The Best Data Science Libraries in Python
Preface
Due to its exceptional abilities, Python is the most commonly used programming language in the field of Data Science these days. While Python provides a lot of functionality, the availability of various multi-purpose, ready-to-use libraries is what makes the language top choice for Data Scientists. Some of these libraries are well known and widely used, while others are not so common. In this article I have tried to compile a list of Python libraries and categorized them according to their functionality.
Core libraries
These libraries are a part of standard Python package and can just be imported if users want to make use of their functionality.
NumPy
Short for Numerical Python, NumPy has been designed specifically for mathematical operations. It primarily supports multi-dimensional arrays and vectors for complex arithmetic operations. In addition to the data structures, the library has a rich set of functions to perform algebraic operations on the supported data types.
Another advantage of the library is its interoperability with other programming languages like C/C++, FORTRAN, and database management systems. Also, as the set of provided functions is precompiled, the computations are performed in an efficient manner.
SciPy
Based