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move a small set of non-scalar tests out of scalar.test_timestamp #18377
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Original file line number | Diff line number | Diff line change |
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import pytest | ||
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import numpy as np | ||
from datetime import date, timedelta, time | ||
from datetime import date, timedelta, time, datetime | ||
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import dateutil | ||
import pandas as pd | ||
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, DataFrame, | ||
Timestamp, datetime, offsets) | ||
Timestamp, offsets) | ||
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from pandas.util.testing import assert_almost_equal | ||
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randn = np.random.randn | ||
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class TestDatetimeIndexLikeTimestamp(object): | ||
# Tests for DatetimeIndex behaving like a vectorized Timestamp | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. I really like the vectorized-timestamp abstraction. It might make sense to have parallel test classes for Timestamp methods and their DatetimeIndex counterparts. |
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def test_dti_date_out_of_range(self): | ||
# see gh-1475 | ||
pytest.raises(ValueError, DatetimeIndex, ['1400-01-01']) | ||
pytest.raises(ValueError, DatetimeIndex, [datetime(1400, 1, 1)]) | ||
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def test_timestamp_fields(self): | ||
# extra fields from DatetimeIndex like quarter and week | ||
idx = tm.makeDateIndex(100) | ||
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fields = ['dayofweek', 'dayofyear', 'week', 'weekofyear', 'quarter', | ||
'days_in_month', 'is_month_start', 'is_month_end', | ||
'is_quarter_start', 'is_quarter_end', 'is_year_start', | ||
'is_year_end', 'weekday_name'] | ||
for f in fields: | ||
expected = getattr(idx, f)[-1] | ||
result = getattr(Timestamp(idx[-1]), f) | ||
assert result == expected | ||
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assert idx.freq == Timestamp(idx[-1], idx.freq).freq | ||
assert idx.freqstr == Timestamp(idx[-1], idx.freq).freqstr | ||
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class TestDatetimeIndex(object): | ||
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def test_get_loc(self): | ||
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This class was previously at the bottom of test_timestamp.