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

它们看起来都非常相似，而且我对哪种软件包对财务数据分析更有利感到好奇.

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

实际上，pandas提供了基于NumPy构建的高级数据处理工具. NumPy本身是一个相当底层的工具，与使用MATLAB非常相似.另一方面，pandas提供了丰富的时间序列功能，数据对齐，对NA友好的统计信息，groupby，合并和联接方法以及许多其他便利.近年来，它已在金融应用中变得非常流行.我的下一本书将专门讨论使用熊猫进行财务数据分析的一章.

Indeed, pandas provides high level data manipulation tools built on top of NumPy. NumPy by itself is a fairly low-level tool, and will be very much similar to using 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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