Python pandas.tseries.offsets.Minute() Examples

def test_is_superperiod_subperiod():

    # input validation
    assert not (is_superperiod(offsets.YearEnd(), None))
    assert not (is_subperiod(offsets.MonthEnd(), None))
    assert not (is_superperiod(None, offsets.YearEnd()))
    assert not (is_subperiod(None, offsets.MonthEnd()))
    assert not (is_superperiod(None, None))
    assert not (is_subperiod(None, None))

    assert (is_superperiod(offsets.YearEnd(), offsets.MonthEnd()))
    assert (is_subperiod(offsets.MonthEnd(), offsets.YearEnd()))

    assert (is_superperiod(offsets.Hour(), offsets.Minute()))
    assert (is_subperiod(offsets.Minute(), offsets.Hour()))

    assert (is_superperiod(offsets.Second(), offsets.Milli()))
    assert (is_subperiod(offsets.Milli(), offsets.Second()))

    assert (is_superperiod(offsets.Milli(), offsets.Micro()))
    assert (is_subperiod(offsets.Micro(), offsets.Milli()))

    assert (is_superperiod(offsets.Micro(), offsets.Nano()))
    assert (is_subperiod(offsets.Nano(), offsets.Micro())) 

def test_intersection(self):
        rng = date_range('1/1/2000', periods=50, freq=Minute())
        rng1 = rng[10:]
        rng2 = rng[:25]
        the_int = rng1.intersection(rng2)
        expected = rng[10:25]
        tm.assert_index_equal(the_int, expected)
        assert isinstance(the_int, DatetimeIndex)
        assert the_int.freq == rng.freq

        the_int = rng1.intersection(rng2.view(DatetimeIndex))
        tm.assert_index_equal(the_int, expected)

        # non-overlapping
        the_int = rng[:10].intersection(rng[10:])
        expected = DatetimeIndex([])
        tm.assert_index_equal(the_int, expected) 

def test_is_superperiod_subperiod():

    # input validation
    assert not (is_superperiod(offsets.YearEnd(), None))
    assert not (is_subperiod(offsets.MonthEnd(), None))
    assert not (is_superperiod(None, offsets.YearEnd()))
    assert not (is_subperiod(None, offsets.MonthEnd()))
    assert not (is_superperiod(None, None))
    assert not (is_subperiod(None, None))

    assert (is_superperiod(offsets.YearEnd(), offsets.MonthEnd()))
    assert (is_subperiod(offsets.MonthEnd(), offsets.YearEnd()))

    assert (is_superperiod(offsets.Hour(), offsets.Minute()))
    assert (is_subperiod(offsets.Minute(), offsets.Hour()))

    assert (is_superperiod(offsets.Second(), offsets.Milli()))
    assert (is_subperiod(offsets.Milli(), offsets.Second()))

    assert (is_superperiod(offsets.Milli(), offsets.Micro()))
    assert (is_subperiod(offsets.Micro(), offsets.Milli()))

    assert (is_superperiod(offsets.Micro(), offsets.Nano()))
    assert (is_subperiod(offsets.Nano(), offsets.Micro())) 

def test_resample_ohlc(self):
        s = self.series

        grouper = TimeGrouper(Minute(5))
        expect = s.groupby(grouper).agg(lambda x: x[-1])
        result = s.resample('5Min').ohlc()

        assert len(result) == len(expect)
        assert len(result.columns) == 4

        xs = result.iloc[-2]
        assert xs['open'] == s[-6]
        assert xs['high'] == s[-6:-1].max()
        assert xs['low'] == s[-6:-1].min()
        assert xs['close'] == s[-2]

        xs = result.iloc[0]
        assert xs['open'] == s[0]
        assert xs['high'] == s[:5].max()
        assert xs['low'] == s[:5].min()
        assert xs['close'] == s[4] 

def test_intersection(self):
        rng = date_range('1/1/2000', periods=50, freq=Minute())
        rng1 = rng[10:]
        rng2 = rng[:25]
        the_int = rng1.intersection(rng2)
        expected = rng[10:25]
        tm.assert_index_equal(the_int, expected)
        assert isinstance(the_int, DatetimeIndex)
        assert the_int.freq == rng.freq

        the_int = rng1.intersection(rng2.view(DatetimeIndex))
        tm.assert_index_equal(the_int, expected)

        # non-overlapping
        the_int = rng[:10].intersection(rng[10:])
        expected = DatetimeIndex([])
        tm.assert_index_equal(the_int, expected) 

def test_is_superperiod_subperiod():

    # input validation
    assert not (frequencies.is_superperiod(offsets.YearEnd(), None))
    assert not (frequencies.is_subperiod(offsets.MonthEnd(), None))
    assert not (frequencies.is_superperiod(None, offsets.YearEnd()))
    assert not (frequencies.is_subperiod(None, offsets.MonthEnd()))
    assert not (frequencies.is_superperiod(None, None))
    assert not (frequencies.is_subperiod(None, None))

    assert (frequencies.is_superperiod(offsets.YearEnd(), offsets.MonthEnd()))
    assert (frequencies.is_subperiod(offsets.MonthEnd(), offsets.YearEnd()))

    assert (frequencies.is_superperiod(offsets.Hour(), offsets.Minute()))
    assert (frequencies.is_subperiod(offsets.Minute(), offsets.Hour()))

    assert (frequencies.is_superperiod(offsets.Second(), offsets.Milli()))
    assert (frequencies.is_subperiod(offsets.Milli(), offsets.Second()))

    assert (frequencies.is_superperiod(offsets.Milli(), offsets.Micro()))
    assert (frequencies.is_subperiod(offsets.Micro(), offsets.Milli()))

    assert (frequencies.is_superperiod(offsets.Micro(), offsets.Nano()))
    assert (frequencies.is_subperiod(offsets.Nano(), offsets.Micro())) 

def test_with_tz_ambiguous_times(self):
        tz = self.tz('US/Eastern')

        # March 13, 2011, spring forward, skip from 2 AM to 3 AM
        dr = date_range(datetime(2011, 3, 13, 1, 30), periods=3,
                        freq=offsets.Hour())
        pytest.raises(pytz.NonExistentTimeError, dr.tz_localize, tz)

        # after dst transition, it works
        dr = date_range(datetime(2011, 3, 13, 3, 30), periods=3,
                        freq=offsets.Hour(), tz=tz)

        # November 6, 2011, fall back, repeat 2 AM hour
        dr = date_range(datetime(2011, 11, 6, 1, 30), periods=3,
                        freq=offsets.Hour())
        pytest.raises(pytz.AmbiguousTimeError, dr.tz_localize, tz)

        # UTC is OK
        dr = date_range(datetime(2011, 3, 13), periods=48,
                        freq=offsets.Minute(30), tz=pytz.utc) 

def test_resample_ohlc(self):
        s = self.series

        grouper = TimeGrouper(Minute(5))
        expect = s.groupby(grouper).agg(lambda x: x[-1])
        result = s.resample('5Min').ohlc()

        assert len(result) == len(expect)
        assert len(result.columns) == 4

        xs = result.iloc[-2]
        assert xs['open'] == s[-6]
        assert xs['high'] == s[-6:-1].max()
        assert xs['low'] == s[-6:-1].min()
        assert xs['close'] == s[-2]

        xs = result.iloc[0]
        assert xs['open'] == s[0]
        assert xs['high'] == s[:5].max()
        assert xs['low'] == s[:5].min()
        assert xs['close'] == s[4] 

def test_resample_basic(self):
        rng = date_range('1/1/2000 00:00:00', '1/1/2000 00:13:00', freq='min',
                         name='index')
        s = Series(np.random.randn(14), index=rng)
        result = s.resample('5min', closed='right', label='right').mean()

        exp_idx = date_range('1/1/2000', periods=4, freq='5min', name='index')
        expected = Series([s[0], s[1:6].mean(), s[6:11].mean(), s[11:].mean()],
                          index=exp_idx)
        assert_series_equal(result, expected)
        assert result.index.name == 'index'

        result = s.resample('5min', closed='left', label='right').mean()

        exp_idx = date_range('1/1/2000 00:05', periods=3, freq='5min',
                             name='index')
        expected = Series([s[:5].mean(), s[5:10].mean(),
                           s[10:].mean()], index=exp_idx)
        assert_series_equal(result, expected)

        s = self.series
        result = s.resample('5Min').last()
        grouper = TimeGrouper(Minute(5), closed='left', label='left')
        expect = s.groupby(grouper).agg(lambda x: x[-1])
        assert_series_equal(result, expect) 

def test_resample_ohlc(series):
    s = series

    grouper = TimeGrouper(Minute(5))
    expect = s.groupby(grouper).agg(lambda x: x[-1])
    result = s.resample('5Min').ohlc()

    assert len(result) == len(expect)
    assert len(result.columns) == 4

    xs = result.iloc[-2]
    assert xs['open'] == s[-6]
    assert xs['high'] == s[-6:-1].max()
    assert xs['low'] == s[-6:-1].min()
    assert xs['close'] == s[-2]

    xs = result.iloc[0]
    assert xs['open'] == s[0]
    assert xs['high'] == s[:5].max()
    assert xs['low'] == s[:5].min()
    assert xs['close'] == s[4] 

def test_resample_loffset(loffset):
    # GH 7687
    rng = date_range('1/1/2000 00:00:00', '1/1/2000 00:13:00', freq='min')
    s = Series(np.random.randn(14), index=rng)

    result = s.resample('5min', closed='right', label='right',
                        loffset=loffset).mean()
    idx = date_range('1/1/2000', periods=4, freq='5min')
    expected = Series([s[0], s[1:6].mean(), s[6:11].mean(), s[11:].mean()],
                      index=idx + timedelta(minutes=1))
    assert_series_equal(result, expected)
    assert result.index.freq == Minute(5)

    # from daily
    dti = date_range(start=datetime(2005, 1, 1),
                     end=datetime(2005, 1, 10), freq='D')
    ser = Series(np.random.rand(len(dti)), dti)

    # to weekly
    result = ser.resample('w-sun').last()
    business_day_offset = BDay()
    expected = ser.resample('w-sun', loffset=-business_day_offset).last()
    assert result.index[0] - business_day_offset == expected.index[0] 

def test_intersection(self):
        rng = date_range('1/1/2000', periods=50, freq=Minute())
        rng1 = rng[10:]
        rng2 = rng[:25]
        the_int = rng1.intersection(rng2)
        expected = rng[10:25]
        tm.assert_index_equal(the_int, expected)
        assert isinstance(the_int, DatetimeIndex)
        assert the_int.freq == rng.freq

        the_int = rng1.intersection(rng2.view(DatetimeIndex))
        tm.assert_index_equal(the_int, expected)

        # non-overlapping
        the_int = rng[:10].intersection(rng[10:])
        expected = DatetimeIndex([])
        tm.assert_index_equal(the_int, expected) 

def test_resample_ohlc(self):
        s = self.series

        grouper = TimeGrouper(Minute(5))
        expect = s.groupby(grouper).agg(lambda x: x[-1])
        result = s.resample('5Min', how='ohlc')

        self.assertEquals(len(result), len(expect))
        self.assertEquals(len(result.columns), 4)

        xs = result.irow(-2)
        self.assertEquals(xs['open'], s[-6])
        self.assertEquals(xs['high'], s[-6:-1].max())
        self.assertEquals(xs['low'], s[-6:-1].min())
        self.assertEquals(xs['close'], s[-2])

        xs = result.irow(0)
        self.assertEquals(xs['open'], s[0])
        self.assertEquals(xs['high'], s[:5].max())
        self.assertEquals(xs['low'], s[:5].min())
        self.assertEquals(xs['close'], s[4]) 

def test_resample_basic(self):
        rng = date_range('1/1/2000 00:00:00', '1/1/2000 00:13:00', freq='min',
                         name='index')
        s = Series(np.random.randn(14), index=rng)
        result = s.resample('5min', how='mean', closed='right', label='right')
        expected = Series([s[0], s[1:6].mean(), s[6:11].mean(), s[11:].mean()],
                          index=date_range('1/1/2000', periods=4, freq='5min'))
        assert_series_equal(result, expected)
        self.assert_(result.index.name == 'index')

        result = s.resample('5min', how='mean', closed='left', label='right')
        expected = Series([s[:5].mean(), s[5:10].mean(), s[10:].mean()],
                          index=date_range('1/1/2000 00:05', periods=3,
                                           freq='5min'))
        assert_series_equal(result, expected)

        s = self.series
        result = s.resample('5Min', how='last')
        grouper = TimeGrouper(Minute(5), closed='left', label='left')
        expect = s.groupby(grouper).agg(lambda x: x[-1])
        assert_series_equal(result, expect) 

def test_resample_loffset(loffset):
    # GH 7687
    rng = date_range('1/1/2000 00:00:00', '1/1/2000 00:13:00', freq='min')
    s = Series(np.random.randn(14), index=rng)

    result = s.resample('5min', closed='right', label='right',
                        loffset=loffset).mean()
    idx = date_range('1/1/2000', periods=4, freq='5min')
    expected = Series([s[0], s[1:6].mean(), s[6:11].mean(), s[11:].mean()],
                      index=idx + timedelta(minutes=1))
    assert_series_equal(result, expected)
    assert result.index.freq == Minute(5)

    # from daily
    dti = date_range(start=datetime(2005, 1, 1),
                     end=datetime(2005, 1, 10), freq='D')
    ser = Series(np.random.rand(len(dti)), dti)

    # to weekly
    result = ser.resample('w-sun').last()
    business_day_offset = BDay()
    expected = ser.resample('w-sun', loffset=-business_day_offset).last()
    assert result.index[0] - business_day_offset == expected.index[0] 

def test_resample_ohlc(series):
    s = series

    grouper = TimeGrouper(Minute(5))
    expect = s.groupby(grouper).agg(lambda x: x[-1])
    result = s.resample('5Min').ohlc()

    assert len(result) == len(expect)
    assert len(result.columns) == 4

    xs = result.iloc[-2]
    assert xs['open'] == s[-6]
    assert xs['high'] == s[-6:-1].max()
    assert xs['low'] == s[-6:-1].min()
    assert xs['close'] == s[-2]

    xs = result.iloc[0]
    assert xs['open'] == s[0]
    assert xs['high'] == s[:5].max()
    assert xs['low'] == s[:5].min()
    assert xs['close'] == s[4] 

def test_resample_ohlc(self):
        s = self.series

        grouper = TimeGrouper(Minute(5))
        expect = s.groupby(grouper).agg(lambda x: x[-1])
        result = s.resample('5Min').ohlc()

        assert len(result) == len(expect)
        assert len(result.columns) == 4

        xs = result.iloc[-2]
        assert xs['open'] == s[-6]
        assert xs['high'] == s[-6:-1].max()
        assert xs['low'] == s[-6:-1].min()
        assert xs['close'] == s[-2]

        xs = result.iloc[0]
        assert xs['open'] == s[0]
        assert xs['high'] == s[:5].max()
        assert xs['low'] == s[:5].min()
        assert xs['close'] == s[4] 

def test_frequency_misc(self):
        assert (resolution.get_freq_group('T') ==
                FreqGroup.FR_MIN)

        code, stride = get_freq_code(offsets.Hour())
        assert code == FreqGroup.FR_HR

        code, stride = get_freq_code((5, 'T'))
        assert code == FreqGroup.FR_MIN
        assert stride == 5

        offset = offsets.Hour()
        result = frequencies.to_offset(offset)
        assert result == offset

        result = frequencies.to_offset((5, 'T'))
        expected = offsets.Minute(5)
        assert result == expected

        with pytest.raises(ValueError, match='Invalid frequency'):
            get_freq_code((5, 'baz'))

        with pytest.raises(ValueError, match='Invalid frequency'):
            frequencies.to_offset('100foo')

        with pytest.raises(ValueError, match='Could not evaluate'):
            frequencies.to_offset(('', '')) 

def test_resample_basic_grouper(series):
    s = series
    result = s.resample('5Min').last()
    grouper = TimeGrouper(Minute(5), closed='left', label='left')
    expected = s.groupby(grouper).agg(lambda x: x[-1])
    assert_series_equal(result, expected) 

def test_to_offset_pd_timedelta(self):
        # Tests for #9064
        td = Timedelta(days=1, seconds=1)
        result = frequencies.to_offset(td)
        expected = offsets.Second(86401)
        assert (expected == result)

        td = Timedelta(days=-1, seconds=1)
        result = frequencies.to_offset(td)
        expected = offsets.Second(-86399)
        assert (expected == result)

        td = Timedelta(hours=1, minutes=10)
        result = frequencies.to_offset(td)
        expected = offsets.Minute(70)
        assert (expected == result)

        td = Timedelta(hours=1, minutes=-10)
        result = frequencies.to_offset(td)
        expected = offsets.Minute(50)
        assert (expected == result)

        td = Timedelta(weeks=1)
        result = frequencies.to_offset(td)
        expected = offsets.Day(7)
        assert (expected == result)

        td1 = Timedelta(hours=1)
        result1 = frequencies.to_offset(td1)
        result2 = frequencies.to_offset('60min')
        assert (result1 == result2)

        td = Timedelta(microseconds=1)
        result = frequencies.to_offset(td)
        expected = offsets.Micro(1)
        assert (expected == result)

        td = Timedelta(microseconds=0)
        pytest.raises(ValueError, lambda: frequencies.to_offset(td)) 

def test_frequency_misc(self):
        assert (resolution.get_freq_group('T') ==
                FreqGroup.FR_MIN)

        code, stride = get_freq_code(offsets.Hour())
        assert code == FreqGroup.FR_HR

        code, stride = get_freq_code((5, 'T'))
        assert code == FreqGroup.FR_MIN
        assert stride == 5

        offset = offsets.Hour()
        result = frequencies.to_offset(offset)
        assert result == offset

        result = frequencies.to_offset((5, 'T'))
        expected = offsets.Minute(5)
        assert result == expected

        with pytest.raises(ValueError, match='Invalid frequency'):
            get_freq_code((5, 'baz'))

        with pytest.raises(ValueError, match='Invalid frequency'):
            frequencies.to_offset('100foo')

        with pytest.raises(ValueError, match='Could not evaluate'):
            frequencies.to_offset(('', '')) 

def test_frequency_misc(self):
        assert (frequencies.get_freq_group('T') ==
                frequencies.FreqGroup.FR_MIN)

        code, stride = frequencies.get_freq_code(offsets.Hour())
        assert code == frequencies.FreqGroup.FR_HR

        code, stride = frequencies.get_freq_code((5, 'T'))
        assert code == frequencies.FreqGroup.FR_MIN
        assert stride == 5

        offset = offsets.Hour()
        result = frequencies.to_offset(offset)
        assert result == offset

        result = frequencies.to_offset((5, 'T'))
        expected = offsets.Minute(5)
        assert result == expected

        pytest.raises(ValueError, frequencies.get_freq_code, (5, 'baz'))

        pytest.raises(ValueError, frequencies.to_offset, '100foo')

        pytest.raises(ValueError, frequencies.to_offset, ('', ''))

        with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
            result = frequencies.get_standard_freq(offsets.Hour())
        assert result == 'H' 

def test_union_not_cacheable(self):
        rng = date_range('1/1/2000', periods=50, freq=Minute())
        rng1 = rng[10:]
        rng2 = rng[:25]
        the_union = rng1.union(rng2)
        tm.assert_index_equal(the_union, rng)

        rng1 = rng[10:]
        rng2 = rng[15:35]
        the_union = rng1.union(rng2)
        expected = rng[10:]
        tm.assert_index_equal(the_union, expected) 

def test_to_offset_pd_timedelta(self):
        # Tests for #9064
        td = Timedelta(days=1, seconds=1)
        result = frequencies.to_offset(td)
        expected = offsets.Second(86401)
        assert (expected == result)

        td = Timedelta(days=-1, seconds=1)
        result = frequencies.to_offset(td)
        expected = offsets.Second(-86399)
        assert (expected == result)

        td = Timedelta(hours=1, minutes=10)
        result = frequencies.to_offset(td)
        expected = offsets.Minute(70)
        assert (expected == result)

        td = Timedelta(hours=1, minutes=-10)
        result = frequencies.to_offset(td)
        expected = offsets.Minute(50)
        assert (expected == result)

        td = Timedelta(weeks=1)
        result = frequencies.to_offset(td)
        expected = offsets.Day(7)
        assert (expected == result)

        td1 = Timedelta(hours=1)
        result1 = frequencies.to_offset(td1)
        result2 = frequencies.to_offset('60min')
        assert (result1 == result2)

        td = Timedelta(microseconds=1)
        result = frequencies.to_offset(td)
        expected = offsets.Micro(1)
        assert (expected == result)

        td = Timedelta(microseconds=0)
        pytest.raises(ValueError, lambda: frequencies.to_offset(td)) 

def test_Minute():
    assert_offset_equal(Minute(),
                        datetime(2010, 1, 1), datetime(2010, 1, 1, 0, 1))
    assert_offset_equal(Minute(-1),
                        datetime(2010, 1, 1, 0, 1), datetime(2010, 1, 1))
    assert_offset_equal(2 * Minute(),
                        datetime(2010, 1, 1), datetime(2010, 1, 1, 0, 2))
    assert_offset_equal(-1 * Minute(),
                        datetime(2010, 1, 1, 0, 1), datetime(2010, 1, 1))

    assert Minute(3) + Minute(2) == Minute(5)
    assert Minute(3) - Minute(2) == Minute()
    assert Minute(5) != Minute() 

def test_to_offset_pd_timedelta(self):
        # Tests for #9064
        td = Timedelta(days=1, seconds=1)
        result = frequencies.to_offset(td)
        expected = offsets.Second(86401)
        assert (expected == result)

        td = Timedelta(days=-1, seconds=1)
        result = frequencies.to_offset(td)
        expected = offsets.Second(-86399)
        assert (expected == result)

        td = Timedelta(hours=1, minutes=10)
        result = frequencies.to_offset(td)
        expected = offsets.Minute(70)
        assert (expected == result)

        td = Timedelta(hours=1, minutes=-10)
        result = frequencies.to_offset(td)
        expected = offsets.Minute(50)
        assert (expected == result)

        td = Timedelta(weeks=1)
        result = frequencies.to_offset(td)
        expected = offsets.Day(7)
        assert (expected == result)

        td1 = Timedelta(hours=1)
        result1 = frequencies.to_offset(td1)
        result2 = frequencies.to_offset('60min')
        assert (result1 == result2)

        td = Timedelta(microseconds=1)
        result = frequencies.to_offset(td)
        expected = offsets.Micro(1)
        assert (expected == result)

        td = Timedelta(microseconds=0)
        pytest.raises(ValueError, lambda: frequencies.to_offset(td)) 

def test_union_not_cacheable(self):
        rng = date_range('1/1/2000', periods=50, freq=Minute())
        rng1 = rng[10:]
        rng2 = rng[:25]
        the_union = rng1.union(rng2)
        tm.assert_index_equal(the_union, rng)

        rng1 = rng[10:]
        rng2 = rng[15:35]
        the_union = rng1.union(rng2)
        expected = rng[10:]
        tm.assert_index_equal(the_union, expected) 

def test_custom_grouper(self):

        dti = DatetimeIndex(freq='Min', start=datetime(2005, 1, 1),
                            end=datetime(2005, 1, 10))

        s = Series(np.array([1] * len(dti)), index=dti, dtype='int64')

        b = TimeGrouper(Minute(5))
        g = s.groupby(b)

        # check all cython functions work
        funcs = ['add', 'mean', 'prod', 'ohlc', 'min', 'max', 'var']
        for f in funcs:
            g._cython_agg_general(f)

        b = TimeGrouper(Minute(5), closed='right', label='right')
        g = s.groupby(b)
        # check all cython functions work
        funcs = ['add', 'mean', 'prod', 'ohlc', 'min', 'max', 'var']
        for f in funcs:
            g._cython_agg_general(f)

        assert g.ngroups == 2593
        assert notna(g.mean()).all()

        # construct expected val
        arr = [1] + [5] * 2592
        idx = dti[0:-1:5]
        idx = idx.append(dti[-1:])
        expect = Series(arr, index=idx)

        # GH2763 - return in put dtype if we can
        result = g.agg(np.sum)
        assert_series_equal(result, expect)

        df = DataFrame(np.random.rand(len(dti), 10),
                       index=dti, dtype='float64')
        r = df.groupby(b).agg(np.sum)

        assert len(r.columns) == 10
        assert len(r.index) == 2593 

def test_resample_basic(self):
        rng = date_range('1/1/2000 00:00:00', '1/1/2000 00:13:00', freq='min',
                         name='index')
        s = Series(np.random.randn(14), index=rng)

        result = s.resample('5min', closed='right', label='right').mean()

        exp_idx = date_range('1/1/2000', periods=4, freq='5min', name='index')
        expected = Series([s[0], s[1:6].mean(), s[6:11].mean(), s[11:].mean()],
                          index=exp_idx)
        assert_series_equal(result, expected)
        assert result.index.name == 'index'

        result = s.resample('5min', closed='left', label='right').mean()

        exp_idx = date_range('1/1/2000 00:05', periods=3, freq='5min',
                             name='index')
        expected = Series([s[:5].mean(), s[5:10].mean(),
                           s[10:].mean()], index=exp_idx)
        assert_series_equal(result, expected)

        s = self.series
        result = s.resample('5Min').last()
        grouper = TimeGrouper(Minute(5), closed='left', label='left')
        expect = s.groupby(grouper).agg(lambda x: x[-1])
        assert_series_equal(result, expect) 

def test_resample_loffset(self):
        rng = date_range('1/1/2000 00:00:00', '1/1/2000 00:13:00', freq='min')
        s = Series(np.random.randn(14), index=rng)

        result = s.resample('5min', closed='right', label='right',
                            loffset=timedelta(minutes=1)).mean()
        idx = date_range('1/1/2000', periods=4, freq='5min')
        expected = Series([s[0], s[1:6].mean(), s[6:11].mean(), s[11:].mean()],
                          index=idx + timedelta(minutes=1))
        assert_series_equal(result, expected)

        expected = s.resample(
            '5min', closed='right', label='right',
            loffset='1min').mean()
        assert_series_equal(result, expected)

        expected = s.resample(
            '5min', closed='right', label='right',
            loffset=Minute(1)).mean()
        assert_series_equal(result, expected)

        assert result.index.freq == Minute(5)

        # from daily
        dti = DatetimeIndex(start=datetime(2005, 1, 1),
                            end=datetime(2005, 1, 10), freq='D')
        ser = Series(np.random.rand(len(dti)), dti)

        # to weekly
        result = ser.resample('w-sun').last()
        expected = ser.resample('w-sun', loffset=-bday).last()
        assert result.index[0] - bday == expected.index[0]