pandas.read_gbq — pandas 0.24.0rc1 documentation (original) (raw)

pandas. read_gbq(query, project_id=None, index_col=None, col_order=None, reauth=False, auth_local_webserver=False, dialect=None, location=None, configuration=None, credentials=None, private_key=None, verbose=None)[source]¶

Load data from Google BigQuery.

This function requires the pandas-gbq package.

See the How to authenticate with Google BigQueryguide for authentication instructions.

Parameters:	query : str SQL-Like Query to return data values. project_id : str, optional Google BigQuery Account project ID. Optional when available from the environment. index_col : str, optional Name of result column to use for index in results DataFrame. col_order : list(str), optional List of BigQuery column names in the desired order for results DataFrame. reauth : boolean, default False Force Google BigQuery to re-authenticate the user. This is useful if multiple accounts are used. auth_local_webserver : boolean, default False Use the local webserver flow instead of the console flowwhen getting user credentials. New in version 0.2.0 of pandas-gbq. dialect : str, default ‘legacy’ Note: The default value is changing to ‘standard’ in a future verion. SQL syntax dialect to use. Value can be one of: 'legacy' Use BigQuery’s legacy SQL dialect. For more information seeBigQuery Legacy SQL Reference. 'standard' Use BigQuery’s standard SQL, which is compliant with the SQL 2011 standard. For more information see BigQuery Standard SQL Reference. Changed in version 0.24.0. location : str, optional Location where the query job should run. See the BigQuery locations documentation for a list of available locations. The location must match that of any datasets used in the query. New in version 0.5.0 of pandas-gbq. configuration : dict, optional Query config parameters for job processing. For example: configuration = {‘query’: {‘useQueryCache’: False}} For more information see BigQuery REST API Reference. credentials : google.auth.credentials.Credentials, optional Credentials for accessing Google APIs. Use this parameter to override default credentials, such as to use Compute Enginegoogle.auth.compute_engine.Credentials or Service Accountgoogle.oauth2.service_account.Credentials directly. New in version 0.8.0 of pandas-gbq. New in version 0.24.0. private_key : str, deprecated Deprecated in pandas-gbq version 0.8.0. Use the credentialsparameter andgoogle.oauth2.service_account.Credentials.from_service_account_info()orgoogle.oauth2.service_account.Credentials.from_service_account_file()instead. Service account private key in JSON format. Can be file path or string contents. This is useful for remote server authentication (eg. Jupyter/IPython notebook on remote host). verbose : None, deprecated Deprecated in pandas-gbq version 0.4.0. Use the logging module to adjust verbosity instead.
Returns:	df: DataFrame DataFrame representing results of query.

Parameters:

query : str SQL-Like Query to return data values. project_id : str, optional Google BigQuery Account project ID. Optional when available from the environment. index_col : str, optional Name of result column to use for index in results DataFrame. col_order : list(str), optional List of BigQuery column names in the desired order for results DataFrame. reauth : boolean, default False Force Google BigQuery to re-authenticate the user. This is useful if multiple accounts are used. auth_local_webserver : boolean, default False Use the local webserver flow instead of the console flowwhen getting user credentials. New in version 0.2.0 of pandas-gbq. dialect : str, default ‘legacy’ Note: The default value is changing to ‘standard’ in a future verion. SQL syntax dialect to use. Value can be one of: 'legacy' Use BigQuery’s legacy SQL dialect. For more information seeBigQuery Legacy SQL Reference. 'standard' Use BigQuery’s standard SQL, which is compliant with the SQL 2011 standard. For more information see BigQuery Standard SQL Reference. Changed in version 0.24.0. location : str, optional Location where the query job should run. See the BigQuery locations documentation for a list of available locations. The location must match that of any datasets used in the query. New in version 0.5.0 of pandas-gbq. configuration : dict, optional Query config parameters for job processing. For example: configuration = {‘query’: {‘useQueryCache’: False}} For more information see BigQuery REST API Reference. credentials : google.auth.credentials.Credentials, optional Credentials for accessing Google APIs. Use this parameter to override default credentials, such as to use Compute Enginegoogle.auth.compute_engine.Credentials or Service Accountgoogle.oauth2.service_account.Credentials directly. New in version 0.8.0 of pandas-gbq. New in version 0.24.0. private_key : str, deprecated Deprecated in pandas-gbq version 0.8.0. Use the credentialsparameter andgoogle.oauth2.service_account.Credentials.from_service_account_info()orgoogle.oauth2.service_account.Credentials.from_service_account_file()instead. Service account private key in JSON format. Can be file path or string contents. This is useful for remote server authentication (eg. Jupyter/IPython notebook on remote host). verbose : None, deprecated Deprecated in pandas-gbq version 0.4.0. Use the logging module to adjust verbosity instead.

Returns:

df: DataFrame DataFrame representing results of query.