pandas.read_gbq — pandas 2.2.3 documentation (original) (raw)
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.
Deprecated since version 2.2.0: Please use pandas_gbq.read_gbq
instead.
This function requires the pandas-gbq package.
See the How to authenticate with Google BigQueryguide 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 flowwhen 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 seeBigQuery 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 Enginegoogle.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.createpermission 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 the google-cloud-bigquery-storage
andfastavro
packages.
max_resultsint, optional
If set, limit the maximum number of rows to fetch from the query results.
progress_bar_typeOptional, str
If set, use the tqdm library to display a progress bar while the data downloads. Install thetqdm
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 to sys.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.
Returns:
df: DataFrame
DataFrame representing results of query.
See also
pandas_gbq.read_gbq
This function in the pandas-gbq library.
Write a DataFrame to Google BigQuery.
Examples
Example taken from Google BigQuery documentation
sql = "SELECT name FROM table_name WHERE state = 'TX' LIMIT 100;" df = pd.read_gbq(sql, dialect="standard")
project_id = "your-project-id"
df = pd.read_gbq(sql, ... project_id=project_id, ... dialect="standard" ... )