Python pandas.timedelta_range方法代碼示例

# 需要導入模塊: import pandas [as 別名]
# 或者: from pandas import timedelta_range [as 別名]
def test_tdi_total_seconds(self):
        # GH#10939
        # test index
        rng = timedelta_range('1 days, 10:11:12.100123456', periods=2,
                              freq='s')
        expt = [1 * 86400 + 10 * 3600 + 11 * 60 + 12 + 100123456. / 1e9,
                1 * 86400 + 10 * 3600 + 11 * 60 + 13 + 100123456. / 1e9]
        tm.assert_almost_equal(rng.total_seconds(), Index(expt))

        # test Series
        ser = Series(rng)
        s_expt = Series(expt, index=[0, 1])
        tm.assert_series_equal(ser.dt.total_seconds(), s_expt)

        # with nat
        ser[1] = np.nan
        s_expt = Series([1 * 86400 + 10 * 3600 + 11 * 60 +
                         12 + 100123456. / 1e9, np.nan], index=[0, 1])
        tm.assert_series_equal(ser.dt.total_seconds(), s_expt)

        # with both nat
        ser = Series([np.nan, np.nan], dtype='timedelta64[ns]')
        tm.assert_series_equal(ser.dt.total_seconds(),
                               Series([np.nan, np.nan], index=[0, 1])) 

# 需要導入模塊: import pandas [as 別名]
# 或者: from pandas import timedelta_range [as 別名]
def test_tdi_round(self):
        td = pd.timedelta_range(start='16801 days', periods=5, freq='30Min')
        elt = td[1]

        expected_rng = TimedeltaIndex([Timedelta('16801 days 00:00:00'),
                                       Timedelta('16801 days 00:00:00'),
                                       Timedelta('16801 days 01:00:00'),
                                       Timedelta('16801 days 02:00:00'),
                                       Timedelta('16801 days 02:00:00')])
        expected_elt = expected_rng[1]

        tm.assert_index_equal(td.round(freq='H'), expected_rng)
        assert elt.round(freq='H') == expected_elt

        msg = pd._libs.tslibs.frequencies.INVALID_FREQ_ERR_MSG
        with pytest.raises(ValueError, match=msg):
            td.round(freq='foo')
        with pytest.raises(ValueError, match=msg):
            elt.round(freq='foo')

        msg = "<MonthEnd> is a non-fixed frequency"
        with pytest.raises(ValueError, match=msg):
            td.round(freq='M')
        with pytest.raises(ValueError, match=msg):
            elt.round(freq='M') 

# 需要導入模塊: import pandas [as 別名]
# 或者: from pandas import timedelta_range [as 別名]
def test_take_invalid_kwargs(self):
        idx = timedelta_range('1 day', '31 day', freq='D', name='idx')
        indices = [1, 6, 5, 9, 10, 13, 15, 3]

        msg = r"take\(\) got an unexpected keyword argument 'foo'"
        with pytest.raises(TypeError, match=msg):
            idx.take(indices, foo=2)

        msg = "the 'out' parameter is not supported"
        with pytest.raises(ValueError, match=msg):
            idx.take(indices, out=indices)

        msg = "the 'mode' parameter is not supported"
        with pytest.raises(ValueError, match=msg):
            idx.take(indices, mode='clip')

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

# 需要導入模塊: import pandas [as 別名]
# 或者: from pandas import timedelta_range [as 別名]
def test_astype(self):
        # GH 13149, GH 13209
        idx = TimedeltaIndex([1e14, 'NaT', NaT, np.NaN])

        result = idx.astype(object)
        expected = Index([Timedelta('1 days 03:46:40')] + [NaT] * 3,
                         dtype=object)
        tm.assert_index_equal(result, expected)

        result = idx.astype(int)
        expected = Int64Index([100000000000000] + [-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)

        rng = timedelta_range('1 days', periods=10)
        result = rng.astype('i8')
        tm.assert_index_equal(result, Index(rng.asi8))
        tm.assert_numpy_array_equal(rng.asi8, result.values) 

# 需要導入模塊: import pandas [as 別名]
# 或者: from pandas import timedelta_range [as 別名]
def test_errors(self):
        # not enough params
        msg = ('Of the four parameters: start, end, periods, and freq, '
               'exactly three must be specified')
        with pytest.raises(ValueError, match=msg):
            timedelta_range(start='0 days')

        with pytest.raises(ValueError, match=msg):
            timedelta_range(end='5 days')

        with pytest.raises(ValueError, match=msg):
            timedelta_range(periods=2)

        with pytest.raises(ValueError, match=msg):
            timedelta_range()

        # too many params
        with pytest.raises(ValueError, match=msg):
            timedelta_range(start='0 days', end='5 days', periods=10, freq='H') 

# 需要導入模塊: import pandas [as 別名]
# 或者: from pandas import timedelta_range [as 別名]
def test_partial_slice(self):
        rng = timedelta_range('1 day 10:11:12', freq='h', periods=500)
        s = Series(np.arange(len(rng)), index=rng)

        result = s['5 day':'6 day']
        expected = s.iloc[86:134]
        assert_series_equal(result, expected)

        result = s['5 day':]
        expected = s.iloc[86:]
        assert_series_equal(result, expected)

        result = s[:'6 day']
        expected = s.iloc[:134]
        assert_series_equal(result, expected)

        result = s['6 days, 23:11:12']
        assert result == s.iloc[133]

        pytest.raises(KeyError, s.__getitem__, '50 days') 

# 需要導入模塊: import pandas [as 別名]
# 或者: from pandas import timedelta_range [as 別名]
def test_partial_slice_high_reso(self):

        # higher reso
        rng = timedelta_range('1 day 10:11:12', freq='us', periods=2000)
        s = Series(np.arange(len(rng)), index=rng)

        result = s['1 day 10:11:12':]
        expected = s.iloc[0:]
        assert_series_equal(result, expected)

        result = s['1 day 10:11:12.001':]
        expected = s.iloc[1000:]
        assert_series_equal(result, expected)

        result = s['1 days, 10:11:12.001001']
        assert result == s.iloc[1001] 

# 需要導入模塊: import pandas [as 別名]
# 或者: from pandas import timedelta_range [as 別名]
def test_slice_with_negative_step(self):
        ts = Series(np.arange(20), timedelta_range('0', periods=20, freq='H'))
        SLC = pd.IndexSlice

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

        assert_slices_equivalent(SLC[Timedelta(hours=7)::-1], SLC[7::-1])
        assert_slices_equivalent(SLC['7 hours'::-1], SLC[7::-1])

        assert_slices_equivalent(SLC[:Timedelta(hours=7):-1], SLC[:6:-1])
        assert_slices_equivalent(SLC[:'7 hours':-1], SLC[:6:-1])

        assert_slices_equivalent(SLC['15 hours':'7 hours':-1], SLC[15:6:-1])
        assert_slices_equivalent(SLC[Timedelta(hours=15):Timedelta(hours=7):-
                                     1], SLC[15:6:-1])
        assert_slices_equivalent(SLC['15 hours':Timedelta(hours=7):-1],
                                 SLC[15:6:-1])
        assert_slices_equivalent(SLC[Timedelta(hours=15):'7 hours':-1],
                                 SLC[15:6:-1])

        assert_slices_equivalent(SLC['7 hours':'15 hours':-1], SLC[:0]) 

# 需要導入模塊: import pandas [as 別名]
# 或者: from pandas import timedelta_range [as 別名]
def test_drop_duplicates(self):
        # to check Index/Series compat
        base = pd.timedelta_range('1 day', '31 day', 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))) 

# 需要導入模塊: import pandas [as 別名]
# 或者: from pandas import timedelta_range [as 別名]
def test_convert_non_ns(self):
        # convert from a numpy array of non-ns timedelta64
        arr = np.array([1, 2, 3], dtype='timedelta64[s]')
        s = Series(arr)
        expected = Series(pd.timedelta_range('00:00:01', periods=3, freq='s'))
        assert_series_equal(s, expected)

        # convert from a numpy array of non-ns datetime64
        # note that creating a numpy datetime64 is in LOCAL time!!!!
        # seems to work for M8[D], but not for M8[s]

        s = Series(np.array(['2013-01-01', '2013-01-02',
                             '2013-01-03'], dtype='datetime64[D]'))
        assert_series_equal(s, Series(date_range('20130101', periods=3,
                                                 freq='D')))

        # s = Series(np.array(['2013-01-01 00:00:01','2013-01-01
        # 00:00:02','2013-01-01 00:00:03'],dtype='datetime64[s]'))

        # assert_series_equal(s,date_range('20130101
        # 00:00:01',period=3,freq='s')) 

# 需要導入模塊: import pandas [as 別名]
# 或者: from pandas import timedelta_range [as 別名]
def test_select_dtypes_include_exclude_using_scalars(self):
        df = DataFrame({'a': list('abc'),
                        'b': list(range(1, 4)),
                        'c': np.arange(3, 6).astype('u1'),
                        'd': np.arange(4.0, 7.0, dtype='float64'),
                        'e': [True, False, True],
                        'f': pd.Categorical(list('abc')),
                        'g': pd.date_range('20130101', periods=3),
                        'h': pd.date_range('20130101', periods=3,
                                           tz='US/Eastern'),
                        'i': pd.date_range('20130101', periods=3,
                                           tz='CET'),
                        'j': pd.period_range('2013-01', periods=3,
                                             freq='M'),
                        'k': pd.timedelta_range('1 day', periods=3)})

        ri = df.select_dtypes(include=np.number, exclude='floating')
        ei = df[['b', 'c', 'k']]
        assert_frame_equal(ri, ei) 

# 需要導入模塊: import pandas [as 別名]
# 或者: from pandas import timedelta_range [as 別名]
def test_select_dtypes_include_exclude_mixed_scalars_lists(self):
        df = DataFrame({'a': list('abc'),
                        'b': list(range(1, 4)),
                        'c': np.arange(3, 6).astype('u1'),
                        'd': np.arange(4.0, 7.0, dtype='float64'),
                        'e': [True, False, True],
                        'f': pd.Categorical(list('abc')),
                        'g': pd.date_range('20130101', periods=3),
                        'h': pd.date_range('20130101', periods=3,
                                           tz='US/Eastern'),
                        'i': pd.date_range('20130101', periods=3,
                                           tz='CET'),
                        'j': pd.period_range('2013-01', periods=3,
                                             freq='M'),
                        'k': pd.timedelta_range('1 day', periods=3)})

        ri = df.select_dtypes(include=np.number,
                              exclude=['floating', 'timedelta'])
        ei = df[['b', 'c']]
        assert_frame_equal(ri, ei)

        ri = df.select_dtypes(include=[np.number, 'category'],
                              exclude='floating')
        ei = df[['b', 'c', 'f', 'k']]
        assert_frame_equal(ri, ei) 

# 需要導入模塊: import pandas [as 別名]
# 或者: from pandas import timedelta_range [as 別名]
def df_main_dtypes():
    return pd.DataFrame(
        {'group': [1, 1, 2],
         'int': [1, 2, 3],
         'float': [4., 5., 6.],
         'string': list('abc'),
         'category_string': pd.Series(list('abc')).astype('category'),
         'category_int': [7, 8, 9],
         'datetime': pd.date_range('20130101', periods=3),
         'datetimetz': pd.date_range('20130101',
                                     periods=3,
                                     tz='US/Eastern'),
         'timedelta': pd.timedelta_range('1 s', periods=3, freq='s')},
        columns=['group', 'int', 'float', 'string',
                 'category_string', 'category_int',
                 'datetime', 'datetimetz',
                 'timedelta']) 

# 需要導入模塊: import pandas [as 別名]
# 或者: from pandas import timedelta_range [as 別名]
def test_comparisons_coverage(self):
        rng = timedelta_range('1 days', periods=10)

        result = rng < rng[3]
        expected = np.array([True, True, True] + [False] * 7)
        tm.assert_numpy_array_equal(result, expected)

        # raise TypeError for now
        with pytest.raises(TypeError):
            rng < rng[3].value

        result = rng == list(rng)
        exp = rng == rng
        tm.assert_numpy_array_equal(result, exp)


# ------------------------------------------------------------------
# Timedelta64[ns] dtype Arithmetic Operations 

# 需要導入模塊: import pandas [as 別名]
# 或者: from pandas import timedelta_range [as 別名]
def test_td64_df_add_int_frame(self):
        # GH#22696 Check that we don't dispatch to numpy implementation,
        #  which treats int64 as m8[ns]
        tdi = pd.timedelta_range('1', periods=3)
        df = tdi.to_frame()
        other = pd.DataFrame([1, 2, 3], index=tdi)  # indexed like `df`
        with pytest.raises(TypeError):
            df + other
        with pytest.raises(TypeError):
            other + df
        with pytest.raises(TypeError):
            df - other
        with pytest.raises(TypeError):
            other - df

    # TODO: moved from tests.indexes.timedeltas.test_arithmetic; needs
    #  parametrization+de-duplication