Python for Data Analysis: Data Wrangling with Pandas, Numpy, and Ipython (2ND ed.)

基本信息

Format:Paperback / softback 522 pages

Publisher:O'Reilly Media, Inc, USA

Imprint:O'Reilly Media, Inc, USA

ISBN:9781491957660

Published:3 Nov 2017

Weight:960g

Dimensions:233 x 179 x 27 (mm)

页面参数仅供参考，具体以实物为准

书籍简介

本书由Python pandas项目创始人Wes McKinney亲笔撰写，详细介绍利用Python进行操作、处理、清洗和规整数据等方面的具体细节和基本要点。第2版针对Python 3.6进行全面修订和更新，涵盖新版的pandas、NumPy、IPython和Jupyter，并增加大量实际案例，可以帮助你高效解决一系列数据分析问题。

第2版中的主要更新包括：

• 所有的代码，包括把Python的教程更新到了Python 3.6版本(第1版中使用的是Python 2.7)

• 更新了Python第三方发布版Anaconda和其他所需Python包的安装指引

• 更新pandas库到2017年的新版

• 新增一章，关于更多高级pandas工具和一些使用提示

• 新增statsmodels和scikit-learn的简明使用介绍

Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6, the second edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You’ll learn the latest versions of pandas, NumPy, IPython, and Jupyter in the process.

Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It’s ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub.

Use the IPython shell and Jupyter notebook for exploratory computing

Learn basic and advanced features in NumPy (Numerical Python)

Get started with data analysis tools in the pandas library

Use flexible tools to load, clean, transform, merge, and reshape data

Create informative visualizations with matplotlib

Apply the pandas groupby facility to slice, dice, and summarize datasets

Analyze and manipulate regular and irregular time series data

Learn how to solve real-world data analysis problems with thorough, detailed examples

作者简介

Wes McKinney 是流行的Python开源数据分析库pandas的创始人。他是一名活跃的演讲者，也是Python数据社区和Apache软件基金会的Python/C 开源开发者。目前他在纽约从事软件架构师工作。

Wes McKinney is a New York?based software developer and entrepreneur. After finishing his undergraduate degree in mathematics at MIT in 2007, he went on to do quantitative finance work at AQR Capital Management in Greenwich, CT. Frustrated by cumbersome data analysis tools, he learned Python and started building what would later become the pandas project. He's now an active member of the Python data community and is an advocate for the use of Python in data analysis, finance, and statistical computing applications.

Wes was later the co-founder and CEO of DataPad, whose technology assets and team were acquired by Cloudera in 2014. He has since become involved in big data technology, joining the Project Management Committees for the Apache Arrow and Apache Parquet projects in the Apache Software Foundation. In 2016, he joined Two Sigma Investments in New York City, where he continues working to make data analysis faster and easier through open source software.