32-bit issues in test/series/reshape/resample/window

Author: topper-123

pandas/tests/indexing/test_loc.py

@@ -436,7 +436,7 @@ def test_loc_to_fail(self):
         )
 
         msg = (
-            r"\"None of \[NumericIndex\(\[1, 2\], dtype='int64'\)\] are "
+            rf"\"None of \[NumericIndex\(\[1, 2\], dtype='{np.intp().dtype}'\)\] are "
             r"in the \[index\]\""
         )
         with pytest.raises(KeyError, match=msg):
@@ -454,7 +454,7 @@ def test_loc_to_fail2(self):
             s.loc[-1]
 
         msg = (
-            r"\"None of \[NumericIndex\(\[-1, -2\], dtype='int64'\)\] are "
+            fr"\"None of \[NumericIndex\(\[-1, -2\], dtype='{np.intp().dtype}'\)\] are "
             r"in the \[index\]\""
         )
         with pytest.raises(KeyError, match=msg):
@@ -470,7 +470,7 @@ def test_loc_to_fail2(self):
 
         s["a"] = 2
         msg = (
-            r"\"None of \[NumericIndex\(\[-2\], dtype='int64'\)\] are "
+            fr"\"None of \[NumericIndex\(\[-2\], dtype='{np.intp().dtype}'\)\] are "
             r"in the \[index\]\""
         )
         with pytest.raises(KeyError, match=msg):
@@ -487,7 +487,7 @@ def test_loc_to_fail3(self):
         df = DataFrame([["a"], ["b"]], index=[1, 2], columns=["value"])
 
         msg = (
-            r"\"None of \[NumericIndex\(\[3\], dtype='int64'\)\] are "
+            fr"\"None of \[NumericIndex\(\[3\], dtype='{np.intp().dtype}'\)\] are "
             r"in the \[index\]\""
         )
         with pytest.raises(KeyError, match=msg):
@@ -507,7 +507,7 @@ def test_loc_getitem_list_with_fail(self):
         with pytest.raises(
             KeyError,
             match=re.escape(
-                "\"None of [NumericIndex([3], dtype='int64')] are in the [index]\""
+                f"\"None of [NumericIndex([3], dtype='{np.intp().dtype}')] are in the [index]\""
             ),
         ):
             s.loc[[3]]
@@ -1213,7 +1213,7 @@ def test_loc_setitem_empty_append_raises(self):
         df = DataFrame(columns=["x", "y"])
         df.index = df.index.astype(np.int64)
         msg = (
-            r"None of \[NumericIndex\(\[0, 1\], dtype='int64'\)\] "
+            fr"None of \[NumericIndex\(\[0, 1\], dtype='{np.intp().dtype}'\)\] "
             r"are in the \[index\]"
         )
         with pytest.raises(KeyError, match=msg):

pandas/tests/indexing/test_partial.py

@@ -403,7 +403,7 @@ def test_series_partial_set(self):
 
         # raises as nothing is in the index
         msg = (
-            r"\"None of \[NumericIndex\(\[3, 3, 3\], dtype='int64'\)\] are "
+            fr"\"None of \[NumericIndex\(\[3, 3, 3\], dtype='{np.intp().dtype}'\)\] are "
             r"in the \[index\]\""
         )
         with pytest.raises(KeyError, match=msg):
@@ -484,7 +484,7 @@ def test_series_partial_set_with_name(self):
 
         # raises as nothing is in the index
         msg = (
-            r"\"None of \[NumericIndex\(\[3, 3, 3\], dtype='int64', "
+            fr"\"None of \[NumericIndex\(\[3, 3, 3\], dtype='{np.intp().dtype}', "
             r"name='idx'\)\] are in the \[index\]\""
         )
         with pytest.raises(KeyError, match=msg):

pandas/tests/resample/test_resampler_grouper.py

@@ -316,7 +316,7 @@ def test_resample_groupby_with_label():
     result = df.groupby("col0").resample("1W", label="left").sum()
 
     mi = [
-        np.array([0, 0, 1, 2]),
+        np.array([0, 0, 1, 2], dtype=np.int64),
         pd.to_datetime(
             np.array(["1999-12-26", "2000-01-02", "2000-01-02", "2000-01-02"])
         ),

pandas/tests/reshape/test_crosstab.py

@@ -112,7 +112,7 @@ def test_crosstab_non_aligned(self):
         # GH 17005
         a = Series([0, 1, 1], index=["a", "b", "c"])
         b = Series([3, 4, 3, 4, 3], index=["a", "b", "c", "d", "f"])
-        c = np.array([3, 4, 3])
+        c = np.array([3, 4, 3], dtype=np.int64)
 
         expected = DataFrame(
             [[1, 0], [1, 1]],

pandas/tests/series/methods/test_reindex.py

@@ -126,7 +126,7 @@ def test_reindex_pad():
     reindexed2 = s2.reindex(s.index, method="ffill")
     tm.assert_series_equal(reindexed, reindexed2)
 
-    expected = Series([0, 0, 2, 2, 4, 4, 6, 6, 8, 8], index=np.arange(10))
+    expected = Series([0, 0, 2, 2, 4, 4, 6, 6, 8, 8])
     tm.assert_series_equal(reindexed, expected)
 
     # GH4604

pandas/tests/series/test_constructors.py

@@ -1199,7 +1199,7 @@ def test_construction_interval(self, interval_constructor):
         # construction from interval & array of intervals
         intervals = interval_constructor.from_breaks(np.arange(3), closed="right")
         result = Series(intervals)
-        assert result.dtype == "interval[int64, right]"
+        assert result.dtype == f"interval[{np.intp().dtype}, right]"
         tm.assert_index_equal(Index(result.values), Index(intervals))
 
     @pytest.mark.parametrize(

pandas/tests/series/test_repr.py

@@ -322,7 +322,7 @@ def test_categorical_series_repr(self):
         assert repr(s) == exp
 
         s = Series(Categorical(np.arange(10)))
-        exp = """0    0
+        exp = f"""0    0
 1    1
 2    2
 3    3
@@ -333,7 +333,7 @@ def test_categorical_series_repr(self):
 8    8
 9    9
 dtype: category
-Categories (10, int64): [0, 1, 2, 3, ..., 6, 7, 8, 9]"""
+Categories (10, {np.intp().dtype}): [0, 1, 2, 3, ..., 6, 7, 8, 9]"""
 
         assert repr(s) == exp
 
@@ -348,7 +348,7 @@ def test_categorical_series_repr_ordered(self):
         assert repr(s) == exp
 
         s = Series(Categorical(np.arange(10), ordered=True))
-        exp = """0    0
+        exp = f"""0    0
 1    1
 2    2
 3    3
@@ -359,7 +359,7 @@ def test_categorical_series_repr_ordered(self):
 8    8
 9    9
 dtype: category
-Categories (10, int64): [0 < 1 < 2 < 3 ... 6 < 7 < 8 < 9]"""
+Categories (10, {np.intp().dtype}): [0 < 1 < 2 < 3 ... 6 < 7 < 8 < 9]"""
 
         assert repr(s) == exp
 

pandas/tests/window/test_groupby.py

@@ -811,7 +811,7 @@ def test_groupby_rolling_var(self, window, min_periods, closed, expected):
         expected_result = DataFrame(
             np.array(expected, dtype="float64"),
             index=MultiIndex(
-                levels=[[1, 2], [0, 1, 2, 3, 4, 5, 6, 7]],
+                levels=[np.array([1, 2]), [0, 1, 2, 3, 4, 5, 6, 7]],
                 codes=[[0, 0, 0, 0, 1, 1, 1, 1], [0, 2, 4, 6, 1, 3, 5, 7]],
             ),
         )