出版社: O'Reilly Media
副标题: Data Wrangling With Pandas, Numpy, and Jupyter
出版年: 2022-9-20
页数: 579
装帧: Paperback
ISBN: 9781098103965
内容简介 · · · · · ·
Get the definitive handbook for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.10 and pandas 1.4, the third 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, and Jupyter in the process.
Wr...
Get the definitive handbook for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.10 and pandas 1.4, the third 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, 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 Jupyter notebook and IPython shell for exploratory computing
Learn basic and advanced features in NumPy
Get started with data analysis tools in the panda's library
Use flexible tools to load, clean, transform, merge, and reshape data
Create informative visualizations with matplotlib
Apply the panda's 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
Python for Data Analysis, 3rd Edition的创作者
· · · · · ·
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Wes McKinney 作者
作者简介 · · · · · ·
Wes McKinney is a Nashville-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 me...
Wes McKinney is a Nashville-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 cofounder 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 2018, he founded Ursa Labs, a not-for-profit organization focused Apache Arrow development, in partnership with RStudio and Two Sigma Investments. In 2021, he cofounded technology startup Voltron Data, where he currently works as the Chief Technology Officer.
目录 · · · · · ·
1 Preliminaries
2 Python Language Basics, IPython, and Jupyter Notebooks
3 Built-In Data Structures, Functions, and Files
4 NumPy Basics: Arrays and Vectorized Computation
5 Getting Started with pandas
· · · · · · (更多)
1 Preliminaries
2 Python Language Basics, IPython, and Jupyter Notebooks
3 Built-In Data Structures, Functions, and Files
4 NumPy Basics: Arrays and Vectorized Computation
5 Getting Started with pandas
6 Data Loading, Storage, and File Formats
7 Data Cleaning and Preparation
8 Data Wrangling: Join, Combine, and Reshape
9 Plotting and Visualization
10 Data Aggregation and Group Operations
11 Time Series
12 Introduction to Modeling Libraries in Python
13 Data Analysis Examples
· · · · · · (收起)
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Python for Data Analysis, 3rd Edition的书评 · · · · · · ( 全部 81 条 )
【勘误】学习Python,从数据分析到人工智能
作者用心写书,译者用脚翻译
五星给内容,三星给翻译
跟pandas的开发者学数据分析
> 更多书评 81篇
论坛 · · · · · ·
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5 有用 端端 2023-08-19 09:00:35 美国
暑假读过的工具书,真的是从头到尾一字不拉地看完了,每条代码都跑了一遍。看完有点空虚,因为不知道以后工作会不会用到,用不到时间长就忘了,以及chatgpt的推出让这门技术的门槛下降了很多。感觉有用的是对pandas包熟悉了很多,看代码的怯懦情绪降低了一些。感觉这类工具书基本都是作者整理的个人笔记,是工作的副产品,提升干活效率的技巧合集。
4 有用 风乍起 2023-04-22 14:18:47 广东
看的网页版(https://wesmckinney.com/book),适合我自己较为快速的学这个工具的方式: 1、认真仔细的通读这本书,建立一个概览和框架。哪怕之前版本读过,也用其他的的数据分析工具有些年头了。 2、看软件的帮助文档(https://pandas.pydata.org/docs/),里面有很多细节,如果第一步比较扎实,这里可以补充很多细节。当然很多细节平时不咋能用得上。 3、努力... 看的网页版(https://wesmckinney.com/book),适合我自己较为快速的学这个工具的方式: 1、认真仔细的通读这本书,建立一个概览和框架。哪怕之前版本读过,也用其他的的数据分析工具有些年头了。 2、看软件的帮助文档(https://pandas.pydata.org/docs/),里面有很多细节,如果第一步比较扎实,这里可以补充很多细节。当然很多细节平时不咋能用得上。 3、努力找作者关于设计思路(不一定能找到特别系统的材料),问几个为什么这么设计的原因,搞清楚WHY,这样记忆加深理解深化,顺带看看源代码 4、具体干活的过程中,反复迭代上面过程;如果有更熟悉的工具写的代码,“翻译”为当前工具,尽可能用当前工具的“成语”或“特性” (展开)
0 有用 lubio 2024-04-24 21:24:37 上海
确实很有用,结合chatgpt真的能提供不少帮助
0 有用 Sleepwalker 2024-11-13 01:47:37 加拿大
DA告一段落
0 有用 Flake 2024-09-29 22:21:48 中国澳门
有点枯燥,但还能读得下去吧,书的结构还是可以的。 p 90有个错误,an unsigned integer 应该是only present “non-negative 非负” integers,而不是”nonzero”