Python pandas.period_range方法代码示例

# 需要导入模块: import pandas [as 别名]
# 或者: from pandas import period_range [as 别名]
def test_union_misc(self, sort):
        index = period_range('1/1/2000', '1/20/2000', freq='D')

        result = index[:-5].union(index[10:], sort=sort)
        tm.assert_index_equal(result, index)

        # not in order
        result = _permute(index[:-5]).union(_permute(index[10:]), sort=sort)
        if sort is None:
            tm.assert_index_equal(result, index)
        assert tm.equalContents(result, index)

        # raise if different frequencies
        index = period_range('1/1/2000', '1/20/2000', freq='D')
        index2 = period_range('1/1/2000', '1/20/2000', freq='W-WED')
        with pytest.raises(period.IncompatibleFrequency):
            index.union(index2, sort=sort)

        msg = 'can only call with other PeriodIndex-ed objects'
        with pytest.raises(ValueError, match=msg):
            index.join(index.to_timestamp())

        index3 = period_range('1/1/2000', '1/20/2000', freq='2D')
        with pytest.raises(period.IncompatibleFrequency):
            index.join(index3) 

# 需要导入模块: import pandas [as 别名]
# 或者: from pandas import period_range [as 别名]
def test_intersection(self, sort):
        index = period_range('1/1/2000', '1/20/2000', freq='D')

        result = index[:-5].intersection(index[10:], sort=sort)
        tm.assert_index_equal(result, index[10:-5])

        # not in order
        left = _permute(index[:-5])
        right = _permute(index[10:])
        result = left.intersection(right, sort=sort)
        if sort is None:
            tm.assert_index_equal(result, index[10:-5])
        assert tm.equalContents(result, index[10:-5])

        # raise if different frequencies
        index = period_range('1/1/2000', '1/20/2000', freq='D')
        index2 = period_range('1/1/2000', '1/20/2000', freq='W-WED')
        with pytest.raises(period.IncompatibleFrequency):
            index.intersection(index2, sort=sort)

        index3 = period_range('1/1/2000', '1/20/2000', freq='2D')
        with pytest.raises(period.IncompatibleFrequency):
            index.intersection(index3, sort=sort) 

# 需要导入模块: import pandas [as 别名]
# 或者: from pandas import period_range [as 别名]
def test_getitem_seconds(self):
        # GH#6716
        didx = pd.date_range(start='2013/01/01 09:00:00', freq='S',
                             periods=4000)
        pidx = period_range(start='2013/01/01 09:00:00', freq='S',
                            periods=4000)

        for idx in [didx, pidx]:
            # getitem against index should raise ValueError
            values = ['2014', '2013/02', '2013/01/02', '2013/02/01 9H',
                      '2013/02/01 09:00']
            for v in values:
                # GH7116
                # these show deprecations as we are trying
                # to slice with non-integer indexers
                # with pytest.raises(IndexError):
                #    idx[v]
                continue

            s = Series(np.random.rand(len(idx)), index=idx)
            tm.assert_series_equal(s['2013/01/01 10:00'], s[3600:3660])
            tm.assert_series_equal(s['2013/01/01 9H'], s[:3600])
            for d in ['2013/01/01', '2013/01', '2013']:
                tm.assert_series_equal(s[d], s) 

# 需要导入模块: import pandas [as 别名]
# 或者: from pandas import period_range [as 别名]
def test_where_other(self):
        i = period_range('20130101', periods=5, freq='D')
        for arr in [np.nan, pd.NaT]:
            result = i.where(notna(i), other=np.nan)
            expected = i
            tm.assert_index_equal(result, expected)

        i2 = i.copy()
        i2 = pd.PeriodIndex([pd.NaT, pd.NaT] + i[2:].tolist(),
                            freq='D')
        result = i.where(notna(i2), i2)
        tm.assert_index_equal(result, i2)

        i2 = i.copy()
        i2 = pd.PeriodIndex([pd.NaT, pd.NaT] + i[2:].tolist(),
                            freq='D')
        result = i.where(notna(i2), i2.values)
        tm.assert_index_equal(result, i2) 

# 需要导入模块: import pandas [as 别名]
# 或者: from pandas import period_range [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_range [as 别名]
def test_to_timestamp_pi_combined(self):
        idx = period_range(start='2011', periods=2, freq='1D1H', name='idx')

        result = idx.to_timestamp()
        expected = DatetimeIndex(['2011-01-01 00:00', '2011-01-02 01:00'],
                                 name='idx')
        tm.assert_index_equal(result, expected)

        result = idx.to_timestamp(how='E')
        expected = DatetimeIndex(['2011-01-02 00:59:59',
                                  '2011-01-03 01:59:59'],
                                 name='idx')
        expected = expected + Timedelta(1, 's') - Timedelta(1, 'ns')
        tm.assert_index_equal(result, expected)

        result = idx.to_timestamp(how='E', freq='H')
        expected = DatetimeIndex(['2011-01-02 00:00', '2011-01-03 01:00'],
                                 name='idx')
        expected = expected + Timedelta(1, 'h') - Timedelta(1, 'ns')
        tm.assert_index_equal(result, expected) 

# 需要导入模块: import pandas [as 别名]
# 或者: from pandas import period_range [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_range [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]) 

# 需要导入模块: import pandas [as 别名]
# 或者: from pandas import period_range [as 别名]
def test_range_slice_day(self):
        # GH#6716
        didx = pd.date_range(start='2013/01/01', freq='D', periods=400)
        pidx = period_range(start='2013/01/01', freq='D', periods=400)

        for idx in [didx, pidx]:
            # slices against index should raise IndexError
            values = ['2014', '2013/02', '2013/01/02', '2013/02/01 9H',
                      '2013/02/01 09:00']
            for v in values:
                with pytest.raises(TypeError):
                    idx[v:]

            s = Series(np.random.rand(len(idx)), index=idx)

            tm.assert_series_equal(s['2013/01/02':], s[1:])
            tm.assert_series_equal(s['2013/01/02':'2013/01/05'], s[1:5])
            tm.assert_series_equal(s['2013/02':], s[31:])
            tm.assert_series_equal(s['2014':], s[365:])

            invalid = ['2013/02/01 9H', '2013/02/01 09:00']
            for v in invalid:
                with pytest.raises(TypeError):
                    idx[v:] 

# 需要导入模块: import pandas [as 别名]
# 或者: from pandas import period_range [as 别名]
def test_range_slice_seconds(self):
        # GH#6716
        didx = pd.date_range(start='2013/01/01 09:00:00', freq='S',
                             periods=4000)
        pidx = period_range(start='2013/01/01 09:00:00', freq='S',
                            periods=4000)

        for idx in [didx, pidx]:
            # slices against index should raise IndexError
            values = ['2014', '2013/02', '2013/01/02', '2013/02/01 9H',
                      '2013/02/01 09:00']
            for v in values:
                with pytest.raises(TypeError):
                    idx[v:]

            s = Series(np.random.rand(len(idx)), index=idx)

            tm.assert_series_equal(s['2013/01/01 09:05':'2013/01/01 09:10'],
                                   s[300:660])
            tm.assert_series_equal(s['2013/01/01 10:00':'2013/01/01 10:05'],
                                   s[3600:3960])
            tm.assert_series_equal(s['2013/01/01 10H':], s[3600:])
            tm.assert_series_equal(s[:'2013/01/01 09:30'], s[:1860])
            for d in ['2013/01/01', '2013/01', '2013']:
                tm.assert_series_equal(s[d:], s) 

# 需要导入模块: import pandas [as 别名]
# 或者: from pandas import period_range [as 别名]
def test_range_slice_outofbounds(self):
        # GH#5407
        didx = pd.date_range(start='2013/10/01', freq='D', periods=10)
        pidx = period_range(start='2013/10/01', freq='D', periods=10)

        for idx in [didx, pidx]:
            df = DataFrame(dict(units=[100 + i for i in range(10)]), index=idx)
            empty = DataFrame(index=idx.__class__([], freq='D'),
                              columns=['units'])
            empty['units'] = empty['units'].astype('int64')

            tm.assert_frame_equal(df['2013/09/01':'2013/09/30'], empty)
            tm.assert_frame_equal(df['2013/09/30':'2013/10/02'], df.iloc[:2])
            tm.assert_frame_equal(df['2013/10/01':'2013/10/02'], df.iloc[:2])
            tm.assert_frame_equal(df['2013/10/02':'2013/09/30'], empty)
            tm.assert_frame_equal(df['2013/10/15':'2013/10/17'], empty)
            tm.assert_frame_equal(df['2013-06':'2013-09'], empty)
            tm.assert_frame_equal(df['2013-11':'2013-12'], empty) 

# 需要导入模块: import pandas [as 别名]
# 或者: from pandas import period_range [as 别名]
def test_difference_freq(self, sort):
        # GH14323: difference of Period MUST preserve frequency
        # but the ability to union results must be preserved

        index = period_range("20160920", "20160925", freq="D")

        other = period_range("20160921", "20160924", freq="D")
        expected = PeriodIndex(["20160920", "20160925"], freq='D')
        idx_diff = index.difference(other, sort)
        tm.assert_index_equal(idx_diff, expected)
        tm.assert_attr_equal('freq', idx_diff, expected)

        other = period_range("20160922", "20160925", freq="D")
        idx_diff = index.difference(other, sort)
        expected = PeriodIndex(["20160920", "20160921"], freq='D')
        tm.assert_index_equal(idx_diff, expected)
        tm.assert_attr_equal('freq', idx_diff, expected) 

# 需要导入模块: import pandas [as 别名]
# 或者: from pandas import period_range [as 别名]
def test_is_(self):
        create_index = lambda: period_range(freq='A', start='1/1/2001',
                                            end='12/1/2009')
        index = create_index()
        assert index.is_(index)
        assert not index.is_(create_index())
        assert index.is_(index.view())
        assert index.is_(index.view().view().view().view().view())
        assert index.view().is_(index)
        ind2 = index.view()
        index.name = "Apple"
        assert ind2.is_(index)
        assert not index.is_(index[:])
        assert not index.is_(index.asfreq('M'))
        assert not index.is_(index.asfreq('A'))

        assert not index.is_(index - 2)
        assert not index.is_(index - 0) 

# 需要导入模块: import pandas [as 别名]
# 或者: from pandas import period_range [as 别名]
def test_pindex_multiples(self):
        with tm.assert_produces_warning(FutureWarning):
            pi = PeriodIndex(start='1/1/11', end='12/31/11', freq='2M')
        expected = PeriodIndex(['2011-01', '2011-03', '2011-05', '2011-07',
                                '2011-09', '2011-11'], freq='2M')
        tm.assert_index_equal(pi, expected)
        assert pi.freq == offsets.MonthEnd(2)
        assert pi.freqstr == '2M'

        pi = period_range(start='1/1/11', end='12/31/11', freq='2M')
        tm.assert_index_equal(pi, expected)
        assert pi.freq == offsets.MonthEnd(2)
        assert pi.freqstr == '2M'

        pi = period_range(start='1/1/11', periods=6, freq='2M')
        tm.assert_index_equal(pi, expected)
        assert pi.freq == offsets.MonthEnd(2)
        assert pi.freqstr == '2M' 

# 需要导入模块: import pandas [as 别名]
# 或者: from pandas import period_range [as 别名]
def test_drop_duplicates(self):
        # to check Index/Series compat
        base = pd.period_range('2011-01-01', '2011-01-31', freq='D',
                               name='idx')
        idx = base.append(base[:5])

        res = idx.drop_duplicates()
        tm.assert_index_equal(res, base)
        res = Series(idx).drop_duplicates()
        tm.assert_series_equal(res, Series(base))

        res = idx.drop_duplicates(keep='last')
        exp = base[5:].append(base[:5])
        tm.assert_index_equal(res, exp)
        res = Series(idx).drop_duplicates(keep='last')
        tm.assert_series_equal(res, Series(exp, index=np.arange(5, 36)))

        res = idx.drop_duplicates(keep=False)
        tm.assert_index_equal(res, base[5:])
        res = Series(idx).drop_duplicates(keep=False)
        tm.assert_series_equal(res, Series(base[5:], index=np.arange(5, 31)))