code: def dataframe_from_excel(path, sheetname=0, header=0, skiprows=None):  # , parse_dates=False):
      
      sheetname = sheetname or 0
      if isinstance(sheetname, (basestring, float)):
          try:
              sheetname = int(sheetname)
          except (TypeError, ValueError, OverflowError):
              sheetname = str(sheetname)
      wb = xlrd.open_workbook(path)
      # if isinstance(sheetname, int):
      #     sheet = wb.sheet_by_index(sheetname)
      # else:
      #     sheet = wb.sheet_by_name(sheetname)
      # assert(not parse_dates, "`parse_dates` argument and function not yet implemented!")
      # table = [sheet.row_values(i) for i in range(sheet.nrows)]
      return pd.io.excel.read_excel(wb, sheetname=sheetname, header=header, skiprows=skiprows, engine='xlrd')
docs: Thin wrapper for pandas.io.excel.read_excel() that accepts a file path and sheet index/name
  
      Arguments:
        path (str): file or folder to retrieve CSV files and `pandas.DataFrame`s from
        ext (str): file name extension (to filter files by)
        date_parser (function): if the MultiIndex can be interpretted as a datetime, this parser will be used
  
      Returns:
        dict of DataFrame: { file_path: flattened_data_frame }