150 lines
4.3 KiB
Markdown
150 lines
4.3 KiB
Markdown
---
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title: Find median values
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seotitle: Find median values in Flux
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list_title: Median
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description: >
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Use `median()` to return a value representing the `0.5` quantile (50th percentile) or median of input data.
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weight: 210
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menu:
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influxdb_v2:
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parent: Query with Flux
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name: Median
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influxdb/v2/tags: [query, median]
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related:
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- /influxdb/v2/query-data/flux/percentile-quantile/
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- /flux/v0/stdlib/universe/median/
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- /flux/v0/stdlib/universe/quantile/
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list_query_example: median
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---
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Use the [`median()` function](/flux/v0/stdlib/universe/median/)
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to return a value representing the `0.5` quantile (50th percentile) or median of input data.
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## Select a method for calculating the median
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Select one of the following methods to calculate the median:
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- [estimate_tdigest](#estimate_tdigest)
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- [exact_mean](#exact_mean)
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- [exact_selector](#exact_selector)
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### estimate_tdigest
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**(Default)** An aggregate method that uses a [t-digest data structure](https://github.com/tdunning/t-digest)
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to compute an accurate `0.5` quantile estimate on large data sources.
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Output tables consist of a single row containing the calculated median.
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{{< flex >}}
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{{% flex-content %}}
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**Given the following input table:**
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| _time | _value |
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|:----- | ------:|
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| 2020-01-01T00:01:00Z | 1.0 |
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| 2020-01-01T00:02:00Z | 1.0 |
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| 2020-01-01T00:03:00Z | 2.0 |
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| 2020-01-01T00:04:00Z | 3.0 |
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{{% /flex-content %}}
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{{% flex-content %}}
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**`estimate_tdigest` returns:**
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| _value |
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|:------:|
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| 1.5 |
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{{% /flex-content %}}
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{{< /flex >}}
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### exact_mean
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An aggregate method that takes the average of the two points closest to the `0.5` quantile value.
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Output tables consist of a single row containing the calculated median.
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{{< flex >}}
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{{% flex-content %}}
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**Given the following input table:**
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| _time | _value |
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|:----- | ------:|
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| 2020-01-01T00:01:00Z | 1.0 |
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| 2020-01-01T00:02:00Z | 1.0 |
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| 2020-01-01T00:03:00Z | 2.0 |
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| 2020-01-01T00:04:00Z | 3.0 |
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{{% /flex-content %}}
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{{% flex-content %}}
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**`exact_mean` returns:**
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| _value |
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|:------:|
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| 1.5 |
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{{% /flex-content %}}
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{{< /flex >}}
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### exact_selector
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A selector method that returns the data point for which at least 50% of points are less than.
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Output tables consist of a single row containing the calculated median.
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{{< flex >}}
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{{% flex-content %}}
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**Given the following input table:**
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| _time | _value |
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|:----- | ------:|
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| 2020-01-01T00:01:00Z | 1.0 |
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| 2020-01-01T00:02:00Z | 1.0 |
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| 2020-01-01T00:03:00Z | 2.0 |
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| 2020-01-01T00:04:00Z | 3.0 |
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{{% /flex-content %}}
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{{% flex-content %}}
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**`exact_selector` returns:**
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| _time | _value |
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|:----- | ------:|
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| 2020-01-01T00:02:00Z | 1.0 |
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{{% /flex-content %}}
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{{< /flex >}}
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{{% note %}}
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The examples below use the [example data variable](/influxdb/v2/query-data/flux/#example-data-variable).
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{{% /note %}}
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## Find the value that represents the median
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Use the default method, `"estimate_tdigest"`, to return all rows in a table that
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contain values in the 50th percentile of data in the table.
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```js
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data
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|> median()
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```
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## Find the average of values closest to the median
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Use the `exact_mean` method to return a single row per input table containing the
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average of the two values closest to the mathematical median of data in the table.
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```js
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data
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|> median(method: "exact_mean")
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```
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## Find the point with the median value
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Use the `exact_selector` method to return a single row per input table containing the
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value that 50% of values in the table are less than.
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```js
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data
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|> median(method: "exact_selector")
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```
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## Use median() with aggregateWindow()
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[`aggregateWindow()`](/flux/v0/stdlib/universe/aggregatewindow/)
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segments data into windows of time, aggregates data in each window into a single
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point, and then removes the time-based segmentation.
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It is primarily used to [downsample data](/influxdb/v2/process-data/common-tasks/downsample-data/).
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To specify the [median calculation method](#select-a-method-for-calculating-the-median) in `aggregateWindow()`, use the
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[full function syntax](/flux/v0/stdlib/universe/aggregatewindow/#specify-parameters-of-the-aggregate-function):
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```js
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data
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|> aggregateWindow(
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every: 5m,
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fn: (tables=<-, column) => tables |> median(method: "exact_selector"),
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)
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```
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