此系列文章参照NumPy官方用户指南1.2.1版本进行翻译、解读（直译说不清楚的可能会加入自己的一些理解）。
《NumPy: the absolute basics for beginners》以问答的形式说明了NumPy比较基础、重要的一些概念和应用范式以便于初学者快速掌握NumPy的应用。
NumPy简介：Welcome to NumPy!
NumPy (Numerical Python) 是一个几乎应用于科学和工程各个领域的开源Python库，它是Python处理数值型数据的通用标准，也是Python科学计算和Python数据科学生态系统的核心。NumPy用户包括从最初的程序员到从事最先进的科学和工业研究与开发的有经验的研究人员。NumPyAPI广泛用于Pandas、SciPy、Matplotlib、sciket-learn、scikit-image和大多数其他Python数据科学和科学计算包中。
NumPy库包含多维数组和矩阵数据结构（您将在后面的部分中找到有关这方面的更多信息）。它为ndarray（一个均匀的n维数组对象）提供了有效操作的方法。NumPy可以用于对数组执行各种各样的数学运算。它为Python添加了强大的数据结构，保证了数组和矩阵的高效计算，并提供了一个庞大的高级数学函数库，这些函数可以对这些数组和矩阵进行操作。
在这里了解更多关于NumPy的信息！
NumPy (Numerical Python) is an open source Python library that’s used in almost every field of science and engineering. It’s the universal standard for working with numerical data in Python, and it’s at the core of the scientific Python and PyData ecosystems. NumPy users include everyone from beginning coders to experienced researchers doing state-of-the-art scientific and industrial research and development. The NumPy API is used extensively in Pandas, SciPy, Matplotlib, scikit-learn, scikit-image and most other data science and scientific Python packages.
The NumPy library contains multidimensional array and matrix data structures (you’ll find more information about this in later sections). It provides ndarray, a homogeneous n-dimensional array object, with methods to efficiently operate on it. NumPy can be used to perform a wide variety of mathematical operations on arrays. It adds powerful data structures to Python that guarantee efficient calculations with arrays and matrices and it supplies an enormous library of high-level mathematical functions that operate on these arrays and matrices.
Learn more about NumPy here!
参考
https://numpy.org/doc/stable/user/absolute_beginners.html