# Django 5.2.8 documentation

# PostgreSQL specific aggregation functions

These functions are available from the `django.contrib.postgres.aggregates` module. They are described in more detail in the PostgreSQL docs.

Note

All functions come without default aliases, so you must explicitly provide one. For example:

    >>> SomeModel.objects.aggregate(arr=ArrayAgg("somefield"))
    {'arr': [0, 1, 2]}

Common aggregate options

All aggregates have the filter keyword argument and most also have the default keyword argument.

## General-purpose aggregation functions

### `ArrayAgg`

class ArrayAgg(expression, distinct=False, filter=None, default=None, ordering=(), **extra)

  Returns a list of values, including nulls, concatenated into an array, or `default` if there are no values.

  distinct

    An optional boolean argument that determines if array values will be distinct. Defaults to `False`.

  ordering

    An optional string of a field name (with an optional `"-"` prefix which indicates descending order) or an expression (or a tuple or list of strings and/or expressions) that specifies the ordering of the elements in the result list.

    Examples:

        from django.db.models import F

        ArrayAgg("a_field", ordering="-some_field")
        ArrayAgg("a_field", ordering=F("some_field").desc())

  Changed in Django 5.0:

  In older versions, if there are no rows and `default` is not provided, `ArrayAgg` returned an empty list instead of `None`. If you need it, explicitly set `default` to `Value([])`.

### `BitAnd`

class BitAnd(expression, filter=None, default=None, **extra)

  Returns an `int` of the bitwise `AND` of all non-null input values, or `default` if all values are null.

### `BitOr`

class BitOr(expression, filter=None, default=None, **extra)

  Returns an `int` of the bitwise `OR` of all non-null input values, or `default` if all values are null.

### `BitXor`

class BitXor(expression, filter=None, default=None, **extra)

  Returns an `int` of the bitwise `XOR` of all non-null input values, or `default` if all values are null. It requires PostgreSQL 14+.

### `BoolAnd`

class BoolAnd(expression, filter=None, default=None, **extra)

  Returns `True`, if all input values are true, `default` if all values are null or if there are no values, otherwise `False`.

  Usage example:

      class Comment(models.Model):
          body = models.TextField()
          published = models.BooleanField()
          rank = models.IntegerField()

      >>> from django.db.models import Q
      >>> from django.contrib.postgres.aggregates import BoolAnd
      >>> Comment.objects.aggregate(booland=BoolAnd("published"))
      {'booland': False}
      >>> Comment.objects.aggregate(booland=BoolAnd(Q(rank__lt=100)))
      {'booland': True}

### `BoolOr`

class BoolOr(expression, filter=None, default=None, **extra)

  Returns `True` if at least one input value is true, `default` if all values are null or if there are no values, otherwise `False`.

  Usage example:

      class Comment(models.Model):
          body = models.TextField()
          published = models.BooleanField()
          rank = models.IntegerField()

      >>> from django.db.models import Q
      >>> from django.contrib.postgres.aggregates import BoolOr
      >>> Comment.objects.aggregate(boolor=BoolOr("published"))
      {'boolor': True}
      >>> Comment.objects.aggregate(boolor=BoolOr(Q(rank__gt=2)))
      {'boolor': False}

### `JSONBAgg`

class JSONBAgg(expressions, distinct=False, filter=None, default=None, ordering=(), **extra)

  Returns the input values as a `JSON` array, or `default` if there are no values. You can query the result using `key and index lookups`.

  distinct

    An optional boolean argument that determines if array values will be distinct. Defaults to `False`.

  ordering

    An optional string of a field name (with an optional `"-"` prefix which indicates descending order) or an expression (or a tuple or list of strings and/or expressions) that specifies the ordering of the elements in the result list.

    Examples are the same as for `ArrayAgg.ordering`.

  Usage example:

      class Room(models.Model):
          number = models.IntegerField(unique=True)

      class HotelReservation(models.Model):
          room = models.ForeignKey("Room", on_delete=models.CASCADE)
          start = models.DateTimeField()
          end = models.DateTimeField()
          requirements = models.JSONField(blank=True, null=True)

      >>> from django.contrib.postgres.aggregates import JSONBAgg
      >>> Room.objects.annotate(
      ...     requirements=JSONBAgg(
      ...         "hotelreservation__requirements",
      ...         ordering="-hotelreservation__start",
      ...     )
      ... ).filter(requirements__0__sea_view=True).values("number", "requirements")
      <QuerySet [{'number': 102, 'requirements': [
          {'parking': False, 'sea_view': True, 'double_bed': False},
          {'parking': True, 'double_bed': True}
      ]}]>

  Changed in Django 5.0:

  In older versions, if there are no rows and `default` is not provided, `JSONBAgg` returned an empty list instead of `None`. If you need it, explicitly set `default` to `Value([])`.

### `StringAgg`

class StringAgg(expression, delimiter, distinct=False, filter=None, default=None, ordering=())

  Returns the input values concatenated into a string, separated by the `delimiter` string, or `default` if there are no values.

  delimiter

    Required argument. Needs to be a string.

  distinct

    An optional boolean argument that determines if concatenated values will be distinct. Defaults to `False`.

  ordering

    An optional string of a field name (with an optional `"-"` prefix which indicates descending order) or an expression (or a tuple or list of strings and/or expressions) that specifies the ordering of the elements in the result string.

    Examples are the same as for `ArrayAgg.ordering`.

  Usage example:

      class Publication(models.Model):
          title = models.CharField(max_length=30)

      class Article(models.Model):
          headline = models.CharField(max_length=100)
          publications = models.ManyToManyField(Publication)

      >>> article = Article.objects.create(headline="NASA uses Python")
      >>> article.publications.create(title="The Python Journal")
      <Publication: Publication object (1)>
      >>> article.publications.create(title="Science News")
      <Publication: Publication object (2)>
      >>> from django.contrib.postgres.aggregates import StringAgg
      >>> Article.objects.annotate(
      ...     publication_names=StringAgg(
      ...         "publications__title",
      ...         delimiter=", ",
      ...         ordering="publications__title",
      ...     )
      ... ).values("headline", "publication_names")
      <QuerySet [{
          'headline': 'NASA uses Python', 'publication_names': 'Science News, The Python Journal'
      }]>

  Changed in Django 5.0:

  In older versions, if there are no rows and `default` is not provided, `StringAgg` returned an empty string instead of `None`. If you need it, explicitly set `default` to `Value("")`.

## Aggregate functions for statistics

### `y` and `x`

The arguments `y` and `x` for all these functions can be the name of a field or an expression returning a numeric data. Both are required.

### `Corr`

class Corr(y, x, filter=None, default=None)

  Returns the correlation coefficient as a `float`, or `default` if there aren’t any matching rows.

### `CovarPop`

class CovarPop(y, x, sample=False, filter=None, default=None)

  Returns the population covariance as a `float`, or `default` if there aren’t any matching rows.

  sample

    Optional. By default `CovarPop` returns the general population covariance. However, if `sample=True`, the return value will be the sample population covariance.

### `RegrAvgX`

class RegrAvgX(y, x, filter=None, default=None)

  Returns the average of the independent variable (`sum(x)/N`) as a `float`, or `default` if there aren’t any matching rows.

### `RegrAvgY`

class RegrAvgY(y, x, filter=None, default=None)

  Returns the average of the dependent variable (`sum(y)/N`) as a `float`, or `default` if there aren’t any matching rows.

### `RegrCount`

class RegrCount(y, x, filter=None)

  Returns an `int` of the number of input rows in which both expressions are not null.

  Note

  The `default` argument is not supported.

### `RegrIntercept`

class RegrIntercept(y, x, filter=None, default=None)

  Returns the y-intercept of the least-squares-fit linear equation determined by the `(x, y)` pairs as a `float`, or `default` if there aren’t any matching rows.

### `RegrR2`

class RegrR2(y, x, filter=None, default=None)

  Returns the square of the correlation coefficient as a `float`, or `default` if there aren’t any matching rows.

### `RegrSlope`

class RegrSlope(y, x, filter=None, default=None)

  Returns the slope of the least-squares-fit linear equation determined by the `(x, y)` pairs as a `float`, or `default` if there aren’t any matching rows.

### `RegrSXX`

class RegrSXX(y, x, filter=None, default=None)

  Returns `sum(x^2) - sum(x)^2/N` (“sum of squares” of the independent variable) as a `float`, or `default` if there aren’t any matching rows.

### `RegrSXY`

class RegrSXY(y, x, filter=None, default=None)

  Returns `sum(x*y) - sum(x) * sum(y)/N` (“sum of products” of independent times dependent variable) as a `float`, or `default` if there aren’t any matching rows.

### `RegrSYY`

class RegrSYY(y, x, filter=None, default=None)

  Returns `sum(y^2) - sum(y)^2/N` (“sum of squares” of the dependent variable) as a `float`, or `default` if there aren’t any matching rows.

## Usage examples

We will use this example table:

    | FIELD1 | FIELD2 | FIELD3 |
    |--------|--------|--------|
    |    foo |      1 |     13 |
    |    bar |      2 | (null) |
    |   test |      3 |     13 |

Here’s some examples of some of the general-purpose aggregation functions:

    >>> TestModel.objects.aggregate(result=StringAgg("field1", delimiter=";"))
    {'result': 'foo;bar;test'}
    >>> TestModel.objects.aggregate(result=ArrayAgg("field2"))
    {'result': [1, 2, 3]}
    >>> TestModel.objects.aggregate(result=ArrayAgg("field1"))
    {'result': ['foo', 'bar', 'test']}

The next example shows the usage of statistical aggregate functions. The underlying math will be not described (you can read about this, for example, at wikipedia):

    >>> TestModel.objects.aggregate(count=RegrCount(y="field3", x="field2"))
    {'count': 2}
    >>> TestModel.objects.aggregate(
    ...     avgx=RegrAvgX(y="field3", x="field2"), avgy=RegrAvgY(y="field3", x="field2")
    ... )
    {'avgx': 2, 'avgy': 13}