docs-v2/content/flux/v0/stdlib/universe/tripleema.md

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---
title: tripleEMA() function
description: >
`tripleEMA()` returns the triple exponential moving average (TEMA) of values in
the `_value` column.
menu:
flux_v0_ref:
name: tripleEMA
parent: universe
identifier: universe/tripleEMA
weight: 101
flux/v0/tags: [transformations]
introduced: 0.38.0
---
<!------------------------------------------------------------------------------
IMPORTANT: This page was generated from comments in the Flux source code. Any
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To make updates to this documentation, update the function comments above the
function definition in the Flux source code:
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Contributing to Flux: https://github.com/influxdata/flux#contributing
Fluxdoc syntax: https://github.com/influxdata/flux/blob/master/docs/fluxdoc.md
------------------------------------------------------------------------------->
`tripleEMA()` returns the triple exponential moving average (TEMA) of values in
the `_value` column.
`tripleEMA` uses `n` number of points to calculate the TEMA, giving more
weight to recent data with less lag than `exponentialMovingAverage()` and
`doubleEMA()`.
#### Triple exponential moving average rules
- A triple exponential moving average is defined as `tripleEMA = (3 * EMA_1) - (3 * EMA_2) + EMA_3`.
- `EMA_1` is the exponential moving average of the original data.
- `EMA_2` is the exponential moving average of `EMA_1`.
- `EMA_3` is the exponential moving average of `EMA_2`.
- A true triple exponential moving average requires at least requires at least
`3 * n - 2` values. If not enough values exist to calculate the TEMA, it
returns a `NaN` value.
- `tripleEMA()` inherits all `exponentialMovingAverage()` rules.
##### Function type signature
```js
(<-tables: stream[{A with _value: B}], n: int) => stream[C] where B: Numeric, C: Record
```
{{% caption %}}
For more information, see [Function type signatures](/flux/v0/function-type-signatures/).
{{% /caption %}}
## Parameters
### n
({{< req >}})
Number of points to use in the calculation.
### tables
Input data. Default is piped-forward data (`<-`).
## Examples
### Calculate a three point triple exponential moving average
```js
import "sampledata"
sampledata.int()
|> tripleEMA(n: 3)
```
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{{% 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 |
| -------------------- | ------------------ | ---- |
| 2021-01-01T00:00:50Z | 7.6250000000000036 | t1 |
| _time | _value | *tag |
| -------------------- | ------------------ | ---- |
| 2021-01-01T00:00:50Z | 4.0729166666666625 | t2 |
{{% /expand %}}
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