NumPy (Numerical Python) Basics:

• Numerical computing packages in Python. 
• provides various libraries API written in C, C++, or FORTRAN. 
• provides a multidimensional array object, various derived objects (such as masked arrays and matrices),
• and a variety 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.

CHARACTERISTICS: - 

POWERFUL N-DIMENSIONAL ARRAYS
Fast and versatile, the NumPy vectorization, indexing, and broadcasting concepts are the Standards of array computing.

NUMERICAL COMPUTING TOOLS
Provides comprehensive mathematical functions, random number generators, linear algebra routines, Fourier transforms, and more.

INTER-OPERABLE
supports a wide range of hardware and computing platforms, and provides distributed GPU (Graphics processing unit), and sparse array (2dim.) libraries.

PERFORMANT
The core of NumPy is well-optimized C code. the flexibility of Python with the speed of compiled code.

EASY TO USE
NumPy’s high-level syntax makes it accessible and productive for programmers from any background or experience level.

OPEN-SOURCE
Using the BSD (Berkeley Source Distribution) license, NumPy is developed and maintained publicly on GitHub by a vibrant, responsive, and diverse community.