This package is a PyData project and is subject to the NumFocus privacy policy. Your use of Google APIs with this module is subject to each API's respective terms of service.
The :mod:`pandas_gbq` module accesses Google Cloud Platform resources from your local machine. Your machine communicates directly with the Google APIs.
The :func:`~pandas_gbq.read_gbq` function can read and write BigQuery data (and other data such as Google Sheets or Cloud Storage, via the federated query feature) through the BigQuery query interface via queries you supply.
The :func:`~pandas_gbq.to_gbq` method can write data you supply to a BigQuery table.
By default, your credentials are stored to a local file, such as
~/.config/pandas_gbq/bigquery_credentials.dat. See the
:ref:`authentication-user` guide for details. All user data is stored on
your local machine. Use caution when using this library on a shared
machine.
The pandas-gbq library only communicates with Google APIs. No user data is shared with PyData, NumFocus, or any other servers.
Do not use the default client ID when using the pandas-gbq library from an application, library, or tool. Per the Google User Data Policy, your application must accurately represent itself when authenticating to Google API servcies.