Documentation

exponentialMovingAverage() function

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

For more information, see 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

import "sampledata"

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

View example input and output

Calculate a three point exponential moving average with null values

import "sampledata"

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

View example input and output


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The future of Flux

Flux is going into maintenance mode. You can continue using it as you currently are without any changes to your code.

Flux is going into maintenance mode and will not be supported in InfluxDB 3.0. This was a decision based on the broad demand for SQL and the continued growth and adoption of InfluxQL. We are continuing to support Flux for users in 1.x and 2.x so you can continue using it with no changes to your code. If you are interested in transitioning to InfluxDB 3.0 and want to future-proof your code, we suggest using InfluxQL.

For information about the future of Flux, see the following: