Pinned Loading

1. simulation_stock.py simulation_stock.py

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   number_of_samples = 10

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   historical_result = list()

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   n_iterations = 100

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   def get_sample(population, number_of_samples):

2. frame_ticker.py frame_ticker.py

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   frame_ticker = frame[['ticker', 'date']].groupby('ticker').agg(['min', 'max']).reset_index()

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   frame_ticker.columns = ['_'.join(col) for col in frame_ticker.columns.values]

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   frame_ticker.rename(columns={'ticker_':'ticker'}, inplace=True)

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   frame_ticker = pd.merge(

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       frame_ticker,

3. frame_week.py frame_week.py

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   #create column with year and week year number

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   frame['year_week'] = frame['date'].apply(lambda x: str(x.isocalendar()[0])+'_'+str(x.isocalendar()[1]))

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   #create a copy of dataframe to be used and get week initial and final day

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   frame_week = frame[['ticker', 'year_week', 'date']].groupby(['ticker', 'year_week']).agg(['min', 'max'])

4. sep500_analysis sep500_analysis Public

   Jupyter Notebook