chapter overview

learning objectives

This chapter explores how the Python programming language takes data, organizes it into collections or groupings, with the goal of doing something to that data.

It introduces:

• data types and variables for categorizing and saving data

• functions and methods for working with data

• iterative and logical structures

• basic Python syntax

Python environments

There are many ways to use Python. For this workshop, we will be using Jupyter-Notebooks, installed through the Python Anaconda distrubtion. This option is convenient because it creates a “local” version of Python directly on your computer, which means you can use it in mutiple ways and without an internet connection.

For those of you who cannot download Python, you can use Google Colab, a browser-based tool for running Python code. Like Google Docs, Google Colab creates a collaborative environment hosted on the Google cloud for authoring content. Whereas most Python environments require installations (some of which can be really complicated), Google Colab offers Python software pre-installed on the cloud environment. It enables new users to jump right into programming.