elasticsearch/docs/reference/aggregations/metrics/stats-aggregation.asciidoc

[[search-aggregations-metrics-stats-aggregation]]
=== Stats Aggregation

A `multi-value` metrics aggregation that computes stats over numeric values extracted from the aggregated documents. These values can be extracted either from specific numeric fields in the documents, or be generated by a provided script.

The stats that are returned consist of: `min`, `max`, `sum`, `count` and `avg`.

Assuming the data consists of documents representing exams grades (between 0 and 100) of students

[source,js]
--------------------------------------------------
{
    "aggs" : {
        "grades_stats" : { "stats" : { "field" : "grade" } }
    }
}
--------------------------------------------------

The above aggregation computes the grades statistics over all documents. The aggregation type is `stats` and the `field` setting defines the numeric field of the documents the stats will be computed on. The above will return the following:


[source,js]
--------------------------------------------------
{
    ...

    "aggregations": {
        "grades_stats": {
            "count": 6,
            "min": 60,
            "max": 98,
            "avg": 78.5,
            "sum": 471
        }
    }
}
--------------------------------------------------

The name of the aggregation (`grades_stats` above) also serves as the key by which the aggregation result can be retrieved from the returned response.

==== Script

Computing the grades stats based on a script:

[source,js]
--------------------------------------------------
{
    ...,

    "aggs" : {
        "grades_stats" : { "stats" : { "script" : "doc['grade'].value" } }
    }
}
--------------------------------------------------

TIP: The `script` parameter expects an inline script. Use `script_id` for indexed scripts and `script_file` for scripts in the `config/scripts/` directory.

===== Value Script

It turned out that the exam was way above the level of the students and a grade correction needs to be applied. We can use a value script to get the new stats:

[source,js]
--------------------------------------------------
{
    "aggs" : {
        ...

        "aggs" : {
            "grades_stats" : {
                "stats" : {
                    "field" : "grade",
                    "script" : "_value * correction",
                    "params" : {
                        "correction" : 1.2
                    }
                }
            }
        }
    }
}
--------------------------------------------------

==== Missing value

The `missing` parameter defines how documents that are missing a value should be treated.
By default they will be ignored but it is also possible to treat them as if they
had a value.

[source,js]
--------------------------------------------------
{
    "aggs" : {
        "grades_stats" : {
            "stats" : {
                "field" : "grade",
                "missing": 0 <1>
            }
        }
    }
}
--------------------------------------------------

<1> Documents without a value in the `grade` field will fall into the same bucket as documents that have the value `0`.