Revert "np.int_ -> np.intp"

This reverts commit d759966.

Author: topper-123

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

@@ -108,7 +108,7 @@ 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/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)):
@@ -1195,7 +1195,7 @@ 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 == np.intp
+        assert df["key_0"].dtype == np.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/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