Python pandas.Period方法代码示例

# 需要导入模块: import pandas [as 别名]
# 或者: from pandas import Period [as 别名]
def test_parameter_array_indexed(simple_linear_model):
    """
    Test ArrayIndexedParameter

    """
    model = simple_linear_model
    A = np.arange(len(model.timestepper), dtype=np.float64)
    p = ArrayIndexedParameter(model, A)
    model.setup()
    # scenario indices (not used for this test)
    si = ScenarioIndex(0, np.array([0], dtype=np.int32))
    for v, ts in zip(A, model.timestepper):
        np.testing.assert_allclose(p.value(ts, si), v)

    # Now check that IndexError is raised if an out of bounds Timestep is given.
    ts = Timestep(pd.Period('2016-01-01', freq='1D'), 366, 1)
    with pytest.raises(IndexError):
        p.value(ts, si) 

# 需要导入模块: import pandas [as 别名]
# 或者: from pandas import Period [as 别名]
def test_min_max(self):
        arr = period_array([
            '2000-01-03',
            '2000-01-03',
            'NaT',
            '2000-01-02',
            '2000-01-05',
            '2000-01-04',
        ], freq='D')

        result = arr.min()
        expected = pd.Period('2000-01-02', freq='D')
        assert result == expected

        result = arr.max()
        expected = pd.Period('2000-01-05', freq='D')
        assert result == expected

        result = arr.min(skipna=False)
        assert result is pd.NaT

        result = arr.max(skipna=False)
        assert result is pd.NaT 

# 需要导入模块: import pandas [as 别名]
# 或者: from pandas import Period [as 别名]
def test_take_fill_valid(self, datetime_index, tz_naive_fixture):
        dti = datetime_index.tz_localize(tz_naive_fixture)
        arr = DatetimeArray(dti)

        now = pd.Timestamp.now().tz_localize(dti.tz)
        result = arr.take([-1, 1], allow_fill=True, fill_value=now)
        assert result[0] == now

        with pytest.raises(ValueError):
            # fill_value Timedelta invalid
            arr.take([-1, 1], allow_fill=True, fill_value=now - now)

        with pytest.raises(ValueError):
            # fill_value Period invalid
            arr.take([-1, 1], allow_fill=True, fill_value=pd.Period('2014Q1'))

        tz = None if dti.tz is not None else 'US/Eastern'
        now = pd.Timestamp.now().tz_localize(tz)
        with pytest.raises(TypeError):
            # Timestamp with mismatched tz-awareness
            arr.take([-1, 1], allow_fill=True, fill_value=now)

        with pytest.raises(ValueError):
            # require NaT, not iNaT, as it could be confused with an integer
            arr.take([-1, 1], allow_fill=True, fill_value=pd.NaT.value) 

# 需要导入模块: import pandas [as 别名]
# 或者: from pandas import Period [as 别名]
def test_is_monotonic_increasing(self):
        # GH 17717
        p0 = pd.Period('2017-09-01')
        p1 = pd.Period('2017-09-02')
        p2 = pd.Period('2017-09-03')

        idx_inc0 = pd.PeriodIndex([p0, p1, p2])
        idx_inc1 = pd.PeriodIndex([p0, p1, p1])
        idx_dec0 = pd.PeriodIndex([p2, p1, p0])
        idx_dec1 = pd.PeriodIndex([p2, p1, p1])
        idx = pd.PeriodIndex([p1, p2, p0])

        assert idx_inc0.is_monotonic_increasing is True
        assert idx_inc1.is_monotonic_increasing is True
        assert idx_dec0.is_monotonic_increasing is False
        assert idx_dec1.is_monotonic_increasing is False
        assert idx.is_monotonic_increasing is False 

# 需要导入模块: import pandas [as 别名]
# 或者: from pandas import Period [as 别名]
def test_is_monotonic_decreasing(self):
        # GH 17717
        p0 = pd.Period('2017-09-01')
        p1 = pd.Period('2017-09-02')
        p2 = pd.Period('2017-09-03')

        idx_inc0 = pd.PeriodIndex([p0, p1, p2])
        idx_inc1 = pd.PeriodIndex([p0, p1, p1])
        idx_dec0 = pd.PeriodIndex([p2, p1, p0])
        idx_dec1 = pd.PeriodIndex([p2, p1, p1])
        idx = pd.PeriodIndex([p1, p2, p0])

        assert idx_inc0.is_monotonic_decreasing is False
        assert idx_inc1.is_monotonic_decreasing is False
        assert idx_dec0.is_monotonic_decreasing is True
        assert idx_dec1.is_monotonic_decreasing is True
        assert idx.is_monotonic_decreasing is False 

# 需要导入模块: import pandas [as 别名]
# 或者: from pandas import Period [as 别名]
def test_contains(self):
        # GH 17717
        p0 = pd.Period('2017-09-01')
        p1 = pd.Period('2017-09-02')
        p2 = pd.Period('2017-09-03')
        p3 = pd.Period('2017-09-04')

        ps0 = [p0, p1, p2]
        idx0 = pd.PeriodIndex(ps0)

        for p in ps0:
            assert idx0.contains(p)
            assert p in idx0

            assert idx0.contains(str(p))
            assert str(p) in idx0

        assert idx0.contains('2017-09-01 00:00:01')
        assert '2017-09-01 00:00:01' in idx0

        assert idx0.contains('2017-09')
        assert '2017-09' in idx0

        assert not idx0.contains(p3)
        assert p3 not in idx0 

# 需要导入模块: import pandas [as 别名]
# 或者: from pandas import Period [as 别名]
def test_get_indexer_non_unique(self):
        # GH 17717
        p1 = pd.Period('2017-09-02')
        p2 = pd.Period('2017-09-03')
        p3 = pd.Period('2017-09-04')
        p4 = pd.Period('2017-09-05')

        idx1 = pd.PeriodIndex([p1, p2, p1])
        idx2 = pd.PeriodIndex([p2, p1, p3, p4])

        result = idx1.get_indexer_non_unique(idx2)
        expected_indexer = np.array([1, 0, 2, -1, -1], dtype=np.intp)
        expected_missing = np.array([2, 3], dtype=np.int64)

        tm.assert_numpy_array_equal(result[0], expected_indexer)
        tm.assert_numpy_array_equal(result[1], expected_missing)

    # TODO: This method came from test_period; de-dup with version above 

# 需要导入模块: import pandas [as 别名]
# 或者: from pandas import Period [as 别名]
def test_construction_base_constructor(self):
        # GH 13664
        arr = [pd.Period('2011-01', freq='M'), pd.NaT,
               pd.Period('2011-03', freq='M')]
        tm.assert_index_equal(pd.Index(arr), pd.PeriodIndex(arr))
        tm.assert_index_equal(pd.Index(np.array(arr)),
                              pd.PeriodIndex(np.array(arr)))

        arr = [np.nan, pd.NaT, pd.Period('2011-03', freq='M')]
        tm.assert_index_equal(pd.Index(arr), pd.PeriodIndex(arr))
        tm.assert_index_equal(pd.Index(np.array(arr)),
                              pd.PeriodIndex(np.array(arr)))

        arr = [pd.Period('2011-01', freq='M'), pd.NaT,
               pd.Period('2011-03', freq='D')]
        tm.assert_index_equal(pd.Index(arr), pd.Index(arr, dtype=object))

        tm.assert_index_equal(pd.Index(np.array(arr)),
                              pd.Index(np.array(arr), dtype=object)) 

# 需要导入模块: import pandas [as 别名]
# 或者: from pandas import Period [as 别名]
def test_constructor_incompat_freq(self):
        msg = "Input has different freq=D from PeriodIndex\\(freq=M\\)"

        with pytest.raises(period.IncompatibleFrequency, match=msg):
            PeriodIndex([Period('2011-01', freq='M'), pd.NaT,
                         Period('2011-01', freq='D')])

        with pytest.raises(period.IncompatibleFrequency, match=msg):
            PeriodIndex(np.array([Period('2011-01', freq='M'), pd.NaT,
                                  Period('2011-01', freq='D')]))

        # first element is pd.NaT
        with pytest.raises(period.IncompatibleFrequency, match=msg):
            PeriodIndex([pd.NaT, Period('2011-01', freq='M'),
                         Period('2011-01', freq='D')])

        with pytest.raises(period.IncompatibleFrequency, match=msg):
            PeriodIndex(np.array([pd.NaT, Period('2011-01', freq='M'),
                                  Period('2011-01', freq='D')])) 

# 需要导入模块: import pandas [as 别名]
# 或者: from pandas import Period [as 别名]
def test_negone_ordinals(self):
        freqs = ['A', 'M', 'Q', 'D', 'H', 'T', 'S']

        period = Period(ordinal=-1, freq='D')
        for freq in freqs:
            repr(period.asfreq(freq))

        for freq in freqs:
            period = Period(ordinal=-1, freq=freq)
            repr(period)
            assert period.year == 1969

        period = Period(ordinal=-1, freq='B')
        repr(period)
        period = Period(ordinal=-1, freq='W')
        repr(period) 

# 需要导入模块: import pandas [as 别名]
# 或者: from pandas import Period [as 别名]
def test_dti_to_period(self):
        dti = pd.date_range(start='1/1/2005', end='12/1/2005', freq='M')
        pi1 = dti.to_period()
        pi2 = dti.to_period(freq='D')
        pi3 = dti.to_period(freq='3D')

        assert pi1[0] == Period('Jan 2005', freq='M')
        assert pi2[0] == Period('1/31/2005', freq='D')
        assert pi3[0] == Period('1/31/2005', freq='3D')

        assert pi1[-1] == Period('Nov 2005', freq='M')
        assert pi2[-1] == Period('11/30/2005', freq='D')
        assert pi3[-1], Period('11/30/2005', freq='3D')

        tm.assert_index_equal(pi1, period_range('1/1/2005', '11/1/2005',
                                                freq='M'))
        tm.assert_index_equal(pi2, period_range('1/1/2005', '11/1/2005',
                                                freq='M').asfreq('D'))
        tm.assert_index_equal(pi3, period_range('1/1/2005', '11/1/2005',
                                                freq='M').asfreq('3D')) 

# 需要导入模块: import pandas [as 别名]
# 或者: from pandas import Period [as 别名]
def test_searchsorted(self, freq):
        pidx = pd.PeriodIndex(['2014-01-01', '2014-01-02', '2014-01-03',
                               '2014-01-04', '2014-01-05'], freq=freq)

        p1 = pd.Period('2014-01-01', freq=freq)
        assert pidx.searchsorted(p1) == 0

        p2 = pd.Period('2014-01-04', freq=freq)
        assert pidx.searchsorted(p2) == 3

        msg = "Input has different freq=H from PeriodIndex"
        with pytest.raises(period.IncompatibleFrequency, match=msg):
            pidx.searchsorted(pd.Period('2014-01-01', freq='H'))

        msg = "Input has different freq=5D from PeriodIndex"
        with pytest.raises(period.IncompatibleFrequency, match=msg):
            pidx.searchsorted(pd.Period('2014-01-01', freq='5D')) 

# 需要导入模块: import pandas [as 别名]
# 或者: from pandas import Period [as 别名]
def test_astype_conversion(self):
        # GH#13149, GH#13209
        idx = PeriodIndex(['2016-05-16', 'NaT', NaT, np.NaN], freq='D')

        result = idx.astype(object)
        expected = Index([Period('2016-05-16', freq='D')] +
                         [Period(NaT, freq='D')] * 3, dtype='object')
        tm.assert_index_equal(result, expected)

        result = idx.astype(np.int64)
        expected = Int64Index([16937] + [-9223372036854775808] * 3,
                              dtype=np.int64)
        tm.assert_index_equal(result, expected)

        result = idx.astype(str)
        expected = Index(str(x) for x in idx)
        tm.assert_index_equal(result, expected)

        idx = period_range('1990', '2009', freq='A')
        result = idx.astype('i8')
        tm.assert_index_equal(result, Index(idx.asi8))
        tm.assert_numpy_array_equal(result.values, idx.asi8) 

# 需要导入模块: import pandas [as 别名]
# 或者: from pandas import Period [as 别名]
def test_astype_object(self):
        idx = pd.PeriodIndex([], freq='M')

        exp = np.array([], dtype=object)
        tm.assert_numpy_array_equal(idx.astype(object).values, exp)
        tm.assert_numpy_array_equal(idx._mpl_repr(), exp)

        idx = pd.PeriodIndex(['2011-01', pd.NaT], freq='M')

        exp = np.array([pd.Period('2011-01', freq='M'), pd.NaT], dtype=object)
        tm.assert_numpy_array_equal(idx.astype(object).values, exp)
        tm.assert_numpy_array_equal(idx._mpl_repr(), exp)

        exp = np.array([pd.Period('2011-01-01', freq='D'), pd.NaT],
                       dtype=object)
        idx = pd.PeriodIndex(['2011-01-01', pd.NaT], freq='D')
        tm.assert_numpy_array_equal(idx.astype(object).values, exp)
        tm.assert_numpy_array_equal(idx._mpl_repr(), exp)

    # TODO: de-duplicate this version (from test_ops) with the one above
    # (from test_period) 

# 需要导入模块: import pandas [as 别名]
# 或者: from pandas import Period [as 别名]
def test_slice_with_negative_step(self):
        ts = Series(np.arange(20),
                    period_range('2014-01', periods=20, freq='M'))
        SLC = pd.IndexSlice

        def assert_slices_equivalent(l_slc, i_slc):
            tm.assert_series_equal(ts[l_slc], ts.iloc[i_slc])
            tm.assert_series_equal(ts.loc[l_slc], ts.iloc[i_slc])
            tm.assert_series_equal(ts.loc[l_slc], ts.iloc[i_slc])

        assert_slices_equivalent(SLC[Period('2014-10')::-1], SLC[9::-1])
        assert_slices_equivalent(SLC['2014-10'::-1], SLC[9::-1])

        assert_slices_equivalent(SLC[:Period('2014-10'):-1], SLC[:8:-1])
        assert_slices_equivalent(SLC[:'2014-10':-1], SLC[:8:-1])

        assert_slices_equivalent(SLC['2015-02':'2014-10':-1], SLC[13:8:-1])
        assert_slices_equivalent(SLC[Period('2015-02'):Period('2014-10'):-1],
                                 SLC[13:8:-1])
        assert_slices_equivalent(SLC['2015-02':Period('2014-10'):-1],
                                 SLC[13:8:-1])
        assert_slices_equivalent(SLC[Period('2015-02'):'2014-10':-1],
                                 SLC[13:8:-1])

        assert_slices_equivalent(SLC['2014-10':'2015-02':-1], SLC[:0])