histogram() function

histogram() 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.

Each input table is converted into a single output table representing a single histogram. Each output table has the same group key as the corresponding input table. Columns not part of the group key are dropped. Output tables include additional columns for the upper bound and count of bins.

Function type signature
    <-tables: stream[A],
    bins: [float],
    ?column: string,
    ?countColumn: string,
    ?normalize: bool,
    ?upperBoundColumn: string,
) => stream[B] where A: Record, B: Record

For more information, see Function type signatures.



Column containing input values. Column must be of type float. Default is _value.


Column to store bin upper bounds in. Default is le.


Column to store bin counts in. Default is _value.


(Required) List of upper bounds to use when computing the histogram frequencies.

Bins should contain a bin whose bound is 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.

  • linearBins()
  • logarithmicBins()


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

Note: Normalized histograms cannot be aggregated by summing their counts.


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


Create a cumulative histogram

import "sampledata"

    |> histogram(bins: [0.0, 5.0, 10.0, 20.0])

View example input and output

Create a cumulative histogram with dynamically generated bins

import "sampledata"

    |> histogram(bins: linearBins(start: 0.0, width: 4.0, count: 3))

View example input and output

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The future of Flux

Flux is going into maintenance mode. You can continue using it as you currently are without any changes to your code.

Flux is going into maintenance mode and will not be supported in InfluxDB 3.0. This was a decision based on the broad demand for SQL and the continued growth and adoption of InfluxQL. We are continuing to support Flux for users in 1.x and 2.x so you can continue using it with no changes to your code. If you are interested in transitioning to InfluxDB 3.0 and want to future-proof your code, we suggest using InfluxQL.

For information about the future of Flux, see the following: