Backport PR pandas-dev#34721 on branch 1.0.x (Debug CI Issue)

Author: WillAyd

pandas/compat/numpy/__init__.py

@@ -13,6 +13,8 @@
 _np_version_under1p16 = _nlv < LooseVersion("1.16")
 _np_version_under1p17 = _nlv < LooseVersion("1.17")
 _np_version_under1p18 = _nlv < LooseVersion("1.18")
+_np_version_under1p19 = _nlv < LooseVersion("1.19")
+_np_version_under1p20 = _nlv < LooseVersion("1.20")
 _is_numpy_dev = ".dev" in str(_nlv)
 
 

pandas/tests/extension/base/dtype.py

@@ -68,18 +68,22 @@ def test_check_dtype(self, data):
             {"A": pd.Series(data, dtype=dtype), "B": data, "C": "foo", "D": 1}
         )
 
-        # np.dtype('int64') == 'Int64' == 'int64'
-        # so can't distinguish
-        if dtype.name == "Int64":
-            expected = pd.Series([True, True, False, True], index=list("ABCD"))
-        else:
-            expected = pd.Series([True, True, False, False], index=list("ABCD"))
-
-        # XXX: This should probably be *fixed* not ignored.
-        # See libops.scalar_compare
+        # TODO(numpy-1.20): This warnings filter and if block can be removed
+        # once we require numpy>=1.20
         with warnings.catch_warnings():
             warnings.simplefilter("ignore", DeprecationWarning)
             result = df.dtypes == str(dtype)
+            # NumPy>=1.20.0, but not pandas.compat.numpy till there
+            # is a wheel available with this change.
+            try:
+                new_numpy_behavior = np.dtype("int64") != "Int64"
+            except TypeError:
+                new_numpy_behavior = True
+
+        if dtype.name == "Int64" and not new_numpy_behavior:
+            expected = pd.Series([True, True, False, True], index=list("ABCD"))
+        else:
+            expected = pd.Series([True, True, False, False], index=list("ABCD"))
 
         self.assert_series_equal(result, expected)
 

pandas/tests/plotting/test_misc.py

@@ -98,13 +98,17 @@ def test_bootstrap_plot(self):
 class TestDataFramePlots(TestPlotBase):
     @td.skip_if_no_scipy
     def test_scatter_matrix_axis(self):
+        from pandas.plotting._matplotlib.compat import _mpl_ge_3_0_0
+
         scatter_matrix = plotting.scatter_matrix
 
         with tm.RNGContext(42):
             df = DataFrame(randn(100, 3))
 
         # we are plotting multiples on a sub-plot
-        with tm.assert_produces_warning(UserWarning):
+        with tm.assert_produces_warning(
+            UserWarning, raise_on_extra_warnings=_mpl_ge_3_0_0()
+        ):
             axes = _check_plot_works(
                 scatter_matrix, filterwarnings="always", frame=df, range_padding=0.1
             )