Learn how to create, index, slice, reshape, and perform arithmetic operations on arrays using NumPy, the most popular Python library for data science.

How NumPy speeds array math in Python. A big part of NumPy’s speed comes from using machine-native datatypes, instead of Python’s object types.

Arrays in Python give you a huge amount of flexibility for storing, organizing, and accessing data. This is crucial, not least because of Python’s popularity for use in data science.

PuLP is a Python library that provides a high-level interface for creating and solving linear programming problems. PuLP allows you to define the variables, objective function, and constraints of ...