Python中的Pandas和NumPy+SciPy有什么区别? [英] What are the differences between Pandas and NumPy+SciPy in Python?

问题描述

它们看起来极其相似，我很好奇哪个包对财务数据分析更有利.

They both seem exceedingly similar and I'm curious as to which package would be more beneficial for financial data analysis.

推荐答案

pandas 提供了构建在 NumPy 之上的高级数据操作工具.NumPy 本身是一个相当低级的工具，类似于 MATLAB.另一方面，pandas 提供了丰富的时间序列功能、数据对齐、NA 友好的统计、分组、合并和连接方法以及许多其他便利.近年来，它在金融应用中变得非常流行.在我即将出版的书中，我将有一章专门介绍使用 Pandas 进行金融数据分析.

pandas provides high level data manipulation tools built on top of NumPy. NumPy by itself is a fairly low-level tool, similar to MATLAB. pandas on the other hand provides rich time series functionality, data alignment, NA-friendly statistics, groupby, merge and join methods, and lots of other conveniences. It has become very popular in recent years in financial applications. I will have a chapter dedicated to financial data analysis using pandas in my upcoming book.

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