un-xfail and adjust more tests

Author: lithomas1

pandas/tests/frame/methods/test_quantile.py

@@ -1,8 +1,6 @@
 import numpy as np
 import pytest
 
-from pandas._config import using_string_dtype
-
 import pandas as pd
 from pandas import (
     DataFrame,
@@ -354,7 +352,6 @@ def test_quantile_multi_empty(self, interp_method):
         )
         tm.assert_frame_equal(result, expected)
 
-    @pytest.mark.xfail(using_string_dtype(), reason="TODO(infer_string)")
     def test_quantile_datetime(self, unit):
         dti = pd.to_datetime(["2010", "2011"]).as_unit(unit)
         df = DataFrame({"a": dti, "b": [0, 5]})
@@ -408,7 +405,6 @@ def test_quantile_datetime(self, unit):
         expected = DataFrame(index=[0.5], columns=[])
         tm.assert_frame_equal(result, expected)
 
-    @pytest.mark.xfail(using_string_dtype(), reason="TODO(infer_string)")
     @pytest.mark.parametrize(
         "dtype",
         [
@@ -679,7 +675,6 @@ def test_quantile_nat(self, interp_method, request, using_array_manager, unit):
         )
         tm.assert_frame_equal(res, exp)
 
-    @pytest.mark.xfail(using_string_dtype(), reason="TODO(infer_string)")
     def test_quantile_empty_no_rows_floats(self, interp_method):
         interpolation, method = interp_method
 
@@ -918,7 +913,6 @@ def test_quantile_ea_scalar(self, request, obj, index):
         else:
             tm.assert_series_equal(result, expected)
 
-    @pytest.mark.xfail(using_string_dtype(), reason="TODO(infer_string)", strict=False)
     @pytest.mark.parametrize(
         "dtype, expected_data, expected_index, axis",
         [
@@ -937,7 +931,6 @@ def test_empty_numeric(self, dtype, expected_data, expected_index, axis):
         )
         tm.assert_series_equal(result, expected)
 
-    @pytest.mark.xfail(using_string_dtype(), reason="TODO(infer_string)", strict=False)
     @pytest.mark.parametrize(
         "dtype, expected_data, expected_index, axis, expected_dtype",
         [
@@ -956,7 +949,6 @@ def test_empty_datelike(
         )
         tm.assert_series_equal(result, expected)
 
-    @pytest.mark.xfail(using_string_dtype(), reason="TODO(infer_string)", strict=False)
     @pytest.mark.parametrize(
         "expected_data, expected_index, axis",
         [

pandas/tests/groupby/test_numeric_only.py

@@ -275,9 +275,12 @@ def test_axis1_numeric_only(request, groupby_func, numeric_only, using_infer_str
             "has no kernel",
         )
         if using_infer_string:
-            import pyarrow as pa
+            try:
+                import pyarrow as pa
 
-            errs = (TypeError, pa.lib.ArrowNotImplementedError)
+                errs = (TypeError, pa.lib.ArrowNotImplementedError)
+            except ImportError:
+                errs = TypeError
         else:
             errs = TypeError
         with pytest.raises(errs, match=f"({'|'.join(msgs)})"):

pandas/tests/groupby/test_raises.py

@@ -219,7 +219,6 @@ def func(x):
         getattr(gb, how)(func)
 
 
-@pytest.mark.xfail(using_string_dtype(), reason="TODO(infer_string)")
 @pytest.mark.parametrize("how", ["agg", "transform"])
 @pytest.mark.parametrize("groupby_func_np", [np.sum, np.mean])
 def test_groupby_raises_string_np(

pandas/tests/io/excel/test_writers.py

@@ -286,7 +286,6 @@ def test_excel_multindex_roundtrip(
             )
             tm.assert_frame_equal(df, act, check_names=check_names)
 
-    @pytest.mark.xfail(using_string_dtype(), reason="TODO(infer_string)")
     def test_read_excel_parse_dates(self, ext):
         # see gh-11544, gh-12051
         df = DataFrame(