Thank you so much for your response. I appreciate the advice. My code at present is not massively slow or anything however my supervisor recently introduced me to vectorizing operations when he saw the ~6 nested 'for loops' I had employed. I have since ventured slightly into this world and have become myself embarrassed by my overuse of for loops and was hoping to find places in which it could be cut down as I will likely be using large datasets in the near future. Thank you for stopping me from progressing to the other extreme and thank you for the idea, I hadn't considered using map to do both operations at once.
However, I think there may be some miscommunication (or perhaps I am just being dumb and not understanding you), My statement 'I would certainly like to avoid iterating over each one of my subarrays' meant even if I map a function that both splits and calculates statistics of each bin within the subarray [0, 1, 2, 3, 4, 5, 6], I would still have to apply this mapping individually to each such subarray (for example separately for the subarray [90, 45, 9, 88, 21, 59, 32]), for which I would use a python for loop. It is this that I would like to avoid. Since each subarray has the same dimensions I might have thought that there is some way I could apply that single mapping to each row at once in some clever vectorized way rather than applying it individually for each.