remove numpy deprecated calls

python/cudf/cudf/core/dataframe.py

@@ -5808,7 +5808,7 @@ def _prepare_for_rowwise_op(self, method, skipna):
         is_pure_dt = all(is_datetime_dtype(dt) for dt in self.dtypes)
 
         if not is_pure_dt:
-            filtered = self.select_dtypes(include=[np.number, np.bool])
+            filtered = self.select_dtypes(include=[np.number, np.bool_])
         else:
             filtered = self.copy(deep=False)
 
@@ -6587,8 +6587,8 @@ def kurtosis(
             msg = "Kurtosis only supports int, float, and bool dtypes."
             raise NotImplementedError(msg)
 
-        self = self.select_dtypes(include=[np.number, np.bool])
-        return self._apply_support_method(
+        filtered = self.select_dtypes(include=[np.number, np.bool_])
+        return filtered._apply_support_method(
             "kurtosis",
             axis=axis,
             skipna=skipna,
@@ -6636,8 +6636,8 @@ def skew(
             msg = "Skew only supports int, float, and bool dtypes."
             raise NotImplementedError(msg)
 
-        self = self.select_dtypes(include=[np.number, np.bool])
-        return self._apply_support_method(
+        filtered = self.select_dtypes(include=[np.number, np.bool_])
+        return filtered._apply_support_method(
             "skew",
             axis=axis,
             skipna=skipna,

python/cudf/cudf/core/frame.py

@@ -1195,7 +1195,7 @@ def scatter_by_map(
             map_index = as_column(map_index)
 
         # Convert float to integer
-        if map_index.dtype == np.float:
+        if map_index.dtype == float:
             map_index = map_index.astype(np.int32)
 
         # Convert string or categorical to integer

python/cudf/cudf/core/indexing.py

@@ -173,7 +173,7 @@ def _loc_to_iloc(self, arg):
 
         else:
             arg = Series(column.as_column(arg))
-            if arg.dtype in [np.bool, np.bool_]:
+            if arg.dtype in (bool, np.bool_):
                 return arg
             else:
                 indices = indices_from_labels(self._sr, arg)

python/cudf/cudf/core/scalar.py

@@ -251,7 +251,7 @@ def __repr__(self):
 
     def _binop_result_dtype_or_error(self, other, op):
         if op in {"__eq__", "__ne__", "__lt__", "__gt__", "__le__", "__ge__"}:
-            return np.bool
+            return np.bool_
 
         out_dtype = get_allowed_combinations_for_operator(
             self.dtype, other.dtype, op

python/cudf/cudf/tests/test_applymap.py

@@ -22,7 +22,7 @@ def test_applymap_round(nelem, masked):
         # Make mask
         bitmask = utils.random_bitmask(nelem)
         boolmask = np.asarray(
-            utils.expand_bits_to_bytes(bitmask), dtype=np.bool
+            utils.expand_bits_to_bytes(bitmask), dtype=np.bool_
         )[:nelem]
         data[~boolmask] = np.nan
 

python/cudf/cudf/tests/test_binops.py

@@ -290,15 +290,15 @@ def test_validity_add(nelem, lhs_nulls, rhs_nulls):
     res = lhs + rhs
     if lhs_nulls == "some" and rhs_nulls == "some":
         res_mask = np.asarray(
-            utils.expand_bits_to_bytes(lhs_mask & rhs_mask), dtype=np.bool
+            utils.expand_bits_to_bytes(lhs_mask & rhs_mask), dtype=np.bool_
         )[:nelem]
     if lhs_nulls == "some" and rhs_nulls == "none":
         res_mask = np.asarray(
-            utils.expand_bits_to_bytes(lhs_mask), dtype=np.bool
+            utils.expand_bits_to_bytes(lhs_mask), dtype=np.bool_
         )[:nelem]
     if lhs_nulls == "none" and rhs_nulls == "some":
         res_mask = np.asarray(
-            utils.expand_bits_to_bytes(rhs_mask), dtype=np.bool
+            utils.expand_bits_to_bytes(rhs_mask), dtype=np.bool_
         )[:nelem]
     # Fill NA values
     na_value = -10000

python/cudf/cudf/tests/test_dataframe.py

@@ -1214,7 +1214,7 @@ def test_dataframe_concat_different_numerical_columns(dtype1, dtype2):
 
 
 def test_dataframe_concat_different_column_types():
-    df1 = cudf.Series([42], dtype=np.float)
+    df1 = cudf.Series([42], dtype=float)
     df2 = cudf.Series(["a"], dtype="category")
     with pytest.raises(ValueError):
         cudf.concat([df1, df2])
@@ -2353,7 +2353,7 @@ def check_frame_series_equality(left, right):
 
 def test_tail_for_string():
     gdf = cudf.DataFrame()
-    gdf["id"] = cudf.Series(["a", "b"], dtype=np.object)
+    gdf["id"] = cudf.Series(["a", "b"], dtype=np.object_)
     gdf["v"] = cudf.Series([1, 2])
     assert_eq(gdf.tail(3), gdf.to_pandas().tail(3))
 

python/cudf/cudf/tests/test_joining.py

@@ -821,17 +821,17 @@ def test_join_empty_table_dtype():
     "column_a",
     [
         (
-            pd.Series([None, 1, 2, 3, 4, 5, 6, 7]).astype(np.float),
-            pd.Series([8, 9, 10, 11, 12, None, 14, 15]).astype(np.float),
+            pd.Series([None, 1, 2, 3, 4, 5, 6, 7], dtype=np.float_),
+            pd.Series([8, 9, 10, 11, 12, None, 14, 15], dtype=np.float_),
         )
     ],
 )
 @pytest.mark.parametrize(
     "column_b",
     [
         (
-            pd.Series([0, 1, 0, None, 1, 0, 0, 0]).astype(np.float),
-            pd.Series([None, 1, 2, 1, 2, 2, 0, 0]).astype(np.float),
+            pd.Series([0, 1, 0, None, 1, 0, 0, 0], dtype=np.float_),
+            pd.Series([None, 1, 2, 1, 2, 2, 0, 0], dtype=np.float_),
         )
     ],
 )

python/cudf/cudf/tests/test_pandas_interop.py

@@ -23,8 +23,8 @@ def test_to_pandas():
 
     # Notice, the dtype differ when Pandas and cudf boolean series
     # contains None/NaN
-    assert df["c"].dtype == np.bool
-    assert pdf["c"].dtype == np.object
+    assert df["c"].dtype == np.bool_
+    assert pdf["c"].dtype == np.object_
 
     assert len(df["a"]) == len(pdf["a"])
     assert len(df["b"]) == len(pdf["b"])

python/cudf/cudf/tests/utils.py

@@ -259,7 +259,9 @@ def gen_rand(dtype, size, **kwargs):
     elif dtype.kind == "b":
         low = kwargs.get("low", 0)
         high = kwargs.get("high", 2)
-        return np.random.randint(low=low, high=high, size=size).astype(np.bool)
+        return np.random.randint(low=low, high=high, size=size).astype(
+            np.bool_
+        )
     elif dtype.kind == "M":
         low = kwargs.get("low", 0)
         time_unit, _ = np.datetime_data(dtype)

python/cudf/cudf/utils/utils.py

@@ -194,7 +194,7 @@ def wrapper(*args, **kwargs):
     return wrapper
 
 
-def get_null_series(size, dtype=np.bool):
+def get_null_series(size, dtype=np.bool_):
     """
     Creates a null series of provided dtype and size