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TST: Parametrize dtypes tests - test_common.py and test_concat.py #20340
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,77 +1,53 @@ | ||
| # -*- coding: utf-8 -*- | ||
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| import pandas as pd | ||
| import pytest | ||
| import pandas.core.dtypes.concat as _concat | ||
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| class TestConcatCompat(object): | ||
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| def check_concat(self, to_concat, exp): | ||
| for klass in [pd.Index, pd.Series]: | ||
| to_concat_klass = [klass(c) for c in to_concat] | ||
| res = _concat.get_dtype_kinds(to_concat_klass) | ||
| assert res == set(exp) | ||
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| def test_get_dtype_kinds(self): | ||
| to_concat = [['a'], [1, 2]] | ||
| self.check_concat(to_concat, ['i', 'object']) | ||
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| to_concat = [[3, 4], [1, 2]] | ||
| self.check_concat(to_concat, ['i']) | ||
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| to_concat = [[3, 4], [1, 2.1]] | ||
| self.check_concat(to_concat, ['i', 'f']) | ||
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| def test_get_dtype_kinds_datetimelike(self): | ||
| to_concat = [pd.DatetimeIndex(['2011-01-01']), | ||
| pd.DatetimeIndex(['2011-01-02'])] | ||
| self.check_concat(to_concat, ['datetime']) | ||
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| to_concat = [pd.TimedeltaIndex(['1 days']), | ||
| pd.TimedeltaIndex(['2 days'])] | ||
| self.check_concat(to_concat, ['timedelta']) | ||
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| def test_get_dtype_kinds_datetimelike_object(self): | ||
| to_concat = [pd.DatetimeIndex(['2011-01-01']), | ||
| pd.DatetimeIndex(['2011-01-02'], tz='US/Eastern')] | ||
| self.check_concat(to_concat, | ||
| ['datetime', 'datetime64[ns, US/Eastern]']) | ||
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| to_concat = [pd.DatetimeIndex(['2011-01-01'], tz='Asia/Tokyo'), | ||
| pd.DatetimeIndex(['2011-01-02'], tz='US/Eastern')] | ||
| self.check_concat(to_concat, | ||
| ['datetime64[ns, Asia/Tokyo]', | ||
| 'datetime64[ns, US/Eastern]']) | ||
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| # timedelta has single type | ||
| to_concat = [pd.TimedeltaIndex(['1 days']), | ||
| pd.TimedeltaIndex(['2 hours'])] | ||
| self.check_concat(to_concat, ['timedelta']) | ||
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| to_concat = [pd.DatetimeIndex(['2011-01-01'], tz='Asia/Tokyo'), | ||
| pd.TimedeltaIndex(['1 days'])] | ||
| self.check_concat(to_concat, | ||
| ['datetime64[ns, Asia/Tokyo]', 'timedelta']) | ||
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| def test_get_dtype_kinds_period(self): | ||
| # because we don't have Period dtype (yet), | ||
| # Series results in object dtype | ||
| to_concat = [pd.PeriodIndex(['2011-01'], freq='M'), | ||
| pd.PeriodIndex(['2011-01'], freq='M')] | ||
| res = _concat.get_dtype_kinds(to_concat) | ||
| assert res == set(['period[M]']) | ||
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| to_concat = [pd.Series([pd.Period('2011-01', freq='M')]), | ||
| pd.Series([pd.Period('2011-02', freq='M')])] | ||
| res = _concat.get_dtype_kinds(to_concat) | ||
| assert res == set(['object']) | ||
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| to_concat = [pd.PeriodIndex(['2011-01'], freq='M'), | ||
| pd.PeriodIndex(['2011-01'], freq='D')] | ||
| res = _concat.get_dtype_kinds(to_concat) | ||
| assert res == set(['period[M]', 'period[D]']) | ||
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| to_concat = [pd.Series([pd.Period('2011-01', freq='M')]), | ||
| pd.Series([pd.Period('2011-02', freq='D')])] | ||
| res = _concat.get_dtype_kinds(to_concat) | ||
| assert res == set(['object']) | ||
| from pandas import ( | ||
| Index, DatetimeIndex, PeriodIndex, TimedeltaIndex, Series, Period) | ||
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| @pytest.mark.parametrize('to_concat, expected', [ | ||
| # int/float/str | ||
| ([['a'], [1, 2]], ['i', 'object']), | ||
| ([[3, 4], [1, 2]], ['i']), | ||
| ([[3, 4], [1, 2.1]], ['i', 'f']), | ||
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| # datetimelike | ||
| ([DatetimeIndex(['2011-01-01']), DatetimeIndex(['2011-01-02'])], | ||
| ['datetime']), | ||
| ([TimedeltaIndex(['1 days']), TimedeltaIndex(['2 days'])], | ||
| ['timedelta']), | ||
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| # datetimelike object | ||
| ([DatetimeIndex(['2011-01-01']), | ||
| DatetimeIndex(['2011-01-02'], tz='US/Eastern')], | ||
| ['datetime', 'datetime64[ns, US/Eastern]']), | ||
| ([DatetimeIndex(['2011-01-01'], tz='Asia/Tokyo'), | ||
| DatetimeIndex(['2011-01-02'], tz='US/Eastern')], | ||
| ['datetime64[ns, Asia/Tokyo]', 'datetime64[ns, US/Eastern]']), | ||
| ([TimedeltaIndex(['1 days']), TimedeltaIndex(['2 hours'])], | ||
| ['timedelta']), | ||
| ([DatetimeIndex(['2011-01-01'], tz='Asia/Tokyo'), | ||
| TimedeltaIndex(['1 days'])], | ||
| ['datetime64[ns, Asia/Tokyo]', 'timedelta'])]) | ||
| @pytest.mark.parametrize('klass', [Index, Series]) | ||
| def test_get_dtype_kinds(klass, to_concat, expected): | ||
| to_concat_klass = [klass(c) for c in to_concat] | ||
| result = _concat.get_dtype_kinds(to_concat_klass) | ||
| assert result == set(expected) | ||
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| @pytest.mark.parametrize('to_concat, expected', [ | ||
| # because we don't have Period dtype (yet), | ||
| # Series results in object dtype | ||
| ([PeriodIndex(['2011-01'], freq='M'), | ||
| PeriodIndex(['2011-01'], freq='M')], ['period[M]']), | ||
| ([Series([Period('2011-01', freq='M')]), | ||
| Series([Period('2011-02', freq='M')])], ['object']), | ||
| ([PeriodIndex(['2011-01'], freq='M'), | ||
| PeriodIndex(['2011-01'], freq='D')], ['period[M]', 'period[D]']), | ||
| ([Series([Period('2011-01', freq='M')]), | ||
| Series([Period('2011-02', freq='D')])], ['object'])]) | ||
| def test_get_dtype_kinds_period(to_concat, expected): | ||
| result = _concat.get_dtype_kinds(to_concat) | ||
| assert result == set(expected) |
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Not sure this test is actually necessary? Split this off from the
test_invalid_dtype_error, as it appears to be testing valid instead of invalid dtypes. Previously this didn't have any type ofassertstatement; it just calledpandas_dtypeand the test passed if no error was raised.There was a problem hiding this comment.
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yeah this is ok, this is just testing that pandas_dtype doesn't raise on numpy dtypes