# Association rule mining for continuous variables

I'm trying to study the relationships between several numerical variables, eg. electricity generation between different stations at 30min intervals over several months. My data has the format

I want to find the relationships between station1 and station2, station1 and station3, etc, and I'm trying to look for a more sophisticated method than correlation matrices. If necessary, I can also add columns showing time of day, day of week and other time variables extracted from the datetime column.

Association rule mining and apriori algorithm (finding support, confidence, lift) seems to be closest to what I want. But all the literature/tutorials I've seen so far involves shopping basket-type situations.

Is the apriori algorithm suitable for what I'm trying to do? Or is there something better?