Machine Learning for iOS Developers

Appendix BIntroduction to NumPy and Pandas

WHAT'S IN THIS APPENDIX

• Learning the basics of the NumPy Python library
• Learning the basics of the Pandas Python library

In this appendix you will learn to use two popular Python libraries used by data scientists—NumPy and Pandas. These libraries are commonly used during the data exploration and feature engineering phase of a project. The examples in this appendix require the use of Jupyter Notebooks.

NOTE  To follow along with this appendix, ensure you have installed Anaconda Navigator and Jupyter Notebooks, as described in Appendix A.

You can download the code files for this appendix from Wrox.com or from GitHub using the following URL:

https://github.com/asmtechnology/awsmlbook-appendixb.git

NumPy

NumPy is a math library for Python that allows for fast and efficient manipulation of arrays. The main object provided by NumPy is a homogenous multidimensional array called an ndarray. All the elements of an ndarray must be of the same data type, and dimensions are referred to as axes in NumPy terminology.

To use NumPy in a Python project, you typically add the following import statement to your Python file:

import numpy as np

The lowercase alias np is a standard convention for referring to NumPy in Python projects.

Creating NumPy Arrays

There are a number of ways in which you can create an ndarray. To create an ndarray object out of a three-element Python list, use the np.array() statement. The following code snippet, when ...