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52 lines
1.3 KiB
52 lines
1.3 KiB
import time
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from fincal.fincal import TimeSeries
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# start = time.time()
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# dfd = pd.read_csv("test_files/msft.csv") # , dtype=dict(nav=str))
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# # dfd = dfd[dfd["amfi_code"] == 118825].reset_index(drop=True)
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# print("instantiation took", round((time.time() - start) * 1000, 2), "ms")
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# ts = TimeSeries([(i.date, i.nav) for i in dfd.itertuples()], frequency="D")
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# print(repr(ts))
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start = time.time()
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# mdd = ts.max_drawdown()
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# print(mdd)
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# print("max drawdown calc took", round((time.time() - start) * 1000, 2), "ms")
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# # print(ts[['2022-01-31', '2021-05-28']])
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# rr = ts.calculate_rolling_returns(
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# from_date='2021-01-01',
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# to_date='2022-01-01',
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# frequency='D',
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# interval_type='days',
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# interval_value=30,
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# compounding=False
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# )
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data = [
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("2022-01-01", 10),
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# ("2022-01-08", 12),
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("2022-01-15", 14),
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("2022-01-22", 16)
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# ("2020-02-07", 18),
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# ("2020-02-14", 20),
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# ("2020-02-21", 22),
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# ("2020-02-28", 24),
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# ("2020-03-01", 26),
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# ("2020-03-01", 28),
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# ("2020-03-01", 30),
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# ("2020-03-01", 32),
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# ("2021-03-01", 34),
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]
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ts = TimeSeries(data, "W")
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# ts_expanded = ts.expand("D", "ffill", skip_weekends=True)
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# for i in ts_expanded:
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# print(i)
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print(ts.get("2022-01-01"))
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print(ts.ffill())
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