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# $median (aggregation)

## Definition

`$median`

*New in version 7.0*.Returns an approximation of the median, the 50th percentile, as a scalar value.

You can use

`$median`

as an accumulator in the`$group`

stage or as an aggegation expression.

## Syntax

The syntax for `$median`

is:

{ $median: { input: <number>, method: <string> } }

## Command Fields

`$median`

takes the following fields:

Field | Type | Necessity | Description |
---|---|---|---|

`input` | Expression | Required | `$median` calculates the 50th percentile value of this data.
`input` must be a field name or an expression that evaluates to
a numeric type. If the expression cannot be converted to a
numeric type, the `$median` calculation ignores it. |

`method` | String | Required | The method that `mongod` uses to calculate the 50th percentile
value. The method must be `'approximate'` . |

## Behavior

You can use `$median`

in:

`$group`

stages as an accumulator`$setWindowFields`

stages as an accumulator`$project`

stages as an aggregation expression

`$median`

has the following characteristics as an accumulator, it:

Calculates a single result for all the documents in the stage.

Uses the t-digest algorithm to calculate approximate, percentile based metrics.

Uses approximate methods to scale to large volumes of data.

`$median`

has the following characteristics as an aggregation
expression, it:

Accepts an array as input

Calculates a separate result for each input document

### Type of Operation

In a `$group`

stage, `$median`

is an accumulator and calculates
a value for all documents in the window.

In a `$project`

stage, `$median`

is an aggregation expression and
calculates values for each document.

In `$setWindowFields`

stages, `$median`

returns a result
for each document like an aggregation expression, but the results are
computed over groups of documents like an accumulator.

### Calculation Considerations

In `$group`

stages, `$median`

always uses an approximate
calculation method.

In `$project`

stages, `$median`

might use the discrete
calculation method even when the approximate method is specified.

In `$setWindowFields`

stages, the workload determines the calculation
method that `$median`

uses.

The computed percentiles `$median`

returns might vary, even on the
same datasets. This is because the algorithm calculates approximate
values.

Duplicate samples can cause ambiguity. If there are a large number of duplicates, the percentile values may not represent the actual sample distribution. Consider a data set where all the samples are the same. All of the values in the data set fall at or below any percentile. A "50th percentile" value would actually represent either 0 or 100 percent of the samples.

### Array Input

If you use `$median`

as an aggregation expression in a
`$project`

stage, you can use an array as input.
`$median`

ignores non-numeric array values.

The syntax is:

{ $median: { input: [ <expression1, <expression2>, ..., <expressionN> ], method: <string> } }

### Window Functions

A window function lets you calculate results over a moving "window" of
neighboring documents. As each document passes though the pipeline, the
`$setWindowFields`

stage:

Recomputes the set of documents in the current window

calculates a value for all documents in the set

returns a single value for that document

You can use `$median`

in a `$setWindowFields`

stage to calculate
rolling statistics for time series or
other related data.

When you use `$median`

in a `$setWindowField`

stage, the
`input`

value must be a field name. If you enter an array instead of a
field name, the operation fails.

## Examples

The following examples use the `testScores`

collection. Create the
collection:

db.testScores.insertMany( [ { studentId: "2345", test01: 62, test02: 81, test03: 80 }, { studentId: "2356", test01: 60, test02: 83, test03: 79 }, { studentId: "2358", test01: 67, test02: 82, test03: 78 }, { studentId: "2367", test01: 64, test02: 72, test03: 77 }, { studentId: "2369", test01: 60, test02: 53, test03: 72 } ] )

### Use `$median`

as an Accumulator

Create an accumulator that calculates the median value:

db.testScores.aggregate( [ { $group: { _id: null, test01_median: { $median: { input: "$test01", method: 'approximate' } } } } ] )

Output:

{ _id: null, test01_median: 62 }

The `_id`

field value is `null`

so `$group`

selects all the
documents in the collection.

The `$median`

accumulator takes its input from the `test01`

field. `$median`

calculates the median value for the field, `62`

in this example.

### Use `$median`

in a `$project`

Stage

In a `$group`

stage, `$median`

is an accumulator and calculates
a single value for all documents. In a `$project`

stage,
`$median`

is an aggregation expression and calculates values for
each document.

You can use a field name or an array as input in a `$project`

stage.

db.testScores.aggregate( [ { $project: { _id: 0, studentId: 1, testMedians: { $median: { input: [ "$test01", "$test02", "$test03" ], method: 'approximate' } } } } ] )

Output:

{ studentId: '2345', testMedians: 80 }, { studentId: '2356', testMedians: 79 }, { studentId: '2358', testMedians: 78 }, { studentId: '2367', testMedians: 72 }, { studentId: '2369', testMedians: 60 }

When `$median`

is an aggregation expression there is a result for
each `studentId`

.

### Use `$median`

in a `$setWindowField`

Stage

To base your percentile values on local data trends, use `$median`

in a `$setWindowField`

aggregation pipeline stage.

This example creates a window to filter scores:

db.testScores.aggregate( [ { $setWindowFields: { sortBy: { test01: 1 }, output: { test01_median: { $median: { input: "$test01", method: 'approximate' }, window: { range: [ -3, 3 ] } } } } }, { $project: { _id: 0, studentId: 1, test01_median: 1 } } ] )

Output:

{ studentId: '2356', test01_median: 60 }, { studentId: '2369', test01_median: 60 }, { studentId: '2345', test01_median: 60 }, { studentId: '2367', test01_median: 64 }, { studentId: '2358', test01_median: 64 }

In this example, the median calculation for each document also incorporates data from the three documents before and after it.

## Learn More

The `$percentile`

operator is a more general
version of the `$median`

operator that allows you to set one or
more percentile values.

For more information on window functions, see:
`$setWindowFields`

.