REF: Separate out DataFrame/Series Construction Helpers (#24100)

Author: jbrockmendel

pandas/core/arrays/categorical.py

@@ -380,12 +380,12 @@ def __init__(self, values, categories=None, ordered=None, dtype=None,
                 dtype = CategoricalDtype(values.categories, dtype.ordered)
 
         elif not isinstance(values, (ABCIndexClass, ABCSeries)):
-            # _sanitize_array coerces np.nan to a string under certain versions
+            # sanitize_array coerces np.nan to a string under certain versions
             # of numpy
             values = maybe_infer_to_datetimelike(values, convert_dates=True)
             if not isinstance(values, np.ndarray):
                 values = _convert_to_list_like(values)
-                from pandas.core.series import _sanitize_array
+                from pandas.core.internals.construction import sanitize_array
                 # By convention, empty lists result in object dtype:
                 if len(values) == 0:
                     sanitize_dtype = 'object'
@@ -394,7 +394,7 @@ def __init__(self, values, categories=None, ordered=None, dtype=None,
                 null_mask = isna(values)
                 if null_mask.any():
                     values = [values[idx] for idx in np.where(~null_mask)[0]]
-                values = _sanitize_array(values, None, dtype=sanitize_dtype)
+                values = sanitize_array(values, None, dtype=sanitize_dtype)
 
         if dtype.categories is None:
             try:
@@ -2442,12 +2442,12 @@ def isin(self, values):
         >>> s.isin(['lama'])
         array([ True, False,  True, False,  True, False])
         """
-        from pandas.core.series import _sanitize_array
+        from pandas.core.internals.construction import sanitize_array
         if not is_list_like(values):
             raise TypeError("only list-like objects are allowed to be passed"
                             " to isin(), you passed a [{values_type}]"
                             .format(values_type=type(values).__name__))
-        values = _sanitize_array(values, None, None)
+        values = sanitize_array(values, None, None)
         null_mask = np.asarray(isna(values))
         code_values = self.categories.get_indexer(values)
         code_values = code_values[null_mask | (code_values >= 0)]

pandas/core/arrays/sparse.py

@@ -631,8 +631,8 @@ def __init__(self, data, sparse_index=None, index=None, fill_value=None,
         if not is_array_like(data):
             try:
                 # probably shared code in sanitize_series
-                from pandas.core.series import _sanitize_array
-                data = _sanitize_array(data, index=None)
+                from pandas.core.internals.construction import sanitize_array
+                data = sanitize_array(data, index=None)
             except ValueError:
                 # NumPy may raise a ValueError on data like [1, []]
                 # we retry with object dtype here.