---
title: exponentialMovingAverage() function
description: exponentialMovingAverage() calculates the exponential moving average of n number of values in the _value column giving more weight to more recent data.
url: https://docs.influxdata.com/flux/v0/stdlib/universe/exponentialmovingaverage/
estimated_tokens: 1609
product: Flux
version: v0
publisher: InfluxData
canonical: https://docs.influxdata.com/flux/v0/stdlib/universe/exponentialmovingaverage/
date: '2024-04-08T16:01:02-06:00'
lastmod: '2024-04-08T16:01:02-06:00'
---

* Flux 0.37.0+

InfluxDB support

`exponentialMovingAverage()` calculates the exponential moving average of `n`number of values in the `_value` column giving more weight to more recent data.

### Exponential moving average rules

* The first value of an exponential moving average over `n` values is the algebraic mean of `n` values.
* Subsequent values are calculated as `y(t) = x(t) * k + y(t-1) * (1 - k)`, where:
  * `y(t)` is the exponential moving average at time `t`.
  * `x(t)` is the value at time `t`.
  * `k = 2 / (1 + n)`.

* The average over a period populated by only `null` values is `null`.
* Exponential moving averages skip `null` values.

##### Function type signature

```js
(<-tables: stream[{A with _value: B}], n: int) => stream[{A with _value: B}] where B: Numeric
```

For more information, see [Function type signatures](/flux/v0/function-type-signatures/).

## Parameters

### n

(Required)
Number of values to average.

### tables

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

## Examples

* [Calculate a three point exponential moving average](#calculate-a-three-point-exponential-moving-average)
* [Calculate a three point exponential moving average with null values](#calculate-a-three-point-exponential-moving-average-with-null-values)

### Calculate a three point exponential moving average

```js
import "sampledata"

sampledata.int()
    |> exponentialMovingAverage(n: 3)
```

[](#view-example-input-and-output)

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   | t1  |
|2021-01-01T00:00:40Z|  13   | t1  |
|2021-01-01T00:00:50Z|  8.5  | t1  |

|       \_time       |     \_value      |\*tag|
|--------------------|------------------|-----|
|2021-01-01T00:00:20Z|6.666666666666667 | t2  |
|2021-01-01T00:00:30Z|12.833333333333334| t2  |
|2021-01-01T00:00:40Z|12.916666666666668| t2  |
|2021-01-01T00:00:50Z|6.958333333333334 | t2  |

### Calculate a three point exponential moving average with null values

```js
import "sampledata"

sampledata.int(includeNull: true)
    |> exponentialMovingAverage(n: 3)
```

[](#view-example-input-and-output)

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|  2.5  | t1  |
|2021-01-01T00:00:40Z|  2.5  | t1  |
|2021-01-01T00:00:50Z| 3.25  | t1  |

|       \_time       |\_value|\*tag|
|--------------------|-------|-----|
|2021-01-01T00:00:20Z|  0.5  | t2  |
|2021-01-01T00:00:30Z| 9.75  | t2  |
|2021-01-01T00:00:40Z| 9.75  | t2  |
|2021-01-01T00:00:50Z| 5.375 | t2  |

#### Related

* [movingAverage() function](/flux/v0/stdlib/universe/movingaverage/)
* [timedMovingAverage() function](/flux/v0/stdlib/universe/timedmovingaverage/)
* [doubleEMA() function](/flux/v0/stdlib/universe/doubleema/)
* [tripleEMA() function](/flux/v0/stdlib/universe/tripleema/)
* [InfluxQL EXPONENTIAL\_MOVING\_AVERAGE()](/influxdb/v1/query_language/functions/#exponential-moving-average)

[transformations](/flux/v0/tags/transformations/)
| _time | _value | *tag |
| --- | --- | --- |
| _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 |
| --- | --- | --- |
| _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 |

| _time | _value | *tag |
| --- | --- | --- |
| _time | _value | *tag |
| 2021-01-01T00:00:20Z | 5 | t1 |
| 2021-01-01T00:00:30Z | 11 | t1 |
| 2021-01-01T00:00:40Z | 13 | t1 |
| 2021-01-01T00:00:50Z | 8.5 | t1 |

| _time | _value | *tag |
| --- | --- | --- |
| _time | _value | *tag |
| 2021-01-01T00:00:20Z | 6.666666666666667 | t2 |
| 2021-01-01T00:00:30Z | 12.833333333333334 | t2 |
| 2021-01-01T00:00:40Z | 12.916666666666668 | t2 |
| 2021-01-01T00:00:50Z | 6.958333333333334 | t2 |

| _time | _value | *tag |
| --- | --- | --- |
| _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 |
| --- | --- | --- |
| _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 |

| _time | _value | *tag |
| --- | --- | --- |
| _time | _value | *tag |
| 2021-01-01T00:00:20Z | 2.5 | t1 |
| 2021-01-01T00:00:30Z | 2.5 | t1 |
| 2021-01-01T00:00:40Z | 2.5 | t1 |
| 2021-01-01T00:00:50Z | 3.25 | t1 |

| _time | _value | *tag |
| --- | --- | --- |
| _time | _value | *tag |
| 2021-01-01T00:00:20Z | 0.5 | t2 |
| 2021-01-01T00:00:30Z | 9.75 | t2 |
| 2021-01-01T00:00:40Z | 9.75 | t2 |
| 2021-01-01T00:00:50Z | 5.375 | t2 |