Merge remote-tracking branch 'upstream/main' into string-dtype-tests-all-xfail

Author: jorisvandenbossche

ci/code_checks.sh

@@ -223,7 +223,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         -i "pandas.Timestamp.fromordinal SA01" \
         -i "pandas.Timestamp.fromtimestamp PR01,SA01" \
         -i "pandas.Timestamp.hour GL08" \
-        -i "pandas.Timestamp.isoweekday SA01" \
         -i "pandas.Timestamp.max PR02" \
         -i "pandas.Timestamp.microsecond GL08" \
         -i "pandas.Timestamp.min PR02" \
@@ -328,7 +327,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         -i "pandas.core.groupby.DataFrameGroupBy.hist RT03" \
         -i "pandas.core.groupby.DataFrameGroupBy.indices SA01" \
         -i "pandas.core.groupby.DataFrameGroupBy.max SA01" \
-        -i "pandas.core.groupby.DataFrameGroupBy.median SA01" \
         -i "pandas.core.groupby.DataFrameGroupBy.min SA01" \
         -i "pandas.core.groupby.DataFrameGroupBy.nth PR02" \
         -i "pandas.core.groupby.DataFrameGroupBy.nunique SA01" \
@@ -347,7 +345,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         -i "pandas.core.groupby.SeriesGroupBy.is_monotonic_decreasing SA01" \
         -i "pandas.core.groupby.SeriesGroupBy.is_monotonic_increasing SA01" \
         -i "pandas.core.groupby.SeriesGroupBy.max SA01" \
-        -i "pandas.core.groupby.SeriesGroupBy.median SA01" \
         -i "pandas.core.groupby.SeriesGroupBy.min SA01" \
         -i "pandas.core.groupby.SeriesGroupBy.nth PR02" \
         -i "pandas.core.groupby.SeriesGroupBy.ohlc SA01" \
@@ -362,7 +359,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         -i "pandas.core.resample.Resampler.indices SA01" \
         -i "pandas.core.resample.Resampler.max PR01,RT03,SA01" \
         -i "pandas.core.resample.Resampler.mean SA01" \
-        -i "pandas.core.resample.Resampler.median SA01" \
         -i "pandas.core.resample.Resampler.min PR01,RT03,SA01" \
         -i "pandas.core.resample.Resampler.ohlc SA01" \
         -i "pandas.core.resample.Resampler.prod SA01" \

pandas/_libs/tslibs/nattype.pyx

@@ -441,6 +441,13 @@ class NaTType(_NaT):
 
         Monday == 1 ... Sunday == 7.
 
+        See Also
+        --------
+        Timestamp.weekday : Return the day of the week with Monday=0, Sunday=6.
+        Timestamp.isocalendar : Return a tuple containing ISO year, week number
+            and weekday.
+        datetime.date.isoweekday : Equivalent method in datetime module.
+
         Examples
         --------
         >>> ts = pd.Timestamp('2023-01-01 10:00:00')

pandas/_libs/tslibs/timestamps.pyx

@@ -2775,6 +2775,13 @@ default 'raise'
 
         Monday == 1 ... Sunday == 7.
 
+        See Also
+        --------
+        Timestamp.weekday : Return the day of the week with Monday=0, Sunday=6.
+        Timestamp.isocalendar : Return a tuple containing ISO year, week number
+            and weekday.
+        datetime.date.isoweekday : Equivalent method in datetime module.
+
         Examples
         --------
         >>> ts = pd.Timestamp('2023-01-01 10:00:00')

pandas/core/groupby/groupby.py

@@ -2347,6 +2347,12 @@ def median(self, numeric_only: bool = False) -> NDFrameT:
         Series or DataFrame
             Median of values within each group.
 
+        See Also
+        --------
+        Series.groupby : Apply a function groupby to a Series.
+        DataFrame.groupby : Apply a function groupby to each row or column of a
+            DataFrame.
+
         Examples
         --------
         For SeriesGroupBy:

pandas/tests/arithmetic/test_datetime64.py

@@ -389,6 +389,22 @@ def test_dt64_compare_datetime_scalar(self, datetimelike, op, expected):
         expected = Series(expected, name="A")
         tm.assert_series_equal(result, expected)
 
+    def test_ts_series_numpy_maximum(self):
+        # GH#50864, test numpy.maximum does not fail
+        # given a TimeStamp and Series(with dtype datetime64) comparison
+        ts = Timestamp("2024-07-01")
+        ts_series = Series(
+            ["2024-06-01", "2024-07-01", "2024-08-01"],
+            dtype="datetime64[us]",
+        )
+
+        expected = Series(
+            ["2024-07-01", "2024-07-01", "2024-08-01"],
+            dtype="datetime64[us]",
+        )
+
+        tm.assert_series_equal(expected, np.maximum(ts, ts_series))
+
 
 class TestDatetimeIndexComparisons:
     # TODO: moved from tests.indexes.test_base; parametrize and de-duplicate

pandas/tests/indexing/test_loc.py

@@ -3265,3 +3265,11 @@ def test_loc_nonunique_masked_index(self):
             index=Index(np.array(ids).repeat(1000), dtype="Int64"),
         )
         tm.assert_frame_equal(result, expected)
+
+    def test_loc_index_alignment_for_series(self):
+        # GH #56024
+        df = DataFrame({"a": [1, 2], "b": [3, 4]})
+        other = Series([200, 999], index=[1, 0])
+        df.loc[:, "a"] = other
+        expected = DataFrame({"a": [999, 200], "b": [3, 4]})
+        tm.assert_frame_equal(expected, df)