How should I process this data?

[SuchUmami]

I don't need coding help but I would really appreciate some ideas about how to tackle this problem.

I have this dataset:




Now these numbers should be inversely related. So if one goes up, the other should go down. However, this is not always the case. What I'm really looking for are times when there is a movement in the stress level but also the tolerance to move in the same direction or even in the same direction. This is quite easy to do column by column. But I want to process the data in a way that will find times when they're moving and mostly coordinated in the same direction.

I thought about turning each move into a move in terms of percentage (from row to row) because percentage terms is much better than absolute numbers when they're so different.



You can now clearly see at 19:35 that they both move in the same direction (going negative). I would like to process the whole data to find the points which are like this but also which points are most congruent across the whole dataset as it might span across multiple rows.

I am absolutely flummoxed.

[Pedroski55]

Well, start somewhere, maybe the bottom row or the top row. Compare each column 2 and column 3 for 2 rows, see if both increase, or decrease. If so, do whatever it is you want to do.

if row1, column2 > row2, column2 and row1, column3 > row2, column3:
    doSomething()

[RockBlok]

I was about to suggest doing a delta calculation and comparing, but pedroski's method seems much cleaner.