10.11.1 pandas.io.gbq.read_gbq

pandas.io.gbq.read_gbq(query, project_id=None, index_col=None, col_order=None, reauth=False, verbose=True, private_key=None)[source]

Load data from Google BigQuery.

THIS IS AN EXPERIMENTAL LIBRARY

The main method a user calls to execute a Query in Google BigQuery and read results into a pandas DataFrame.

Google BigQuery API Client Library v2 for Python is used. Documentation is available at https://developers.google.com/api-client-library/python/apis/bigquery/v2

Authentication to the Google BigQuery service is via OAuth 2.0. By default user account credentials are used. You will be asked to grant permissions for product name ‘pandas GBQ’. It is also posible to authenticate via service account credentials by using private_key parameter.

Parameters:

query : str SQL-Like Query to return data values project_id : str Google BigQuery Account project ID. 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 reauthenticate the user. This is useful if multiple accounts are used. verbose : boolean (default True) Verbose output private_key : str (optional) 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)

Returns:

df: DataFrame DataFrame representing results of query