1.1.1. Computational Tools#
This text uses the Python 3 programming language, along with a standard set of numerical and data visualization tools that are used widely in commercial applications, scientific experiments, and open-source projects. Python has recruited enthusiasts from many professions that use data to draw conclusions. By learning the Python language, you will join a million-person-strong community of software developers and data scientists.
Getting Started. The easiest and recommended way to start writing programs in Python is to log into the companion site for this text, datahub.berkeley.edu. If you have a @berkeley.edu email address, you already have full access to the programming environment hosted on that site.
You are not at all restricted to using this web-based programming environment. A Python program can be executed by any computer, regardless of its manufacturer or operating system, provided that support for the language is installed. If you wish to install the version of Python and its accompanying libraries that will match this text, we recommend the Anaconda distribution that packages together the Python 3 language interpreter, IPython libraries, and the Jupyter notebook environment.
This text includes a complete introduction to all of these computational tools. You will learn to write programs, generate images from data, and work with real-world data sets that are published online.