Read SQL query into a DataFrame.

    Returns a DataFrame corresponding to the result set of the query
    string. Optionally provide an `index_col` parameter to use one of the
    columns as the index, otherwise default integer index will be used.

    Parameters
    ----------
    sql : string SQL query or SQLAlchemy Selectable (select or text object)
        SQL query to be executed.
    con : SQLAlchemy connectable(engine/connection), database string URI,
        or sqlite3 DBAPI2 connection
        Using SQLAlchemy makes it possible to use any DB supported by that
        library.
        If a DBAPI2 object, only sqlite3 is supported.
    index_col : string or list of strings, optional, default: None
        Column(s) to set as index(MultiIndex).
    coerce_float : boolean, default True
        Attempts to convert values of non-string, non-numeric objects (like
        decimal.Decimal) to floating point. Useful for SQL result sets.
    params : list, tuple or dict, optional, default: None
        List of parameters to pass to execute method.  The syntax used
        to pass parameters is database driver dependent. Check your
        database driver documentation for which of the five syntax styles,
        described in PEP 249's paramstyle, is supported.
        Eg. for psycopg2, uses %(name)s so use params={'name' : 'value'}
    parse_dates : list or dict, default: None
        - List of column names to parse as dates.
        - Dict of ``{column_name: format string}`` where format string is
          strftime compatible in case of parsing string times, or is one of
          (D, s, ns, ms, us) in case of parsing integer timestamps.
        - Dict of ``{column_name: arg dict}``, where the arg dict corresponds
          to the keyword arguments of :func:`pandas.to_datetime`
          Especially useful with databases without native Datetime support,
          such as SQLite.
    chunksize : int, default None
        If specified, return an iterator where `chunksize` is the number of
        rows to include in each chunk.

    Returns
    -------
    DataFrame

    See Also
    --------
    read_sql_table : Read SQL database table into a DataFrame.
    read_sql

    Notes
    -----
    Any datetime values with time zone information parsed via the `parse_dates`
    parameter will be converted to UTC.

def read_sql_query(sql, con, index_col=None, coerce_float=True, params=None,
                   parse_dates=None, chunksize=None):
    """Read SQL query into a DataFrame.

    Returns a DataFrame corresponding to the result set of the query
    string. Optionally provide an `index_col` parameter to use one of the
    columns as the index, otherwise default integer index will be used.

    Parameters
    ----------
    sql : string SQL query or SQLAlchemy Selectable (select or text object)
        SQL query to be executed.
    con : SQLAlchemy connectable(engine/connection), database string URI,
        or sqlite3 DBAPI2 connection
        Using SQLAlchemy makes it possible to use any DB supported by that
        library.
        If a DBAPI2 object, only sqlite3 is supported.
    index_col : string or list of strings, optional, default: None
        Column(s) to set as index(MultiIndex).
    coerce_float : boolean, default True
        Attempts to convert values of non-string, non-numeric objects (like
        decimal.Decimal) to floating point. Useful for SQL result sets.
    params : list, tuple or dict, optional, default: None
        List of parameters to pass to execute method.  The syntax used
        to pass parameters is database driver dependent. Check your
        database driver documentation for which of the five syntax styles,
        described in PEP 249's paramstyle, is supported.
        Eg. for psycopg2, uses %(name)s so use params={'name' : 'value'}
    parse_dates : list or dict, default: None
        - List of column names to parse as dates.
        - Dict of ``{column_name: format string}`` where format string is
          strftime compatible in case of parsing string times, or is one of
          (D, s, ns, ms, us) in case of parsing integer timestamps.
        - Dict of ``{column_name: arg dict}``, where the arg dict corresponds
          to the keyword arguments of :func:`pandas.to_datetime`
          Especially useful with databases without native Datetime support,
          such as SQLite.
    chunksize : int, default None
        If specified, return an iterator where `chunksize` is the number of
        rows to include in each chunk.

    Returns
    -------
    DataFrame

    See Also
    --------
    read_sql_table : Read SQL database table into a DataFrame.
    read_sql

    Notes
    -----
    Any datetime values with time zone information parsed via the `parse_dates`
    parameter will be converted to UTC.
    """
    pandas_sql = pandasSQL_builder(con)
    return pandas_sql.read_query(
        sql, index_col=index_col, params=params, coerce_float=coerce_float,
        parse_dates=parse_dates, chunksize=chunksize)