Got things to work finally.
Still things to do (one bug discovered, see TODOs)
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@ -3,7 +3,7 @@ import pandas as pd
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class SimpleStockData:
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def __init__(self, ticker_list: list, period_start: str, period_end: str, to_currency: str = ""):
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def __init__(self, ticker_list: list, period_start: str, period_end: str, to_currency: str, ohcl: str = "Close"):
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"""
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:param period_start:
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start date (format YYYY-MM-DD)
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@ -11,14 +11,16 @@ class SimpleStockData:
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end date (format YYYY-MM-DD)
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:param ticker_list:
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list containing all stocks/exchange rates (yfinance considers both as "Tickers")
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Example: []
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:param to_currency:
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currency to convert rates to
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currency to convert rates to (e.g. EUR)
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"""
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self.ticker_list = ticker_list
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self.to_currency = to_currency
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self.to_currency = to_currency.upper() # make it uppercase
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self._period_start = period_start
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self._period_end = period_end
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self._ohcl = ohcl.capitalize()
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self._exchange_df = None # Mapping: time mapped to conversion factor, to get the right converted value per date
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self._create_exchange_dataframe() # initialize self.exchange_df attribute
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@ -43,7 +45,7 @@ class SimpleStockData:
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The mapping is recreated by this function following the information in the
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_from_currency_list.
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return:
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boolean
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boolean - success or not
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"""
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# check if a to_currency is even given
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@ -54,26 +56,29 @@ class SimpleStockData:
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_from_currency_list = []
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for i in range(len(self.ticker_list)): # to get all indexes; this adds an entry for each currency
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add_currency = f"{self.get_info(i, 'currency')}{self.to_currency}=X" # Format: "fffttt=X" f=from, t=to
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add_currency = add_currency.upper() # make everything uppercase
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# for the case that FROM and TO are equal, just don't download the data (as conversion factor's 1)
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if add_currency == f"{self.to_currency}{self.to_currency}=X":
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pass
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elif add_currency not in _from_currency_list: # add a new item if not already there
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_from_currency_list.append(add_currency)
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print(_from_currency_list)
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# now the real process begins
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tickers = yf.Tickers(" ".join(_from_currency_list)) # create a new Ticker instance with all wanted currencies
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exchange_rates = []
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for i in tickers.tickers: # get all the history of each currency conversion factors
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# for simplicity: using the conversion factor of closing (.Close at the end)
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exchange_rates.append(tickers.tickers[i].history(start=self._period_start, end=self._period_end).Close)
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self._exchange_df = pd.DataFrame(
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exchange_rates).T # transpose the dataframe (imagine just switching rows and columns)
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self._exchange_df.columns = _from_currency_list # set the right names for the columns in the dataframe
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self._exchange_df[
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f"{self.to_currency}{self.to_currency}=X"] = 1.0 # for FROM and TO being equal: set factor to 1
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exchange_rates = [] # temporary variable where all exchange rates are stored in (as objects of pd.Series)
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for er_name in tickers.tickers: # get all the history of each currency conversion factors
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# for simplicity: using the conversion factor of closing (.Close at the end)
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exchange_rates.append((tickers.tickers[er_name].history(start=self._period_start, end=self._period_end)[self._ohcl], er_name))
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# now exchange_rates contains tuples of the form (ticker, er_name) where er_name is the name of the
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# currency ticker, used only internal in this method (_from_currency_list variable). The index is now taken
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# to set the right names for every row in the dataframe
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# now, the rates are taken from the exchange_rates list and are all wrapped up in a beautiful DataFrame
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self._exchange_df = pd.DataFrame()
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for exchange_rate, er_name in exchange_rates:
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self._exchange_df[er_name] = exchange_rate
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self._exchange_df[f"{self.to_currency}{self.to_currency}=X"] = 1.0 # for FROM and TO being equal: set factor to 1
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return True
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@ -102,20 +107,45 @@ class SimpleStockData:
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:param convert:
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decides if the resulting values should be converted to the specified to_convert currency (given at
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object creation)
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:return: pandas.DataFrame
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:return: pandas.DataFrame (with extra columns for the converted value if wanted)
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"""
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# TODO: Not working. Something is wrong with the access to the _exchange_df via [].
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result = self._get_history(idx, interval)
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result = self._get_history(idx, interval)[self._ohcl].to_frame()
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result["Ticker Index"] = idx
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ticker_currency = self.get_info(idx, "currency")
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ticker_currency = self.get_info(idx, "currency").upper() # upper it as sometimes it doesn't fit
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if convert:
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value_list = ["Open", "High", "Low", "Close"]
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for value in value_list:
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result["rating_name"] = f"{ticker_currency}{self.to_currency}=X"
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result["rating"] = self._exchange_df[f"{ticker_currency}{self.to_currency}=X"]
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result[f"{value}.conv"] = result[value] / result["rating"]
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exrate_name = f"{ticker_currency}{self.to_currency}=X"
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result["ex_rate_name"] = exrate_name
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ex_rate_series = self._exchange_df[exrate_name]
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# now there's a result dataframe with ticker, currency, rate name etc. as column names
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# to add only matching ex rates per day (sometimes there are more days with exchange rates recorded than
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# share prices), the result df has to be transposed so that the following function df.append can select
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# by columns. TODO: implement the bug fix when not the exact same timestamps and amount of data are given in both the series and the df
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"""
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result = result.T
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ex_rate_df = ex_rate_df.to_list()
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print(ex_rate_df)
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result.append(ex_rate_df[result.columns], ignore_index=True) # magic - see above :)
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result = result.T # transpose back
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result[f"{self._ohcl} in {self.to_currency}"] = result[self._ohcl] / result["ex_rate"]
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"""
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result["ex_rate"] = ex_rate_series.to_list()
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result[f"{self._ohcl} in {self.to_currency}"] = result[self._ohcl] / result["ex_rate"]
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return result
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def test():
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ssd = SimpleStockData(["RHM.DE", "BAS.DE", "AZN.L"], "2024-01-02", "2024-01-18", "EUR")
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print(ssd.get_info(0))
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print(ssd.get_info(1))
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print(ssd.get_info(2))
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print(ssd.get_history(0))
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print(ssd.get_history(1))
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print(ssd.get_history(2))
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