CLN: remove xfails/skips for no-longer-supported numpys (#36128)

Author: jbrockmendel

pandas/plotting/_matplotlib/style.py

@@ -11,7 +11,7 @@
 
 
 def get_standard_colors(
-    num_colors=None, colormap=None, color_type: str = "default", color=None
+    num_colors: int, colormap=None, color_type: str = "default", color=None
 ):
     import matplotlib.pyplot as plt
 

pandas/tests/arrays/sparse/test_array.py

@@ -194,8 +194,7 @@ def test_constructor_inferred_fill_value(self, data, fill_value):
 
     @pytest.mark.parametrize("format", ["coo", "csc", "csr"])
     @pytest.mark.parametrize(
-        "size",
-        [pytest.param(0, marks=td.skip_if_np_lt("1.16", reason="NumPy-11383")), 10],
+        "size", [0, 10],
     )
     @td.skip_if_no_scipy
     def test_from_spmatrix(self, size, format):
@@ -904,7 +903,6 @@ def test_all(self, data, pos, neg):
             ([1.0, 2.0, 1.0], 1.0, 0.0),
         ],
     )
-    @td.skip_if_np_lt("1.15")  # prior didn't dispatch
     def test_numpy_all(self, data, pos, neg):
         # GH 17570
         out = np.all(SparseArray(data))
@@ -956,7 +954,6 @@ def test_any(self, data, pos, neg):
             ([0.0, 2.0, 0.0], 2.0, 0.0),
         ],
     )
-    @td.skip_if_np_lt("1.15")  # prior didn't dispatch
     def test_numpy_any(self, data, pos, neg):
         # GH 17570
         out = np.any(SparseArray(data))

pandas/tests/frame/test_analytics.py

@@ -1060,54 +1060,14 @@ def test_any_all_bool_only(self):
             (np.any, {"A": pd.Series([0.0, 1.0], dtype="float")}, True),
             (np.all, {"A": pd.Series([0, 1], dtype=int)}, False),
             (np.any, {"A": pd.Series([0, 1], dtype=int)}, True),
-            pytest.param(
-                np.all,
-                {"A": pd.Series([0, 1], dtype="M8[ns]")},
-                False,
-                marks=[td.skip_if_np_lt("1.15")],
-            ),
-            pytest.param(
-                np.any,
-                {"A": pd.Series([0, 1], dtype="M8[ns]")},
-                True,
-                marks=[td.skip_if_np_lt("1.15")],
-            ),
-            pytest.param(
-                np.all,
-                {"A": pd.Series([1, 2], dtype="M8[ns]")},
-                True,
-                marks=[td.skip_if_np_lt("1.15")],
-            ),
-            pytest.param(
-                np.any,
-                {"A": pd.Series([1, 2], dtype="M8[ns]")},
-                True,
-                marks=[td.skip_if_np_lt("1.15")],
-            ),
-            pytest.param(
-                np.all,
-                {"A": pd.Series([0, 1], dtype="m8[ns]")},
-                False,
-                marks=[td.skip_if_np_lt("1.15")],
-            ),
-            pytest.param(
-                np.any,
-                {"A": pd.Series([0, 1], dtype="m8[ns]")},
-                True,
-                marks=[td.skip_if_np_lt("1.15")],
-            ),
-            pytest.param(
-                np.all,
-                {"A": pd.Series([1, 2], dtype="m8[ns]")},
-                True,
-                marks=[td.skip_if_np_lt("1.15")],
-            ),
-            pytest.param(
-                np.any,
-                {"A": pd.Series([1, 2], dtype="m8[ns]")},
-                True,
-                marks=[td.skip_if_np_lt("1.15")],
-            ),
+            pytest.param(np.all, {"A": pd.Series([0, 1], dtype="M8[ns]")}, False,),
+            pytest.param(np.any, {"A": pd.Series([0, 1], dtype="M8[ns]")}, True,),
+            pytest.param(np.all, {"A": pd.Series([1, 2], dtype="M8[ns]")}, True,),
+            pytest.param(np.any, {"A": pd.Series([1, 2], dtype="M8[ns]")}, True,),
+            pytest.param(np.all, {"A": pd.Series([0, 1], dtype="m8[ns]")}, False,),
+            pytest.param(np.any, {"A": pd.Series([0, 1], dtype="m8[ns]")}, True,),
+            pytest.param(np.all, {"A": pd.Series([1, 2], dtype="m8[ns]")}, True,),
+            pytest.param(np.any, {"A": pd.Series([1, 2], dtype="m8[ns]")}, True,),
             (np.all, {"A": pd.Series([0, 1], dtype="category")}, False),
             (np.any, {"A": pd.Series([0, 1], dtype="category")}, True),
             (np.all, {"A": pd.Series([1, 2], dtype="category")}, True),
@@ -1120,8 +1080,6 @@ def test_any_all_bool_only(self):
                     "B": pd.Series([10, 20], dtype="m8[ns]"),
                 },
                 True,
-                # In 1.13.3 and 1.14 np.all(df) returns a Timedelta here
-                marks=[td.skip_if_np_lt("1.15")],
             ),
         ],
     )

pandas/tests/io/formats/test_to_csv.py

@@ -11,10 +11,6 @@
 
 
 class TestToCSV:
-    @pytest.mark.xfail(
-        (3, 6, 5) > sys.version_info,
-        reason=("Python csv library bug (see https://bugs.python.org/issue32255)"),
-    )
     def test_to_csv_with_single_column(self):
         # see gh-18676, https://bugs.python.org/issue32255
         #

pandas/tests/series/test_analytics.py

@@ -3,8 +3,6 @@
 import numpy as np
 import pytest
 
-import pandas.util._test_decorators as td
-
 import pandas as pd
 from pandas import DataFrame, Series
 import pandas._testing as tm
@@ -130,7 +128,6 @@ def test_is_monotonic(self):
 
     @pytest.mark.parametrize("func", [np.any, np.all])
     @pytest.mark.parametrize("kwargs", [dict(keepdims=True), dict(out=object())])
-    @td.skip_if_np_lt("1.15")
     def test_validate_any_all_out_keepdims_raises(self, kwargs, func):
         s = pd.Series([1, 2])
         param = list(kwargs)[0]
@@ -144,7 +141,6 @@ def test_validate_any_all_out_keepdims_raises(self, kwargs, func):
         with pytest.raises(ValueError, match=msg):
             func(s, **kwargs)
 
-    @td.skip_if_np_lt("1.15")
     def test_validate_sum_initial(self):
         s = pd.Series([1, 2])
         msg = (
@@ -167,7 +163,6 @@ def test_validate_median_initial(self):
             # method instead of the ufunc.
             s.median(overwrite_input=True)
 
-    @td.skip_if_np_lt("1.15")
     def test_validate_stat_keepdims(self):
         s = pd.Series([1, 2])
         msg = (