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_series(self):
# GH6407
# inferring series
# invalid type of Series
for s in [Series(np.arange(10)), Series(np.arange(10.))]:
self.assertRaises(TypeError, lambda: frequencies.infer_freq(s))
# a non-convertible string
self.assertRaises(ValueError,
lambda: frequencies.infer_freq(
Series(['foo', 'bar'])))
# cannot infer on PeriodIndex
for freq in [None, 'L']:
s = Series(period_range('2013', periods=10, freq=freq))
self.assertRaises(TypeError, lambda: frequencies.infer_freq(s))
for freq in ['Y']:
msg = frequencies._INVALID_FREQ_ERROR
with tm.assertRaisesRegexp(ValueError, msg):
s = Series(period_range('2013', periods=10, freq=freq))
self.assertRaises(TypeError, lambda: frequencies.infer_freq(s))
# DateTimeIndex
for freq in ['M', 'L', 'S']:
s = Series(date_range('20130101', periods=10, freq=freq))
inferred = frequencies.infer_freq(s)
self.assertEqual(inferred, freq)
s = Series(date_range('20130101', '20130110'))
inferred = frequencies.infer_freq(s)
self.assertEqual(inferred, 'D')
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')
tm.assert_index_equal(index, 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)
tm.assert_index_equal(index, expected)
years = [2007, 2007, 2007]
months = [1, 2]
msg = "Mismatched Period array lengths"
with pytest.raises(ValueError, match=msg):
PeriodIndex(year=years, month=months, freq='M')
with pytest.raises(ValueError, match=msg):
PeriodIndex(year=years, month=months, freq='2M')
msg = "Can either instantiate from fields or endpoints, but not both"
with pytest.raises(ValueError, match=msg):
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')
tm.assert_index_equal(idx, exp)
def slide9():
p = pd.Period(2007, freq='A-DEC')
print p
print 'after 5 years'
print p + 5
print 'before 2 yeaars'
print p - 2
print pd.Period('2014', freq='A-DEC') - p
rng = pd.period_range('1/1/2000', '6/30/2000', freq='M')
print rng
print Series(np.random.randn(6), index=rng)
values = ['2001Q3', '2002Q2', '2003Q1']
index = pd.PeriodIndex(values, freq='Q-DEC')
print index
print '2007, A-DEC'
p = pd.Period('2007', freq='A-DEC')
print p.asfreq('M', 'start')
print p.asfreq('M', 'end')
print '2007, A-JUN'
p = pd.Period('2007', freq='A-JUN')
print p.asfreq('M', 'start')
print p.asfreq('M', 'end')
p = pd.Period('2007-08', 'M')
print p.asfreq('A-JUN')
rng = pd.period_range('2006', '2009', freq='A-DEC')
ts = Series(np.random.randn(len(rng)), index=rng)
print ts
def test_categorical_repr_period_ordered(self):
idx = period_range('2011-01-01 09:00', freq='H', periods=5)
c = Categorical(idx, ordered=True)
exp = """[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]
Categories (5, period[H]): [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]""" # noqa
assert repr(c) == exp
c = Categorical(idx.append(idx), categories=idx, ordered=True)
exp = """[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, 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]
Categories (5, period[H]): [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]""" # noqa
assert repr(c) == exp
idx = period_range('2011-01', freq='M', periods=5)
c = Categorical(idx, ordered=True)
exp = """[2011-01, 2011-02, 2011-03, 2011-04, 2011-05]
Categories (5, period[M]): [2011-01 < 2011-02 < 2011-03 < 2011-04 < 2011-05]"""
assert repr(c) == exp
c = Categorical(idx.append(idx), categories=idx, ordered=True)
exp = """[2011-01, 2011-02, 2011-03, 2011-04, 2011-05, 2011-01, 2011-02, 2011-03, 2011-04, 2011-05]
Categories (5, period[M]): [2011-01 < 2011-02 < 2011-03 < 2011-04 < 2011-05]""" # noqa
assert repr(c) == exp
def row_process(s):
row = [s['key']]
for c in dataset['dimension_keys']:
if c in s['dimensions']:
row.append(s['dimensions'][c])
else:
row.append('')
p_start_date = pandas.Period(ordinal=s['start_date'], freq=freq)
p_end_date = pandas.Period(ordinal=s['end_date'], freq=freq)
"""
pDmin : pandas.Period() la plus ancienne
p_start_date-1 : périod en cours -1
>>> p_start_date -1
Period('1994', 'A-DEC')
Bug: ne renvoi rien si
p_start_date -1 devient identique à pDmin
"""
# Les None sont pour les périodes qui n'ont pas de valeur correspondantes
_row = [None for d in pandas.period_range(pDmin, p_start_date-1, freq=freq)]
row.extend(_row)
_row = [val["value"] for val in s['values']]
row.extend(_row)
_row = [None for d in pandas.period_range(p_end_date+1, pDmax, freq=freq)]
row.extend(_row)
return row
def test_construction_from_period(self):
# upsampling
start, end = Period('2017Q1', freq='Q'), Period('2018Q1', freq='Q')
expected = date_range(start='2017-03-31', end='2018-03-31', freq='M',
name='foo').to_period()
result = period_range(start=start, end=end, freq='M', name='foo')
tm.assert_index_equal(result, expected)
# downsampling
start, end = Period('2017-1', freq='M'), Period('2019-12', freq='M')
expected = date_range(start='2017-01-31', end='2019-12-31', freq='Q',
name='foo').to_period()
result = period_range(start=start, end=end, freq='Q', name='foo')
tm.assert_index_equal(result, expected)
# empty
expected = PeriodIndex([], freq='W', name='foo')
result = period_range(start=start, periods=0, freq='W', name='foo')
tm.assert_index_equal(result, expected)
result = period_range(end=end, periods=0, freq='W', name='foo')
tm.assert_index_equal(result, expected)
result = period_range(start=end, end=start, freq='W', name='foo')
tm.assert_index_equal(result, expected)
def test_series(self):
# GH6407
# inferring series
# invalid type of Series
for s in [Series(np.arange(10)), Series(np.arange(10.0))]:
self.assertRaises(TypeError, lambda: frequencies.infer_freq(s))
# a non-convertible string
self.assertRaises(ValueError, lambda: frequencies.infer_freq(Series(["foo", "bar"])))
# cannot infer on PeriodIndex
for freq in [None, "L"]:
s = Series(period_range("2013", periods=10, freq=freq))
self.assertRaises(TypeError, lambda: frequencies.infer_freq(s))
for freq in ["Y"]:
msg = frequencies._INVALID_FREQ_ERROR
with tm.assertRaisesRegexp(ValueError, msg):
s = Series(period_range("2013", periods=10, freq=freq))
self.assertRaises(TypeError, lambda: frequencies.infer_freq(s))
# DateTimeIndex
for freq in ["M", "L", "S"]:
s = Series(date_range("20130101", periods=10, freq=freq))
inferred = frequencies.infer_freq(s)
self.assertEqual(inferred, freq)
s = Series(date_range("20130101", "20130110"))
inferred = frequencies.infer_freq(s)
self.assertEqual(inferred, "D")
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='2M')
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='3D')
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_get_loc2(self):
idx = pd.period_range('2000-01-01', periods=3)
for method in [None, 'pad', 'backfill', 'nearest']:
assert idx.get_loc(idx[1], method) == 1
assert idx.get_loc(idx[1].asfreq('H', how='start'), method) == 1
assert idx.get_loc(idx[1].to_timestamp(), method) == 1
assert idx.get_loc(idx[1].to_timestamp()
.to_pydatetime(), method) == 1
assert idx.get_loc(str(idx[1]), method) == 1
idx = pd.period_range('2000-01-01', periods=5)[::2]
assert idx.get_loc('2000-01-02T12', method='nearest',
tolerance='1 day') == 1
assert idx.get_loc('2000-01-02T12', method='nearest',
tolerance=pd.Timedelta('1D')) == 1
assert idx.get_loc('2000-01-02T12', method='nearest',
tolerance=np.timedelta64(1, 'D')) == 1
assert idx.get_loc('2000-01-02T12', method='nearest',
tolerance=timedelta(1)) == 1
with tm.assert_raises_regex(ValueError,
'unit abbreviation w/o a number'):
idx.get_loc('2000-01-10', method='nearest', tolerance='foo')
msg = 'Input has different freq from PeriodIndex\\(freq=D\\)'
with tm.assert_raises_regex(ValueError, msg):
idx.get_loc('2000-01-10', method='nearest', tolerance='1 hour')
with pytest.raises(KeyError):
idx.get_loc('2000-01-10', method='nearest', tolerance='1 day')
with pytest.raises(
ValueError,
match='list-like tolerance size must match target index size'):
idx.get_loc('2000-01-10', method='nearest',
tolerance=[pd.Timedelta('1 day').to_timedelta64(),
pd.Timedelta('1 day').to_timedelta64()])
def test_categorical_series_repr_period_ordered(self):
idx = period_range('2011-01-01 09:00', freq='H', periods=5)
s = Series(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[H]): [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]""" # noqa
assert repr(s) == exp
idx = period_range('2011-01', freq='M', periods=5)
s = Series(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[M]): [2011-01 < 2011-02 < 2011-03 < 2011-04 < 2011-05]"""
assert repr(s) == exp
def test_pi_add_sub_td64_array_tick(self):
# PeriodIndex + Timedelta-like is allowed only with
# tick-like frequencies
rng = pd.period_range('1/1/2000', freq='90D', periods=3)
tdi = pd.TimedeltaIndex(['-1 Day', '-1 Day', '-1 Day'])
tdarr = tdi.values
expected = pd.period_range('12/31/1999', freq='90D', periods=3)
result = rng + tdi
tm.assert_index_equal(result, expected)
result = rng + tdarr
tm.assert_index_equal(result, expected)
result = tdi + rng
tm.assert_index_equal(result, expected)
result = tdarr + rng
tm.assert_index_equal(result, expected)
expected = pd.period_range('1/2/2000', freq='90D', periods=3)
result = rng - tdi
tm.assert_index_equal(result, expected)
result = rng - tdarr
tm.assert_index_equal(result, expected)
with pytest.raises(TypeError):
tdarr - rng
with pytest.raises(TypeError):
tdi - rng
def test_series(self):
# GH6407
# inferring series
# invalid type of Series
for s in [ Series(np.arange(10)),
Series(np.arange(10.))]:
self.assertRaises(TypeError, lambda : frequencies.infer_freq(s))
# a non-convertible string
self.assertRaises(ValueError, lambda : frequencies.infer_freq(Series(['foo','bar'])))
# cannot infer on PeriodIndex
for freq in [None, 'L']:
s = Series(period_range('2013',periods=10,freq=freq))
self.assertRaises(TypeError, lambda : frequencies.infer_freq(s))
for freq in ['Y']:
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
s = Series(period_range('2013',periods=10,freq=freq))
self.assertRaises(TypeError, lambda : frequencies.infer_freq(s))
# DateTimeIndex
for freq in ['M', 'L', 'S']:
s = Series(date_range('20130101',periods=10,freq=freq))
inferred = frequencies.infer_freq(s)
self.assertEqual(inferred,freq)
s = Series(date_range('20130101','20130110'))
inferred = frequencies.infer_freq(s)
self.assertEqual(inferred,'D')
def test_get_loc(self):
idx = pd.period_range('2000-01-01', periods=3)
for method in [None, 'pad', 'backfill', 'nearest']:
self.assertEqual(idx.get_loc(idx[1], method), 1)
self.assertEqual(
idx.get_loc(idx[1].asfreq('H', how='start'), method), 1)
self.assertEqual(idx.get_loc(idx[1].to_timestamp(), method), 1)
self.assertEqual(
idx.get_loc(idx[1].to_timestamp().to_pydatetime(), method), 1)
self.assertEqual(idx.get_loc(str(idx[1]), method), 1)
idx = pd.period_range('2000-01-01', periods=5)[::2]
self.assertEqual(idx.get_loc('2000-01-02T12', method='nearest',
tolerance='1 day'), 1)
self.assertEqual(idx.get_loc('2000-01-02T12', method='nearest',
tolerance=pd.Timedelta('1D')), 1)
self.assertEqual(idx.get_loc('2000-01-02T12', method='nearest',
tolerance=np.timedelta64(1, 'D')), 1)
self.assertEqual(idx.get_loc('2000-01-02T12', method='nearest',
tolerance=timedelta(1)), 1)
with tm.assertRaisesRegexp(ValueError, 'must be convertible'):
idx.get_loc('2000-01-10', method='nearest', tolerance='foo')
msg = 'Input has different freq from PeriodIndex\\(freq=D\\)'
with tm.assertRaisesRegexp(ValueError, msg):
idx.get_loc('2000-01-10', method='nearest', tolerance='1 hour')
with tm.assertRaises(KeyError):
idx.get_loc('2000-01-10', method='nearest', tolerance='1 day')
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)
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')
tm.assert_index_equal(index, 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)
tm.assert_index_equal(index, 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')
tm.assert_index_equal(idx, exp)
def test_resample_count(self, freq, expected_vals):
# GH12774
series = Series(1, index=pd.period_range(start='2000', periods=100))
result = series.resample(freq).count()
expected_index = pd.period_range(start='2000', freq=freq,
periods=len(expected_vals))
expected = Series(expected_vals, index=expected_index)
assert_series_equal(result, expected)
def test_pi_add_iadd_int(self, one):
# Variants of `one` for #19012
rng = pd.period_range('2000-01-01 09:00', freq='H', periods=10)
result = rng + one
expected = pd.period_range('2000-01-01 10:00', freq='H', periods=10)
tm.assert_index_equal(result, expected)
rng += one
tm.assert_index_equal(rng, expected)
def test_parr_sub_pi_mismatched_freq(self, box_with_array):
rng = pd.period_range('1/1/2000', freq='D', periods=5)
other = pd.period_range('1/6/2000', freq='H', periods=5)
# TODO: parametrize over boxes for other?
rng = tm.box_expected(rng, box_with_array)
with pytest.raises(IncompatibleFrequency):
rng - other
def test_representation_to_series(self):
# GH#10971
idx1 = PeriodIndex([], freq='D')
idx2 = PeriodIndex(['2011-01-01'], freq='D')
idx3 = PeriodIndex(['2011-01-01', '2011-01-02'], freq='D')
idx4 = PeriodIndex(['2011-01-01', '2011-01-02', '2011-01-03'],
freq='D')
idx5 = PeriodIndex(['2011', '2012', '2013'], freq='A')
idx6 = PeriodIndex(['2011-01-01 09:00', '2012-02-01 10:00', 'NaT'],
freq='H')
idx7 = pd.period_range('2013Q1', periods=1, freq="Q")
idx8 = pd.period_range('2013Q1', periods=2, freq="Q")
idx9 = pd.period_range('2013Q1', periods=3, freq="Q")
exp1 = """Series([], dtype: period[D])"""
exp2 = """0 2011-01-01
dtype: period[D]"""
exp3 = """0 2011-01-01
1 2011-01-02
dtype: period[D]"""
exp4 = """0 2011-01-01
1 2011-01-02
2 2011-01-03
dtype: period[D]"""
exp5 = """0 2011
1 2012
2 2013
dtype: period[A-DEC]"""
exp6 = """0 2011-01-01 09:00
1 2012-02-01 10:00
2 NaT
dtype: period[H]"""
exp7 = """0 2013Q1
dtype: period[Q-DEC]"""
exp8 = """0 2013Q1
1 2013Q2
dtype: period[Q-DEC]"""
exp9 = """0 2013Q1
1 2013Q2
2 2013Q3
dtype: period[Q-DEC]"""
for idx, expected in zip([idx1, idx2, idx3, idx4, idx5,
idx6, idx7, idx8, idx9],
[exp1, exp2, exp3, exp4, exp5,
exp6, exp7, exp8, exp9]):
result = repr(pd.Series(idx))
assert result == expected
def test_pi_add_iadd_timedeltalike_M(self):
rng = pd.period_range('2014-01', '2016-12', freq='M')
expected = pd.period_range('2014-06', '2017-05', freq='M')
result = rng + pd.offsets.MonthEnd(5)
tm.assert_index_equal(result, expected)
rng += pd.offsets.MonthEnd(5)
tm.assert_index_equal(rng, expected)
def test_add_iadd_timedeltalike_annual(self):
# offset
# DateOffset
rng = pd.period_range('2014', '2024', freq='A')
result = rng + pd.offsets.YearEnd(5)
expected = pd.period_range('2019', '2029', freq='A')
tm.assert_index_equal(result, expected)
rng += pd.offsets.YearEnd(5)
tm.assert_index_equal(rng, expected)
def test_union_dataframe_index(self):
rng1 = pd.period_range('1/1/1999', '1/1/2012', freq='M')
s1 = pd.Series(np.random.randn(len(rng1)), rng1)
rng2 = pd.period_range('1/1/1980', '12/1/2001', freq='M')
s2 = pd.Series(np.random.randn(len(rng2)), rng2)
df = pd.DataFrame({'s1': s1, 's2': s2})
exp = pd.period_range('1/1/1980', '1/1/2012', freq='M')
tm.assert_index_equal(df.index, exp)
def test_constructor_use_start_freq(self):
# GH #1118
p = Period('4/2/2012', freq='B')
with tm.assert_produces_warning(FutureWarning):
index = PeriodIndex(start=p, periods=10)
expected = period_range(start='4/2/2012', periods=10, freq='B')
tm.assert_index_equal(index, expected)
index = period_range(start=p, periods=10)
tm.assert_index_equal(index, expected)
def test_pi_add_iadd_pi_raises(self):
rng = pd.period_range('1/1/2000', freq='D', periods=5)
other = pd.period_range('1/6/2000', freq='D', periods=5)
# previously performed setop union, now raises TypeError (GH14164)
with pytest.raises(TypeError):
rng + other
with pytest.raises(TypeError):
rng += other
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)
tm.assert_index_equal(df.index, idx1)
df = df.set_index(idx2)
tm.assert_index_equal(df.index, idx2)
def test_fields(self):
# year, month, day, hour, minute
# second, weekofyear, week, dayofweek, weekday, dayofyear, quarter
# qyear
pi = period_range(freq='A', start='1/1/2001', end='12/1/2005')
self._check_all_fields(pi)
pi = period_range(freq='Q', start='1/1/2001', end='12/1/2002')
self._check_all_fields(pi)
pi = period_range(freq='M', start='1/1/2001', end='1/1/2002')
self._check_all_fields(pi)
pi = period_range(freq='D', start='12/1/2001', end='6/1/2001')
self._check_all_fields(pi)
pi = period_range(freq='B', start='12/1/2001', end='6/1/2001')
self._check_all_fields(pi)
pi = period_range(freq='H', start='12/31/2001', end='1/1/2002 23:00')
self._check_all_fields(pi)
pi = period_range(freq='Min', start='12/31/2001', end='1/1/2002 00:20')
self._check_all_fields(pi)
pi = period_range(freq='S', start='12/31/2001 00:00:00',
end='12/31/2001 00:05:00')
self._check_all_fields(pi)
end_intv = Period('2006-12-31', 'W')
i1 = period_range(end=end_intv, periods=10)
self._check_all_fields(i1)
def test_union_categorical(self):
# GH 13361
data = [
(list('abc'), list('abd'), list('abcabd')),
([0, 1, 2], [2, 3, 4], [0, 1, 2, 2, 3, 4]),
([0, 1.2, 2], [2, 3.4, 4], [0, 1.2, 2, 2, 3.4, 4]),
(['b', 'b', np.nan, 'a'], ['a', np.nan, 'c'],
['b', 'b', np.nan, 'a', 'a', np.nan, 'c']),
(pd.date_range('2014-01-01', '2014-01-05'),
pd.date_range('2014-01-06', '2014-01-07'),
pd.date_range('2014-01-01', '2014-01-07')),
(pd.date_range('2014-01-01', '2014-01-05', tz='US/Central'),
pd.date_range('2014-01-06', '2014-01-07', tz='US/Central'),
pd.date_range('2014-01-01', '2014-01-07', tz='US/Central')),
(pd.period_range('2014-01-01', '2014-01-05'),
pd.period_range('2014-01-06', '2014-01-07'),
pd.period_range('2014-01-01', '2014-01-07')),
]
for a, b, combined in data:
for box in [Categorical, CategoricalIndex, Series]:
result = union_categoricals([box(Categorical(a)),
box(Categorical(b))])
expected = Categorical(combined)
tm.assert_categorical_equal(result, expected,
check_category_order=True)
# new categories ordered by appearance
s = Categorical(['x', 'y', 'z'])
s2 = Categorical(['a', 'b', 'c'])
result = union_categoricals([s, s2])
expected = Categorical(['x', 'y', 'z', 'a', 'b', 'c'],
categories=['x', 'y', 'z', 'a', 'b', 'c'])
tm.assert_categorical_equal(result, expected)
s = Categorical([0, 1.2, 2], ordered=True)
s2 = Categorical([0, 1.2, 2], ordered=True)
result = union_categoricals([s, s2])
expected = Categorical([0, 1.2, 2, 0, 1.2, 2], ordered=True)
tm.assert_categorical_equal(result, expected)
# must exactly match types
s = Categorical([0, 1.2, 2])
s2 = Categorical([2, 3, 4])
msg = 'dtype of categories must be the same'
with tm.assertRaisesRegexp(TypeError, msg):
union_categoricals([s, s2])
msg = 'No Categoricals to union'
with tm.assertRaisesRegexp(ValueError, msg):
union_categoricals([])
def test_pi_sub_isub_timedeltalike_daily(self, three_days):
# Tick-like 3 Days
other = three_days
rng = pd.period_range('2014-05-01', '2014-05-15', freq='D')
expected = pd.period_range('2014-04-28', '2014-05-12', freq='D')
result = rng - other
tm.assert_index_equal(result, expected)
rng -= other
tm.assert_index_equal(rng, expected)
def test_pi_sub_isub_timedeltalike_hourly(self, two_hours):
other = two_hours
rng = pd.period_range('2014-01-01 10:00', '2014-01-05 10:00', freq='H')
expected = pd.period_range('2014-01-01 08:00', '2014-01-05 08:00',
freq='H')
result = rng - other
tm.assert_index_equal(result, expected)
rng -= other
tm.assert_index_equal(rng, expected)
def test_period_index_roundtrip():
idx = pd.period_range(start='2017-01-01', end='2018-01-01', freq='M')
decoded_idx = roundtrip(idx)
assert_index_equal(decoded_idx, idx)
