Python has several groups of processing functions that can tax computer system power. Let us use some of these in Jupyter and determine if the functionality performs as expected.
NumPy is a package in Python providing multidimensional arrays and routines for array processing. We bring in the NumPy package using import * from numpy statement. In particular, the NumPy package defines the array keyword, referencing a NumPy object with extensive functionality.
The NumPy array processing functions run from the mundane, such as min() and max() functions (which provide the minimum and maximum values over the array dimensions provided), to more interesting utility functions for producing histograms and calculating correlations using the elements of a data frame.
With NumPy, you can manipulate arrays in many ways. For example, we will go over some of these functions with the following scripts, where we will use NumPy...
