GH-51301: [Python] Fix NumPy and pandas nightly warnings

python/pyarrow/tests/test_array.py

@@ -2678,6 +2678,10 @@ def test_array_from_list_of_timestamps(unit):
 
 
 @pytest.mark.numpy
+@pytest.mark.filterwarnings(
+    "ignore:The 'generic' unit for NumPy timedelta is deprecated:"
+    "DeprecationWarning"
+)
 def test_array_from_timestamp_with_generic_unit():
     n = np.datetime64('NaT')
     x = np.datetime64('2017-01-01 01:01:01.111111111')
@@ -2718,6 +2722,10 @@ def test_array_from_numpy_timedelta(dtype, type):
 
 
 @pytest.mark.numpy
+@pytest.mark.filterwarnings(
+    "ignore:The 'generic' unit for NumPy timedelta is deprecated:"
+    "DeprecationWarning"
+)
 def test_array_from_numpy_timedelta_incorrect_unit():
     # generic (no unit)
     td = np.timedelta64(1)

python/pyarrow/tests/test_compute.py

@@ -2645,8 +2645,8 @@ def _check_datetime_components(timestamps, timezone=None):
     year = ts.dt.year.astype("int64")
     month = ts.dt.month.astype("int64")
     day = ts.dt.day.astype("int64")
-    dayofweek = ts.dt.dayofweek.astype("int64")
-    dayofyear = ts.dt.dayofyear.astype("int64")
+    dayofweek = ts.dt.day_of_week.astype("int64")
+    dayofyear = ts.dt.day_of_year.astype("int64")
     quarter = ts.dt.quarter.astype("int64")
     hour = ts.dt.hour.astype("int64")
     minute = ts.dt.minute.astype("int64")
@@ -2969,7 +2969,7 @@ def test_round_temporal(unit):
     if sys.platform == "win32":
         timestamps = timestamps[:3] + timestamps[5:]
 
-    ts = pd.Series([pd.Timestamp(x, unit="ns") for x in timestamps])
+    ts = pd.Series([pd.Timestamp(x) for x in timestamps])
     _check_temporal_rounding(ts, values, unit)
 
     timezones = ["Asia/Kolkata", "America/New_York", "Etc/GMT-4", "Etc/GMT+4",

python/pyarrow/tests/test_dataset.py

@@ -240,7 +240,7 @@ def multisourcefs(request):
 
     # create one with schema partitioning by weekday and color
     mockfs.create_dir('schema')
-    for part, chunk in df_b.groupby([df_b.date.dt.dayofweek, df_b.color]):
+    for part, chunk in df_b.groupby([df_b.date.dt.day_of_week, df_b.color]):
         folder = f'schema/{part[0]}/{part[1]}'
         path = f'{folder}/chunk.parquet'
         mockfs.create_dir(folder)

python/pyarrow/tests/test_dlpack.py

@@ -270,10 +270,11 @@ def immutable_tensor():
 @pytest.mark.parametrize('max_version', [None, (0, 8)])
 def test_dlpack_legacy_capsule_immutable_tensor(max_version):
     tensor = immutable_tensor()
-    with pytest.raises(NotImplementedError,
-                       match="Legacy DLPack support is not implemented "
-                             "for immutable tensors"):
-        tensor.__dlpack__(max_version=max_version)
+    with pytest.warns(DeprecationWarning, match="unversioned DLPack capsule"):
+        with pytest.raises(NotImplementedError,
+                           match="Legacy DLPack support is not implemented "
+                                 "for immutable tensors"):
+            tensor.__dlpack__(max_version=max_version)
 
 
 @check_bytes_allocated
@@ -307,7 +308,7 @@ def test_dlpack_versioned_capsule(obj, max_version, copy):
 @check_bytes_allocated
 @pytest.mark.parametrize('obj', dlpack_objects())
 def test_dlpack_versioned_roundtrip(obj):
-    expected = np.from_dlpack(DLPackForwarder(obj, max_version=None))
+    expected = np.from_dlpack(DLPackForwarder(obj, max_version=(1, 0)))
     for copy in [None, False, True]:
         result = np.from_dlpack(
             DLPackForwarder(obj, max_version=(1, 0), copy=copy))
@@ -335,24 +336,24 @@ def test_dlpack_not_supported():
     arr = pa.array([1, None, 3])
     with pytest.raises(TypeError, match="Can only use DLPack "
                        "on arrays with no nulls."):
-        np.from_dlpack(arr)
+        np.from_dlpack(DLPackForwarder(arr, max_version=(1, 0)))
 
     arr = pa.array(
         [[0, 1], [3, 4]],
         type=pa.list_(pa.int32())
     )
     with pytest.raises(TypeError, match="DataType is not compatible with DLPack spec"):
-        np.from_dlpack(arr)
+        np.from_dlpack(DLPackForwarder(arr, max_version=(1, 0)))
 
     arr = pa.array([])
     with pytest.raises(TypeError, match="DataType is not compatible with DLPack spec"):
-        np.from_dlpack(arr)
+        np.from_dlpack(DLPackForwarder(arr, max_version=(1, 0)))
 
     # DLPack doesn't support bit-packed boolean values
     arr = pa.array([True, False, True])
     with pytest.raises(TypeError, match="Bit-packed boolean data type "
                        "not supported by DLPack."):
-        np.from_dlpack(arr)
+        np.from_dlpack(DLPackForwarder(arr, max_version=(1, 0)))
 
 
 def test_dlpack_cuda_not_supported():

python/pyarrow/tests/test_pandas.py

@@ -124,6 +124,7 @@ def _check_pandas_roundtrip(df, expected=None, use_threads=False,
         warnings.filterwarnings(
             "ignore", "elementwise comparison failed", DeprecationWarning)
         tm.assert_frame_equal(result, expected, check_dtype=check_dtype,
+                              check_freq=False,
                               check_index_type=('equiv' if preserve_index
                                                 else False))
 
@@ -5006,7 +5007,7 @@ def test_does_not_mutate_timedelta_dtype():
 
     assert np.dtype(np.timedelta64) == expected
 
-    df = pd.DataFrame({"a": [np.timedelta64()]})
+    df = pd.DataFrame({"a": [np.timedelta64(0, "ns")]})
     t = pa.Table.from_pandas(df)
     t.to_pandas()