Updated script that can be controled by Nodejs web app
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from datetime import datetime
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import pytest
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import pandas as pd
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from pandas import (
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Series,
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date_range,
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)
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import pandas._testing as tm
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class TestTruncate:
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def test_truncate_datetimeindex_tz(self):
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# GH 9243
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idx = date_range("4/1/2005", "4/30/2005", freq="D", tz="US/Pacific")
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s = Series(range(len(idx)), index=idx)
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with pytest.raises(TypeError, match="Cannot compare tz-naive"):
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# GH#36148 as of 2.0 we require tzawareness compat
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s.truncate(datetime(2005, 4, 2), datetime(2005, 4, 4))
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lb = idx[1]
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ub = idx[3]
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result = s.truncate(lb.to_pydatetime(), ub.to_pydatetime())
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expected = Series([1, 2, 3], index=idx[1:4])
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tm.assert_series_equal(result, expected)
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def test_truncate_periodindex(self):
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# GH 17717
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idx1 = pd.PeriodIndex(
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[pd.Period("2017-09-02"), pd.Period("2017-09-02"), pd.Period("2017-09-03")]
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)
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series1 = Series([1, 2, 3], index=idx1)
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result1 = series1.truncate(after="2017-09-02")
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expected_idx1 = pd.PeriodIndex(
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[pd.Period("2017-09-02"), pd.Period("2017-09-02")]
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)
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tm.assert_series_equal(result1, Series([1, 2], index=expected_idx1))
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idx2 = pd.PeriodIndex(
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[pd.Period("2017-09-03"), pd.Period("2017-09-02"), pd.Period("2017-09-03")]
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)
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series2 = Series([1, 2, 3], index=idx2)
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result2 = series2.sort_index().truncate(after="2017-09-02")
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expected_idx2 = pd.PeriodIndex([pd.Period("2017-09-02")])
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tm.assert_series_equal(result2, Series([2], index=expected_idx2))
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def test_truncate_one_element_series(self):
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# GH 35544
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series = Series([0.1], index=pd.DatetimeIndex(["2020-08-04"]))
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before = pd.Timestamp("2020-08-02")
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after = pd.Timestamp("2020-08-04")
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result = series.truncate(before=before, after=after)
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# the input Series and the expected Series are the same
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tm.assert_series_equal(result, series)
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def test_truncate_index_only_one_unique_value(self):
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# GH 42365
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obj = Series(0, index=date_range("2021-06-30", "2021-06-30")).repeat(5)
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truncated = obj.truncate("2021-06-28", "2021-07-01")
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tm.assert_series_equal(truncated, obj)
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