docs-v2/content/flux/v0.x/stdlib/universe/timedmovingaverage.md

title	description	menu	weight	flux/v0.x/tags	introduced
timedMovingAverage() function	`timedMovingAverage()` returns the mean of values in a defined time range at a specified frequency.	flux_0_x_ref name parent identifier timedMovingAverage universe universe/timedMovingAverage	101	transformations	0.36.0

timedMovingAverage() returns the mean of values in a defined time range at a specified frequency.

For each row in a table, timedMovingAverage() returns the average of the current value and all row values in the previous period (duration). It returns moving averages at a frequency defined by the every parameter.

Aggregate by calendar months and years

every and period parameters support all valid duration units, including calendar months (1mo) and years (1y).

Aggregate by week

When aggregating by week (1w), weeks are determined using the Unix epoch (1970-01-01T00:00:00Z UTC). The Unix epoch was on a Thursday, so all calculated weeks begin on Thursday.

Function type signature

(<-tables: stream[A], every: duration, period: duration, ?column: string) => stream[B] where A: Record, B: Record

{{% caption %}}For more information, see Function type signatures.{{% /caption %}}

Parameters

every

({{< req >}}) Frequency of time window.

period

({{< req >}}) Length of each averaged time window.

A negative duration indicates start and stop boundaries are reversed.

column

Column to operate on. Default is _value.

tables

Input data. Default is piped-forward data (<-).

Examples

Calculate a five year moving average every year

data
    |> timedMovingAverage(every: 1y, period: 5y)

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Input data

*_start	*_stop	_time	_value
2015-01-01T00:00:00Z	2021-01-01T00:00:00Z	2015-01-01T00:00:00Z	0
2015-01-01T00:00:00Z	2021-01-01T00:00:00Z	2016-01-01T08:00:00Z	1
2015-01-01T00:00:00Z	2021-01-01T00:00:00Z	2016-12-31T16:00:00Z	4
2015-01-01T00:00:00Z	2021-01-01T00:00:00Z	2018-01-01T00:00:00Z	9
2015-01-01T00:00:00Z	2021-01-01T00:00:00Z	2019-01-01T08:00:00Z	16
2015-01-01T00:00:00Z	2021-01-01T00:00:00Z	2020-01-01T16:00:00Z	25

Output data

*_start	*_stop	_value	_time
2015-01-01T00:00:00Z	2021-01-01T00:00:00Z	0	2016-01-01T00:00:00Z
2015-01-01T00:00:00Z	2021-01-01T00:00:00Z	1.6666666666666667	2017-01-01T00:00:00Z
2015-01-01T00:00:00Z	2021-01-01T00:00:00Z	1.6666666666666667	2018-01-01T00:00:00Z
2015-01-01T00:00:00Z	2021-01-01T00:00:00Z	3.5	2019-01-01T00:00:00Z
2015-01-01T00:00:00Z	2021-01-01T00:00:00Z	6	2020-01-01T00:00:00Z
2015-01-01T00:00:00Z	2021-01-01T00:00:00Z	11	2021-01-01T00:00:00Z
2015-01-01T00:00:00Z	2021-01-01T00:00:00Z	16.666666666666668	2021-01-01T00:00:00Z
2015-01-01T00:00:00Z	2021-01-01T00:00:00Z	16.666666666666668	2021-01-01T00:00:00Z
2015-01-01T00:00:00Z	2021-01-01T00:00:00Z	20.5	2021-01-01T00:00:00Z
2015-01-01T00:00:00Z	2021-01-01T00:00:00Z	25	2021-01-01T00:00:00Z

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