获取Python中操作、处理、清理和处理数据集的权威手册。为Python3.9和pandas 1.2进行了更新，本实践指南的第三版包含了大量实际案例研究，向您展示了如何有效地解决广泛的数据分析问题。你呢？？Ã?¢??在这个过程中，我们将学习熊猫、NumPy和Jupyter的最新版本。
这本书由Python熊猫项目的创始人韦斯·麦金尼（Wes McKinney）撰写，是Python中数据科学工具的实用、现代的介绍。是吗？？Ã?¢??它是Python新手分析人员和数据科学和科学计算新手Python程序员的理想选择。数据文件和相关材料可在GitHub上获得。
使用Jupyter笔记本和IPython外壳进行探索性计算
学习NumPy的基本和高级功能
开始使用pandas库中的数据分析工具
使用灵活的工具加载、清理、转换、合并和重塑数据
使用matplotlib创建信息可视化
应用pandas groupby工具对数据集进行切片、切分和汇总
分析和处理规则和不规则的时间序列数据
了解如何通过全面、详细的示例解决实际数据分析问题
Python for Data Analysis, 3rd Edition (Fifth Early Release)
Get the definitive handbook for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.9 and pandas 1.2, 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 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
OR
