NumPy

In terms of using Python for scientific work, NumPy (Numerical Python) is one of the most important modules to effectively and efficiently complete tasks. So what is NumPy exactly?

NumPy is the fundamental package for scientific computing in Python. It is a Python library that provides a multidimensional array object, various derived objects (such as masked arrays and matrices), and an assortment of routines for fast operations on arrays, including mathematical, logical, shape manipulation, sorting, selecting, I/O, discrete Fourier transforms, basic linear algebra, basic statistical operations, random simulation and much more. (SciPy/NumPy)

Since native Python does not contain a true array object, NumPy is the module that expands the capabilities of the root Python language with fast array methods. NumPy is a standard module and comes pre-packaged with both miniconda and anaconda distributions of Python.

To import NumPy the following is the most common method

import numpy as np

Many modules that are used within the scientific Python stack depend on NumPy and if you use an automated read function the data will more likely than not be a NumPy array.