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DOC: synchronize docs changes with pandas (#190)
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The docs needs some corrections in order to pass the Pandas docs linter
in pandas-dev/pandas#21628
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@tswast
tswast authored Jun 25, 2018
1 parent ade32a2 commit 06ff699
Showing 1 changed file with 87 additions and 69 deletions.
156 changes: 87 additions & 69 deletions pandas_gbq/gbq.py
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Original file line number Diff line number Diff line change
Expand Up @@ -470,9 +470,9 @@ def _parse_data(schema, rows):


def read_gbq(query, project_id=None, index_col=None, col_order=None,
reauth=False, verbose=None, private_key=None,
auth_local_webserver=False, dialect='legacy', location=None,
configuration=None):
reauth=False, private_key=None, auth_local_webserver=False,
dialect='legacy', location=None, configuration=None,
verbose=None):
r"""Load data from Google BigQuery using google-cloud-python
The main method a user calls to execute a Query in Google BigQuery
Expand All @@ -488,63 +488,69 @@ def read_gbq(query, project_id=None, index_col=None, col_order=None,
Parameters
----------
query : str
SQL-Like Query to return data values
project_id : str (optional when available in environment)
Google BigQuery Account project ID.
index_col : str (optional)
Name of result column to use for index in results DataFrame
col_order : list(str) (optional)
SQL-Like Query to return data values.
project_id : str, optional
Google BigQuery Account project ID. Optional when available from
the environment.
index_col : str, optional
Name of result column to use for index in results DataFrame.
col_order : list(str), optional
List of BigQuery column names in the desired order for results
DataFrame
reauth : boolean (default False)
Force Google BigQuery to reauthenticate the user. This is useful
DataFrame.
reauth : boolean, default False
Force Google BigQuery to re-authenticate the user. This is useful
if multiple accounts are used.
private_key : str (optional)
private_key : str, optional
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)
authentication (eg. Jupyter/IPython notebook on remote host).
auth_local_webserver : boolean, default False
Use the [local webserver flow] instead of the [console flow] when
getting user credentials. A file named bigquery_credentials.dat will
be created in current dir. You can also set PANDAS_GBQ_CREDENTIALS_FILE
environment variable so as to define a specific path to store this
credential (eg. /etc/keys/bigquery.dat).
Use the `local webserver flow`_ instead of the `console flow`_
when getting user credentials.
.. [local webserver flow]
.. _local webserver flow:
http://google-auth-oauthlib.readthedocs.io/en/latest/reference/google_auth_oauthlib.flow.html#google_auth_oauthlib.flow.InstalledAppFlow.run_local_server
.. [console flow]
.. _console flow:
http://google-auth-oauthlib.readthedocs.io/en/latest/reference/google_auth_oauthlib.flow.html#google_auth_oauthlib.flow.InstalledAppFlow.run_console
.. versionadded:: 0.2.0
dialect : {'legacy', 'standard'}, default 'legacy'
'legacy' : Use BigQuery's legacy SQL dialect.
'standard' : Use BigQuery's standard SQL (beta), which is
compliant with the SQL 2011 standard. For more information
see `BigQuery SQL Reference
<https://cloud.google.com/bigquery/sql-reference/>`__
location : str (optional)
.. versionadded:: 0.2.0
dialect : str, default 'legacy'
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
<https://cloud.google.com/bigquery/docs/reference/legacy-sql>`__.
``'standard'``
Use BigQuery's standard SQL, which is
compliant with the SQL 2011 standard. For more information
see `BigQuery Standard SQL Reference
<https://cloud.google.com/bigquery/docs/reference/standard-sql/>`__.
location : str, optional
Location where the query job should run. See the `BigQuery locations
documentation
<https://cloud.google.com/bigquery/docs/dataset-locations>`__ for a
list of available locations. The location must match that of any
datasets used in the query.
.. versionadded:: 0.5.0
configuration : dict (optional)
configuration : dict, optional
Query config parameters for job processing.
For example:
configuration = {'query': {'useQueryCache': False}}
For more information see `BigQuery SQL Reference
<https://cloud.google.com/bigquery/docs/reference/rest/v2/jobs#configuration.query>`__
For more information see `BigQuery REST API Reference
<https://cloud.google.com/bigquery/docs/reference/rest/v2/jobs#configuration.query>`__.
verbose : None, deprecated
Deprecated in Pandas-GBQ 0.4.0. Use the `logging module
to adjust verbosity instead
<https://pandas-gbq.readthedocs.io/en/latest/intro.html#logging>`__.
Returns
-------
df: DataFrame
DataFrame representing results of query
DataFrame representing results of query.
"""

_test_google_api_imports()
Expand Down Expand Up @@ -603,9 +609,9 @@ def read_gbq(query, project_id=None, index_col=None, col_order=None,


def to_gbq(dataframe, destination_table, project_id=None, chunksize=None,
verbose=None, reauth=False, if_exists='fail', private_key=None,
reauth=False, if_exists='fail', private_key=None,
auth_local_webserver=False, table_schema=None, location=None,
progress_bar=True):
progress_bar=True, verbose=None):
"""Write a DataFrame to a Google BigQuery table.
The main method a user calls to export pandas DataFrame contents to
Expand All @@ -621,54 +627,66 @@ def to_gbq(dataframe, destination_table, project_id=None, chunksize=None,
Parameters
----------
dataframe : pandas.DataFrame
DataFrame to be written
DataFrame to be written to a Google BigQuery table.
destination_table : str
Name of table to be written, in the form 'dataset.tablename'
project_id : str (optional when available in environment)
Google BigQuery Account project ID.
chunksize : int (default None)
Number of rows to be inserted in each chunk from the dataframe. Use
``None`` to load the dataframe in a single chunk.
reauth : boolean (default False)
Force Google BigQuery to reauthenticate the user. This is useful
Name of table to be written, in the form ``dataset.tablename``.
project_id : str, optional
Google BigQuery Account project ID. Optional when available from
the environment.
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.
reauth : bool, default False
Force Google BigQuery to re-authenticate the user. This is useful
if multiple accounts are used.
if_exists : {'fail', 'replace', 'append'}, default 'fail'
'fail': If table exists, do nothing.
'replace': If table exists, drop it, recreate it, and insert data.
'append': If table exists and the dataframe schema is a subset of
the destination table schema, insert data. Create destination table
if does not exist.
private_key : str (optional)
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.
private_key : str, optional
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)
auth_local_webserver : boolean, default False
Use the [local webserver flow] instead of the [console flow] when
getting user credentials.
authentication (eg. Jupyter/IPython notebook on remote host).
auth_local_webserver : bool, default False
Use the `local webserver flow`_ instead of the `console flow`_
when getting user credentials.
.. [local webserver flow]
.. _local webserver flow:
http://google-auth-oauthlib.readthedocs.io/en/latest/reference/google_auth_oauthlib.flow.html#google_auth_oauthlib.flow.InstalledAppFlow.run_local_server
.. [console flow]
.. _console flow:
http://google-auth-oauthlib.readthedocs.io/en/latest/reference/google_auth_oauthlib.flow.html#google_auth_oauthlib.flow.InstalledAppFlow.run_console
.. versionadded:: 0.2.0
table_schema : list of dicts
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.
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.
.. versionadded:: 0.3.1
location : str (optional)
location : str, optional
Location where the load job should run. See the `BigQuery locations
documentation
<https://cloud.google.com/bigquery/docs/dataset-locations>`__ for a
list of available locations. The location must match that of the
target dataset.
.. versionadded:: 0.5.0
progress_bar : boolean, True by default. It uses the library `tqdm` to show
the progress bar for the upload, chunk by chunk.
progress_bar : bool, default True
Use the library `tqdm` to show the progress bar for the upload,
chunk by chunk.
.. versionadded:: 0.5.0
verbose : None, deprecated
verbose : bool, deprecated
Deprecated in Pandas-GBQ 0.4.0. Use the `logging module
to adjust verbosity instead
<https://pandas-gbq.readthedocs.io/en/latest/intro.html#logging>`__.
"""

_test_google_api_imports()
Expand Down

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