pandasのDataFrameに格納

es2df_sample.py

import elasticsearch
import pandas as pd


es = elasticsearch.Elasticsearch("localhost:9200")
INDEX = 'ldgourmet'

AGGS = "aggregations"
BKTS = "buckets"
aNames = ['a1','a2']

def qBuilder(qField,qValue,field1,field2):
    qBody = {}

    qBody["query"] =  {
        "term":{
            qField: {
                "value": qValue
            }
        }
    }
    
    qBody[AGGS] =  {
        aNames[0]:{
            "terms": {
                "field": field1,
                "size": 47
            },
            AGGS:{
                aNames[1]:{
                    "significant_terms":{
                        "field": field2,
                        "size":50,
                        "min_doc_count": 5, 
                        "chi_square": {}
                    }
                }
            }
        }
    }
    import json
    print(json.dumps(qBody,ensure_ascii=False))
    return qBody

def searchEs(qBody):
    _r = es.search(
        index=INDEX,
        body=qBody
    )
    
    def myAggs4DF(result):
        _bs = result[AGGS][aNames[0]][BKTS]
        aggs = []
        for _b in _bs:
            k = _b['key']
            dc = _b['doc_count']
            innerBs = [(
                ib['key'],
                ib['doc_count']
                ) for ib in _b[aNames[1]][BKTS]]
                
            aggs.append([k,dc,innerBs])
        return (aggs,['k','dc','bkts'])
        
    aggs = myAggs4DF(_r)

    h = [i['_source']
        for i in _r['hits']['hits']]

    return h,aggs

h,a = searchEs(qBuilder("pref.raw","13__東京都","area_name.raw","cates.raw"))
#hDF = pd.json_normalize(h)
hDF = pd.DataFrame(h)
aDF = pd.DataFrame(a[0],columns=a[1])