No need to use pd.api.types.is_string_dtype anymore

Author: seisman

pygmt/clib/conversion.py

@@ -228,9 +228,9 @@ def vectors_to_arrays(vectors: Sequence[Any]) -> list[np.ndarray]:
         # If fails, then the array can't be recognized.
         if array.dtype.type == np.object_:
             try:
-                array = np.asarray(array, dtype=np.datetime64)
+                array = np.ascontiguousarray(array, dtype=np.datetime64)
             except ValueError:
-                array = np.asarray(array, dtype=np.str_)
+                array = np.ascontiguousarray(array, dtype=np.str_)
         arrays.append(array)
     return arrays
 

pygmt/clib/session.py

@@ -1378,7 +1378,7 @@ def virtualfile_from_vectors(self, *vectors):
         # Assumes that first 2 columns contains coordinates like longitude
         # latitude, or datetime string types.
         for col, array in enumerate(arrays[2:]):
-            if pd.api.types.is_string_dtype(array.dtype):
+            if array.dtype.type == np.str_:
                 columns = col + 2
                 break