[Enhancement] Add new daily and IEX methods following the Tiingo API more closely about tiingo-python HOT 8 OPEN

# Get Daily Data
def get_daily_data(self, tickers,
                  startDate=None, endDate=None, metric_name=None,
                  frequency='daily', fmt='csv'):

    """ Returns historical prices for one or more ticker symbols.

        By default, return latest EOD Composite Adjusted Closing Price for a list of stock tickers.
        On average, each feed contains 3 data sources.

        Supported tickers + Available Day Ranges are here:
        https://apimedia.tiingo.com/docs/tiingo/daily/supported_tickers.zip
        or from the TiingoClient.list_tickers() method.

        Args:
            tickers (string/list): One or more unique identifiers for a stock ticker.
            startDate (string): Start of ticker range in YYYY-MM-DD format.
            endDate (string): End of ticker range in YYYY-MM-DD format.
            metric_name (string): Optional parameter specifying metric to be returned for each
                ticker.  In the event of a single ticker, this is optional and if not specified
                all of the available data will be returned.  In the event of a list of tickers,
                this parameter is required.
            frequency (string): Resample frequency (defaults to daily).
            fmt (string): 'csv' or 'json'
    """
    valid_columns = {'open', 'high', 'low', 'close', 'volume', 'adjOpen', 'adjHigh', 'adjLow',
                     'adjClose', 'adjVolume', 'divCash', 'splitFactor'}

    if metric_name is not None and metric_name not in valid_columns:
        raise APIColumnNameError('Valid data items are: ' + str(valid_columns))

    if metric_name is None and isinstance(tickers, list):
        raise MissingRequiredArgumentError("""When tickers is provided as a list, metric_name is a required argument.
        Please provide a metric_name, or call this method with one ticker at a time.""")

    params = {
        'format': fmt,
        'resampleFreq': frequency
    }
    if startDate:
        params['startDate'] = startDate
    if endDate:
        params['endDate'] = endDate

    if pandas_is_installed:
        if type(tickers) is str:
            prices = self._request_pandas(
                ticker=tickers, params=params, metric_name=metric_name)
        else:
            prices = pd.DataFrame()
            for stock in tickers:
                ticker_series = self._request_pandas(
                    ticker=stock, params=params, metric_name=metric_name)
                ticker_series = ticker_series.rename(stock)
                prices = pd.concat([prices, ticker_series], axis=1, sort=True)

        return prices

    else:
        error_message = ("Pandas is not installed, but .get_ticker_price() was "
                         "called with fmt=pandas.  In order to install tiingo with "
                         "pandas, reinstall with pandas as an optional dependency. \n"
                         "Install tiingo with pandas dependency: \'pip install tiingo[pandas]\'\n"
                         "Alternatively, just install pandas: pip install pandas.")
        raise InstallPandasException(error_message)

def get_iex_data(self, tickers,
                  startDate=None, endDate=None, metric_name=None,
                  frequency='1hour', fmt='csv'):

    """ Return a pandas.DataFrame of historical prices for one or more ticker symbols.

        By default, return latest EOD Composite Price for a list of stock tickers.
        On average, each feed contains 3 data sources.

        Supported tickers + Available Day Ranges are here:
        https://apimedia.tiingo.com/docs/tiingo/daily/supported_tickers.zip
        or from the TiingoClient.list_tickers() method.

        Args:
            tickers (string/list): One or more unique identifiers for a stock ticker.
            startDate (string): Start of ticker range in YYYY-MM-DD format.
            endDate (string): End of ticker range in YYYY-MM-DD format.
            metric_name (string): Optional parameter specifying metric to be returned for each
                ticker.  In the event of a single ticker, this is optional and if not specified
                all of the available data will be returned.  In the event of a list of tickers,
                this parameter is required.
            frequency (string): Resample frequency (defaults to daily).
            fmt (string): 'csv' or 'json'
    """

    valid_columns = {'open', 'high', 'low', 'close', 'volume'}

    if metric_name is not None and metric_name not in valid_columns:
        raise APIColumnNameError('Valid data items are: ' + str(valid_columns))

    if metric_name is None and isinstance(tickers, list):
        raise MissingRequiredArgumentError("""When tickers is provided as a list, metric_name is a required argument.
        Please provide a metric_name, or call this method with one ticker at a time.""")

    params = {
        'format': fmt,
        'resampleFreq': frequency
    }
    if startDate:
        params['startDate'] = startDate
    if endDate:
        params['endDate'] = endDate

    if pandas_is_installed:
        if type(tickers) is str:
            prices = self._request_pandas(
                ticker=tickers, params=params, metric_name=metric_name)
        else:
            prices = pd.DataFrame()
            for stock in tickers:
                ticker_series = self._request_pandas(
                    ticker=stock, params=params, metric_name=metric_name)
                ticker_series = ticker_series.rename(stock)
                prices = pd.concat([prices, ticker_series], axis=1, sort=True)

        return prices

    else:
        error_message = ("Pandas is not installed, but .get_ticker_price() was "
                         "called with fmt=pandas.  In order to install tiingo with "
                         "pandas, reinstall with pandas as an optional dependency. \n"
                         "Install tiingo with pandas dependency: \'pip install tiingo[pandas]\'\n"
                         "Alternatively, just install pandas: pip install pandas.")
        raise InstallPandasException(error_message)

def get_iex_data(self, tickers,
                  startDate=None, endDate=None, metric_name=None, afterHours='false',
                  frequency='1hour', fmt='csv'):

    """ Return a pandas.DataFrame of historical prices for one or more ticker symbols.

        By default, return latest EOD Composite Price for a list of stock tickers.
        On average, each feed contains 3 data sources.

        Supported tickers + Available Day Ranges are here:
        https://apimedia.tiingo.com/docs/tiingo/daily/supported_tickers.zip
        or from the TiingoClient.list_tickers() method.

        Args:
            tickers (string/list): One or more unique identifiers for a stock ticker.
            startDate (string): Start of ticker range in YYYY-MM-DD format.
            endDate (string): End of ticker range in YYYY-MM-DD format.
            metric_name (string): Optional parameter specifying metric to be returned for each
                ticker.  In the event of a single ticker, this is optional and if not specified
                all of the available data will be returned.  In the event of a list of tickers,
                this parameter is required.
            afterHours (boolean): Optional parameter that selects whether to include extended hours quotes NOTE: MUST BE LOWERCASE
                                  AND THEREFORE ENCAPSULTED, e.g. 'true' or 'false'
            frequency (string): Resample frequency (defaults to daily).
            fmt (string): 'csv' or 'json'
    """

    valid_columns = {'open', 'high', 'low', 'close', 'volume'}

    if metric_name is not None and metric_name not in valid_columns:
        raise APIColumnNameError('Valid data items are: ' + str(valid_columns))

    if metric_name is None and isinstance(tickers, list):
        raise MissingRequiredArgumentError("""When tickers is provided as a list, metric_name is a required argument.
        Please provide a metric_name, or call this method with one ticker at a time.""")

    params = {
        'format': fmt,
        'resampleFreq': frequency,
        'afterHours': afterHours
    }
    if startDate:
        params['startDate'] = startDate
    if endDate:
        params['endDate'] = endDate

    if pandas_is_installed:
        if type(tickers) is str:
            prices = self._request_pandas(
                ticker=tickers, params=params, metric_name=metric_name)
        else:
            prices = pd.DataFrame()
            for stock in tickers:
                ticker_series = self._request_pandas(
                    ticker=stock, params=params, metric_name=metric_name)
                ticker_series = ticker_series.rename(stock)
                prices = pd.concat([prices, ticker_series], axis=1, sort=True)

        return prices

    else:
        error_message = ("Pandas is not installed, but .get_ticker_price() was "
                         "called with fmt=pandas.  In order to install tiingo with "
                         "pandas, reinstall with pandas as an optional dependency. \n"
                         "Install tiingo with pandas dependency: \'pip install tiingo[pandas]\'\n"
                         "Alternatively, just install pandas: pip install pandas.")
        raise InstallPandasException(error_message)