Reference · Statistics

stats.fmean

stats.fmean(list, list | null=) -> float

What it does

The mean of a list of numbers as a float, optionally weighted. With a second list of weights, one per value, the answer is the sum of each value times its weight, divided by the sum of the weights. Without weights, or with null, it is the same as stats.mean: Python's fmean is only a faster mean, and here both give the same float.

Examples

print(stats.fmean([1, 2, 3, 4]))print(stats.fmean([80, 90], [0.6, 0.4]))print(stats.fmean([1, 2, 3], [3, 1, 1]))

2.584.01.6

Edge cases

• Weights can be ints or floats and need not add up to 1.
• A weight can be negative or zero as long as the weights' sum is not zero.
• null for the weights means no weights.
• One value gives that value, as a float.

print(stats.fmean([1, 2, 3], [1, 1, 1]), stats.fmean([1, 2, 3], null))print(stats.fmean([1, 2], [2, -1]), stats.fmean([5], [10]))

2.0 2.00.0 5.0

Errors

No data, weights of another length than the data, and weights that add up to zero are each a runtime error, not an error value. So is anything in either list that is not a number.

print(stats.fmean([1, 2], [1]))

line 1: `stats.fmean`: data and weights must be the same length

print(stats.fmean([1, 2], [0, 0]))

line 1: `stats.fmean`: the sum of the weights must be non-zero

print(stats.fmean([]))

line 1: `stats.fmean` requires at least one data point

Chaining

In a pipeline the data comes first and the weights are the argument:

let grades = [80, 90, 70]let credits = [3, 1, 2]print(grades | stats.fmean(credits))print(grades | stats.fmean | round(1))

78.3333333333333380.0

See also

stats.mean, stats.geometric_mean, stats.harmonic_mean, sum

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