Numpy an External Library

This lesson introduces an external numpy library by discussing in detail how numpy provides support to handle single or multidimensional arrays and different functionalities.

Handling arrays with NumPy #

Single dimensional arrays #

For the sake of simplicity, you can think of Numpy as a fast and efficient library for storing and manipulating data - usually through array data structures (which are similar to Python lists). You can find all the documentation for Numpy here. Numpy arrays are different from standard Python lists in many ways; notably, they are faster, take up less space, and have more functionality. It is important to note, though, that these arrays are of a fixed size and type that you define at creation. You cannot infinitely append new values as you might with a list.

Let’s see some of the ways you can use arrays in action.

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