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@ -101,7 +101,8 @@ def test_merge_informative_pair_monthly():
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candle1 = result.loc[(result["date"] == "2022-12-31T22:00:00.000Z")]
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assert candle1.iloc[0]["date"] == pd.Timestamp("2022-12-31T22:00:00.000Z")
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assert candle1.iloc[0]["date_1M"] == pd.Timestamp("2022-11-01T00:00:00.000Z")
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assert candle1.iloc[0]["volume_1M"] == np.float64(199.11048557037446)
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prev_m_vol = informative.loc[informative["date"] == "2022-11-01T00:00:00.000", "volume"]
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assert candle1.iloc[0]["volume_1M"] == prev_m_vol.iloc[0]
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candle2 = result.loc[(result["date"] == "2022-12-31T23:00:00.000Z")]
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assert candle2.iloc[0]["date"] == pd.Timestamp("2022-12-31T23:00:00.000Z")
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@ -110,7 +111,8 @@ def test_merge_informative_pair_monthly():
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# Candle is empty, as the start-date did fail.
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candle3 = result.loc[(result["date"] == "2022-11-30T22:00:00.000Z")]
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assert candle3.iloc[0]["date"] == pd.Timestamp("2022-11-30T22:00:00.000Z")
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assert candle3.iloc[0]["volume_1M"] == np.float64(199.2462638356425)
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prev_m_vol = informative.loc[informative["date"] == "2022-10-01 00:00:00+00:00", "volume"]
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assert candle3.iloc[0]["volume_1M"] == prev_m_vol.iloc[0]
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# First candle with 1M data merged.
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candle4 = result.loc[(result["date"] == "2022-11-30T23:00:00.000Z")]
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