尝试遍历股票价格时出现 Python 错误关闭

Question

I am trying to loop through stock price csvs in order to add columns such as portfolio weight etc. in order to build a portfolio to analyse in one dataframe. When looping however, I get an error which I do not understand:

gsk_df = web.DataReader("GSK.L", 'yahoo', start=start, end=end)
ocdo_df = web.DataReader("OCDO.L", 'yahoo', start=start, end=end)
rbs_df = web.DataReader("RBS.L", 'yahoo', start=start, end=end)
svt_df = web.DataReader("SVT.L", 'yahoo', start=start, end=end)
iii_df = pd.read_csv("iii (1).csv", parse_dates=['Date'])

#close of each stock

bp_close = bp_df["Adj Close"]
gsk_close = gsk_df["Adj Close"]
ocdo_close = ocdo_df["Adj Close"]
rbs_close = rbs_df["Adj Close"]
svt_close = svt_df["Adj Close"]
iii_close = iii_df["Adj Close"]


#adding normalised returns for portfolio
for stock_df in (bp_close, gsk_close, ocdo_close, rbs_close, svt_close, iii_close):
    stock_df['Norm return'] = stock_df['Adj Close']/stock_df.iloc[0]['Adj Close']

#adding portfolio weights

for stock_df, allocation in zip((bp_close, gsk_close, ocdo_close, rbs_close, svt_close, iii_close),[.0881,.233,.160,.0776,.304,.137]):
    stock_df['Allocation']=stock_df['Norm return']*allocation

#portfolio position value column
for stock_df in (bp_close, gsk_close, ocdo_close, rbs_close, svt_close, iii_close):
    stock_df['Position'] = stock_df['Allocation']*6503800000

print(bp_close.head())

Here is the error:

runfile('C:/Users/Joe Shiafa Pierce/.spyder-py3/portfolio.py', wdir='C:/Users/Joe Shiafa Pierce/.spyder-py3')
Traceback (most recent call last):

  File "<ipython-input-82-6a3db40a9a10>", line 1, in <module>
    runfile('C:/Users/Joe Shiafa Pierce/.spyder-py3/portfolio.py', wdir='C:/Users/Joe Shiafa Pierce/.spyder-py3')

  File "C:\Users\Joe Shiafa Pierce\Anaconda3\lib\site-packages\spyder_kernels\customize\spydercustomize.py", line 786, in runfile
    execfile(filename, namespace)

  File "C:\Users\Joe Shiafa Pierce\Anaconda3\lib\site-packages\spyder_kernels\customize\spydercustomize.py", line 110, in execfile
    exec(compile(f.read(), filename, 'exec'), namespace)

  File "C:/Users/Joe Shiafa Pierce/.spyder-py3/portfolio.py", line 34, in <module>
    stock_df['Norm return'] = stock_df['Adj Close']/stock_df.iloc[0]['Adj Close']

  File "C:\Users\Joe Shiafa Pierce\Anaconda3\lib\site-packages\pandas\core\series.py", line 868, in __getitem__
    result = self.index.get_value(self, key)

  File "C:\Users\Joe Shiafa Pierce\Anaconda3\lib\site-packages\pandas\core\indexes\datetimes.py", line 958, in get_value
    raise KeyError(key)

KeyError: 'Adj Close'

I had to change the "Adjusted_close" heading to "Adj close" in the iii csv as it was from another data set and the for loop would not function with different column headers. Thanks for the help.

Answer 1

assuming these series have the stock as their column name, you can avoid the loops by concatenating them into a dataframe and avoiding the KeyError

stocks = ['GSK.L', 'OCDO.L', 'RBS.L', 'SVT.L']
df = web.DataReader(stocks, 'yahoo',start,end).reset_index(drop=True)
iii_df = pd.read_csv("iii (1).csv", parse_dates=['Date']) # reset_index if needed

stock_df = pd.concat([df, iii_close], axis=1, ignore_index=True)
stock_df['Norm return'] = stock_df / stock_df.loc[0]
stock_df['Allocation'] = stock_df['Norm return'] * [.0881,.233,.160,.0776,.304,.137]
stock_df['Position'] = stock_df['Allocation'] * 6503800000