pandas.DataFrame.to_gbq

DataFrame.to_gbq(self, destination_table, project_id=None, chunksize=None, reauth=False, if_exists='fail', auth_local_webserver=False, table_schema=None, location=None, progress_bar=True, credentials=None, verbose=None, private_key=None)[source]

Write a DataFrame to a Google BigQuery table.

This function requires the pandas-gbq package.

See the How to authenticate with Google BigQuery guide for authentication instructions.

Parameters
destination_tablestr

Name of table to be written, in the form dataset.tablename.

project_idstr, optional

Google BigQuery Account project ID. Optional when available from the environment.

chunksizeint, optional

Number of rows to be inserted in each chunk from the dataframe. Set to None to load the whole dataframe at once.

reauthbool, default False

Force Google BigQuery to re-authenticate the user. This is useful if multiple accounts are used.

if_existsstr, default ‘fail’

Behavior when the destination table exists. Value can be one of:

'fail'

If table exists, do nothing.

'replace'

If table exists, drop it, recreate it, and insert data.

'append'

If table exists, insert data. Create if does not exist.

auth_local_webserverbool, default False

Use the local webserver flow instead of the console flow when getting user credentials.

New in version 0.2.0 of pandas-gbq.

table_schemalist of dicts, optional

List of BigQuery table fields to which according DataFrame columns conform to, e.g. [{'name': 'col1', 'type': 'STRING'},...]. If schema is not provided, it will be generated according to dtypes of DataFrame columns. See BigQuery API documentation on available names of a field.

New in version 0.3.1 of pandas-gbq.

locationstr, optional

Location where the load job should run. See the BigQuery locations documentation for a list of available locations. The location must match that of the target dataset.

New in version 0.5.0 of pandas-gbq.

progress_barbool, default True

Use the library tqdm to show the progress bar for the upload, chunk by chunk.

New in version 0.5.0 of pandas-gbq.

credentialsgoogle.auth.credentials.Credentials, optional

Credentials for accessing Google APIs. Use this parameter to override default credentials, 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.

verbosebool, deprecated

Deprecated in pandas-gbq version 0.4.0. Use the logging module to adjust verbosity instead.

private_keystr, deprecated

Deprecated in 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.

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).

See also

pandas_gbq.to_gbq

This function in the pandas-gbq library.

read_gbq

Read a DataFrame from Google BigQuery.

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