[[search-aggregations-pipeline-stats-bucket-aggregation]]
=== Stats Bucket Aggregation

experimental[]

A sibling pipeline aggregation which calculates a variety of stats across all bucket of a specified metric in a sibling aggregation.
The specified metric must be numeric and the sibling aggregation must be a multi-bucket aggregation.

==== Syntax

A `stats_bucket` aggregation looks like this in isolation:

[source,js]
--------------------------------------------------
{
    "stats_bucket": {
        "buckets_path": "the_sum"
    }
}
--------------------------------------------------

.`stats_bucket` Parameters
|===
|Parameter Name |Description |Required |Default Value
|`buckets_path` |The path to the buckets we wish to calculate stats for (see <<buckets-path-syntax>> for more
 details) |Required |
|`gap_policy` |The policy to apply when gaps are found in the data (see <<gap-policy>> for more
 details)|Optional | `skip`
|`format` |format to apply to the output value of this aggregation |Optional | `null`
|===

The following snippet calculates the sum of all the total monthly `sales` buckets:

[source,js]
--------------------------------------------------
{
    "aggs" : {
        "sales_per_month" : {
            "date_histogram" : {
                "field" : "date",
                "interval" : "month"
            },
            "aggs": {
                "sales": {
                    "sum": {
                        "field": "price"
                    }
                }
            }
        },
        "stats_monthly_sales": {
            "stats_bucket": {
                "buckets_path": "sales_per_month>sales" <1>
            }
        }
    }
}
--------------------------------------------------
<1> `bucket_paths` instructs this `stats_bucket` aggregation that we want the calculate stats for the `sales` aggregation in the
`sales_per_month` date histogram.

And the following may be the response:

[source,js]
--------------------------------------------------
{
   "aggregations": {
      "sales_per_month": {
         "buckets": [
            {
               "key_as_string": "2015/01/01 00:00:00",
               "key": 1420070400000,
               "doc_count": 3,
               "sales": {
                  "value": 550
               }
            },
            {
               "key_as_string": "2015/02/01 00:00:00",
               "key": 1422748800000,
               "doc_count": 2,
               "sales": {
                  "value": 60
               }
            },
            {
               "key_as_string": "2015/03/01 00:00:00",
               "key": 1425168000000,
               "doc_count": 2,
               "sales": {
                  "value": 375
               }
            }
         ]
      },
      "stats_monthly_sales": {
         "count": 3,
         "min": 60,
         "max": 550,
         "avg": 328.333333333,
         "sum": 985
      }
   }
}
--------------------------------------------------