The code and data in this repository is an example of a reproducible research workflow for MACS 30200 "Perspectives on Computational Research" at the University of Chicago.

The code is written in Python 3.9.7 and all of its dependencies can be installed by running the following in the terminal (with the requirements.txt file included in this repository):

pip install -r requirements.txt

Then, you can import the analysis module located in this repository to reproduce the analysis in the (hypothetical) publication that this code supplements (in a Jupyter Notebook, like README.ipynb in this repository, or in any other Python script):

import analysis

You can then use the process_data function in the analysis module to process the data and get it ready to analyze. The plot function will reproduce Figure 1 from the (hypothetical) publication.

df = analysis.process_data('data.csv')
analysis.plot(df)

Alternatively, to replicate the analysis and produce all of the figures and quantitative analyses from the (hypothetical) publication that this code supplements, build and run the Dockerfile included in this repository via the instructions in the file).

If you use this repository for a scientific publication, we would appreciate it if you cited the Zenodo DOI (see the "Cite as" section on our Zenodo page for more details).