This repository has all the scripts and data that I used and/or created for my PhD. The WebApp is built in streamlit and has two functions: It is a help for (my) research and it enables other researchers to easily access the data in the background.
I recommend using pipenv pipenv install to create a virtual environment for the app and get all dependencies. Tested using python 3.11.5.
If you used pipenv you can simply run pipenv run setup to prepare all the data.
Otherwise you will need to run src/setup.py manually.
Then start the webapp with the command python -m streamlit run src/pamphalazyer.py or
with pipenv run run if you used pipenv to set up a virtual envirnonment.
Run the webapp using pipenv run run. In the webapp, you can look through all the data.
You can run all my analyses yourself using the webapp or with the command pipenv run analysis.