pandas.read_gbq#
- pandas.read_gbq(query, project_id=None, index_col=None, col_order=None, reauth=False, auth_local_webserver=True, dialect=None, location=None, configuration=None, credentials=None, use_bqstorage_api=None, max_results=None, progress_bar_type=None)[source]#
Load data from Google BigQuery.
This function requires the pandas-gbq package.
See the How to authenticate with Google BigQuery guide for authentication instructions.
- Parameters
- querystr
SQL-Like Query to return data values.
- project_idstr, optional
Google BigQuery Account project ID. Optional when available from the environment.
- index_colstr, optional
Name of result column to use for index in results DataFrame.
- col_orderlist(str), optional
List of BigQuery column names in the desired order for results DataFrame.
- reauthbool, default False
Force Google BigQuery to re-authenticate the user. This is useful if multiple accounts are used.
- auth_local_webserverbool, default True
Use the local webserver flow instead of the console flow when getting user credentials.
New in version 0.2.0 of pandas-gbq.
Changed in version 1.5.0: Default value is changed to
True
. Google has deprecated theauth_local_webserver = False
“out of band” (copy-paste) flow.- dialectstr, default ‘legacy’
Note: The default value is changing to ‘standard’ in a future version.
SQL syntax dialect to use. Value can be one of:
'legacy'
Use BigQuery’s legacy SQL dialect. For more information see BigQuery Legacy SQL Reference.
'standard'
Use BigQuery’s standard SQL, which is compliant with the SQL 2011 standard. For more information see BigQuery Standard SQL Reference.
- locationstr, optional
Location where the query job should run. See the BigQuery locations documentation for a list of available locations. The location must match that of any datasets used in the query.
New in version 0.5.0 of pandas-gbq.
- configurationdict, optional
Query config parameters for job processing. For example:
configuration = {‘query’: {‘useQueryCache’: False}}
For more information see BigQuery REST API Reference.
- 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 Accountgoogle.oauth2.service_account.Credentials
directly.New in version 0.8.0 of pandas-gbq.
- use_bqstorage_apibool, default False
Use the BigQuery Storage API to download query results quickly, but at an increased cost. To use this API, first enable it in the Cloud Console. You must also have the bigquery.readsessions.create permission on the project you are billing queries to.
This feature requires version 0.10.0 or later of the
pandas-gbq
package. It also requires thegoogle-cloud-bigquery-storage
andfastavro
packages.New in version 0.25.0.
- max_resultsint, optional
If set, limit the maximum number of rows to fetch from the query results.
New in version 0.12.0 of pandas-gbq.
New in version 1.1.0.
- progress_bar_typeOptional, str
If set, use the tqdm library to display a progress bar while the data downloads. Install the
tqdm
package to use this feature.Possible values of
progress_bar_type
include:None
No progress bar.
'tqdm'
Use the
tqdm.tqdm()
function to print a progress bar tosys.stderr
.'tqdm_notebook'
Use the
tqdm.tqdm_notebook()
function to display a progress bar as a Jupyter notebook widget.'tqdm_gui'
Use the
tqdm.tqdm_gui()
function to display a progress bar as a graphical dialog box.
Note that this feature requires version 0.12.0 or later of the
pandas-gbq
package. And it requires thetqdm
package. Slightly different thanpandas-gbq
, here the default isNone
.New in version 1.0.0.
- Returns
- df: DataFrame
DataFrame representing results of query.
See also
pandas_gbq.read_gbq
This function in the pandas-gbq library.
DataFrame.to_gbq
Write a DataFrame to Google BigQuery.