experimental.histogram() function

The experimental.histogram() function is subject to change at any time. By using this function, you accept the risks of experimental functions.

The experimental.histogram() function approximates the cumulative distribution of a dataset by counting data frequencies for a list of bins. A bin is defined by an upper bound where all data points that are less than or equal to the bound are counted in the bin. Bin counts are cumulative.

import "experimental"

    bins: [50.0, 75.0, 90.0],
    normalize: false,

Output schema

experimental.histogram() outputs a single table for each input table. Each output table represents a unique histogram. Output tables have the same group key as the corresponding input table.

The function does the following:

  • Drops columns that are not part of the group key.
  • Adds an le column to store upper bound values.
  • Stores bin counts in the _value column.



(Required) A list of upper bounds to use when computing the histogram frequencies, including the maximum value of the data set. This value can be set to positive infinity if no maximum is known.

Bin helper functions

The following helper functions can be used to generated bins.



Convert count values into frequency values between 0 and 1. Default is false.

Normalized histograms cannot be aggregated by summing their counts.


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


Histogram with dynamically generated bins

import "experimental"

    |> experimental.histogram(bins: linearBins(start: 0.0, width: 20.0, count: 5))
Input data
_time host _value
2021-01-01T00:00:00Z host1 33.4
2021-01-01T00:01:00Z host1 57.2
2021-01-01T00:02:00Z host1 78.1
2021-01-01T00:03:00Z host1 79.6
_time host _value
2021-01-01T00:00:00Z host2 10.3
2021-01-01T00:01:00Z host2 19.8
2021-01-01T00:02:00Z host2 54.6
2021-01-01T00:03:00Z host2 56.9
Output data
host le _value
host1 0 0
host1 20 0
host1 40 1
host1 60 2
host1 80 4
host1 +Inf 4
host le _value
host2 0 0
host2 20 2
host2 40 2
host2 60 4
host2 80 4
host2 +Inf 4

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