import warnings import pytest import numpy as np from datetime import timedelta import pandas as pd import pandas.util.testing as tm from pandas import (timedelta_range, date_range, Series, Timedelta, TimedeltaIndex, Index, DataFrame, Int64Index) from pandas.util.testing import (assert_almost_equal, assert_series_equal, assert_index_equal) from ..datetimelike import DatetimeLike randn = np.random.randn class TestTimedeltaIndex(DatetimeLike): _holder = TimedeltaIndex def setup_method(self, method): self.indices = dict(index=tm.makeTimedeltaIndex(10)) self.setup_indices() def create_index(self): return pd.to_timedelta(range(5), unit='d') + pd.offsets.Hour(1) def test_numeric_compat(self): # Dummy method to override super's version; this test is now done # in test_arithmetic.py pass def test_shift(self): pass # this is handled in test_arithmetic.py def test_pickle_compat_construction(self): pass def test_fillna_timedelta(self): # GH 11343 idx = pd.TimedeltaIndex(['1 day', pd.NaT, '3 day']) exp = pd.TimedeltaIndex(['1 day', '2 day', '3 day']) tm.assert_index_equal(idx.fillna(pd.Timedelta('2 day')), exp) exp = pd.TimedeltaIndex(['1 day', '3 hour', '3 day']) idx.fillna(pd.Timedelta('3 hour')) exp = pd.Index( [pd.Timedelta('1 day'), 'x', pd.Timedelta('3 day')], dtype=object) tm.assert_index_equal(idx.fillna('x'), exp) def test_difference_freq(self): # GH14323: Difference of TimedeltaIndex should not preserve frequency index = timedelta_range("0 days", "5 days", freq="D") other = timedelta_range("1 days", "4 days", freq="D") expected = TimedeltaIndex(["0 days", "5 days"], freq=None) idx_diff = index.difference(other) tm.assert_index_equal(idx_diff, expected) tm.assert_attr_equal('freq', idx_diff, expected) other = timedelta_range("2 days", "5 days", freq="D") idx_diff = index.difference(other) expected = TimedeltaIndex(["0 days", "1 days"], freq=None) tm.assert_index_equal(idx_diff, expected) tm.assert_attr_equal('freq', idx_diff, expected) def test_isin(self): index = tm.makeTimedeltaIndex(4) result = index.isin(index) assert result.all() result = index.isin(list(index)) assert result.all() assert_almost_equal(index.isin([index[2], 5]), np.array([False, False, True, False])) def test_factorize(self): idx1 = TimedeltaIndex(['1 day', '1 day', '2 day', '2 day', '3 day', '3 day']) exp_arr = np.array([0, 0, 1, 1, 2, 2], dtype=np.intp) exp_idx = TimedeltaIndex(['1 day', '2 day', '3 day']) arr, idx = idx1.factorize() tm.assert_numpy_array_equal(arr, exp_arr) tm.assert_index_equal(idx, exp_idx) arr, idx = idx1.factorize(sort=True) tm.assert_numpy_array_equal(arr, exp_arr) tm.assert_index_equal(idx, exp_idx) # freq must be preserved idx3 = timedelta_range('1 day', periods=4, freq='s') exp_arr = np.array([0, 1, 2, 3], dtype=np.intp) arr, idx = idx3.factorize() tm.assert_numpy_array_equal(arr, exp_arr) tm.assert_index_equal(idx, idx3) def test_join_self(self, join_type): index = timedelta_range('1 day', periods=10) joined = index.join(index, how=join_type) tm.assert_index_equal(index, joined) def test_does_not_convert_mixed_integer(self): df = tm.makeCustomDataframe(10, 10, data_gen_f=lambda *args, **kwargs: randn(), r_idx_type='i', c_idx_type='td') str(df) cols = df.columns.join(df.index, how='outer') joined = cols.join(df.columns) assert cols.dtype == np.dtype('O') assert cols.dtype == joined.dtype tm.assert_index_equal(cols, joined) def test_sort_values(self): idx = TimedeltaIndex(['4d', '1d', '2d']) ordered = idx.sort_values() assert ordered.is_monotonic ordered = idx.sort_values(ascending=False) assert ordered[::-1].is_monotonic ordered, dexer = idx.sort_values(return_indexer=True) assert ordered.is_monotonic tm.assert_numpy_array_equal(dexer, np.array([1, 2, 0]), check_dtype=False) ordered, dexer = idx.sort_values(return_indexer=True, ascending=False) assert ordered[::-1].is_monotonic tm.assert_numpy_array_equal(dexer, np.array([0, 2, 1]), check_dtype=False) def test_get_duplicates(self): idx = TimedeltaIndex(['1 day', '2 day', '2 day', '3 day', '3day', '4day']) with warnings.catch_warnings(record=True): # Deprecated - see GH20239 result = idx.get_duplicates() ex = TimedeltaIndex(['2 day', '3day']) tm.assert_index_equal(result, ex) def test_argmin_argmax(self): idx = TimedeltaIndex(['1 day 00:00:05', '1 day 00:00:01', '1 day 00:00:02']) assert idx.argmin() == 1 assert idx.argmax() == 0 def test_misc_coverage(self): rng = timedelta_range('1 day', periods=5) result = rng.groupby(rng.days) assert isinstance(list(result.values())[0][0], Timedelta) idx = TimedeltaIndex(['3d', '1d', '2d']) assert not idx.equals(list(idx)) non_td = Index(list('abc')) assert not idx.equals(list(non_td)) def test_map(self): # test_map_dictlike generally tests rng = timedelta_range('1 day', periods=10) f = lambda x: x.days result = rng.map(f) exp = Int64Index([f(x) for x in rng]) tm.assert_index_equal(result, exp) def test_pass_TimedeltaIndex_to_index(self): rng = timedelta_range('1 days', '10 days') idx = Index(rng, dtype=object) expected = Index(rng.to_pytimedelta(), dtype=object) tm.assert_numpy_array_equal(idx.values, expected.values) def test_pickle(self): rng = timedelta_range('1 days', periods=10) rng_p = tm.round_trip_pickle(rng) tm.assert_index_equal(rng, rng_p) def test_hash_error(self): index = timedelta_range('1 days', periods=10) with tm.assert_raises_regex(TypeError, "unhashable type: %r" % type(index).__name__): hash(index) def test_append_join_nondatetimeindex(self): rng = timedelta_range('1 days', periods=10) idx = Index(['a', 'b', 'c', 'd']) result = rng.append(idx) assert isinstance(result[0], Timedelta) # it works rng.join(idx, how='outer') def test_append_numpy_bug_1681(self): td = timedelta_range('1 days', '10 days', freq='2D') a = DataFrame() c = DataFrame({'A': 'foo', 'B': td}, index=td) str(c) result = a.append(c) assert (result['B'] == td).all() def test_fields(self): rng = timedelta_range('1 days, 10:11:12.100123456', periods=2, freq='s') tm.assert_index_equal(rng.days, Index([1, 1], dtype='int64')) tm.assert_index_equal( rng.seconds, Index([10 * 3600 + 11 * 60 + 12, 10 * 3600 + 11 * 60 + 13], dtype='int64')) tm.assert_index_equal( rng.microseconds, Index([100 * 1000 + 123, 100 * 1000 + 123], dtype='int64')) tm.assert_index_equal(rng.nanoseconds, Index([456, 456], dtype='int64')) pytest.raises(AttributeError, lambda: rng.hours) pytest.raises(AttributeError, lambda: rng.minutes) pytest.raises(AttributeError, lambda: rng.milliseconds) # with nat s = Series(rng) s[1] = np.nan tm.assert_series_equal(s.dt.days, Series([1, np.nan], index=[0, 1])) tm.assert_series_equal(s.dt.seconds, Series( [10 * 3600 + 11 * 60 + 12, np.nan], index=[0, 1])) # preserve name (GH15589) rng.name = 'name' assert rng.days.name == 'name' def test_freq_conversion(self): # doc example # series td = Series(date_range('20130101', periods=4)) - \ Series(date_range('20121201', periods=4)) td[2] += timedelta(minutes=5, seconds=3) td[3] = np.nan result = td / np.timedelta64(1, 'D') expected = Series([31, 31, (31 * 86400 + 5 * 60 + 3) / 86400.0, np.nan ]) assert_series_equal(result, expected) result = td.astype('timedelta64[D]') expected = Series([31, 31, 31, np.nan]) assert_series_equal(result, expected) result = td / np.timedelta64(1, 's') expected = Series([31 * 86400, 31 * 86400, 31 * 86400 + 5 * 60 + 3, np.nan]) assert_series_equal(result, expected) result = td.astype('timedelta64[s]') assert_series_equal(result, expected) # tdi td = TimedeltaIndex(td) result = td / np.timedelta64(1, 'D') expected = Index([31, 31, (31 * 86400 + 5 * 60 + 3) / 86400.0, np.nan]) assert_index_equal(result, expected) result = td.astype('timedelta64[D]') expected = Index([31, 31, 31, np.nan]) assert_index_equal(result, expected) result = td / np.timedelta64(1, 's') expected = Index([31 * 86400, 31 * 86400, 31 * 86400 + 5 * 60 + 3, np.nan]) assert_index_equal(result, expected) result = td.astype('timedelta64[s]') assert_index_equal(result, expected) class TestTimeSeries(object): def test_series_box_timedelta(self): rng = timedelta_range('1 day 1 s', periods=5, freq='h') s = Series(rng) assert isinstance(s[1], Timedelta) assert isinstance(s.iat[2], Timedelta)