In this repository we use Pandas and Python to imitate an SQL cross-join. This gives us a DataFrame with all the combinations of all the rows of data (staying in order left to right). Using that data frame, we then concat a CQL expression for each combination and convert the data frame into a JSON file for the API push into ChartHop.
| Tool | Link |
|---|---|
| Pandas | https://pandas.pydata.org/docs/getting_started/install.html |
| VS Studio | https://code.visualstudio.com/download |
| Jupyter Notebook Package | https://pypi.org/project/jupyter/ |