Here are three examples of how to (1) load and visualize the data, (2) run PPI, and (3) perform Monte Carlo simulations to estimate the policy priorities. Each file was prepared in a Jupyter notebook. By downloading the file with extension ipynb and opening it with the jupyter app includded in the Anaconda python distribution, you should be able to run the example.

The folder contains not only the examples, but also the necessary code and data. Therefore, by downloading the entire folder, the examples should be able to run off the shelf. However, if you only want to see them, click in a ipynb file and GitHub will render it into a readable format.

The data files in this folder are the same ones that can be found in the National_data folder. They were copied here so that it is easier for the user to download the examples and run them without troubles. Similarly, all the files with extension .py in this folder are the same ones that can be found in the code folder. The reason to copying them here is the same as with the data.