CI: Linux py37_np_dev failing on 1.0.x (#34516)

Author: simonjayhawkins

pandas/core/dtypes/cast.py

@@ -558,7 +558,7 @@ def infer_dtype_from_scalar(val, pandas_dtype: bool = False):
         object
     """
 
-    dtype = np.object_
+    dtype = np.dtype(np.object_)
 
     # a 1-element ndarray
     if isinstance(val, np.ndarray):
@@ -577,7 +577,7 @@ def infer_dtype_from_scalar(val, pandas_dtype: bool = False):
         # instead of np.empty (but then you still don't want things
         # coming out as np.str_!
 
-        dtype = np.object_
+        dtype = np.dtype(np.object_)
 
     elif isinstance(val, (np.datetime64, datetime)):
         val = tslibs.Timestamp(val)
@@ -588,30 +588,30 @@ def infer_dtype_from_scalar(val, pandas_dtype: bool = False):
                 dtype = DatetimeTZDtype(unit="ns", tz=val.tz)
             else:
                 # return datetimetz as object
-                return np.object_, val
+                return np.dtype(np.object_), val
         val = val.value
 
     elif isinstance(val, (np.timedelta64, timedelta)):
         val = tslibs.Timedelta(val).value
         dtype = np.dtype("m8[ns]")
 
     elif is_bool(val):
-        dtype = np.bool_
+        dtype = np.dtype(np.bool_)
 
     elif is_integer(val):
         if isinstance(val, np.integer):
-            dtype = type(val)
+            dtype = np.dtype(type(val))
         else:
-            dtype = np.int64
+            dtype = np.dtype(np.int64)
 
     elif is_float(val):
         if isinstance(val, np.floating):
-            dtype = type(val)
+            dtype = np.dtype(type(val))
         else:
-            dtype = np.float64
+            dtype = np.dtype(np.float64)
 
     elif is_complex(val):
-        dtype = np.complex_
+        dtype = np.dtype(np.complex_)
 
     elif pandas_dtype:
         if lib.is_period(val):

pandas/core/internals/construction.py

@@ -233,7 +233,7 @@ def init_dict(data, index, columns, dtype=None):
         if missing.any() and not is_integer_dtype(dtype):
             if dtype is None or np.issubdtype(dtype, np.flexible):
                 # GH#1783
-                nan_dtype = object
+                nan_dtype = np.dtype(object)
             else:
                 nan_dtype = dtype
             val = construct_1d_arraylike_from_scalar(np.nan, len(index), nan_dtype)