def read_sql_table(table_name, con, schema=None, index_col=None,
                   coerce_float=True, parse_dates=None, columns=None,
                   chunksize=None):
    """Read SQL database table into a DataFrame.

    Given a table name and an SQLAlchemy connectable, returns a DataFrame.
    This function does not support DBAPI connections.

    Parameters
    ----------
    table_name : string
        Name of SQL table in database
    con : SQLAlchemy connectable (or database string URI)
        Sqlite DBAPI connection mode not supported
    schema : string, default None
        Name of SQL schema in database to query (if database flavor
        supports this). If None, use default schema (default).
    index_col : string or list of strings, optional, default: None
        Column(s) to set as index(MultiIndex)
    coerce_float : boolean, default True
        Attempt to convert values to non-string, non-numeric objects (like
        decimal.Decimal) to floating point. Can result in loss of Precision.
    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
    columns : list, default: None
        List of column names to select from sql table
    chunksize : int, default None
        If specified, return an iterator where `chunksize` is the number of
        rows to include in each chunk.

    Returns
    -------
    DataFrame

    Notes
    -----
    Any datetime values with time zone information will be converted to UTC

    See also
    --------
    read_sql_query : Read SQL query into a DataFrame.
    read_sql

    """

    con = _engine_builder(con)
    if not _is_sqlalchemy_connectable(con):
        raise NotImplementedError("read_sql_table only supported for "
                                  "SQLAlchemy connectable.")
    import sqlalchemy
    from sqlalchemy.schema import MetaData
    meta = MetaData(con, schema=schema)
    try:
        meta.reflect(only=[table_name], views=True)
    except sqlalchemy.exc.InvalidRequestError:
        raise ValueError("Table %s not found" % table_name)

    pandas_sql = SQLDatabase(con, meta=meta)
    table = pandas_sql.read_table(
        table_name, index_col=index_col, coerce_float=coerce_float,
        parse_dates=parse_dates, columns=columns, chunksize=chunksize)

    if table is not None:
        return table
    else:
        raise ValueError(table_name % "Table %s not found", con)
dataset/ETHPy150Open pydata/pandas/pandas/io/sql.py/read_sql_table/swapped operands of `%`