dependencies on a per-method basis.(GH9713) • Updated BigQuery connector to no longer use deprecated oauth2client.tools.run() (GH8327) • Bug in subclassed DataFrame. It may not return the correct class, when the Google bq.py command line client. This submodule now uses httplib2 and the Google apiclient and oauth2client API client libraries which should be more stable and, therefore, reliable than bq.py. See the available for installation. • Google’s ‘python-gflags <‘__ , oauth2client , httplib2 and google-api-python-client : Needed for gbq • Backports.lzma: Only for Python

dependencies on a per-method basis.(GH9713) • Updated BigQuery connector to no longer use deprecated oauth2client.tools.run() (GH8327) • Bug in subclassed DataFrame. It may not return the correct class, when the Google bq.py command line client. This submodule now uses httplib2 and the Google apiclient and oauth2client API client libraries which should be more stable and, therefore, reliable than bq.py. See the available for installation. • Google’s ‘python-gflags <‘__ , oauth2client , httplib2 and google-api-python-client : Needed for gbq • Backports.lzma: Only for Python

dependencies on a per-method basis.(GH9713) • Updated BigQuery connector to no longer use deprecated oauth2client.tools.run() (GH8327) • Bug in subclassed DataFrame. It may not return the correct class, when the Google bq.py command line client. This submodule now uses httplib2 and the Google apiclient and oauth2client API client libraries which should be more stable and, therefore, reliable than bq.py. See the https://developers.google.com/api-client-library/python/. Authentication to the Google BigQuery service is via OAuth 2.0 using the product name ‘pandas GBQ’. Parameters query : str SQL-Like Query to return data values

such as to use Compute Engine google.auth.compute_engine.Credentials or Service Account google. oauth2.service_account.Credentials directly. New in version 0.8.0 of pandas-gbq. New in version 0.24.0 pandas-gbq version 0.8.0. Use the credentials parameter and google.oauth2.service_account.Credentials. from_service_account_info() or google.oauth2.service_account. Credentials.from_service_account_file() instead such as to use Com- pute Engine google.auth.compute_engine.Credentials or Service Ac- count google.oauth2.service_account.Credentials directly. New in version 0.8.0 of pandas-gbq. New in version 0.24.0

such as to use Compute Engine google.auth.compute_engine.Credentials or Service Account google. oauth2.service_account.Credentials directly. New in version 0.8.0 of pandas-gbq. New in version 0.24.0 pandas-gbq version 0.8.0. Use the credentials parameter and google.oauth2.service_account.Credentials. from_service_account_info() or google.oauth2.service_account. Credentials.from_service_account_file() instead such as to use Com- pute Engine google.auth.compute_engine.Credentials or Service Ac- count google.oauth2.service_account.Credentials directly. New in version 0.8.0 of pandas-gbq. New in version 0.24.0

such as to use Compute Engine google.auth.compute_engine.Credentials or Service Account google. oauth2.service_account.Credentials directly. New in version 0.8.0 of pandas-gbq. New in version 0.24.0 pandas-gbq version 0.8.0. Use the credentials parameter and google.oauth2.service_account.Credentials. from_service_account_info() or google.oauth2.service_account. Credentials.from_service_account_file() instead such as to use Com- pute Engine google.auth.compute_engine.Credentials or Service Ac- count google.oauth2.service_account.Credentials directly. New in version 0.8.0 of pandas-gbq. New in version 0.24.0

dependencies on a per-method basis.(GH9713) • Updated BigQuery connector to no longer use deprecated oauth2client.tools.run() (GH8327) • Bug in subclassed DataFrame. It may not return the correct class, when the Google bq.py command line client. This submodule now uses httplib2 and the Google apiclient and oauth2client API client libraries which should be more stable and, therefore, reliable than bq.py. See the Python is used. Documentation is available here Authentication to the Google BigQuery service is via OAuth 2.0. • If “private_key” is not provided: By default “application default credentials” are used.

dependencies on a per-method basis.(GH9713) • Updated BigQuery connector to no longer use deprecated oauth2client.tools.run() (GH8327) • Bug in subclassed DataFrame. It may not return the correct class, when the Google bq.py command line client. This submodule now uses httplib2 and the Google apiclient and oauth2client API client libraries which should be more stable and, therefore, reliable than bq.py. See the Python is used. Documentation is available here Authentication to the Google BigQuery service is via OAuth 2.0. • If “private_key” is not provided: By default “application default credentials” are used.

the Google bq.py command line client. This submodule now uses httplib2 and the Google apiclient and oauth2client API client libraries which should be more stable and, therefore, reliable than bq.py. See the project_id = projectid) You will then be authenticated to the specified BigQuery account via Google’s Oauth2 mechanism. In general, this is as simple as following the prompts in a browser window which will https://developers.google.com/api-client-library/python/. Authentication to the Google BigQuery service is via OAuth 2.0 using the product name ‘pandas GBQ’. Parameters query : str SQL-Like Query to return data values

the Google bq.py command line client. This submodule now uses httplib2 and the Google apiclient and oauth2client API client libraries which should be more stable and, therefore, reliable than bq.py. See the project_id = projectid) You will then be authenticated to the specified BigQuery account via Google’s Oauth2 mechanism. In general, this is as simple as following the prompts in a browser window which will https://developers.google.com/api-client-library/python/. Authentication to the Google BigQuery service is via OAuth 2.0 using the product name ‘pandas GBQ’. Parameters query : str SQL-Like Query to return data values