support stats/extended_stats result extraction

CHANGELOG.md

@@ -1,6 +1,7 @@
 
 ### 0.2.0
 
+* support metric agg: `stats`, `extended_stats`
 * support boolean filter: `like`, `rlike`, `startswith`, `notnull`
 * display time in `df.show()`
 

README.md

@@ -100,7 +100,7 @@ df.sort(ScriptSorter('doc["age"].value * 2')).collect()
 df[df.gender == 'male'].agg(df.age.avg).collect()
 # [Row(avg(age)=12)]
 
-# Groupby
+# Groupby only (will give the `doc_count`)
 df.groupby('gender').collect()
 # [Row(doc_count=1), Row(doc_count=2)]
 
@@ -120,6 +120,10 @@ df[df.gender == 'male'].agg(df.age.avg).to_pandas()
 #    avg(age)
 # 0        12
 
+# Advanced ES functinality
+df.groupby(df.gender).agg(df.age.stats).to_pandas()
+df.agg(df.age.extended_stats).to_pandas()
+df.agg(df.age.percentiles).to_pandas()
 ```
 
 

pandasticsearch/operators.py

@@ -1,7 +1,7 @@
 # -*- coding: UTF-8 -*-
 
-_metric_aggs = ('avg', 'min', 'max', 'cardinality', 'value_count', 'sum'
-                'percentiles', 'percentile_ranks')
+_metric_aggs = ('avg', 'min', 'max', 'cardinality', 'value_count', 'sum',
+                'percentiles', 'percentile_ranks', 'stats', 'extended_stats')
 
 _sort_mode = ('min', 'max', 'sum', 'avg', 'median')
 

pandasticsearch/queries.py

@@ -192,8 +192,11 @@ def _process_agg(cls, bucket, indexes=(), names=()):
                     row[k] = v['value']
                 elif 'values' in v:  # percentiles
                     row = v['values']
-            if k == 'doc_count':  # count docs
-                row['doc_count'] = v
+                else:
+                    row.update(v)    # stats
+            else:
+                if k == 'doc_count':  # count docs
+                    row['doc_count'] = v
 
         if len(row) > 0:
             yield (names, indexes, row)

pandasticsearch/types.py

@@ -96,6 +96,14 @@ def percentiles(self):
     def percentile_ranks(self):
         return MetricAggregator(self._field, 'percentile_ranks')
 
+    @property
+    def stats(self):
+        return MetricAggregator(self._field, 'stats')
+
+    @property
+    def extended_stats(self):
+        return MetricAggregator(self._field, 'extended_stats')
+
 
 class Row(tuple):
     """