Find median values

Use the median() function to return a value representing the 0.5 quantile (50th percentile) or median of input data.

Select a method for calculating the median

Select one of the following methods to calculate the median:

estimate_tdigest

(Default) An aggregate method that uses a t-digest data structure to compute an accurate 0.5 quantile estimate on large data sources. Output tables consist of a single row containing the calculated median.

Given the following input table:

_time _value
2020-01-01T00:01:00Z 1.0
2020-01-01T00:02:00Z 1.0
2020-01-01T00:03:00Z 2.0
2020-01-01T00:04:00Z 3.0

estimate_tdigest returns:

_value
1.5

exact_mean

An aggregate method that takes the average of the two points closest to the 0.5 quantile value. Output tables consist of a single row containing the calculated median.

Given the following input table:

_time _value
2020-01-01T00:01:00Z 1.0
2020-01-01T00:02:00Z 1.0
2020-01-01T00:03:00Z 2.0
2020-01-01T00:04:00Z 3.0

exact_mean returns:

_value
1.5

exact_selector

A selector method that returns the data point for which at least 50% of points are less than. Output tables consist of a single row containing the calculated median.

Given the following input table:

_time _value
2020-01-01T00:01:00Z 1.0
2020-01-01T00:02:00Z 1.0
2020-01-01T00:03:00Z 2.0
2020-01-01T00:04:00Z 3.0

exact_selector returns:

_time _value
2020-01-01T00:02:00Z 1.0

The examples below use the example data variable.

Find the value that represents the median

Use the default method, "estimate_tdigest", to return all rows in a table that contain values in the 50th percentile of data in the table.

data
  |> median()

Find the average of values closest to the median

Use the exact_mean method to return a single row per input table containing the average of the two values closest to the mathematical median of data in the table.

data
  |> median(method: "exact_mean")

Find the point with the median value

Use the exact_selector method to return a single row per input table containing the value that 50% of values in the table are less than.

data
  |> median(method: "exact_selector")

Use median() with aggregateWindow()

aggregateWindow() segments data into windows of time, aggregates data in each window into a single point, and then removes the time-based segmentation. It is primarily used to downsample data.

To specify the median calculation method in aggregateWindow(), use the full function syntax:

data
  |> aggregateWindow(
    every: 5m,
    fn: (tables=<-, column) => tables |> median(method: "exact_selector")
  )

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