--- title: movingAverage() function description: > `movingAverage()` calculates the mean of non-null values using the current value and `n - 1` previous values in the `_values` column. menu: flux_v0_ref: name: movingAverage parent: universe identifier: universe/movingAverage weight: 101 flux/v0/tags: [transformations] introduced: 0.35.0 --- `movingAverage()` calculates the mean of non-null values using the current value and `n - 1` previous values in the `_values` column. ### Moving average rules - The average over a period populated by `n` values is equal to their algebraic mean. - The average over a period populated by only `null` values is `null`. - Moving averages skip `null` values. - If `n` is less than the number of records in a table, `movingAverage()` returns the average of the available values. ##### Function type signature ```js (<-tables: stream[{A with _value: B}], n: int) => stream[{A with _value: float}] where B: Numeric ``` {{% caption %}} For more information, see [Function type signatures](/flux/v0/function-type-signatures/). {{% /caption %}} ## Parameters ### n ({{< req >}}) Number of values to average. ### tables Input data. Default is piped-forward data (`<-`). ## Examples - [Calculate a three point moving average](#calculate-a-three-point-moving-average) - [Calculate a three point moving average with null values](#calculate-a-three-point-moving-average-with-null-values) ### Calculate a three point moving average ```js import "sampledata" sampledata.int() |> movingAverage(n: 3) ``` {{< expand-wrapper >}} {{% expand "View example input and output" %}} #### Input data | _time | _value | *tag | | -------------------- | ------- | ---- | | 2021-01-01T00:00:00Z | -2 | t1 | | 2021-01-01T00:00:10Z | 10 | t1 | | 2021-01-01T00:00:20Z | 7 | t1 | | 2021-01-01T00:00:30Z | 17 | t1 | | 2021-01-01T00:00:40Z | 15 | t1 | | 2021-01-01T00:00:50Z | 4 | t1 | | _time | _value | *tag | | -------------------- | ------- | ---- | | 2021-01-01T00:00:00Z | 19 | t2 | | 2021-01-01T00:00:10Z | 4 | t2 | | 2021-01-01T00:00:20Z | -3 | t2 | | 2021-01-01T00:00:30Z | 19 | t2 | | 2021-01-01T00:00:40Z | 13 | t2 | | 2021-01-01T00:00:50Z | 1 | t2 | #### Output data | _time | _value | *tag | | -------------------- | ------------------ | ---- | | 2021-01-01T00:00:20Z | 5 | t1 | | 2021-01-01T00:00:30Z | 11.333333333333334 | t1 | | 2021-01-01T00:00:40Z | 13 | t1 | | 2021-01-01T00:00:50Z | 12 | t1 | | _time | _value | *tag | | -------------------- | ----------------- | ---- | | 2021-01-01T00:00:20Z | 6.666666666666667 | t2 | | 2021-01-01T00:00:30Z | 6.666666666666667 | t2 | | 2021-01-01T00:00:40Z | 9.666666666666666 | t2 | | 2021-01-01T00:00:50Z | 11 | t2 | {{% /expand %}} {{< /expand-wrapper >}} ### Calculate a three point moving average with null values ```js import "sampledata" sampledata.int(includeNull: true) |> movingAverage(n: 3) ``` {{< expand-wrapper >}} {{% expand "View example input and output" %}} #### Input data | _time | _value | *tag | | -------------------- | ------- | ---- | | 2021-01-01T00:00:00Z | -2 | t1 | | 2021-01-01T00:00:10Z | | t1 | | 2021-01-01T00:00:20Z | 7 | t1 | | 2021-01-01T00:00:30Z | | t1 | | 2021-01-01T00:00:40Z | | t1 | | 2021-01-01T00:00:50Z | 4 | t1 | | _time | _value | *tag | | -------------------- | ------- | ---- | | 2021-01-01T00:00:00Z | | t2 | | 2021-01-01T00:00:10Z | 4 | t2 | | 2021-01-01T00:00:20Z | -3 | t2 | | 2021-01-01T00:00:30Z | 19 | t2 | | 2021-01-01T00:00:40Z | | t2 | | 2021-01-01T00:00:50Z | 1 | t2 | #### Output data | _time | _value | *tag | | -------------------- | ------- | ---- | | 2021-01-01T00:00:20Z | 2.5 | t1 | | 2021-01-01T00:00:30Z | 7 | t1 | | 2021-01-01T00:00:40Z | 7 | t1 | | 2021-01-01T00:00:50Z | 4 | t1 | | _time | _value | *tag | | -------------------- | ----------------- | ---- | | 2021-01-01T00:00:20Z | 0.5 | t2 | | 2021-01-01T00:00:30Z | 6.666666666666667 | t2 | | 2021-01-01T00:00:40Z | 8 | t2 | | 2021-01-01T00:00:50Z | 10 | t2 | {{% /expand %}} {{< /expand-wrapper >}}