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# pandas.io.gbq.read_gbq

`pandas.io.gbq.``read_gbq`(query, project_id=None, destination_table=None, index_col=None, col_order=None, **kwargs)

  Load data from Google BigQuery.

  THIS IS AN EXPERIMENTAL LIBRARY

  The main method a user calls to load data from Google BigQuery into a pandas DataFrame. This is a simple wrapper for Google’s bq.py and bigquery_client.py, which we use to get the source data. Because of this, this script respects the user’s bq settings file, ‘~/.bigqueryrc’, if it exists. Such a file can be generated using ‘bq init’. Further, additional parameters for the query can be specified as either `**kwds` in the command, or using FLAGS provided in the ‘gflags’ module. Particular options can be found in bigquery_client.py.

  Parameters : | query : str SQL-Like Query to return data values project_id : str (optional) Google BigQuery Account project ID. Optional, since it may be located in ~/.bigqueryrc 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 destination_table : string (optional) If provided, send the results to the given table. **kwargs : To be passed to bq.Client.Create(). Particularly: ‘trace’, ‘sync’, ‘api’, ‘api_version’
  Returns : | df: DataFrame DataFrame representing results of query

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