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median() function

content/flux/v0/stdlib/universe/median.md

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median() returns the median _value of an input table or all non-null records in the input table with values that fall within the 0.5 quantile (50th percentile).

Function behavior

median() acts as an aggregate or selector transformation depending on the specified method.

  • Aggregate: When using the estimate_tdigest or exact_mean methods, median() acts as an aggregate transformation and outputs the average of non-null records with values that fall within the 0.5 quantile (50th percentile).
  • Selector: When using the exact_selector method, meidan() acts as a selector selector transformation and outputs the non-null record with the value that represents the 0.5 quantile (50th percentile).
Function type signature
js
(<-tables: stream[A], ?column: string, ?compression: float, ?method: string) => stream[A] where A: Record

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

Parameters

column

Column to use to compute the median. Default is _value.

method

Computation method. Default is estimate_tdigest.

Available methods:

  • estimate_tdigest: Aggregate method that uses a t-digest data structure to compute an accurate median estimate on large data sources.
  • exact_mean: Aggregate method that takes the average of the two points closest to the median value.
  • exact_selector: Selector method that returns the row with the value for which at least 50% of points are less than.

compression

Number of centroids to use when compressing the dataset. Default is 0.0.

A larger number produces a more accurate result at the cost of increased memory requirements.

tables

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

Examples

Use median as an aggregate transformation

js
import "sampledata"

sampledata.float()
    |> median()

{{< expand-wrapper >}} {{% expand "View example input and output" %}}

Input data

_time*tag_value
2021-01-01T00:00:00Zt1-2.18
2021-01-01T00:00:10Zt110.92
2021-01-01T00:00:20Zt17.35
2021-01-01T00:00:30Zt117.53
2021-01-01T00:00:40Zt115.23
2021-01-01T00:00:50Zt14.43
_time*tag_value
2021-01-01T00:00:00Zt219.85
2021-01-01T00:00:10Zt24.97
2021-01-01T00:00:20Zt2-3.75
2021-01-01T00:00:30Zt219.77
2021-01-01T00:00:40Zt213.86
2021-01-01T00:00:50Zt21.86

Output data

*tag_value
t19.135
*tag_value
t29.415

{{% /expand %}} {{< /expand-wrapper >}}

Use median as a selector transformation

js
import "sampledata"

sampledata.float()
    |> median(method: "exact_selector")

{{< expand-wrapper >}} {{% expand "View example input and output" %}}

Input data

_time*tag_value
2021-01-01T00:00:00Zt1-2.18
2021-01-01T00:00:10Zt110.92
2021-01-01T00:00:20Zt17.35
2021-01-01T00:00:30Zt117.53
2021-01-01T00:00:40Zt115.23
2021-01-01T00:00:50Zt14.43
_time*tag_value
2021-01-01T00:00:00Zt219.85
2021-01-01T00:00:10Zt24.97
2021-01-01T00:00:20Zt2-3.75
2021-01-01T00:00:30Zt219.77
2021-01-01T00:00:40Zt213.86
2021-01-01T00:00:50Zt21.86

Output data

_time*tag_value
2021-01-01T00:00:20Zt17.35
_time*tag_value
2021-01-01T00:00:10Zt24.97

{{% /expand %}} {{< /expand-wrapper >}}