11. Time Series
12. Advanced pandas
13. Introduction to Modeling Libraries in Python
14. Data Analysis Examples
A. Advanced NumPy.
B. More on the IPython System
Python數據分析 第2版(影印版) [Python for Data Analysis] 下載 mobi epub pdf txt 電子書 格式
Python數據分析 第2版(影印版) [Python for Data Analysis] 下載 mobi pdf epub txt 電子書 格式 2024
Python數據分析 第2版(影印版) [Python for Data Analysis] mobi epub pdf txt 電子書 格式下載 2024