whatsnew and comment

doc/source/whatsnew/v1.3.0.rst

@@ -219,7 +219,7 @@ Other enhancements
 - :meth:`pandas.read_csv` and :meth:`pandas.read_json` expose the argument ``encoding_errors`` to control how encoding errors are handled (:issue:`39450`)
 - :meth:`.GroupBy.any` and :meth:`.GroupBy.all` use Kleene logic with nullable data types (:issue:`37506`)
 - :meth:`.GroupBy.any` and :meth:`.GroupBy.all` return a ``BooleanDtype`` for columns with nullable data types (:issue:`33449`)
--
+- Constructing a :class:`DataFrame` or :class:`Series` with the ``data`` argument being a Python iterable that is *not* a NumPy ``ndarray`` consisting of NumPy scalars will now result in a dtype with a precision the maximum of the NumPy scalars; this was already the case when ``data`` is a NumPy ``ndarray`` (:issue:`40908`)
 
 .. ---------------------------------------------------------------------------
 

pandas/_libs/lib.pyx

@@ -2457,7 +2457,9 @@ def maybe_convert_objects(ndarray[object] objects, bint try_float=False,
                                 result = ints
                 elif seen.is_bool and not seen.nan_:
                     result = bools.view(np.bool_)
+
         if result is uints or result is ints or result is floats or result is complexes:
+            # cast to the largest itemsize when all values are NumPy scalars
             if itemsize_max > 0 and itemsize_max != result.dtype.itemsize:
                 result = result.astype(result.dtype.kind + str(itemsize_max))
             return result