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26 lines
959 B
26 lines
959 B
import datetime
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import time
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import timeit
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import pandas
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from pyfacts.pyfacts import AllFrequencies, TimeSeries, create_date_series
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dfd = pandas.read_csv("test_files/msft.csv")
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dfm = pandas.read_csv("test_files/nav_history_monthly.csv")
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dfq = pandas.read_csv("test_files/nav_history_quarterly.csv")
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data_d = [(i.date, i.nav) for i in dfd.itertuples()]
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data_m = [{"date": i.date, "value": i.nav} for i in dfm.itertuples()]
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data_q = {i.date: i.nav for i in dfq.itertuples()}
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data_q.update({"14-02-2022": 93.7})
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tsd = TimeSeries(data_d, frequency="D")
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tsm = TimeSeries(data_m, frequency="M", date_format="%d-%m-%Y")
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tsq = TimeSeries(data_q, frequency="Q", date_format="%d-%m-%Y")
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start = time.time()
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# ts.calculate_rolling_returns(datetime.datetime(2015, 1, 1), datetime.datetime(2022, 2, 1), years=1)
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bdata = tsq.bfill()
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# rr = tsd.calculate_rolling_returns(datetime.datetime(2022, 1, 1), datetime.datetime(2022, 2, 1), years=1)
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print(time.time() - start)
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