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