• Codebook Series

    One of the Centre’s goals is to foster a broader understanding of the data analytics tools used in digital financial research. One of the core tools used by accounting analytics experts is the Python programming language. We are strong proponents of using Python to gather, process, analyze, and visualize accounting and financial data. We also believe anyone can learn it. For this reason, on this page we will make available a series of code notebooks – called Jupyter notebooks – each of which walks you through a unique coding task. Our hope is that these notebooks prove useful to fellow academics as well as budding data scientists and practitioners interested in analyzing digital financial information.

Latest Notebooks

PANDAS (View on Github)

This is a series of ipython notebooks for analyzing Big Data -- specifically Twitter data -- using Python's powerful PANDAS (Python Data Analysis) library.

For these tutorials I am assuming you have already downloaded some data and are now ready to begin examining it. In the first notebook I will show you how to set up your ipython working environment and import the Twitter data we have downloaded. If you are new to Python, you may wish to go through a series of tutorials I have created in order.

If you want to skip the data download and just use the sample data, but don't yet have Python set up on your computer, you may wish to go through the tutorial "Setting up Your Computer to Use My Python Code".

Also note that we are using the iPython notebook interactive computing framework for running the code in this tutorial. If you're unfamiliar with this see this tutorial "Four Ways to Run your Code".

For a more general set of PANDAS notebook tutorials, I'd recommend this cookbook by Julia Evans. I also have a growing list of "recipes" that contains frequently used PANDAS commands.

Twitter (View on Github)

This is a series of ipython notebooks for downloading Twitter data in Python. For tutorials on how to analyze the data you've downloaded, please refer to a separate series of notebooks here: https://github.com/gdsaxton/PANDAS

In the first notebook I will show you how to use the Twitter API keys you set up in a prior tutorial: Setting up Access to the Twitter API. More notebooks will be forthcoming shortly.

If you are new to Python, you may wish to go through a series of tutorials I have created in order. If you don't wish to do all the tutorials you should at least ensure you have your Twitter API key and you've set up Python on your computer as shown in the tutorial "Setting up Your Computer to Use My Python Code".

Also note that we are using the iPython notebook interactive computing framework for running the code in this tutorial. If you're unfamiliar with this see this tutorial "Four Ways to Run your Code".

For a more general set of PANDAS notebook tutorials, I'd recommend this cookbook by Julia Evans. I also have a growing list of "recipes" that contains frequently used PANDAS commands.