These functions are available from the django.contrib.postgres.aggregates
module. They are described in more detail in the PostgreSQL docs.
注解
All functions come without default aliases, so you must explicitly provide one. For example:
>>> SomeModel.objects.aggregate(arr=ArrayAgg('somefield'))
{'arr': [0, 1, 2]}
ArrayAgg
PArrayAgg
(expression, distinct=False, filter=None, ordering=(), **extra)[源代码]PReturns a list of values, including nulls, concatenated into an array.
distinct
PAn optional boolean argument that determines if array values
will be distinct. Defaults to False
.
ordering
PAn 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.
举例:
'some_field'
'-some_field'
from django.db.models import F
F('some_field').desc()
BitAnd
PBitOr
PBoolAnd
PBoolOr
PJSONBAgg
PStringAgg
PStringAgg
(expression, delimiter, distinct=False, filter=None, ordering=())[源代码]PReturns the input values concatenated into a string, separated by
the delimiter
string.
delimiter
PRequired argument. Needs to be a string.
distinct
PAn optional boolean argument that determines if concatenated values
will be distinct. Defaults to False
.
ordering
PAn 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
.
y
and x
PThe 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
PCovarPop
PCovarPop
(y, x, sample=False, filter=None)[源代码]PReturns the population covariance as a float
, or None
if there
aren't any matching rows.
包含一个可选参数:
sample
PBy default CovarPop
returns the general population covariance.
However, if sample=True
, the return value will be the sample
population covariance.
RegrAvgX
PRegrAvgY
PRegrCount
PRegrIntercept
PRegrR2
PRegrSlope
PRegrSXX
PRegrSXY
PWe 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}
8月 23, 2019