How to efficiently calculate a running standard deviation?

I have an array of lists of numbers, e.g.:

[0] (0.01, 0.01, 0.02, 0.04, 0.03)
[1] (0.00, 0.02, 0.02, 0.03, 0.02)
[2] (0.01, 0.02, 0.02, 0.03, 0.02)
     ...
[n] (0.01, 0.00, 0.01, 0.05, 0.03)

What I would like to do is efficiently calculate the mean and standard deviation at each index of a list, across all array elements.

To do the mean, I have been looping through the array and summing the value at a given index of a list. At the end, I divide each value in my "averages list" by n (I am working with a population, not a sample from the population).

To do the standard deviation, I loop through again, now that I have the mean calculated.

I would like to avoid going through the array twice, once for the mean and then once for the SD (after I have a mean).

Is there an efficient method for calculating both values, only going through the array once? Any code in an interpreted language (e.g. Perl or Python) or pseudocode is fine.

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