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.
This aggregation provides a few more statistics (sum of squares, standard deviation, etc) compared to the stats_bucket aggregation.
A extended_stats_bucket aggregation looks like this in isolation:
{
    "extended_stats_bucket": {
        "buckets_path": "the_sum"
    }
}Table 13. extended_stats_bucket Parameters
| Parameter Name | Description | Required | Default Value | 
|---|---|---|---|
| 
 | The path to the buckets we wish to calculate stats for (see  | Required | |
| 
 | The policy to apply when gaps are found in the data (see Dealing with gaps in the data for more details) | Optional | 
 | 
| 
 | format to apply to the output value of this aggregation | Optional | 
 | 
| 
 | The number of standard deviations above/below the mean to display | Optional | 2 | 
The following snippet calculates the extended stats for monthly sales bucket:
POST /sales/_search
{
    "size": 0,
    "aggs" : {
        "sales_per_month" : {
            "date_histogram" : {
                "field" : "date",
                "interval" : "month"
            },
            "aggs": {
                "sales": {
                    "sum": {
                        "field": "price"
                    }
                }
            }
        },
        "stats_monthly_sales": {
            "extended_stats_bucket": {
                "buckets_path": "sales_per_month>sales"  }
        }
    }
}
            }
        }
    }
}| 
 | 
And the following may be the response:
{
   "took": 11,
   "timed_out": false,
   "_shards": ...,
   "hits": ...,
   "aggregations": {
      "sales_per_month": {
         "buckets": [
            {
               "key_as_string": "2015/01/01 00:00:00",
               "key": 1420070400000,
               "doc_count": 3,
               "sales": {
                  "value": 550.0
               }
            },
            {
               "key_as_string": "2015/02/01 00:00:00",
               "key": 1422748800000,
               "doc_count": 2,
               "sales": {
                  "value": 60.0
               }
            },
            {
               "key_as_string": "2015/03/01 00:00:00",
               "key": 1425168000000,
               "doc_count": 2,
               "sales": {
                  "value": 375.0
               }
            }
         ]
      },
      "stats_monthly_sales": {
         "count": 3,
         "min": 60.0,
         "max": 550.0,
         "avg": 328.3333333333333,
         "sum": 985.0,
         "sum_of_squares": 446725.0,
         "variance": 41105.55555555556,
         "std_deviation": 202.74505063146563,
         "std_deviation_bounds": {
           "upper": 733.8234345962646,
           "lower": -77.15676792959795
         }
      }
   }
}