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.

param destination_table

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

param project_id
str, optional

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

param chunksize
int, optional

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

param reauth
bool, default False

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

param if_exists
str, 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.

param auth_local_webserver
bool, 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.

param table_schema
list 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.

param location
str, 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.

param progress_bar
bool, 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.

param credentials
google.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.

param verbose
bool, deprecated

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

param private_key
str, 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).


This feature is currently unsupported by Intel Scalable Dataframe Compiler