TST: share value_counts tests (#40132)

Author: jbrockmendel

pandas/tests/indexes/datetimelike_/test_value_counts.py

@@ -0,0 +1,103 @@
+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")
+
+        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)
+
+        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)
+
+        for obj in [idx, Series(idx)]:
+            tm.assert_series_equal(obj.value_counts(dropna=False), expected)
+
+        tm.assert_index_equal(idx.unique(), exp_idx)

pandas/tests/indexes/datetimes/test_ops.py

@@ -1,12 +1,10 @@
 from datetime import datetime
 
 from dateutil.tz import tzlocal
-import numpy as np
 import pytest
 
 from pandas.compat import IS64
 
-import pandas as pd
 from pandas import (
     DateOffset,
     DatetimeIndex,
@@ -69,51 +67,6 @@ def test_resolution(self, request, tz_naive_fixture, freq, expected):
         idx = date_range(start="2013-04-01", periods=30, freq=freq, tz=tz)
         assert idx.resolution == expected
 
-    def test_value_counts_unique(self, tz_naive_fixture):
-        tz = tz_naive_fixture
-        # GH 7735
-        idx = date_range("2011-01-01 09:00", freq="H", periods=10)
-        # create repeated values, 'n'th element is repeated by n+1 times
-        idx = DatetimeIndex(np.repeat(idx.values, range(1, len(idx) + 1)), tz=tz)
-
-        exp_idx = date_range("2011-01-01 18:00", freq="-1H", periods=10, tz=tz)
-        expected = Series(range(10, 0, -1), index=exp_idx, dtype="int64")
-        expected.index = expected.index._with_freq(None)
-
-        for obj in [idx, Series(idx)]:
-
-            tm.assert_series_equal(obj.value_counts(), expected)
-
-        expected = date_range("2011-01-01 09:00", freq="H", periods=10, tz=tz)
-        expected = expected._with_freq(None)
-        tm.assert_index_equal(idx.unique(), expected)
-
-        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",
-                pd.NaT,
-            ],
-            tz=tz,
-        )
-
-        exp_idx = DatetimeIndex(["2013-01-01 09:00", "2013-01-01 08:00"], tz=tz)
-        expected = Series([3, 2], index=exp_idx)
-
-        for obj in [idx, Series(idx)]:
-            tm.assert_series_equal(obj.value_counts(), expected)
-
-        exp_idx = DatetimeIndex(["2013-01-01 09:00", "2013-01-01 08:00", pd.NaT], tz=tz)
-        expected = Series([3, 2, 1], index=exp_idx)
-
-        for obj in [idx, Series(idx)]:
-            tm.assert_series_equal(obj.value_counts(dropna=False), expected)
-
-        tm.assert_index_equal(idx.unique(), exp_idx)
-
     def test_infer_freq(self, freq_sample):
         # GH 11018
         idx = date_range("2011-01-01 09:00:00", freq=freq_sample, periods=10)

pandas/tests/indexes/period/test_ops.py

@@ -1,12 +1,6 @@
-import numpy as np
 import pytest
 
 import pandas as pd
-from pandas import (
-    NaT,
-    PeriodIndex,
-    Series,
-)
 import pandas._testing as tm
 
 
@@ -29,61 +23,6 @@ def test_resolution(self, freq, expected):
         idx = pd.period_range(start="2013-04-01", periods=30, freq=freq)
         assert idx.resolution == expected
 
-    def test_value_counts_unique(self):
-        # GH 7735
-        idx = pd.period_range("2011-01-01 09:00", freq="H", periods=10)
-        # create repeated values, 'n'th element is repeated by n+1 times
-        idx = PeriodIndex(np.repeat(idx._values, range(1, len(idx) + 1)), freq="H")
-
-        exp_idx = PeriodIndex(
-            [
-                "2011-01-01 18:00",
-                "2011-01-01 17:00",
-                "2011-01-01 16:00",
-                "2011-01-01 15:00",
-                "2011-01-01 14:00",
-                "2011-01-01 13:00",
-                "2011-01-01 12:00",
-                "2011-01-01 11:00",
-                "2011-01-01 10:00",
-                "2011-01-01 09:00",
-            ],
-            freq="H",
-        )
-        expected = Series(range(10, 0, -1), index=exp_idx, dtype="int64")
-
-        for obj in [idx, Series(idx)]:
-            tm.assert_series_equal(obj.value_counts(), expected)
-
-        expected = pd.period_range("2011-01-01 09:00", freq="H", periods=10)
-        tm.assert_index_equal(idx.unique(), expected)
-
-        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",
-        )
-
-        exp_idx = PeriodIndex(["2013-01-01 09:00", "2013-01-01 08:00"], freq="H")
-        expected = Series([3, 2], index=exp_idx)
-
-        for obj in [idx, Series(idx)]:
-            tm.assert_series_equal(obj.value_counts(), expected)
-
-        exp_idx = PeriodIndex(["2013-01-01 09:00", "2013-01-01 08:00", NaT], freq="H")
-        expected = Series([3, 2, 1], index=exp_idx)
-
-        for obj in [idx, Series(idx)]:
-            tm.assert_series_equal(obj.value_counts(dropna=False), expected)
-
-        tm.assert_index_equal(idx.unique(), exp_idx)
-
     def test_freq_setter_deprecated(self):
         # GH 20678
         idx = pd.period_range("2018Q1", periods=4, freq="Q")

pandas/tests/indexes/timedeltas/test_ops.py

@@ -2,7 +2,6 @@
 import pytest
 
 from pandas import (
-    NaT,
     Series,
     TimedeltaIndex,
     timedelta_range,
@@ -17,50 +16,6 @@
 
 
 class TestTimedeltaIndexOps:
-    def test_value_counts_unique(self):
-        # GH 7735
-        idx = timedelta_range("1 days 09:00:00", freq="H", periods=10)
-        # create repeated values, 'n'th element is repeated by n+1 times
-        idx = TimedeltaIndex(np.repeat(idx.values, range(1, len(idx) + 1)))
-
-        exp_idx = timedelta_range("1 days 18:00:00", freq="-1H", periods=10)
-        exp_idx = exp_idx._with_freq(None)
-        expected = Series(range(10, 0, -1), index=exp_idx, dtype="int64")
-
-        obj = idx
-        tm.assert_series_equal(obj.value_counts(), expected)
-
-        obj = Series(idx)
-        tm.assert_series_equal(obj.value_counts(), expected)
-
-        expected = timedelta_range("1 days 09:00:00", freq="H", periods=10)
-        tm.assert_index_equal(idx.unique(), expected)
-
-        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,
-            ]
-        )
-
-        exp_idx = TimedeltaIndex(["1 days 09:00:00", "1 days 08:00:00"])
-        expected = Series([3, 2], index=exp_idx)
-
-        for obj in [idx, Series(idx)]:
-            tm.assert_series_equal(obj.value_counts(), expected)
-
-        exp_idx = TimedeltaIndex(["1 days 09:00:00", "1 days 08:00:00", NaT])
-        expected = Series([3, 2, 1], index=exp_idx)
-
-        for obj in [idx, Series(idx)]:
-            tm.assert_series_equal(obj.value_counts(dropna=False), expected)
-
-        tm.assert_index_equal(idx.unique(), exp_idx)
-
     def test_nonunique_contains(self):
         # GH 9512
         for idx in map(