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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)