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104 lines
3.1 KiB
104 lines
3.1 KiB
1 year ago
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import numpy as np
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from pandas import (
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DatetimeIndex,
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NaT,
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PeriodIndex,
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Series,
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TimedeltaIndex,
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date_range,
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period_range,
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timedelta_range,
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)
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import pandas._testing as tm
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class TestValueCounts:
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# GH#7735
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def test_value_counts_unique_datetimeindex(self, tz_naive_fixture):
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tz = tz_naive_fixture
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orig = date_range("2011-01-01 09:00", freq="H", periods=10, tz=tz)
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self._check_value_counts_with_repeats(orig)
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def test_value_counts_unique_timedeltaindex(self):
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orig = timedelta_range("1 days 09:00:00", freq="H", periods=10)
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self._check_value_counts_with_repeats(orig)
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def test_value_counts_unique_periodindex(self):
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orig = period_range("2011-01-01 09:00", freq="H", periods=10)
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self._check_value_counts_with_repeats(orig)
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def _check_value_counts_with_repeats(self, orig):
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# create repeated values, 'n'th element is repeated by n+1 times
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idx = type(orig)(
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np.repeat(orig._values, range(1, len(orig) + 1)), dtype=orig.dtype
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)
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exp_idx = orig[::-1]
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if not isinstance(exp_idx, PeriodIndex):
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exp_idx = exp_idx._with_freq(None)
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expected = Series(range(10, 0, -1), index=exp_idx, dtype="int64", name="count")
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for obj in [idx, Series(idx)]:
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tm.assert_series_equal(obj.value_counts(), expected)
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tm.assert_index_equal(idx.unique(), orig)
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def test_value_counts_unique_datetimeindex2(self, tz_naive_fixture):
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tz = tz_naive_fixture
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idx = DatetimeIndex(
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[
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"2013-01-01 09:00",
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"2013-01-01 09:00",
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"2013-01-01 09:00",
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"2013-01-01 08:00",
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"2013-01-01 08:00",
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NaT,
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],
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tz=tz,
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)
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self._check_value_counts_dropna(idx)
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def test_value_counts_unique_timedeltaindex2(self):
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idx = TimedeltaIndex(
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[
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"1 days 09:00:00",
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"1 days 09:00:00",
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"1 days 09:00:00",
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"1 days 08:00:00",
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"1 days 08:00:00",
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NaT,
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]
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)
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self._check_value_counts_dropna(idx)
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def test_value_counts_unique_periodindex2(self):
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idx = PeriodIndex(
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[
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"2013-01-01 09:00",
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"2013-01-01 09:00",
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"2013-01-01 09:00",
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"2013-01-01 08:00",
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"2013-01-01 08:00",
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NaT,
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],
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freq="H",
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)
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self._check_value_counts_dropna(idx)
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def _check_value_counts_dropna(self, idx):
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exp_idx = idx[[2, 3]]
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expected = Series([3, 2], index=exp_idx, name="count")
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for obj in [idx, Series(idx)]:
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tm.assert_series_equal(obj.value_counts(), expected)
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exp_idx = idx[[2, 3, -1]]
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expected = Series([3, 2, 1], index=exp_idx, name="count")
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for obj in [idx, Series(idx)]:
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tm.assert_series_equal(obj.value_counts(dropna=False), expected)
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tm.assert_index_equal(idx.unique(), exp_idx)
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