190 lines
5.3 KiB
Markdown
190 lines
5.3 KiB
Markdown
---
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title: median() function
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description: >
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`median()` returns the median `_value` of an input table or all non-null records
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in the input table with values that fall within the 0.5 quantile (50th percentile).
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menu:
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flux_v0_ref:
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name: median
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parent: universe
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identifier: universe/median
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weight: 101
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flux/v0/tags: [transformations, aggregates, selectors]
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introduced: 0.7.0
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---
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<!------------------------------------------------------------------------------
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IMPORTANT: This page was generated from comments in the Flux source code. Any
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edits made directly to this page will be overwritten the next time the
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documentation is generated.
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To make updates to this documentation, update the function comments above the
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function definition in the Flux source code:
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https://github.com/influxdata/flux/blob/master/stdlib/universe/universe.flux#L3994-L3996
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Contributing to Flux: https://github.com/influxdata/flux#contributing
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Fluxdoc syntax: https://github.com/influxdata/flux/blob/master/docs/fluxdoc.md
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------------------------------------------------------------------------------->
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`median()` returns the median `_value` of an input table or all non-null records
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in the input table with values that fall within the 0.5 quantile (50th percentile).
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### Function behavior
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`median()` acts as an aggregate or selector transformation depending on the
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specified `method`.
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- **Aggregate**: When using the `estimate_tdigest` or `exact_mean` methods,
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`median()` acts as an aggregate transformation and outputs the average of
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non-null records with values that fall within the 0.5 quantile (50th percentile).
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- **Selector**: When using the `exact_selector` method, `meidan()` acts as
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a selector selector transformation and outputs the non-null record with the
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value that represents the 0.5 quantile (50th percentile).
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##### Function type signature
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```js
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(<-tables: stream[A], ?column: string, ?compression: float, ?method: string) => stream[A] where A: Record
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```
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{{% caption %}}
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For more information, see [Function type signatures](/flux/v0/function-type-signatures/).
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{{% /caption %}}
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## Parameters
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### column
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Column to use to compute the median. Default is `_value`.
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### method
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Computation method. Default is `estimate_tdigest`.
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**Available methods**:
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- **estimate_tdigest**: Aggregate method that uses a
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[t-digest data structure](https://github.com/tdunning/t-digest) to
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compute an accurate median estimate on large data sources.
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- **exact_mean**: Aggregate method that takes the average of the two
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points closest to the median value.
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- **exact_selector**: Selector method that returns the row with the value
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for which at least 50% of points are less than.
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### compression
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Number of centroids to use when compressing the dataset.
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Default is `0.0`.
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A larger number produces a more accurate result at the cost of increased
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memory requirements.
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### tables
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Input data. Default is piped-forward data (`<-`).
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## Examples
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- [Use median as an aggregate transformation](#use-median-as-an-aggregate-transformation)
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- [Use median as a selector transformation](#use-median-as-a-selector-transformation)
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### Use median as an aggregate transformation
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```js
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import "sampledata"
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sampledata.float()
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|> median()
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```
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{{< expand-wrapper >}}
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{{% expand "View example input and output" %}}
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#### Input data
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| _time | *tag | _value |
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| -------------------- | ---- | ------- |
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| 2021-01-01T00:00:00Z | t1 | -2.18 |
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| 2021-01-01T00:00:10Z | t1 | 10.92 |
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| 2021-01-01T00:00:20Z | t1 | 7.35 |
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| 2021-01-01T00:00:30Z | t1 | 17.53 |
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| 2021-01-01T00:00:40Z | t1 | 15.23 |
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| 2021-01-01T00:00:50Z | t1 | 4.43 |
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| _time | *tag | _value |
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| -------------------- | ---- | ------- |
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| 2021-01-01T00:00:00Z | t2 | 19.85 |
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| 2021-01-01T00:00:10Z | t2 | 4.97 |
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| 2021-01-01T00:00:20Z | t2 | -3.75 |
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| 2021-01-01T00:00:30Z | t2 | 19.77 |
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| 2021-01-01T00:00:40Z | t2 | 13.86 |
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| 2021-01-01T00:00:50Z | t2 | 1.86 |
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#### Output data
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| *tag | _value |
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| ---- | ------- |
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| t1 | 9.135 |
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| *tag | _value |
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| ---- | ------- |
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| t2 | 9.415 |
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{{% /expand %}}
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{{< /expand-wrapper >}}
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### Use median as a selector transformation
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```js
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import "sampledata"
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sampledata.float()
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|> median(method: "exact_selector")
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```
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{{< expand-wrapper >}}
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{{% expand "View example input and output" %}}
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#### Input data
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| _time | *tag | _value |
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| -------------------- | ---- | ------- |
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| 2021-01-01T00:00:00Z | t1 | -2.18 |
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| 2021-01-01T00:00:10Z | t1 | 10.92 |
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| 2021-01-01T00:00:20Z | t1 | 7.35 |
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| 2021-01-01T00:00:30Z | t1 | 17.53 |
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| 2021-01-01T00:00:40Z | t1 | 15.23 |
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| 2021-01-01T00:00:50Z | t1 | 4.43 |
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| _time | *tag | _value |
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| -------------------- | ---- | ------- |
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| 2021-01-01T00:00:00Z | t2 | 19.85 |
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| 2021-01-01T00:00:10Z | t2 | 4.97 |
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| 2021-01-01T00:00:20Z | t2 | -3.75 |
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| 2021-01-01T00:00:30Z | t2 | 19.77 |
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| 2021-01-01T00:00:40Z | t2 | 13.86 |
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| 2021-01-01T00:00:50Z | t2 | 1.86 |
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#### Output data
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| _time | *tag | _value |
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| -------------------- | ---- | ------- |
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| 2021-01-01T00:00:20Z | t1 | 7.35 |
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| _time | *tag | _value |
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| -------------------- | ---- | ------- |
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| 2021-01-01T00:00:10Z | t2 | 4.97 |
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{{% /expand %}}
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{{< /expand-wrapper >}}
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