July 2018
Intermediate to advanced
491 pages
9h 39m
Chinese
Overview
阅读本书可以获得关于在Python下操作、处理、清洗、规整数据集的完整说明。本书第2版针对Python 3.6进行了更新，并增加了实际案例向你展示如何高效地解决一系列数据分析问题。你将在阅读过程中学习到较新版本的pandas、NumPy、IPython和Jupyter。
本书作者Wes McKinney是Python pandas项目的创始人。本书是对Python数据科学工具的实操化、现代化的介绍，非常适合刚学Python的数据分析师或刚学数据科学以及科学计算的Python编程者。数据文件和相关的材料可以在GitHub上找到。
- 使用IPython shell和Jupyter notebook进行探索性计算
- 学习NumPy(Numerical Python)的基础和高级特性
- 入门pandas库中的数据分析工具
- 使用灵活工具对数据进行载入、清洗、变换、合并和重塑
- 使用matplotlib创建富含信息的可视化
- 将pandas的groupby功能应用于对数据集的切片、切块和汇总
- 分析并操作规则和不规则的时间序列数据
- 利用完整的、详细的示例学习如何解决现实中的数据分析问题
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