32-bit stuff III

Author: Terji Petersen

pandas/tests/frame/methods/test_value_counts.py

@@ -88,7 +88,7 @@ def test_data_frame_value_counts_empty():
     df_no_cols = pd.DataFrame()
 
     result = df_no_cols.value_counts()
-    expected = pd.Series([], dtype=np.int64, index=np.array([], dtype=np.int_))
+    expected = pd.Series([], dtype=np.int64, index=np.array([], dtype=np.intp))
 
     tm.assert_series_equal(result, expected)
 
@@ -97,7 +97,7 @@ def test_data_frame_value_counts_empty_normalize():
     df_no_cols = pd.DataFrame()
 
     result = df_no_cols.value_counts(normalize=True)
-    expected = pd.Series([], dtype=np.float64, index=np.array([], dtype=np.int_))
+    expected = pd.Series([], dtype=np.float64, index=np.array([], dtype=np.intp))
 
     tm.assert_series_equal(result, expected)
 

pandas/tests/groupby/aggregate/test_cython.py

@@ -212,7 +212,7 @@ def test_cython_agg_empty_buckets_nanops(observed):
     # GH-18869 can't call nanops on empty groups, so hardcode expected
     # for these
     df = DataFrame([11, 12, 13], columns=["a"])
-    grps = np.arange(0, 25, 5, dtype=np.intp)
+    grps = np.arange(0, 25, 5, dtype=np.int_)
     # add / sum
     result = df.groupby(pd.cut(df["a"], grps), observed=observed)._cython_agg_general(
         "sum", alt=None, numeric_only=True

pandas/tests/groupby/test_min_max.py

@@ -113,7 +113,7 @@ def test_max_inat_not_all_na():
 
     # Note: in converting to float64, the iNaT + 1 maps to iNaT, i.e. is lossy
     expected = Series({1: np.nan, 2: np.nan, 3: iNaT + 1})
-    expected.index = expected.index.astype(np.intp)
+    expected.index = expected.index.astype(np.int_)
     tm.assert_series_equal(result, expected, check_exact=True)
 
 

pandas/tests/groupby/test_nunique.py

@@ -172,7 +172,7 @@ def test_nunique_preserves_column_level_names():
     # GH 23222
     test = DataFrame([1, 2, 2], columns=pd.Index(["A"], name="level_0"))
     result = test.groupby([0, 0, 0]).nunique()
-    expected = DataFrame([2], index=np.array([0], dtype=np.intp), columns=test.columns)
+    expected = DataFrame([2], index=np.array([0], dtype=np.int_), columns=test.columns)
     tm.assert_frame_equal(result, expected)
 
 

pandas/tests/groupby/test_size.py

@@ -37,7 +37,7 @@ def test_size_axis_1(df, axis_1, by, sort, dropna):
     if sort:
         expected = expected.sort_index()
     if tm.is_integer_dtype(expected.index) and not any(x is None for x in by):
-        expected.index = expected.index.astype(np.intp)
+        expected.index = expected.index.astype(np.int_)
 
     grouped = df.groupby(by=by, axis=axis_1, sort=sort, dropna=dropna)
     result = grouped.size()

pandas/tests/indexes/test_index_new.py

@@ -283,7 +283,7 @@ def test_constructor_int_dtype_nan_raises(self, dtype):
     )
     def test_constructor_dtypes_to_int64(self, vals):
         index = Index(vals, dtype=int)
-        assert isinstance(index, NumericIndex) and index.dtype == np.intp
+        assert isinstance(index, NumericIndex) and index.dtype == np.int_
 
     @pytest.mark.parametrize(
         "vals",

pandas/tests/indexing/multiindex/test_partial.py

@@ -156,7 +156,7 @@ def test_getitem_intkey_leading_level(
         mi = ser.index
         assert isinstance(mi, MultiIndex)
         if dtype is int:
-            assert mi.levels[0].dtype == np.intp
+            assert mi.levels[0].dtype == np.int_
         else:
             assert mi.levels[0].dtype == np.float64
 

pandas/tests/indexing/test_loc.py

@@ -436,7 +436,7 @@ def test_loc_to_fail(self):
         )
 
         msg = (
-            rf"\"None of \[NumericIndex\(\[1, 2\], dtype='{np.intp().dtype}'\)\] are "
+            rf"\"None of \[NumericIndex\(\[1, 2\], dtype='{np.int_().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 = (
-            rf"\"None of \[NumericIndex\(\[-1, -2\], dtype='{np.intp().dtype}'\)\] are "
+            rf"\"None of \[NumericIndex\(\[-1, -2\], dtype='{np.int_().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 = (
-            rf"\"None of \[NumericIndex\(\[-2\], dtype='{np.intp().dtype}'\)\] are "
+            rf"\"None of \[NumericIndex\(\[-2\], dtype='{np.int_().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 = (
-            rf"\"None of \[NumericIndex\(\[3\], dtype='{np.intp().dtype}'\)\] are "
+            rf"\"None of \[NumericIndex\(\[3\], dtype='{np.int_().dtype}'\)\] are "
             r"in the \[index\]\""
         )
         with pytest.raises(KeyError, match=msg):
@@ -505,7 +505,7 @@ def test_loc_getitem_list_with_fail(self):
         s.loc[[2]]
 
         msg = (
-            f"\"None of [NumericIndex([3], dtype='{np.intp().dtype}')] "
+            f"\"None of [NumericIndex([3], dtype='{np.int_().dtype}')] "
             'are in the [index]"'
         )
         with pytest.raises(KeyError, match=re.escape(msg)):
@@ -1212,7 +1212,7 @@ def test_loc_setitem_empty_append_raises(self):
         df = DataFrame(columns=["x", "y"])
         df.index = df.index.astype(np.int64)
         msg = (
-            rf"None of \[NumericIndex\(\[0, 1\], dtype='{np.intp().dtype}'\)\] "
+            rf"None of \[NumericIndex\(\[0, 1\], dtype='{np.int_().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 = (
-            rf"\"None of \[NumericIndex\(\[3, 3, 3\], dtype='{np.intp().dtype}'\)\] "
+            rf"\"None of \[NumericIndex\(\[3, 3, 3\], dtype='{np.int_().dtype}'\)\] "
             r"are 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 = (
-            rf"\"None of \[NumericIndex\(\[3, 3, 3\], dtype='{np.intp().dtype}', "
+            rf"\"None of \[NumericIndex\(\[3, 3, 3\], dtype='{np.int_().dtype}', "
             r"name='idx'\)\] are in the \[index\]\""
         )
         with pytest.raises(KeyError, match=msg):

pandas/tests/reshape/merge/test_merge.py

@@ -355,7 +355,7 @@ def test_merge_join_key_dtype_cast(self):
         lkey = np.array([1])
         rkey = np.array([2])
         df = merge(df1, df2, left_on=lkey, right_on=rkey, how="outer")
-        assert df["key_0"].dtype == "intp"
+        assert df["key_0"].dtype == "int_"
 
     def test_handle_join_key_pass_array(self):
         left = DataFrame(
@@ -379,7 +379,7 @@ def test_handle_join_key_pass_array(self):
         rkey = np.array([1, 1, 2, 3, 4, 5])
 
         merged = merge(left, right, left_on=lkey, right_on=rkey, how="outer")
-        expected = Series([1, 1, 1, 1, 2, 2, 3, 4, 5], dtype=np.intp, name="key_0")
+        expected = Series([1, 1, 1, 1, 2, 2, 3, 4, 5], dtype=np.int_, name="key_0")
         tm.assert_series_equal(merged["key_0"], expected)
 
         left = DataFrame({"value": np.arange(3)})

pandas/tests/reshape/test_pivot.py

@@ -2052,9 +2052,7 @@ def __init__(self, *args, **kwargs) -> None:
             msg = "The following operation may generate"
             with tm.assert_produces_warning(PerformanceWarning, match=msg):
                 with pytest.raises(Exception, match="Don't compute final result."):
-                    df.pivot_table(
-                        index="ind1", columns="ind2", values="count", aggfunc="count"
-                    )
+                    df.pivot_table(index="ind1", columns="ind2", values="count", aggfunc="count")
 
     def test_pivot_table_aggfunc_dropna(self, dropna):
         # GH 22159

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 == f"interval[{np.intp().dtype}, right]"
+        assert result.dtype == f"interval[{np.int_().dtype}, right]"
         tm.assert_index_equal(Index(result.values), Index(intervals))
 
     @pytest.mark.parametrize(

pandas/tests/series/test_repr.py

@@ -333,7 +333,7 @@ def test_categorical_series_repr(self):
 8    8
 9    9
 dtype: category
-Categories (10, {np.intp().dtype}): [0, 1, 2, 3, ..., 6, 7, 8, 9]"""
+Categories (10, {np.int_().dtype}): [0, 1, 2, 3, ..., 6, 7, 8, 9]"""
 
         assert repr(s) == exp
 
@@ -359,7 +359,7 @@ def test_categorical_series_repr_ordered(self):
 8    8
 9    9
 dtype: category
-Categories (10, {np.intp().dtype}): [0 < 1 < 2 < 3 ... 6 < 7 < 8 < 9]"""
+Categories (10, {np.int_().dtype}): [0 < 1 < 2 < 3 ... 6 < 7 < 8 < 9]"""
 
         assert repr(s) == exp
 

pandas/tests/window/test_groupby.py

@@ -920,8 +920,8 @@ def test_nan_and_zero_endpoints(self):
             name="adl2",
             index=MultiIndex.from_arrays(
                 [
-                    Index([0] * 999 + [1], dtype=np.intp, name="index"),
-                    Index([0] * 999 + [1], dtype=np.intp, name="index"),
+                    Index([0] * 999 + [1], dtype=np.int_, name="index"),
+                    Index([0] * 999 + [1], dtype=np.int_, name="index"),
                 ],
             ),
         )

pandas/tests/window/test_pairwise.py

@@ -99,7 +99,7 @@ def test_flex_binary_frame(method, frame):
     exp = DataFrame(
         {k: getattr(frame[k].rolling(window=10), method)(frame2[k]) for k in frame}
     )
-    exp.columns = exp.columns.astype(np.intp)
+    exp.columns = exp.columns.astype(np.int_)
     tm.assert_frame_equal(res3, exp)