我们从Python开源项目中，提取了以下50个代码示例，用于说明如何使用pandas.period_range()。
def test_period_resample_with_local_timezone_pytz(self): # GH5430 tm._skip_if_no_pytz() import pytz local_timezone = pytz.timezone('America/Los_Angeles') start = datetime(year=2013, month=11, day=1, hour=0, minute=0, tzinfo=pytz.utc) # 1 day later end = datetime(year=2013, month=11, day=2, hour=0, minute=0, tzinfo=pytz.utc) index = pd.date_range(start, end, freq='H') series = pd.Series(1, index=index) series = series.tz_convert(local_timezone) result = series.resample('D', kind='period').mean() # Create the expected series # Index is moved back a day with the timezone conversion from UTC to # Pacific expected_index = (pd.period_range(start=start, end=end, freq='D') - 1) expected = pd.Series(1, index=expected_index) assert_series_equal(result, expected)
def test_period_resample_with_local_timezone_dateutil(self): # GH5430 tm._skip_if_no_dateutil() import dateutil local_timezone = 'dateutil/America/Los_Angeles' start = datetime(year=2013, month=11, day=1, hour=0, minute=0, tzinfo=dateutil.tz.tzutc()) # 1 day later end = datetime(year=2013, month=11, day=2, hour=0, minute=0, tzinfo=dateutil.tz.tzutc()) index = pd.date_range(start, end, freq='H') series = pd.Series(1, index=index) series = series.tz_convert(local_timezone) result = series.resample('D', kind='period').mean() # Create the expected series # Index is moved back a day with the timezone conversion from UTC to # Pacific expected_index = (pd.period_range(start=start, end=end, freq='D') - 1) expected = pd.Series(1, index=expected_index) assert_series_equal(result, expected)
def test_resample_timestamp_to_period(self): ts = _simple_ts('1/1/1990', '1/1/2000') result = ts.resample('A-DEC', kind='period').mean() expected = ts.resample('A-DEC').mean() expected.index = period_range('1990', '2000', freq='a-dec') assert_series_equal(result, expected) result = ts.resample('A-JUN', kind='period').mean() expected = ts.resample('A-JUN').mean() expected.index = period_range('1990', '2000', freq='a-jun') assert_series_equal(result, expected) result = ts.resample('M', kind='period').mean() expected = ts.resample('M').mean() expected.index = period_range('1990-01', '2000-01', freq='M') assert_series_equal(result, expected) result = ts.resample('M', kind='period').mean() expected = ts.resample('M').mean() expected.index = period_range('1990-01', '2000-01', freq='M') assert_series_equal(result, expected)
def test_annual_upsample(self): ts = _simple_pts('1/1/1990', '12/31/1995', freq='A-DEC') df = DataFrame({'a': ts}) rdf = df.resample('D').ffill() exp = df['a'].resample('D').ffill() assert_series_equal(rdf['a'], exp) rng = period_range('2000', '2003', freq='A-DEC') ts = Series([1, 2, 3, 4], index=rng) result = ts.resample('M').ffill() ex_index = period_range('2000-01', '2003-12', freq='M') expected = ts.asfreq('M', how='start').reindex(ex_index, method='ffill') assert_series_equal(result, expected)
def test_resample_bms_2752(self): # GH2753 foo = pd.Series(index=pd.bdate_range('20000101', '20000201')) res1 = foo.resample("BMS").mean() res2 = foo.resample("BMS").mean().resample("B").mean() self.assertEqual(res1.index[0], Timestamp('20000103')) self.assertEqual(res1.index[0], res2.index[0]) # def test_monthly_convention_span(self): # rng = period_range('2000-01', periods=3, freq='M') # ts = Series(np.arange(3), index=rng) # # hacky way to get same thing # exp_index = period_range('2000-01-01', '2000-03-31', freq='D') # expected = ts.asfreq('D', how='end').reindex(exp_index) # expected = expected.fillna(method='bfill') # result = ts.resample('D', convention='span').mean() # assert_series_equal(result, expected)
def test_dti_to_period(self): dti = DatetimeIndex(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') self.assertEqual(pi1[0], Period('Jan 2005', freq='M')) self.assertEqual(pi2[0], Period('1/31/2005', freq='D')) self.assertEqual(pi3[0], Period('1/31/2005', freq='3D')) self.assertEqual(pi1[-1], Period('Nov 2005', freq='M')) self.assertEqual(pi2[-1], Period('11/30/2005', freq='D')) self.assertEqual(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'))
def test_pindex_multiples(self): 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='M') tm.assert_index_equal(pi, expected) self.assertEqual(pi.freq, offsets.MonthEnd(2)) self.assertEqual(pi.freqstr, '2M') pi = period_range(start='1/1/11', end='12/31/11', freq='2M') tm.assert_index_equal(pi, expected) self.assertEqual(pi.freq, offsets.MonthEnd(2)) self.assertEqual(pi.freqstr, '2M') pi = period_range(start='1/1/11', periods=6, freq='2M') tm.assert_index_equal(pi, expected) self.assertEqual(pi.freq, offsets.MonthEnd(2)) self.assertEqual(pi.freqstr, '2M')
def test_align_series(self): rng = period_range('1/1/2000', '1/1/2010', freq='A') ts = Series(np.random.randn(len(rng)), index=rng) result = ts + ts[::2] expected = ts + ts expected[1::2] = np.nan assert_series_equal(result, expected) result = ts + _permute(ts[::2]) assert_series_equal(result, expected) # it works! for kind in ['inner', 'outer', 'left', 'right']: ts.align(ts[::2], join=kind) msg = "Input has different freq=D from PeriodIndex\\(freq=A-DEC\\)" with assertRaisesRegexp(ValueError, msg): ts + ts.asfreq('D', how="end")
def test_union(self): index = period_range('1/1/2000', '1/20/2000', freq='D') result = index[:-5].union(index[10:]) self.assertTrue(result.equals(index)) # not in order result = _permute(index[:-5]).union(_permute(index[10:])) self.assertTrue(result.equals(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') self.assertRaises(ValueError, index.union, index2) self.assertRaises(ValueError, index.join, index.to_timestamp()) index3 = period_range('1/1/2000', '1/20/2000', freq='2D') self.assertRaises(ValueError, index.join, index3)
def test_nested_dict_frame_constructor(self): rng = pd.period_range('1/1/2000', periods=5) df = DataFrame(randn(10, 5), columns=rng) data = {} for col in df.columns: for row in df.index: data.setdefault(col, {})[row] = df.get_value(row, col) result = DataFrame(data, columns=rng) assert_frame_equal(result, df) data = {} for col in df.columns: for row in df.index: data.setdefault(row, {})[col] = df.get_value(row, col) result = DataFrame(data, index=rng).T assert_frame_equal(result, df)
def test_reset_index_period(self): # GH 7746 idx = pd.MultiIndex.from_product([pd.period_range('20130101', periods=3, freq='M'), ['a', 'b', 'c']], names=['month', 'feature']) df = pd.DataFrame(np.arange(9, dtype='int64') .reshape(-1, 1), index=idx, columns=['a']) expected = pd.DataFrame({ 'month': ([pd.Period('2013-01', freq='M')] * 3 + [pd.Period('2013-02', freq='M')] * 3 + [pd.Period('2013-03', freq='M')] * 3), 'feature': ['a', 'b', 'c'] * 3, 'a': np.arange(9, dtype='int64') }, columns=['month', 'feature', 'a']) assert_frame_equal(df.reset_index(), expected)
def test_set_index_period(self): # GH 6631 df = DataFrame(np.random.random(6)) idx1 = pd.period_range('2011-01-01', periods=3, freq='M') idx1 = idx1.append(idx1) idx2 = pd.period_range('2013-01-01 09:00', periods=2, freq='H') idx2 = idx2.append(idx2).append(idx2) idx3 = pd.period_range('2005', periods=6, freq='A') df = df.set_index(idx1) df = df.set_index(idx2, append=True) df = df.set_index(idx3, append=True) expected1 = pd.period_range('2011-01-01', periods=3, freq='M') expected2 = pd.period_range('2013-01-01 09:00', periods=2, freq='H') self.assertTrue(df.index.levels[0].equals(expected1)) self.assertTrue(df.index.levels[1].equals(expected2)) self.assertTrue(df.index.levels[2].equals(idx3)) self.assertTrue(df.index.get_level_values(0).equals(idx1)) self.assertTrue(df.index.get_level_values(1).equals(idx2)) self.assertTrue(df.index.get_level_values(2).equals(idx3))
def test_categorical_series_repr_period(self): idx = pd.period_range('2011-01-01 09:00', freq='H', periods=5) s = pd.Series(pd.Categorical(idx)) exp = """0 2011-01-01 09:00 1 2011-01-01 10:00 2 2011-01-01 11:00 3 2011-01-01 12:00 4 2011-01-01 13:00 dtype: category Categories (5, period): [2011-01-01 09:00, 2011-01-01 10:00, 2011-01-01 11:00, 2011-01-01 12:00, 2011-01-01 13:00]""" self.assertEqual(repr(s), exp) idx = pd.period_range('2011-01', freq='M', periods=5) s = pd.Series(pd.Categorical(idx)) exp = """0 2011-01 1 2011-02 2 2011-03 3 2011-04 4 2011-05 dtype: category Categories (5, period): [2011-01, 2011-02, 2011-03, 2011-04, 2011-05]""" self.assertEqual(repr(s), exp)
def test_categorical_series_repr_period_ordered(self): idx = pd.period_range('2011-01-01 09:00', freq='H', periods=5) s = pd.Series(pd.Categorical(idx, ordered=True)) exp = """0 2011-01-01 09:00 1 2011-01-01 10:00 2 2011-01-01 11:00 3 2011-01-01 12:00 4 2011-01-01 13:00 dtype: category Categories (5, period): [2011-01-01 09:00 < 2011-01-01 10:00 < 2011-01-01 11:00 < 2011-01-01 12:00 < 2011-01-01 13:00]""" self.assertEqual(repr(s), exp) idx = pd.period_range('2011-01', freq='M', periods=5) s = pd.Series(pd.Categorical(idx, ordered=True)) exp = """0 2011-01 1 2011-02 2 2011-03 3 2011-04 4 2011-05 dtype: category Categories (5, period): [2011-01 < 2011-02 < 2011-03 < 2011-04 < 2011-05]""" self.assertEqual(repr(s), exp)
def test_f_f_research(self): results = web.DataReader("F-F_Research_Data_Factors", "famafrench", start='2010-01-01', end='2010-12-01') self.assertTrue(isinstance(results, dict)) self.assertEqual(len(results), 3) exp = pd.DataFrame({'Mkt-RF': [-3.36, 3.4, 6.31, 2., -7.89, -5.56, 6.93, -4.77, 9.54, 3.88, 0.6, 6.82], 'SMB': [0.2, 1.44, 1.57, 4.92, -0.09, -2.15, 0.24, -3.03, 3.84, 1.01, 3.69, 0.85], 'HML': [0.61, 2.74, 2.01, 3.12, -2.32, -4.27, 0.04, -1.51, -2.94, -2.23, -0.58, 3.47], 'RF': [0., 0., 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01]}, index=pd.period_range('2010-01-01', '2010-12-01', freq='M', name='Date'), columns=['Mkt-RF', 'SMB', 'HML', 'RF']) tm.assert_frame_equal(results[0], exp)
def get_quarts(start, end): idx = pd.period_range('Q'.join(year_qua(start)), 'Q'.join(year_qua(end)), freq='Q-JAN') return [str(d).split('Q') for d in idx][::-1]
def test_to_period(self): from pandas.tseries.period import period_range ts = _simple_ts('1/1/2000', '1/1/2001') pts = ts.to_period() exp = ts.copy() exp.index = period_range('1/1/2000', '1/1/2001') assert_series_equal(pts, exp) pts = ts.to_period('M') exp.index = exp.index.asfreq('M') self.assertTrue(pts.index.equals(exp.index.asfreq('M'))) assert_series_equal(pts, exp) # GH 7606 without freq idx = DatetimeIndex(['2011-01-01', '2011-01-02', '2011-01-03', '2011-01-04']) exp_idx = pd.PeriodIndex(['2011-01-01', '2011-01-02', '2011-01-03', '2011-01-04'], freq='D') s = Series(np.random.randn(4), index=idx) expected = s.copy() expected.index = exp_idx assert_series_equal(s.to_period(), expected) df = DataFrame(np.random.randn(4, 4), index=idx, columns=idx) expected = df.copy() expected.index = exp_idx assert_frame_equal(df.to_period(), expected) expected = df.copy() expected.columns = exp_idx assert_frame_equal(df.to_period(axis=1), expected)
def test_frame_to_period(self): K = 5 from pandas.tseries.period import period_range dr = date_range('1/1/2000', '1/1/2001') pr = period_range('1/1/2000', '1/1/2001') df = DataFrame(randn(len(dr), K), index=dr) df['mix'] = 'a' pts = df.to_period() exp = df.copy() exp.index = pr assert_frame_equal(pts, exp) pts = df.to_period('M') self.assertTrue(pts.index.equals(exp.index.asfreq('M'))) df = df.T pts = df.to_period(axis=1) exp = df.copy() exp.columns = pr assert_frame_equal(pts, exp) pts = df.to_period('M', axis=1) self.assertTrue(pts.columns.equals(exp.columns.asfreq('M'))) self.assertRaises(ValueError, df.to_period, axis=2)
def test_asobject_tolist(self): idx = pd.period_range(start='2013-01-01', periods=4, freq='M', name='idx') expected_list = [pd.Period('2013-01-31', freq='M'), pd.Period('2013-02-28', freq='M'), pd.Period('2013-03-31', freq='M'), pd.Period('2013-04-30', freq='M')] expected = pd.Index(expected_list, dtype=object, name='idx') result = idx.asobject self.assertTrue(isinstance(result, Index)) self.assertEqual(result.dtype, object) self.assertTrue(result.equals(expected)) self.assertEqual(result.name, expected.name) self.assertEqual(idx.tolist(), expected_list) idx = PeriodIndex(['2013-01-01', '2013-01-02', 'NaT', '2013-01-04'], freq='D', name='idx') expected_list = [pd.Period('2013-01-01', freq='D'), pd.Period('2013-01-02', freq='D'), pd.Period('NaT', freq='D'), pd.Period('2013-01-04', freq='D')] expected = pd.Index(expected_list, dtype=object, name='idx') result = idx.asobject self.assertTrue(isinstance(result, Index)) self.assertEqual(result.dtype, object) for i in [0, 1, 3]: self.assertTrue(result[i], expected[i]) self.assertTrue(result[2].ordinal, pd.tslib.iNaT) self.assertTrue(result[2].freq, 'D') self.assertEqual(result.name, expected.name) result_list = idx.tolist() for i in [0, 1, 3]: self.assertTrue(result_list[i], expected_list[i]) self.assertTrue(result_list[2].ordinal, pd.tslib.iNaT) self.assertTrue(result_list[2].freq, 'D')
def test_resolution(self): for freq, expected in zip(['A', 'Q', 'M', 'D', 'H', 'T', 'S', 'L', 'U'], ['day', 'day', 'day', 'day', 'hour', 'minute', 'second', 'millisecond', 'microsecond']): idx = pd.period_range(start='2013-04-01', periods=30, freq=freq) self.assertEqual(idx.resolution, expected)
def test_value_counts_unique(self): # GH 7735 idx = pd.period_range('2011-01-01 09:00', freq='H', periods=10) # create repeated values, 'n'th element is repeated by n+1 times idx = PeriodIndex( np.repeat(idx.values, range(1, len(idx) + 1)), freq='H') exp_idx = PeriodIndex(['2011-01-01 18:00', '2011-01-01 17:00', '2011-01-01 16:00', '2011-01-01 15:00', '2011-01-01 14:00', '2011-01-01 13:00', '2011-01-01 12:00', '2011-01-01 11:00', '2011-01-01 10:00', '2011-01-01 09:00'], freq='H') expected = Series(range(10, 0, -1), index=exp_idx, dtype='int64') tm.assert_series_equal(idx.value_counts(), expected) expected = pd.period_range('2011-01-01 09:00', freq='H', periods=10) tm.assert_index_equal(idx.unique(), expected) idx = PeriodIndex(['2013-01-01 09:00', '2013-01-01 09:00', '2013-01-01 09:00', '2013-01-01 08:00', '2013-01-01 08:00', pd.NaT], freq='H') exp_idx = PeriodIndex( ['2013-01-01 09:00', '2013-01-01 08:00'], freq='H') expected = Series([3, 2], index=exp_idx) tm.assert_series_equal(idx.value_counts(), expected) exp_idx = PeriodIndex( ['2013-01-01 09:00', '2013-01-01 08:00', pd.NaT], freq='H') expected = Series([3, 2, 1], index=exp_idx) tm.assert_series_equal(idx.value_counts(dropna=False), expected) tm.assert_index_equal(idx.unique(), exp_idx)
def test_drop_duplicates_metadata(self): # GH 10115 idx = pd.period_range('2011-01-01', '2011-01-31', freq='D', name='idx') result = idx.drop_duplicates() self.assert_index_equal(idx, result) self.assertEqual(idx.freq, result.freq) idx_dup = idx.append(idx) # freq will not be reset result = idx_dup.drop_duplicates() self.assert_index_equal(idx, result) self.assertEqual(idx.freq, result.freq)
def test_nat_new(self): idx = pd.period_range('2011-01', freq='M', periods=5, name='x') result = idx._nat_new() exp = pd.PeriodIndex([pd.NaT] * 5, freq='M', name='x') tm.assert_index_equal(result, exp) result = idx._nat_new(box=False) exp = np.array([tslib.iNaT] * 5, dtype=np.int64) tm.assert_numpy_array_equal(result, exp)
def test_resample_to_period_monthly_buglet(self): # GH #1259 rng = date_range('1/1/2000', '12/31/2000') ts = Series(np.random.randn(len(rng)), index=rng) result = ts.resample('M', kind='period').mean() exp_index = period_range('Jan-2000', 'Dec-2000', freq='M') self.assertTrue(result.index.equals(exp_index))
def test_period_with_agg(self): # aggregate a period resampler with a lambda s2 = pd.Series(np.random.randint(0, 5, 50), index=pd.period_range('2012-01-01', freq='H', periods=50), dtype='float64') expected = s2.to_timestamp().resample('D').mean().to_period() result = s2.resample('D').agg(lambda x: x.mean()) assert_series_equal(result, expected)
def test_basic_downsample(self): ts = _simple_pts('1/1/1990', '6/30/1995', freq='M') result = ts.resample('a-dec').mean() expected = ts.groupby(ts.index.year).mean() expected.index = period_range('1/1/1990', '6/30/1995', freq='a-dec') assert_series_equal(result, expected) # this is ok assert_series_equal(ts.resample('a-dec').mean(), result) assert_series_equal(ts.resample('a').mean(), result)
def test_upsample_with_limit(self): rng = period_range('1/1/2000', periods=5, freq='A') ts = Series(np.random.randn(len(rng)), rng) result = ts.resample('M', convention='end').ffill(limit=2) expected = ts.asfreq('M').reindex(result.index, method='ffill', limit=2) assert_series_equal(result, expected)
def test_resample_to_quarterly(self): for month in MONTHS: ts = _simple_pts('1990', '1992', freq='A-%s' % month) quar_ts = ts.resample('Q-%s' % month).ffill() stamps = ts.to_timestamp('D', how='start') qdates = period_range(ts.index[0].asfreq('D', 'start'), ts.index[-1].asfreq('D', 'end'), freq='Q-%s' % month) expected = stamps.reindex(qdates.to_timestamp('D', 's'), method='ffill') expected.index = qdates assert_series_equal(quar_ts, expected) # conforms, but different month ts = _simple_pts('1990', '1992', freq='A-JUN') for how in ['start', 'end']: result = ts.resample('Q-MAR', convention=how).ffill() expected = ts.asfreq('Q-MAR', how=how) expected = expected.reindex(result.index, method='ffill') # .to_timestamp('D') # expected = expected.resample('Q-MAR').ffill() assert_series_equal(result, expected)
def test_resample_5minute(self): rng = period_range('1/1/2000', '1/5/2000', freq='T') ts = Series(np.random.randn(len(rng)), index=rng) result = ts.resample('5min').mean() expected = ts.to_timestamp().resample('5min').mean() assert_series_equal(result, expected)
def test_quarterly_resampling(self): rng = period_range('2000Q1', periods=10, freq='Q-DEC') ts = Series(np.arange(10), index=rng) result = ts.resample('A').mean() exp = ts.to_timestamp().resample('A').mean().to_period() assert_series_equal(result, exp)
def test_all_values_single_bin(self): # 2070 index = period_range(start="2012-01-01", end="2012-12-31", freq="M") s = Series(np.random.randn(len(index)), index=index) result = s.resample("A").mean() tm.assert_almost_equal(result[0], s.mean())
def test_hash_error(self): index = period_range('20010101', periods=10) with tm.assertRaisesRegexp(TypeError, "unhashable type: %r" % type(index).__name__): hash(index)
def test_constructor_field_arrays(self): # GH #1264 years = np.arange(1990, 2010).repeat(4)[2:-2] quarters = np.tile(np.arange(1, 5), 20)[2:-2] index = PeriodIndex(year=years, quarter=quarters, freq='Q-DEC') expected = period_range('1990Q3', '2009Q2', freq='Q-DEC') self.assertTrue(index.equals(expected)) index2 = PeriodIndex(year=years, quarter=quarters, freq='2Q-DEC') tm.assert_numpy_array_equal(index.asi8, index2.asi8) index = PeriodIndex(year=years, quarter=quarters) self.assertTrue(index.equals(expected)) years = [2007, 2007, 2007] months = [1, 2] self.assertRaises(ValueError, PeriodIndex, year=years, month=months, freq='M') self.assertRaises(ValueError, PeriodIndex, year=years, month=months, freq='2M') self.assertRaises(ValueError, PeriodIndex, year=years, month=months, freq='M', start=Period('2007-01', freq='M')) years = [2007, 2007, 2007] months = [1, 2, 3] idx = PeriodIndex(year=years, month=months, freq='M') exp = period_range('2007-01', periods=3, freq='M') self.assertTrue(idx.equals(exp))
def test_constructor_U(self): # U was used as undefined period self.assertRaises(ValueError, period_range, '2007-1-1', periods=500, freq='X')
def test_constructor_corner(self): self.assertRaises(ValueError, PeriodIndex, periods=10, freq='A') start = Period('2007', freq='A-JUN') end = Period('2010', freq='A-DEC') self.assertRaises(ValueError, PeriodIndex, start=start, end=end) self.assertRaises(ValueError, PeriodIndex, start=start) self.assertRaises(ValueError, PeriodIndex, end=end) result = period_range('2007-01', periods=10.5, freq='M') exp = period_range('2007-01', periods=10, freq='M') self.assertTrue(result.equals(exp))
def test_constructor_fromarraylike(self): idx = period_range('2007-01', periods=20, freq='M') self.assertRaises(ValueError, PeriodIndex, idx.values) self.assertRaises(ValueError, PeriodIndex, list(idx.values)) self.assertRaises(ValueError, PeriodIndex, data=Period('2007', freq='A')) result = PeriodIndex(iter(idx)) self.assertTrue(result.equals(idx)) result = PeriodIndex(idx) self.assertTrue(result.equals(idx)) result = PeriodIndex(idx, freq='M') self.assertTrue(result.equals(idx)) result = PeriodIndex(idx, freq=offsets.MonthEnd()) self.assertTrue(result.equals(idx)) self.assertTrue(result.freq, 'M') result = PeriodIndex(idx, freq='2M') self.assertTrue(result.equals(idx)) self.assertTrue(result.freq, '2M') result = PeriodIndex(idx, freq=offsets.MonthEnd(2)) self.assertTrue(result.equals(idx)) self.assertTrue(result.freq, '2M') result = PeriodIndex(idx, freq='D') exp = idx.asfreq('D', 'e') self.assertTrue(result.equals(exp))
def test_constructor_simple_new(self): idx = period_range('2007-01', name='p', periods=20, freq='M') result = idx._simple_new(idx, 'p', freq=idx.freq) self.assertTrue(result.equals(idx)) result = idx._simple_new(idx.astype('i8'), 'p', freq=idx.freq) self.assertTrue(result.equals(idx))
def test_constructor_freq_mult(self): # GH #7811 for func in [PeriodIndex, period_range]: # must be the same, but for sure... pidx = func(start='2014-01', freq='2M', periods=4) expected = PeriodIndex( ['2014-01', '2014-03', '2014-05', '2014-07'], freq='M') tm.assert_index_equal(pidx, expected) pidx = func(start='2014-01-02', end='2014-01-15', freq='3D') expected = PeriodIndex(['2014-01-02', '2014-01-05', '2014-01-08', '2014-01-11', '2014-01-14'], freq='D') tm.assert_index_equal(pidx, expected) pidx = func(end='2014-01-01 17:00', freq='4H', periods=3) expected = PeriodIndex(['2014-01-01 09:00', '2014-01-01 13:00', '2014-01-01 17:00'], freq='4H') tm.assert_index_equal(pidx, expected) msg = ('Frequency must be positive, because it' ' represents span: -1M') with tm.assertRaisesRegexp(ValueError, msg): PeriodIndex(['2011-01'], freq='-1M') msg = ('Frequency must be positive, because it' ' represents span: 0M') with tm.assertRaisesRegexp(ValueError, msg): PeriodIndex(['2011-01'], freq='0M') msg = ('Frequency must be positive, because it' ' represents span: 0M') with tm.assertRaisesRegexp(ValueError, msg): period_range('2011-01', periods=3, freq='0M')
def test_comp_period(self): idx = period_range('2007-01', periods=20, freq='M') result = idx < idx[10] exp = idx.values < idx.values[10] self.assert_numpy_array_equal(result, exp)
def test_getitem_ndim2(self): idx = period_range('2007-01', periods=3, freq='M') result = idx[:, None] # MPL kludge tm.assertIsInstance(result, PeriodIndex)
def test_getitem_partial(self): rng = period_range('2007-01', periods=50, freq='M') ts = Series(np.random.randn(len(rng)), rng) self.assertRaises(KeyError, ts.__getitem__, '2006') result = ts['2008'] self.assertTrue((result.index.year == 2008).all()) result = ts['2008':'2009'] self.assertEqual(len(result), 24) result = ts['2008-1':'2009-12'] self.assertEqual(len(result), 24) result = ts['2008Q1':'2009Q4'] self.assertEqual(len(result), 24) result = ts[:'2009'] self.assertEqual(len(result), 36) result = ts['2009':] self.assertEqual(len(result), 50 - 24) exp = result result = ts[24:] assert_series_equal(exp, result) ts = ts[10:].append(ts[10:]) self.assertRaisesRegexp(KeyError, "left slice bound for non-unique " "label: '2008'", ts.__getitem__, slice('2008', '2009'))
def test_getitem_datetime(self): rng = period_range(start='2012-01-01', periods=10, freq='W-MON') ts = Series(lrange(len(rng)), index=rng) dt1 = datetime(2011, 10, 2) dt4 = datetime(2012, 4, 20) rs = ts[dt1:dt4] assert_series_equal(rs, ts)
def test_slice_with_zero_step_raises(self): ts = Series(np.arange(20), period_range('2014-01', periods=20, freq='M')) self.assertRaisesRegexp(ValueError, 'slice step cannot be zero', lambda: ts[::0]) self.assertRaisesRegexp(ValueError, 'slice step cannot be zero', lambda: ts.loc[::0]) self.assertRaisesRegexp(ValueError, 'slice step cannot be zero', lambda: ts.ix[::0])
def test_contains(self): rng = period_range('2007-01', freq='M', periods=10) self.assertTrue(Period('2007-01', freq='M') in rng) self.assertFalse(Period('2007-01', freq='D') in rng) self.assertFalse(Period('2007-01', freq='2M') in rng)
def test_sub(self): rng = period_range('2007-01', periods=50) result = rng - 5 exp = rng + (-5) self.assertTrue(result.equals(exp))
def test_periods_number_check(self): self.assertRaises(ValueError, period_range, '2011-1-1', '2012-1-1', 'B')
def test_as_frame_columns(self): rng = period_range('1/1/2000', periods=5) df = DataFrame(randn(10, 5), columns=rng) ts = df[rng[0]] assert_series_equal(ts, df.ix[:, 0]) # GH # 1211 repr(df) ts = df['1/1/2000'] assert_series_equal(ts, df.ix[:, 0])
def test_frame_setitem(self): rng = period_range('1/1/2000', periods=5) rng.name = 'index' df = DataFrame(randn(5, 3), index=rng) df['Index'] = rng rs = Index(df['Index']) self.assertTrue(rs.equals(rng)) rs = df.reset_index().set_index('index') tm.assertIsInstance(rs.index, PeriodIndex) self.assertTrue(rs.index.equals(rng))
def test_period_set_index_reindex(self): # GH 6631 df = DataFrame(np.random.random(6)) idx1 = period_range('2011/01/01', periods=6, freq='M') idx2 = period_range('2013', periods=6, freq='A') df = df.set_index(idx1) self.assertTrue(df.index.equals(idx1)) df = df.set_index(idx2) self.assertTrue(df.index.equals(idx2))
