How to use the investpy.Data.Data function in investpy

for elements_ in path_:
            info = []
            for nested_ in elements_.xpath(".//td"):
                info.append(nested_.text_content())

            if info[0] == 'No se encontraron resultados':
                raise IndexError("ERR#0010: etf information unavailable or not found.")

            etf_date = datetime.datetime.strptime(info[0].replace('.', '-'), '%d-%m-%Y')
            etf_close = float(info[1].replace('.', '').replace(',', '.'))
            etf_open = float(info[2].replace('.', '').replace(',', '.'))
            etf_high = float(info[3].replace('.', '').replace(',', '.'))
            etf_low = float(info[4].replace('.', '').replace(',', '.'))

            result.insert(len(result), Data(etf_date, etf_open, etf_high, etf_low, etf_close, None, etf_currency))

        if order in ['ascending', 'asc']:
            result = result[::-1]
        elif order in ['descending', 'desc']:
            result = result

        logger.info('Data parsing process finished...')

        if as_json is True:
            json_ = {'name': name,
                     'recent':
                         [value.etf_as_json() for value in result]
                     }

            return json.dumps(json_, sort_keys=False)
        elif as_json is False:

stock_close = float(info[1].replace('.', '').replace(',', '.'))
                    stock_open = float(info[2].replace('.', '').replace(',', '.'))
                    stock_high = float(info[3].replace('.', '').replace(',', '.'))
                    stock_low = float(info[4].replace('.', '').replace(',', '.'))

                    stock_volume = 0

                    if info[5].__contains__('K'):
                        stock_volume = int(float(info[5].replace('K', '').replace('.', '').replace(',', '.')) * 1000)
                    elif info[5].__contains__('M'):
                        stock_volume = int(float(info[5].replace('M', '').replace('.', '').replace(',', '.')) * 1000000)
                    elif info[5].__contains__('B'):
                        stock_volume = int(float(info[5].replace('B', '').replace('.', '').replace(',', '.')) * 1000000000)

                    result.insert(len(result),
                                  Data(stock_date, stock_open, stock_high, stock_low,
                                       stock_close, stock_volume, stock_currency))

            if data_flag is True:
                if order in ['ascending', 'asc']:
                    result = result[::-1]
                elif order in ['descending', 'desc']:
                    result = result

                if as_json is True:
                    json_ = {'name': name,
                             'historical':
                                 [value.equity_as_json() for value in result]
                             }
                    final.append(json_)
                elif as_json is False:
                    df = pd.DataFrame.from_records([value.equity_to_dict() for value in result])

stock_close = float(info[1].replace('.', '').replace(',', '.'))
            stock_open = float(info[2].replace('.', '').replace(',', '.'))
            stock_high = float(info[3].replace('.', '').replace(',', '.'))
            stock_low = float(info[4].replace('.', '').replace(',', '.'))

            stock_volume = 0

            if info[5].__contains__('K'):
                stock_volume = int(float(info[5].replace('K', '').replace('.', '').replace(',', '.')) * 1000)
            elif info[5].__contains__('M'):
                stock_volume = int(float(info[5].replace('M', '').replace('.', '').replace(',', '.')) * 1000000)
            elif info[5].__contains__('B'):
                stock_volume = int(float(info[5].replace('B', '').replace('.', '').replace(',', '.')) * 1000000000)

            result.insert(len(result),
                          Data(stock_date, stock_open, stock_high, stock_low,
                               stock_close, stock_volume, stock_currency))

        if order in ['ascending', 'asc']:
            result = result[::-1]
        elif order in ['descending', 'desc']:
            result = result

        logger.info('Data parsing process finished...')

        if as_json is True:
            json_ = {'name': name,
                     'recent':
                         [value.equity_as_json() for value in result]
                     }

            return json.dumps(json_, sort_keys=False)

if interval_counter < interval_limit:
                        data_flag = False
                    else:
                        raise IndexError("ERR#0010: etf information unavailable or not found.")
                else:
                    data_flag = True

                if data_flag is True:
                    etf_date = datetime.datetime.strptime(info[0].replace('.', '-'), '%d-%m-%Y')
                    etf_close = float(info[1].replace('.', '').replace(',', '.'))
                    etf_open = float(info[2].replace('.', '').replace(',', '.'))
                    etf_high = float(info[3].replace('.', '').replace(',', '.'))
                    etf_low = float(info[4].replace('.', '').replace(',', '.'))

                    result.insert(len(result),
                                  Data(etf_date, etf_open, etf_high, etf_low, etf_close, None, etf_currency))

            if data_flag is True:
                if order in ['ascending', 'asc']:
                    result = result[::-1]
                elif order in ['descending', 'desc']:
                    result = result

                if as_json is True:
                    json_ = {'name': name,
                             'historical':
                                 [value.etf_as_json() for value in result]
                             }

                    final.append(json_)
                elif as_json is False:
                    df = pd.DataFrame.from_records([value.etf_to_dict() for value in result])

for elements_ in path_:
            info = []
            for nested_ in elements_.xpath(".//td"):
                info.append(nested_.text_content())

            if info[0] == 'No se encontraron resultados':
                raise IndexError("ERR#0008: fund information unavailable or not found.")

            fund_date = datetime.datetime.strptime(info[0].replace('.', '-'), '%d-%m-%Y')
            fund_close = float(info[1].replace('.', '').replace(',', '.'))
            fund_open = float(info[2].replace('.', '').replace(',', '.'))
            fund_high = float(info[3].replace('.', '').replace(',', '.'))
            fund_low = float(info[4].replace('.', '').replace(',', '.'))

            result.insert(len(result), Data(fund_date, fund_open, fund_high, fund_low,
                                            fund_close, None, fund_currency))

        if order in ['ascending', 'asc']:
            result = result[::-1]
        elif order in ['descending', 'desc']:
            result = result

        logger.info('Data parsing process finished...')

        if as_json is True:
            json_ = {'name': name,
                     'recent':
                         [value.fund_as_json() for value in result]
                     }

            return json.dumps(json_, sort_keys=False)

if interval_counter < interval_limit:
                        data_flag = False
                    else:
                        raise IndexError("ERR#0008: fund information unavailable or not found.")

                else:
                    data_flag = True

                if data_flag is True:
                    fund_date = datetime.datetime.strptime(info[0].replace('.', '-'), '%d-%m-%Y')
                    fund_close = float(info[1].replace('.', '').replace(',', '.'))
                    fund_open = float(info[2].replace('.', '').replace(',', '.'))
                    fund_high = float(info[3].replace('.', '').replace(',', '.'))
                    fund_low = float(info[4].replace('.', '').replace(',', '.'))

                    result.insert(len(result), Data(fund_date, fund_open, fund_high, fund_low,
                                                    fund_close, None, fund_currency))

            if data_flag is True:
                if order in ['ascending', 'asc']:
                    result = result[::-1]
                elif order in ['descending', 'desc']:
                    result = result

                if as_json is True:
                    json_ = {'name': name,
                             'historical':
                                 [value.fund_as_json() for value in result]
                             }

                    final.append(json_)
                elif as_json is False: