python - Neo4j Bolt StatementResult to Pandas DataFrame -


based on example neo4j 

from neo4j.v1 import graphdatabase, basic_auth    driver = graphdatabase.driver("bolt://localhost", auth=basic_auth("neo4j", "neo4j"))   session = driver.session()    session.run("create (a:person {name:'arthur', title:'king'})")    result = session.run("match (a:person) a.name = 'arthur' return a.name name, a.title title")   record in result:       print("%s %s" % (record["title"], record["name"]))    session.close()

here result of datatype neo4j.v1.session.statementresult. how access data in pandas dataframe without explicitly iterating?

pd.dataframe.from_records(result) doesn't seem help.

this have using list comprehension

resultlist = [[record['title'], record['name']] record in result] pd.dataframe.from_records(resultlist, columns=['title', 'name'])

the best can come list comprehension similar yours, less verbose:

df = pd.dataframe([r.values() r in result], columns=result.keys())

the py2neo package seems more suitable dataframes, it's straightforward return list of dictionaries. here's equivalent code using py2neo:

import py2neo  # of these keyword arguments unnecessary, default values. graph = py2neo.graph(bolt=true, host='localhost', user='neo4j', password='neo4j')  graph.run("create (a:person {name:'arthur', title:'king'})")  query = "match (a:person) a.name = 'arthur' return a.name name, a.title title" df = pd.dataframe(graph.data(query))

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