I'm keeping a large number of data points in multiple 2d arrays, for example: class c(object): def __init__(self): self.a = np.zeros((24, 60)) self.b = np.zeros((24, 60)) ... After processing the data, I'm serializing these to disk for future reference/post-processing. It's a largish amount of data and is only going to get larger. Would it be more efficient (in terms of memory/disk storage to use a single n-dimensional array: self.a = np.zeros((24, 60, 5)) What other advantages (if any) would I gain from storing the data in a single array rather than multiple? The deeper into this project I get, the more I am probably going to need to correlate data points from one or more of the arrays to one or more of the other arrays. I think I just answered my own question... -- THE SuperBitBucket.com You know you're a geek when you can hold an entire conversation with friends in linux CLI talk, i.e. 'cat /proc/lookattheassonthat!' or 'cd /pub/beer'