# Aggregating functions

To calculate aggregated data, Cypher offers aggregation, analogous to SQL’s `GROUP BY`.

Aggregating functions take a set of values and calculate an aggregated value over them. Examples are `avg()` that calculates the average of multiple numeric values, or `min()` that finds the smallest numeric or string value in a set of values. When we say below that an aggregating function operates on a set of values, we mean these to be the result of the application of the inner expression (such as `n.age`) to all the records within the same aggregation group.

Aggregation can be computed over all the matching paths, or it can be further divided by introducing grouping keys. These are non-aggregate expressions, that are used to group the values going into the aggregate functions.

Assume we have the following return statement:

``RETURN n, count(*)``

We have two return expressions: `n`, and `count()`. The first, `n`, is not an aggregate function, and so it will be the grouping key. The latter, `count(``)` is an aggregate expression. The matching paths will be divided into different buckets, depending on the grouping key. The aggregate function will then be run on these buckets, calculating an aggregate value per bucket.

To use aggregations to sort the result set, the aggregation must be included in the `RETURN` to be used in the `ORDER BY`.

The `DISTINCT` operator works in conjunction with aggregation. It is used to make all values unique before running them through an aggregate function. More information about `DISTINCT` may be found here.

Functions:

The following graph is used for the examples below:

## 1. avg() - Numeric values

`avg()` returns the average of a set of numeric values.

Syntax: `avg(expression)`

Returns:

 Either an Integer or a Float, depending on the values returned by `expression` and whether or not the calculation overflows.

Arguments:

Name Description

`expression`

An expression returning a set of numeric values.

Considerations:

 Any `null` values are excluded from the calculation. `avg(null)` returns `null`.
Query
``````MATCH (n:Person)
RETURN avg(n.age)``````

The average of all the values in the property `age` is returned.

Table 1. Result
avg(n.age)

`30.0`

1 row

## 2. avg() - Durations

`avg()` returns the average of a set of Durations.

Syntax: `avg(expression)`

Returns:

 A Duration.

Arguments:

Name Description

`expression`

An expression returning a set of Durations.

Considerations:

 Any `null` values are excluded from the calculation. `avg(null)` returns `null`.
Query
``````UNWIND [duration('P2DT3H'), duration('PT1H45S')] AS dur
RETURN avg(dur)``````

The average of the two supplied Durations is returned.

Table 2. Result
avg(dur)

`P1DT2H22.5S`

1 row

## 3. collect()

`collect()` returns a list containing the values returned by an expression. Using this function aggregates data by amalgamating multiple records or values into a single list.

Syntax: `collect(expression)`

Returns:

 A list containing heterogeneous elements; the types of the elements are determined by the values returned by `expression`.

Arguments:

Name Description

`expression`

An expression returning a set of values.

Considerations:

 Any `null` values are ignored and will not be added to the list. `collect(null)` returns an empty list.
Query
``````MATCH (n:Person)
RETURN collect(n.age)``````

All the values are collected and returned in a single list.

Table 3. Result
collect(n.age)

`[13,33,44]`

1 row

## 4. count()

`count()` returns the number of values or rows, and appears in two variants:

• `count(*)` returns the number of matching rows, and

• `count(expr)` returns the number of non-`null` values returned by an expression.

Syntax: `count(expression)`

Returns:

 An Integer.

Arguments:

Name Description

`expression`

An expression.

Considerations:

 `count(*)` includes rows returning `null`. `count(expr)` ignores `null` values. `count(null)` returns `0`.

### 4.1. Using `count(*)` to return the number of nodes

`count(*)` can be used to return the number of nodes; for example, the number of nodes connected to some node `n`.

Query
``````MATCH (n { name: 'A' })-->(x)
RETURN labels(n), n.age, count(*)``````

The labels and `age` property of the start node `n` and the number of nodes related to `n` are returned.

Table 4. Result
labels(n) n.age count(*)

`["Person"]`

`13`

`3`

1 row

### 4.2. Using `count(*)` to group and count relationship types

`count(*)` can be used to group relationship types and return the number.

Query
``````MATCH (n { name: 'A' })-[r]->()
RETURN type(r), count(*)``````

The relationship types and their group count are returned.

Table 5. Result
type(r) count(*)

`"KNOWS"`

`3`

1 row

### 4.3. Using `count(expression)` to return the number of values

Instead of simply returning the number of rows with `count(*)`, it may be more useful to return the actual number of values returned by an expression.

Query
``````MATCH (n { name: 'A' })-->(x)
RETURN count(x)``````

The number of nodes connected to the start node is returned.

Table 6. Result
count(x)

`3`

1 row

### 4.4. Counting non-`null` values

`count(expression)` can be used to return the number of non-`null` values returned by the expression.

Query
``````MATCH (n:Person)
RETURN count(n.age)``````

The number of `:Person` nodes having an `age` property is returned.

Table 7. Result
count(n.age)

`3`

1 row

### 4.5. Counting with and without duplicates

In this example we are trying to find all our friends of friends, and count them:

• The first aggregate function, `count(DISTINCT friend_of_friend)`, will only count a `friend_of_friend` once, as `DISTINCT` removes the duplicates.

• The second aggregate function, `count(friend_of_friend)`, will consider the same `friend_of_friend` multiple times.

Query
``````MATCH (me:Person)-->(friend:Person)-->(friend_of_friend:Person)
WHERE me.name = 'A'
RETURN count(DISTINCT friend_of_friend), count(friend_of_friend)``````

Both `B` and `C` know `D` and thus `D` will get counted twice when not using `DISTINCT`.

Table 8. Result
count(DISTINCT friend_of_friend) count(friend_of_friend)

`1`

`2`

1 row

## 5. max()

`max()` returns the maximum value in a set of values.

Syntax: `max(expression)`

Returns:

 A property type, or a list, depending on the values returned by `expression`.

Arguments:

Name Description

`expression`

An expression returning a set containing any combination of property types and lists thereof.

Considerations:

 Any `null` values are excluded from the calculation. In a mixed set, any numeric value is always considered to be higher than any string value, and any string value is always considered to be higher than any list. Lists are compared in dictionary order, i.e. list elements are compared pairwise in ascending order from the start of the list to the end. `max(null)` returns `null`.
Query
``````UNWIND [1, 'a', NULL , 0.2, 'b', '1', '99'] AS val
RETURN max(val)``````

The highest of all the values in the mixed set — in this case, the numeric value `1` — is returned. Note that the (string) value `"99"`, which may appear at first glance to be the highest value in the list, is considered to be a lower value than `1` as the latter is a string.

Table 9. Result
max(val)

`1`

1 row

Query
``````UNWIND [[1, 'a', 89],[1, 2]] AS val
RETURN max(val)``````

The highest of all the lists in the set — in this case, the list `[1, 2]` — is returned, as the number `2` is considered to be a higher value than the string `"a"`, even though the list `[1, 'a', 89]` contains more elements.

Table 10. Result
max(val)

`[1,2]`

1 row

Query
``````MATCH (n:Person)
RETURN max(n.age)``````

The highest of all the values in the property `age` is returned.

Table 11. Result
max(n.age)

`44`

1 row

## 6. min()

`min()` returns the minimum value in a set of values.

Syntax: `min(expression)`

Returns:

 A property type, or a list, depending on the values returned by `expression`.

Arguments:

Name Description

`expression`

An expression returning a set containing any combination of property types and lists thereof.

Considerations:

 Any `null` values are excluded from the calculation. In a mixed set, any string value is always considered to be lower than any numeric value, and any list is always considered to be lower than any string. Lists are compared in dictionary order, i.e. list elements are compared pairwise in ascending order from the start of the list to the end. `min(null)` returns `null`.
Query
``````UNWIND [1, 'a', NULL , 0.2, 'b', '1', '99'] AS val
RETURN min(val)``````

The lowest of all the values in the mixed set — in this case, the string value `"1"` — is returned. Note that the (numeric) value `0.2`, which may appear at first glance to be the lowest value in the list, is considered to be a higher value than `"1"` as the latter is a string.

Table 12. Result
min(val)

`"1"`

1 row

Query
``````UNWIND ['d',[1, 2],['a', 'c', 23]] AS val
RETURN min(val)``````

The lowest of all the values in the set — in this case, the list `['a', 'c', 23]` — is returned, as (i) the two lists are considered to be lower values than the string `"d"`, and (ii) the string `"a"` is considered to be a lower value than the numerical value `1`.

Table 13. Result
min(val)

`["a","c",23]`

1 row

Query
``````MATCH (n:Person)
RETURN min(n.age)``````

The lowest of all the values in the property `age` is returned.

Table 14. Result
min(n.age)

`13`

1 row

## 7. percentileCont()

`percentileCont()` returns the percentile of the given value over a group, with a percentile from 0.0 to 1.0. It uses a linear interpolation method, calculating a weighted average between two values if the desired percentile lies between them. For nearest values using a rounding method, see `percentileDisc`.

Syntax: `percentileCont(expression, percentile)`

Returns:

 A Float.

Arguments:

Name Description

`expression`

A numeric expression.

`percentile`

A numeric value between 0.0 and 1.0

Considerations:

 Any `null` values are excluded from the calculation. `percentileCont(null, percentile)` returns `null`.
Query
``````MATCH (n:Person)
RETURN percentileCont(n.age, 0.4)``````

The 40th percentile of the values in the property `age` is returned, calculated with a weighted average.

Table 15. Result
percentileCont(n.age, 0.4)

`29.0`

1 row

## 8. percentileDisc()

`percentileDisc()` returns the percentile of the given value over a group, with a percentile from 0.0 to 1.0. It uses a rounding method and calculates the nearest value to the percentile. For interpolated values, see `percentileCont`.

Syntax: `percentileDisc(expression, percentile)`

Returns:

 Either an Integer or a Float, depending on the values returned by `expression` and whether or not the calculation overflows.

Arguments:

Name Description

`expression`

A numeric expression.

`percentile`

A numeric value between 0.0 and 1.0

Considerations:

 Any `null` values are excluded from the calculation. `percentileDisc(null, percentile)` returns `null`.
Query
``````MATCH (n:Person)
RETURN percentileDisc(n.age, 0.5)``````

The 50th percentile of the values in the property `age` is returned.

Table 16. Result
percentileDisc(n.age, 0.5)

`33`

1 row

## 9. stDev()

`stDev()` returns the standard deviation for the given value over a group. It uses a standard two-pass method, with `N - 1` as the denominator, and should be used when taking a sample of the population for an unbiased estimate. When the standard variation of the entire population is being calculated, `stdDevP` should be used.

Syntax: `stDev(expression)`

Returns:

 A Float.

Arguments:

Name Description

`expression`

A numeric expression.

Considerations:

 Any `null` values are excluded from the calculation. `stDev(null)` returns `0`.
Query
``````MATCH (n)
WHERE n.name IN ['A', 'B', 'C']
RETURN stDev(n.age)``````

The standard deviation of the values in the property `age` is returned.

Table 17. Result
stDev(n.age)

`15.716233645501712`

1 row

## 10. stDevP()

`stDevP()` returns the standard deviation for the given value over a group. It uses a standard two-pass method, with `N` as the denominator, and should be used when calculating the standard deviation for an entire population. When the standard variation of only a sample of the population is being calculated, `stDev` should be used.

Syntax: `stDevP(expression)`

Returns:

 A Float.

Arguments:

Name Description

`expression`

A numeric expression.

Considerations:

 Any `null` values are excluded from the calculation. `stDevP(null)` returns `0`.
Query
``````MATCH (n)
WHERE n.name IN ['A', 'B', 'C']
RETURN stDevP(n.age)``````

The population standard deviation of the values in the property `age` is returned.

Table 18. Result
stDevP(n.age)

`12.832251036613439`

1 row

## 11. sum() - Numeric values

`sum()` returns the sum of a set of numeric values.

Syntax: `sum(expression)`

Returns:

 Either an Integer or a Float, depending on the values returned by `expression`.

Arguments:

Name Description

`expression`

An expression returning a set of numeric values.

Considerations:

 Any `null` values are excluded from the calculation. `sum(null)` returns `0`.
Query
``````MATCH (n:Person)
RETURN sum(n.age)``````

The sum of all the values in the property `age` is returned.

Table 19. Result
sum(n.age)

`90`

1 row

## 12. sum() - Durations

`sum()` returns the sum of a set of Durations.

Syntax: `sum(expression)`

Returns:

 A Duration.

Arguments:

Name Description

`expression`

An expression returning a set of Durations.

Considerations:

 Any `null` values are excluded from the calculation.
Query
``````UNWIND [duration('P2DT3H'), duration('PT1H45S')] AS dur
RETURN sum(dur)``````

The sum of the two supplied Durations is returned.

Table 20. Result
sum(dur)

`P2DT4H45S`

1 row