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Copy file name to clipboardExpand all lines: doc/source/io.rst
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.. _io.bigquery_reader:
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Authentication
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''''''''''''''
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Authentication is possible with either user account credentials or service account credentials.
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Authenticating with user account credentials is as simple as following the prompts in a browser window
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which will be automatically opened for you. You will be authenticated to the specified
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``BigQuery`` account via Google's ``Oauth2`` mechanism. Additional information on the
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authentication mechanism can be found `here <https://developers.google.com/identity/protocols/OAuth2#clientside/>`__.
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Authentication with service account credentials is possible via the `'private_key'` parameter. This method
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is particularly useful when working on remote servers (eg. jupyter iPython notebook on remote host).
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The remote authentication using user account credentials is not currently supported in Pandas.
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Additional information on service accounts can be found
Copy file name to clipboardExpand all lines: doc/source/whatsnew/v0.18.0.txt
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- ``DataFrame.quantile`` and ``Series.quantile`` now accept ``interpolation`` keyword (:issue:`10174`).
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- ``DataFrame.select_dtypes`` now allows the ``np.float16`` typecode (:issue:`11990`)
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- ``pivot_table()`` now accepts most iterables for the ``values`` parameter (:issue:`12017`)
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- Added Google ``BigQuery`` service account authentication support, which enables authentication on remote servers. (:issue:`11881`). For further details see :ref:`here <io.bigquery_authentication>`
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