Fix arch-specific upstream xfails

We test on more architectures, so upstream's xfails are not always
correct everywhere.  On those known to fail:
arm64 xfail -> all non-x86 xfail
x86 or unconditional strict xfail -> unconditional nonstrict xfail

Author: Rebecca N. Palmer <[email protected]>
Bug: pandas-dev/pandas#38921, pandas-dev/pandas#38798, pandas-dev/pandas#41740, numpy/numpy#19146
Forwarded: no


Gbp-Pq: Name fix_overly_arch_specific_xfails.patch

Author: Debian Science Team

pandas/tests/io/parser/test_c_parser_only.py

@@ -17,6 +17,7 @@
 import numpy as np
 import pytest
 
+from pandas.compat import IS64
 from pandas.compat.numpy import np_version_gte1p24
 from pandas.errors import (
     ParserError,
@@ -29,6 +30,9 @@
     concat,
 )
 import pandas._testing as tm
+import platform
+import re
+is_platform_x86 = bool(re.match("i.?86|x86",platform.uname()[4]))
 
 
 @pytest.mark.parametrize(
@@ -633,11 +637,13 @@ def test_float_precision_options(c_parser_only):
 
     tm.assert_frame_equal(df, df2)
 
-    df3 = parser.read_csv(StringIO(s), float_precision="legacy")
-
-    assert not df.iloc[0, 0] == df3.iloc[0, 0]
-
     msg = "Unrecognized float_precision option: junk"
 
     with pytest.raises(ValueError, match=msg):
         parser.read_csv(StringIO(s), float_precision="junk")
+
+    df3 = parser.read_csv(StringIO(s), float_precision="legacy")
+    if is_platform_x86 and (not IS64) and (df.iloc[0, 0] == df3.iloc[0, 0]):
+        pytest.xfail(reason="maybe x87 extra precision")
+
+    assert not df.iloc[0, 0] == df3.iloc[0, 0]

pandas/tests/window/test_rolling.py

@@ -10,7 +10,11 @@
     IS64,
     is_platform_arm,
     is_platform_power,
+    IS64,
 )
+import platform
+import re
+is_platform_x86 = bool(re.match("i.?86|x86", platform.uname()[4]))
 
 from pandas import (
     DataFrame,
@@ -1176,7 +1180,8 @@ def test_rolling_sem(frame_or_series):
 
 
 @pytest.mark.xfail(
-    is_platform_arm() or is_platform_power(),
+    not (is_platform_x86 and IS64),
+    strict=False,
     reason="GH 38921",
 )
 @pytest.mark.parametrize(