This example explores the linelistrecord Type in the Covid-19 Datalake. Symptom records are combined to build a profile of the most prevalent symptoms of Covid-19. A similar example is given at the end of the python startup notebook on C3.ai's public Datalake documentation here: https://github.com/c3-e/c3aidatalake-notebooks/raw/master/c3aidatalake-notebooks-python.zip
The python implementation is in the python directory. This directory contains a useful conda environment definition file env.yaml. Create a conda environment using conda env create -f env.yaml -p <path_to_prefix> or conda env create -f env.yaml -n <environment_name>. Then launch juptyer with jupyter notebook and start the notebook EpidemiologyExample.ipynb.
Once the notebook is started, you can run the notebook cells which implement the example!
The C3 implementation of this example is in the directory c3-python-connector. Make sure you have access to a C3 tag which has the Datalake package provisioned either directly, or as a dependency of your current package. To ensure your python environment has everything needed, we recommend provisioning a conda environment with
conda env create -f ./env.yaml -p ./venv
After which you can launch jupyter notebook, and open the notebook casesExample.ipynb.
When running the jupyter notebook, there's a cell at the top meant to connect to a running C3 tag. If you're running python/jupyter 'remotely' that is not through C3's system, you will need to replace the <vanity_url>, <tenant>, and <tag> in the cell negotiating the connection to C3. It should look like this:
c3 = get_c3('<vanity_url>', '<tenant>', '<tag>')