Reference · Vectors

vec.rolling_mean

vec.rolling_mean(list, int) -> list

What it does

The moving average: the mean of each run of window neighbouring items, as a list of floats. Only full windows count, so the result has len(xs) - window + 1 items and starts at the first position where a whole window fits. vec.rolling_mean(daily, 7) is a week's moving average.

Examples

print(vec.rolling_mean([1, 2, 3, 4, 5], 3))let daily = [10, 12, 9, 14, 11, 13, 8, 15]print(vec.rolling_mean(daily, 7))

[2.0, 3.0, 4.0][11.0, 11.714285714285714]

Edge cases

• A window of 1 is the list itself, as floats.
• A window as long as the list gives one item, the mean of all.
• A window longer than the list gives the empty list; so do the empty list and null.
• The sums are compensated: the total of [0.1, 0.2, 0.3] is 0.6, not 0.6000000000000001, and the mean is 0.6 / 3, which float division gives as 0.19999999999999998.
• A whole float counts as the int it is: a window of 2.0 is 2.

print(vec.rolling_mean([1, 2, 3], 1), vec.rolling_mean([1, 2, 3], 3))print(vec.rolling_mean([1, 2, 3], 4), vec.rolling_mean([], 2), vec.rolling_mean(null, 1))print(vec.rolling_mean([0.1, 0.2, 0.3], 3))print(vec.rolling_mean([1, 2], 2.0))

[1.0, 2.0, 3.0] [2.0][] [] [][0.19999999999999998][1.5]

Errors

A window below 1, a missing window, a window that is not an int, an item that is not an int or a float, or a first argument that is not a list are runtime errors, not error values.

print(vec.rolling_mean([1, 2], 0))

line 1: `vec.rolling_mean`: the window must be at least 1, got 0

print(vec.rolling_mean([1, 2]))

line 1: `vec.rolling_mean` expects an int as argument 2, got nothing

Chaining

let sales = [3, 5, 4, 6, 8]print(sales | vec.rolling_mean(2))print(sales | vec.rolling_mean(3) | vec.round(1) | last)

[4.0, 4.5, 5.0, 7.0]6.0

See also

vec.rolling_sum, stats.mean, vec.cumsum, vec.diff

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