124 lines
3.8 KiB
Python
124 lines
3.8 KiB
Python
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import numpy as np
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import pytest
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from pandas._libs.tslibs import iNaT
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from pandas._libs.tslibs.period import IncompatibleFrequency
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import pandas as pd
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import pandas._testing as tm
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from pandas.core.arrays import (
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PeriodArray,
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period_array,
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)
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@pytest.mark.parametrize(
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"data, freq, expected",
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[
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([pd.Period("2017", "D")], None, [17167]),
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([pd.Period("2017", "D")], "D", [17167]),
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([2017], "D", [17167]),
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(["2017"], "D", [17167]),
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([pd.Period("2017", "D")], pd.tseries.offsets.Day(), [17167]),
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([pd.Period("2017", "D"), None], None, [17167, iNaT]),
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(pd.Series(pd.date_range("2017", periods=3)), None, [17167, 17168, 17169]),
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(pd.date_range("2017", periods=3), None, [17167, 17168, 17169]),
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(pd.period_range("2017", periods=4, freq="Q"), None, [188, 189, 190, 191]),
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],
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)
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def test_period_array_ok(data, freq, expected):
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result = period_array(data, freq=freq).asi8
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expected = np.asarray(expected, dtype=np.int64)
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tm.assert_numpy_array_equal(result, expected)
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def test_period_array_readonly_object():
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# https://github.com/pandas-dev/pandas/issues/25403
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pa = period_array([pd.Period("2019-01-01")])
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arr = np.asarray(pa, dtype="object")
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arr.setflags(write=False)
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result = period_array(arr)
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tm.assert_period_array_equal(result, pa)
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result = pd.Series(arr)
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tm.assert_series_equal(result, pd.Series(pa))
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result = pd.DataFrame({"A": arr})
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tm.assert_frame_equal(result, pd.DataFrame({"A": pa}))
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def test_from_datetime64_freq_changes():
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# https://github.com/pandas-dev/pandas/issues/23438
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arr = pd.date_range("2017", periods=3, freq="D")
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result = PeriodArray._from_datetime64(arr, freq="M")
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expected = period_array(["2017-01-01", "2017-01-01", "2017-01-01"], freq="M")
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tm.assert_period_array_equal(result, expected)
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@pytest.mark.parametrize(
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"data, freq, msg",
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[
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(
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[pd.Period("2017", "D"), pd.Period("2017", "A")],
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None,
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"Input has different freq",
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),
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([pd.Period("2017", "D")], "A", "Input has different freq"),
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],
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)
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def test_period_array_raises(data, freq, msg):
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with pytest.raises(IncompatibleFrequency, match=msg):
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period_array(data, freq)
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def test_period_array_non_period_series_raies():
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ser = pd.Series([1, 2, 3])
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with pytest.raises(TypeError, match="dtype"):
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PeriodArray(ser, freq="D")
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def test_period_array_freq_mismatch():
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arr = period_array(["2000", "2001"], freq="D")
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with pytest.raises(IncompatibleFrequency, match="freq"):
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PeriodArray(arr, freq="M")
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with pytest.raises(IncompatibleFrequency, match="freq"):
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PeriodArray(arr, freq=pd.tseries.offsets.MonthEnd())
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def test_from_sequence_disallows_i8():
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arr = period_array(["2000", "2001"], freq="D")
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msg = str(arr[0].ordinal)
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with pytest.raises(TypeError, match=msg):
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PeriodArray._from_sequence(arr.asi8, dtype=arr.dtype)
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with pytest.raises(TypeError, match=msg):
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PeriodArray._from_sequence(list(arr.asi8), dtype=arr.dtype)
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def test_from_td64nat_sequence_raises():
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# GH#44507
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td = pd.NaT.to_numpy("m8[ns]")
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dtype = pd.period_range("2005-01-01", periods=3, freq="D").dtype
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arr = np.array([None], dtype=object)
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arr[0] = td
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msg = "Value must be Period, string, integer, or datetime"
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with pytest.raises(ValueError, match=msg):
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PeriodArray._from_sequence(arr, dtype=dtype)
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with pytest.raises(ValueError, match=msg):
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pd.PeriodIndex(arr, dtype=dtype)
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with pytest.raises(ValueError, match=msg):
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pd.Index(arr, dtype=dtype)
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with pytest.raises(ValueError, match=msg):
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pd.array(arr, dtype=dtype)
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with pytest.raises(ValueError, match=msg):
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pd.Series(arr, dtype=dtype)
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with pytest.raises(ValueError, match=msg):
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pd.DataFrame(arr, dtype=dtype)
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