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Merged
merged 6 commits into from
Nov 2, 2017
Merged

Index tests in the wrong places #18074

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5592796
Fix incorrectly-located as_type and to_period tests
jbrockmendel Nov 2, 2017
f71f735
Move union and difference tests;
jbrockmendel Nov 2, 2017
21b642b
fix slice test locations
jbrockmendel Nov 2, 2017
2427cc0
move slice test
jbrockmendel Nov 2, 2017
111316e
reviewer suggestions; parameterize tests
jbrockmendel Nov 2, 2017
846032f
Merge branch 'master' of https://github.com/pandas-dev/pandas into in…
jbrockmendel Nov 2, 2017
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34 changes: 25 additions & 9 deletions pandas/tests/indexes/datetimes/test_astype.py
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Original file line number Diff line number Diff line change
Expand Up @@ -117,6 +117,16 @@ def test_astype_datetime64(self):
dtype='datetime64[ns]')
tm.assert_index_equal(result, expected)

def test_astype_object(self):
# NumPy 1.6.1 weak ns support
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can remove this comment FYI

rng = date_range('1/1/2000', periods=20)

casted = rng.astype('O')
exp_values = list(rng)

tm.assert_index_equal(casted, Index(exp_values, dtype=np.object_))
assert casted.tolist() == exp_values

def test_astype_raises(self):
# GH 13149, GH 13209
idx = DatetimeIndex(['2016-05-16', 'NaT', NaT, np.NaN])
Expand Down Expand Up @@ -287,12 +297,18 @@ def test_to_period_tz_dateutil(self):
assert result == expected
tm.assert_index_equal(ts.to_period(), xp)

def test_astype_object(self):
# NumPy 1.6.1 weak ns support
rng = date_range('1/1/2000', periods=20)

casted = rng.astype('O')
exp_values = list(rng)

tm.assert_index_equal(casted, Index(exp_values, dtype=np.object_))
assert casted.tolist() == exp_values
def test_to_period_nofreq(self):
idx = DatetimeIndex(['2000-01-01', '2000-01-02', '2000-01-04'])
pytest.raises(ValueError, idx.to_period)

idx = DatetimeIndex(['2000-01-01', '2000-01-02', '2000-01-03'],
freq='infer')
assert idx.freqstr == 'D'
expected = pd.PeriodIndex(['2000-01-01', '2000-01-02',
'2000-01-03'], freq='D')
tm.assert_index_equal(idx.to_period(), expected)

# GH 7606
idx = DatetimeIndex(['2000-01-01', '2000-01-02', '2000-01-03'])
assert idx.freqstr is None
tm.assert_index_equal(idx.to_period(), expected)
83 changes: 2 additions & 81 deletions pandas/tests/indexes/datetimes/test_datetime.py
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Expand Up @@ -8,10 +8,10 @@
import pandas.util.testing as tm
from pandas.compat import lrange
from pandas.compat.numpy import np_datetime64_compat
from pandas import (DatetimeIndex, Index, date_range, Series, DataFrame,
from pandas import (DatetimeIndex, Index, date_range, DataFrame,
Timestamp, datetime, offsets)

from pandas.util.testing import assert_series_equal, assert_almost_equal
from pandas.util.testing import assert_almost_equal

randn = np.random.randn

Expand Down Expand Up @@ -223,22 +223,6 @@ def test_append_join_nondatetimeindex(self):
# it works
rng.join(idx, how='outer')

def test_to_period_nofreq(self):
idx = DatetimeIndex(['2000-01-01', '2000-01-02', '2000-01-04'])
pytest.raises(ValueError, idx.to_period)

idx = DatetimeIndex(['2000-01-01', '2000-01-02', '2000-01-03'],
freq='infer')
assert idx.freqstr == 'D'
expected = pd.PeriodIndex(['2000-01-01', '2000-01-02',
'2000-01-03'], freq='D')
tm.assert_index_equal(idx.to_period(), expected)

# GH 7606
idx = DatetimeIndex(['2000-01-01', '2000-01-02', '2000-01-03'])
assert idx.freqstr is None
tm.assert_index_equal(idx.to_period(), expected)

def test_comparisons_coverage(self):
rng = date_range('1/1/2000', periods=10)

Expand Down Expand Up @@ -567,13 +551,6 @@ def test_does_not_convert_mixed_integer(self):
assert cols.dtype == joined.dtype
tm.assert_numpy_array_equal(cols.values, joined.values)

def test_slice_keeps_name(self):
# GH4226
st = pd.Timestamp('2013-07-01 00:00:00', tz='America/Los_Angeles')
et = pd.Timestamp('2013-07-02 00:00:00', tz='America/Los_Angeles')
dr = pd.date_range(st, et, freq='H', name='timebucket')
assert dr[1:].name == dr.name

def test_join_self(self):
index = date_range('1/1/2000', periods=10)
kinds = 'outer', 'inner', 'left', 'right'
Expand Down Expand Up @@ -687,59 +664,3 @@ def test_factorize_dst(self):
arr, res = obj.factorize()
tm.assert_numpy_array_equal(arr, np.arange(12, dtype=np.intp))
tm.assert_index_equal(res, idx)

def test_slice_with_negative_step(self):
ts = Series(np.arange(20),
date_range('2014-01-01', periods=20, freq='MS'))
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[Timestamp('2014-10-01')::-1], SLC[9::-1])
assert_slices_equivalent(SLC['2014-10-01'::-1], SLC[9::-1])

assert_slices_equivalent(SLC[:Timestamp('2014-10-01'):-1], SLC[:8:-1])
assert_slices_equivalent(SLC[:'2014-10-01':-1], SLC[:8:-1])

assert_slices_equivalent(SLC['2015-02-01':'2014-10-01':-1],
SLC[13:8:-1])
assert_slices_equivalent(SLC[Timestamp('2015-02-01'):Timestamp(
'2014-10-01'):-1], SLC[13:8:-1])
assert_slices_equivalent(SLC['2015-02-01':Timestamp('2014-10-01'):-1],
SLC[13:8:-1])
assert_slices_equivalent(SLC[Timestamp('2015-02-01'):'2014-10-01':-1],
SLC[13:8:-1])

assert_slices_equivalent(SLC['2014-10-01':'2015-02-01':-1], SLC[:0])

def test_slice_with_zero_step_raises(self):
ts = Series(np.arange(20),
date_range('2014-01-01', periods=20, freq='MS'))
tm.assert_raises_regex(ValueError, 'slice step cannot be zero',
lambda: ts[::0])
tm.assert_raises_regex(ValueError, 'slice step cannot be zero',
lambda: ts.loc[::0])
tm.assert_raises_regex(ValueError, 'slice step cannot be zero',
lambda: ts.loc[::0])

def test_slice_bounds_empty(self):
# GH 14354
empty_idx = DatetimeIndex(freq='1H', periods=0, end='2015')

right = empty_idx._maybe_cast_slice_bound('2015-01-02', 'right', 'loc')
exp = Timestamp('2015-01-02 23:59:59.999999999')
assert right == exp

left = empty_idx._maybe_cast_slice_bound('2015-01-02', 'left', 'loc')
exp = Timestamp('2015-01-02 00:00:00')
assert left == exp

def test_slice_duplicate_monotonic(self):
# https://github.com/pandas-dev/pandas/issues/16515
idx = pd.DatetimeIndex(['2017', '2017'])
result = idx._maybe_cast_slice_bound('2017-01-01', 'left', 'loc')
expected = Timestamp('2017-01-01')
assert result == expected
43 changes: 0 additions & 43 deletions pandas/tests/indexes/datetimes/test_ops.py
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Expand Up @@ -383,49 +383,6 @@ def test_resolution(self):
tz=tz)
assert idx.resolution == expected

def test_union(self):
for tz in self.tz:
# union
rng1 = pd.date_range('1/1/2000', freq='D', periods=5, tz=tz)
other1 = pd.date_range('1/6/2000', freq='D', periods=5, tz=tz)
expected1 = pd.date_range('1/1/2000', freq='D', periods=10, tz=tz)

rng2 = pd.date_range('1/1/2000', freq='D', periods=5, tz=tz)
other2 = pd.date_range('1/4/2000', freq='D', periods=5, tz=tz)
expected2 = pd.date_range('1/1/2000', freq='D', periods=8, tz=tz)

rng3 = pd.date_range('1/1/2000', freq='D', periods=5, tz=tz)
other3 = pd.DatetimeIndex([], tz=tz)
expected3 = pd.date_range('1/1/2000', freq='D', periods=5, tz=tz)

for rng, other, expected in [(rng1, other1, expected1),
(rng2, other2, expected2),
(rng3, other3, expected3)]:

result_union = rng.union(other)
tm.assert_index_equal(result_union, expected)

def test_difference(self):
for tz in self.tz:
# diff
rng1 = pd.date_range('1/1/2000', freq='D', periods=5, tz=tz)
other1 = pd.date_range('1/6/2000', freq='D', periods=5, tz=tz)
expected1 = pd.date_range('1/1/2000', freq='D', periods=5, tz=tz)

rng2 = pd.date_range('1/1/2000', freq='D', periods=5, tz=tz)
other2 = pd.date_range('1/4/2000', freq='D', periods=5, tz=tz)
expected2 = pd.date_range('1/1/2000', freq='D', periods=3, tz=tz)

rng3 = pd.date_range('1/1/2000', freq='D', periods=5, tz=tz)
other3 = pd.DatetimeIndex([], tz=tz)
expected3 = pd.date_range('1/1/2000', freq='D', periods=5, tz=tz)

for rng, other, expected in [(rng1, other1, expected1),
(rng2, other2, expected2),
(rng3, other3, expected3)]:
result_diff = rng.difference(other)
tm.assert_index_equal(result_diff, expected)

def test_comp_nat(self):
left = pd.DatetimeIndex([pd.Timestamp('2011-01-01'), pd.NaT,
pd.Timestamp('2011-01-03')])
Expand Down
62 changes: 62 additions & 0 deletions pandas/tests/indexes/datetimes/test_partial_slicing.py
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Expand Up @@ -12,6 +12,68 @@


class TestSlicing(object):
def test_slice_keeps_name(self):
# GH4226
st = pd.Timestamp('2013-07-01 00:00:00', tz='America/Los_Angeles')
et = pd.Timestamp('2013-07-02 00:00:00', tz='America/Los_Angeles')
dr = pd.date_range(st, et, freq='H', name='timebucket')
assert dr[1:].name == dr.name

def test_slice_with_negative_step(self):
ts = Series(np.arange(20),
date_range('2014-01-01', periods=20, freq='MS'))
SLC = pd.IndexSlice

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

assert_slices_equivalent(SLC[Timestamp('2014-10-01')::-1], SLC[9::-1])
assert_slices_equivalent(SLC['2014-10-01'::-1], SLC[9::-1])

assert_slices_equivalent(SLC[:Timestamp('2014-10-01'):-1], SLC[:8:-1])
assert_slices_equivalent(SLC[:'2014-10-01':-1], SLC[:8:-1])

assert_slices_equivalent(SLC['2015-02-01':'2014-10-01':-1],
SLC[13:8:-1])
assert_slices_equivalent(SLC[Timestamp('2015-02-01'):Timestamp(
'2014-10-01'):-1], SLC[13:8:-1])
assert_slices_equivalent(SLC['2015-02-01':Timestamp('2014-10-01'):-1],
SLC[13:8:-1])
assert_slices_equivalent(SLC[Timestamp('2015-02-01'):'2014-10-01':-1],
SLC[13:8:-1])

assert_slices_equivalent(SLC['2014-10-01':'2015-02-01':-1], SLC[:0])

def test_slice_with_zero_step_raises(self):
ts = Series(np.arange(20),
date_range('2014-01-01', periods=20, freq='MS'))
tm.assert_raises_regex(ValueError, 'slice step cannot be zero',
lambda: ts[::0])
tm.assert_raises_regex(ValueError, 'slice step cannot be zero',
lambda: ts.loc[::0])
tm.assert_raises_regex(ValueError, 'slice step cannot be zero',
lambda: ts.loc[::0])

def test_slice_bounds_empty(self):
# GH 14354
empty_idx = DatetimeIndex(freq='1H', periods=0, end='2015')

right = empty_idx._maybe_cast_slice_bound('2015-01-02', 'right', 'loc')
exp = Timestamp('2015-01-02 23:59:59.999999999')
assert right == exp

left = empty_idx._maybe_cast_slice_bound('2015-01-02', 'left', 'loc')
exp = Timestamp('2015-01-02 00:00:00')
assert left == exp

def test_slice_duplicate_monotonic(self):
# https://github.com/pandas-dev/pandas/issues/16515
idx = pd.DatetimeIndex(['2017', '2017'])
result = idx._maybe_cast_slice_bound('2017-01-01', 'left', 'loc')
expected = Timestamp('2017-01-01')
assert result == expected

def test_slice_year(self):
dti = DatetimeIndex(freq='B', start=datetime(2005, 1, 1), periods=500)
Expand Down
50 changes: 44 additions & 6 deletions pandas/tests/indexes/datetimes/test_setops.py
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Expand Up @@ -11,14 +11,31 @@
START, END = datetime(2009, 1, 1), datetime(2010, 1, 1)


class TestDatetimeIndex(object):
class TestDatetimeIndexSetOps(object):
tz = [None, 'UTC', 'Asia/Tokyo', 'US/Eastern', 'dateutil/Asia/Singapore',
'dateutil/US/Pacific']

def test_union(self):
i1 = Int64Index(np.arange(0, 20, 2))
i2 = Int64Index(np.arange(10, 30, 2))
result = i1.union(i2)
expected = Int64Index(np.arange(0, 30, 2))
tm.assert_index_equal(result, expected)
for tz in self.tz:
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don't use loops, parametrize

# union
rng1 = pd.date_range('1/1/2000', freq='D', periods=5, tz=tz)
other1 = pd.date_range('1/6/2000', freq='D', periods=5, tz=tz)
expected1 = pd.date_range('1/1/2000', freq='D', periods=10, tz=tz)

rng2 = pd.date_range('1/1/2000', freq='D', periods=5, tz=tz)
other2 = pd.date_range('1/4/2000', freq='D', periods=5, tz=tz)
expected2 = pd.date_range('1/1/2000', freq='D', periods=8, tz=tz)

rng3 = pd.date_range('1/1/2000', freq='D', periods=5, tz=tz)
other3 = pd.DatetimeIndex([], tz=tz)
expected3 = pd.date_range('1/1/2000', freq='D', periods=5, tz=tz)

for rng, other, expected in [(rng1, other1, expected1),
(rng2, other2, expected2),
(rng3, other3, expected3)]:

result_union = rng.union(other)
tm.assert_index_equal(result_union, expected)

def test_union_coverage(self):
idx = DatetimeIndex(['2000-01-03', '2000-01-01', '2000-01-02'])
Expand Down Expand Up @@ -155,6 +172,27 @@ def test_intersection_bug_1708(self):
result = index_1 & index_2
assert len(result) == 0

def test_difference(self):
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same

for tz in self.tz:
# diff
rng1 = pd.date_range('1/1/2000', freq='D', periods=5, tz=tz)
other1 = pd.date_range('1/6/2000', freq='D', periods=5, tz=tz)
expected1 = pd.date_range('1/1/2000', freq='D', periods=5, tz=tz)

rng2 = pd.date_range('1/1/2000', freq='D', periods=5, tz=tz)
other2 = pd.date_range('1/4/2000', freq='D', periods=5, tz=tz)
expected2 = pd.date_range('1/1/2000', freq='D', periods=3, tz=tz)

rng3 = pd.date_range('1/1/2000', freq='D', periods=5, tz=tz)
other3 = pd.DatetimeIndex([], tz=tz)
expected3 = pd.date_range('1/1/2000', freq='D', periods=5, tz=tz)

for rng, other, expected in [(rng1, other1, expected1),
(rng2, other2, expected2),
(rng3, other3, expected3)]:
result_diff = rng.difference(other)
tm.assert_index_equal(result_diff, expected)

def test_difference_freq(self):
# GH14323: difference of DatetimeIndex should not preserve frequency

Expand Down
4 changes: 4 additions & 0 deletions pandas/tests/indexes/timedeltas/test_partial_slicing.py
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Expand Up @@ -9,6 +9,10 @@


class TestSlicing(object):
def test_slice_keeps_name(self):
# GH4226
dr = pd.timedelta_range('1d', '5d', freq='H', name='timebucket')
assert dr[1:].name == dr.name

def test_partial_slice(self):
rng = timedelta_range('1 day 10:11:12', freq='h', periods=500)
Expand Down
6 changes: 0 additions & 6 deletions pandas/tests/indexes/timedeltas/test_timedelta.py
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Expand Up @@ -233,12 +233,6 @@ def test_join_self(self):
joined = index.join(index, how=kind)
tm.assert_index_equal(index, joined)

def test_slice_keeps_name(self):

# GH4226
dr = pd.timedelta_range('1d', '5d', freq='H', name='timebucket')
assert dr[1:].name == dr.name

def test_does_not_convert_mixed_integer(self):
df = tm.makeCustomDataframe(10, 10,
data_gen_f=lambda *args, **kwargs: randn(),
Expand Down