Chapter 1. Getting Started with Python Libraries

Let's get started. We can find a mind map describing software that can be used for data analysis at http://www.xmind.net/m/WvfC/. Obviously, we can't install all of this software in this chapter. We will install NumPy, SciPy, matplotlib, and IPython on different operating systems and have a look at some simple code that uses NumPy.

NumPy is a fundamental Python library that provides numerical arrays and functions.

SciPy is a scientific Python library, which supplements and slightly overlaps NumPy. NumPy and SciPy historically shared their code base but were later separated.

matplotlib is a plotting library based on NumPy. You can read more about matplotlib in Chapter 6, Data Visualization.

IPython provides an architecture for interactive computing. The most notable part of this project is the IPython shell. We will cover the IPython shell later in this chapter.

Installation instructions for the other software we need will be given throughout the book at the appropriate time. At the end of this chapter, you will find pointers on how to find additional information online if you get stuck or are uncertain about the best way to solve problems.

In this chapter, we will cover:

• Installing Python, SciPy, matplotlib, IPython, and NumPy on Windows, Linux, and Macintosh
• Writing a simple application using NumPy arrays
• Getting to know IPython
• Online resources and help