code: def read_table(self, table_name, index_col=None, coerce_float=True,
                     parse_dates=None, columns=None, schema=None,
                     chunksize=None):
          
          table = SQLTable(table_name, self, index=index_col, schema=schema)
          return table.read(coerce_float=coerce_float,
                            parse_dates=parse_dates, columns=columns,
                            chunksize=chunksize)
docs: Read SQL database table into a DataFrame.
  
          Parameters
          ----------
          table_name : string
              Name of SQL table in database.
          index_col : string, optional, default: None
              Column to set as index.
          coerce_float : boolean, default True
              Attempts to convert values of non-string, non-numeric objects
              (like decimal.Decimal) to floating point. This 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}``, where the arg 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.
          schema : string, default None
              Name of SQL schema in database to query (if database flavor
              supports this).  If specified, this overwrites the default
              schema of the SQL database object.
          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
          --------
          pandas.read_sql_table
          SQLDatabase.read_query