def get_pandas_df(self, bql, parameters=None):
"""
Returns a Pandas DataFrame for the results produced by a BigQuery
query. The DbApiHook method must be overridden because Pandas
doesn't support PEP 249 connections, except for SQLite. See:
https://github.com/pydata/pandas/blob/master/pandas/io/sql.py#L447
https://github.com/pydata/pandas/issues/6900
:param bql: The BigQuery SQL to execute.
:type bql: string
"""
service = self.get_service()
connection_extras = self._extras_dejson()
project = connection_extras['project']
connector = BigQueryPandasConnector(project, service)
schema, pages = connector.run_query(bql, verbose=False)
dataframe_list = []
while len(pages) > 0:
page = pages.pop()
dataframe_list.append(gbq_parse_data(schema, page))
if len(dataframe_list) > 0:
return concat(dataframe_list, ignore_index=True)
else:
return gbq_parse_data(schema, [])
def get_pandas_df(self, bql, parameters=None):
"""
Returns a Pandas DataFrame for the results produced by a BigQuery
query. The DbApiHook method must be overridden because Pandas
doesn't support PEP 249 connections, except for SQLite. See:
https://github.com/pydata/pandas/blob/master/pandas/io/sql.py#L447
https://github.com/pydata/pandas/issues/6900
:param bql: The BigQuery SQL to execute.
:type bql: string
"""
service = self.get_service()
project = self._get_field('project')
connector = BigQueryPandasConnector(project, service)
schema, pages = connector.run_query(bql)
dataframe_list = []
while len(pages) > 0:
page = pages.pop()
dataframe_list.append(gbq_parse_data(schema, page))
if len(dataframe_list) > 0:
return concat(dataframe_list, ignore_index=True)
else:
return gbq_parse_data(schema, [])
def get_pandas_df(self, bql, parameters=None):
"""
Returns a Pandas DataFrame for the results produced by a BigQuery query.
"""
service = self.get_conn()
connection_info = self.get_connection(self.bigquery_conn_id)
connection_extras = connection_info.extra_dejson
project = connection_extras['project']
connector = BigQueryPandasConnector(project, service)
schema, pages = connector.run_query(bql, verbose=False)
dataframe_list = []
while len(pages) > 0:
page = pages.pop()
dataframe_list.append(gbq_parse_data(schema, page))
if len(dataframe_list) > 0:
return concat(dataframe_list, ignore_index=True)
else:
return gbq_parse_data(schema, [])
def get_pandas_df(self, bql, parameters=None):
"""
Returns a Pandas DataFrame for the results produced by a BigQuery query.
"""
service = self.get_conn()
connection_info = self.get_connection(self.bigquery_conn_id)
connection_extras = connection_info.extra_dejson
project = connection_extras['project']
connector = BigQueryPandasConnector(project, service)
schema, pages = connector.run_query(bql, verbose=False)
dataframe_list = []
while len(pages) > 0:
page = pages.pop()
dataframe_list.append(gbq_parse_data(schema, page))
if len(dataframe_list) > 0:
return concat(dataframe_list, ignore_index=True)
else:
return gbq_parse_data(schema, [])
