CI: silence numpy-dev failures (pandas-dev#32025)

Author: simonjayhawkins

pandas/__init__.py

@@ -25,6 +25,7 @@
     _np_version_under1p16,
     _np_version_under1p17,
     _np_version_under1p18,
+    _is_numpy_dev,
 )
 
 try:

pandas/tests/api/test_api.py

@@ -198,6 +198,7 @@ class TestPDApi(Base):
         "_np_version_under1p16",
         "_np_version_under1p17",
         "_np_version_under1p18",
+        "_is_numpy_dev",
         "_testing",
         "_tslib",
         "_typing",

pandas/tests/frame/test_cumulative.py

@@ -7,8 +7,9 @@
 """
 
 import numpy as np
+import pytest
 
-from pandas import DataFrame, Series
+from pandas import DataFrame, Series, _is_numpy_dev
 import pandas._testing as tm
 
 
@@ -73,6 +74,9 @@ def test_cumprod(self, datetime_frame):
         df.cumprod(0)
         df.cumprod(1)
 
+    @pytest.mark.xfail(
+        _is_numpy_dev, reason="https://github.com/pandas-dev/pandas/issues/31992"
+    )
     def test_cummin(self, datetime_frame):
         datetime_frame.loc[5:10, 0] = np.nan
         datetime_frame.loc[10:15, 1] = np.nan
@@ -96,6 +100,9 @@ def test_cummin(self, datetime_frame):
         cummin_xs = datetime_frame.cummin(axis=1)
         assert np.shape(cummin_xs) == np.shape(datetime_frame)
 
+    @pytest.mark.xfail(
+        _is_numpy_dev, reason="https://github.com/pandas-dev/pandas/issues/31992"
+    )
     def test_cummax(self, datetime_frame):
         datetime_frame.loc[5:10, 0] = np.nan
         datetime_frame.loc[10:15, 1] = np.nan

pandas/tests/groupby/test_function.py

@@ -17,6 +17,7 @@
     NaT,
     Series,
     Timestamp,
+    _is_numpy_dev,
     date_range,
     isna,
 )
@@ -685,6 +686,9 @@ def test_numpy_compat(func):
         getattr(g, func)(foo=1)
 
 
+@pytest.mark.xfail(
+    _is_numpy_dev, reason="https://github.com/pandas-dev/pandas/issues/31992"
+)
 def test_cummin_cummax():
     # GH 15048
     num_types = [np.int32, np.int64, np.float32, np.float64]

pandas/tests/groupby/test_transform.py

@@ -15,6 +15,7 @@
     MultiIndex,
     Series,
     Timestamp,
+    _is_numpy_dev,
     concat,
     date_range,
 )
@@ -317,6 +318,34 @@ def test_dispatch_transform(tsframe):
     tm.assert_frame_equal(filled, expected)
 
 
+def test_transform_transformation_func(transformation_func):
+    # GH 30918
+    df = DataFrame(
+        {
+            "A": ["foo", "foo", "foo", "foo", "bar", "bar", "baz"],
+            "B": [1, 2, np.nan, 3, 3, np.nan, 4],
+        }
+    )
+
+    if transformation_func in ["pad", "backfill", "tshift", "corrwith", "cumcount"]:
+        # These transformation functions are not yet covered in this test
+        pytest.xfail("See GH 31269 and GH 31270")
+    elif _is_numpy_dev and transformation_func in ["cummin"]:
+        pytest.xfail("https://github.com/pandas-dev/pandas/issues/31992")
+    elif transformation_func == "fillna":
+        test_op = lambda x: x.transform("fillna", value=0)
+        mock_op = lambda x: x.fillna(value=0)
+    else:
+        test_op = lambda x: x.transform(transformation_func)
+        mock_op = lambda x: getattr(x, transformation_func)()
+
+    result = test_op(df.groupby("A"))
+    groups = [df[["B"]].iloc[:4], df[["B"]].iloc[4:6], df[["B"]].iloc[6:]]
+    expected = concat([mock_op(g) for g in groups])
+
+    tm.assert_frame_equal(result, expected)
+
+
 def test_transform_select_columns(df):
     f = lambda x: x.mean()
     result = df.groupby("A")[["C", "D"]].transform(f)

pandas/tests/scalar/timedelta/test_arithmetic.py

@@ -8,7 +8,7 @@
 import pytest
 
 import pandas as pd
-from pandas import NaT, Timedelta, Timestamp, offsets
+from pandas import NaT, Timedelta, Timestamp, _is_numpy_dev, offsets
 import pandas._testing as tm
 from pandas.core import ops
 
@@ -377,7 +377,20 @@ def test_td_div_numeric_scalar(self):
         assert isinstance(result, Timedelta)
         assert result == Timedelta(days=2)
 
-    @pytest.mark.parametrize("nan", [np.nan, np.float64("NaN"), float("nan")])
+    @pytest.mark.parametrize(
+        "nan",
+        [
+            np.nan,
+            pytest.param(
+                np.float64("NaN"),
+                marks=pytest.mark.xfail(
+                    _is_numpy_dev,
+                    reason="https://github.com/pandas-dev/pandas/issues/31992",
+                ),
+            ),
+            float("nan"),
+        ],
+    )
     def test_td_div_nan(self, nan):
         # np.float64('NaN') has a 'dtype' attr, avoid treating as array
         td = Timedelta(10, unit="d")

pandas/tests/series/test_cumulative.py

@@ -11,6 +11,7 @@
 import pytest
 
 import pandas as pd
+from pandas import _is_numpy_dev
 import pandas._testing as tm
 
 
@@ -37,6 +38,9 @@ def test_cumsum(self, datetime_series):
     def test_cumprod(self, datetime_series):
         _check_accum_op("cumprod", datetime_series)
 
+    @pytest.mark.xfail(
+        _is_numpy_dev, reason="https://github.com/pandas-dev/pandas/issues/31992"
+    )
     def test_cummin(self, datetime_series):
         tm.assert_numpy_array_equal(
             datetime_series.cummin().values,
@@ -49,6 +53,9 @@ def test_cummin(self, datetime_series):
 
         tm.assert_series_equal(result, expected)
 
+    @pytest.mark.xfail(
+        _is_numpy_dev, reason="https://github.com/pandas-dev/pandas/issues/31992"
+    )
     def test_cummax(self, datetime_series):
         tm.assert_numpy_array_equal(
             datetime_series.cummax().values,