) to set as index(MultiIndex).
    coerce_float : bool, 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.
    dtype : Type name or dict of columns
        Data type for data or columns. E.g. np.float64 or
        {‘a’: np.float64, ‘b’: np.int32, ‘c’: ‘Int64’}.

        .. versionadded:: 1.3.0
    dtype_backend : {"numpy_nullable", "pyarrow"}, defaults to NumPy backed DataFrames
        Which dtype_backend to use, e.g. whether a DataFrame should have NumPy
        arrays, nullable dtypes are used for all dtypes that have a nullable
        implementation when "numpy_nullable" is set, pyarrow is used for all
        dtypes if "pyarrow" is set.

        The dtype_backends are still experimential.

        .. versionadded:: 2.0

    Returns
    -------
    DataFrame or Iterator[DataFrame]

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

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