CLN: use lib.no_default instead of lib.NoDefault in .pivot

pandas/core/frame.py

@@ -47,11 +47,7 @@
     properties,
 )
 from pandas._libs.hashtable import duplicated
-from pandas._libs.lib import (
-    NoDefault,
-    is_range_indexer,
-    no_default,
-)
+from pandas._libs.lib import is_range_indexer
 from pandas.compat import PYPY
 from pandas.compat._optional import import_optional_dependency
 from pandas.compat.numpy import (
@@ -6118,8 +6114,8 @@ def dropna(
         self,
         *,
         axis: Axis = ...,
-        how: AnyAll | NoDefault = ...,
-        thresh: int | NoDefault = ...,
+        how: AnyAll | lib.NoDefault = ...,
+        thresh: int | lib.NoDefault = ...,
         subset: IndexLabel = ...,
         inplace: Literal[False] = ...,
         ignore_index: bool = ...,
@@ -6131,8 +6127,8 @@ def dropna(
         self,
         *,
         axis: Axis = ...,
-        how: AnyAll | NoDefault = ...,
-        thresh: int | NoDefault = ...,
+        how: AnyAll | lib.NoDefault = ...,
+        thresh: int | lib.NoDefault = ...,
         subset: IndexLabel = ...,
         inplace: Literal[True],
         ignore_index: bool = ...,
@@ -6143,8 +6139,8 @@ def dropna(
         self,
         *,
         axis: Axis = 0,
-        how: AnyAll | NoDefault = no_default,
-        thresh: int | NoDefault = no_default,
+        how: AnyAll | lib.NoDefault = lib.no_default,
+        thresh: int | lib.NoDefault = lib.no_default,
         subset: IndexLabel = None,
         inplace: bool = False,
         ignore_index: bool = False,
@@ -6247,12 +6243,12 @@ def dropna(
         1    Batman  Batmobile 1940-04-25
         2  Catwoman   Bullwhip        NaT
         """
-        if (how is not no_default) and (thresh is not no_default):
+        if (how is not lib.no_default) and (thresh is not lib.no_default):
             raise TypeError(
                 "You cannot set both the how and thresh arguments at the same time."
             )
 
-        if how is no_default:
+        if how is lib.no_default:
             how = "any"
 
         inplace = validate_bool_kwarg(inplace, "inplace")
@@ -6275,7 +6271,7 @@ def dropna(
                 raise KeyError(np.array(subset)[check].tolist())
             agg_obj = self.take(indices, axis=agg_axis)
 
-        if thresh is not no_default:
+        if thresh is not lib.no_default:
             count = agg_obj.count(axis=agg_axis)
             mask = count >= thresh
         elif how == "any":
@@ -8645,7 +8641,7 @@ def update(
     def groupby(
         self,
         by=None,
-        axis: Axis | lib.NoDefault = no_default,
+        axis: Axis | lib.NoDefault = lib.no_default,
         level: IndexLabel | None = None,
         as_index: bool = True,
         sort: bool = True,
@@ -8828,7 +8824,9 @@ def groupby(
 
     @Substitution("")
     @Appender(_shared_docs["pivot"])
-    def pivot(self, *, columns, index=lib.NoDefault, values=lib.NoDefault) -> DataFrame:
+    def pivot(
+        self, *, columns, index=lib.no_default, values=lib.no_default
+    ) -> DataFrame:
         from pandas.core.reshape.pivot import pivot
 
         return pivot(self, index=index, columns=columns, values=values)

pandas/core/reshape/pivot.py

@@ -511,8 +511,8 @@ def pivot(
     data: DataFrame,
     *,
     columns: IndexLabel,
-    index: IndexLabel | lib.NoDefault = lib.NoDefault,
-    values: IndexLabel | lib.NoDefault = lib.NoDefault,
+    index: IndexLabel | lib.NoDefault = lib.no_default,
+    values: IndexLabel | lib.NoDefault = lib.no_default,
 ) -> DataFrame:
     columns_listlike = com.convert_to_list_like(columns)
 
@@ -522,24 +522,24 @@ def pivot(
     data = data.copy(deep=False)
     data.index = data.index.copy()
     data.index.names = [
-        name if name is not None else lib.NoDefault for name in data.index.names
+        name if name is not None else lib.no_default for name in data.index.names
     ]
 
     indexed: DataFrame | Series
-    if values is lib.NoDefault:
-        if index is not lib.NoDefault:
+    if values is lib.no_default:
+        if index is not lib.no_default:
             cols = com.convert_to_list_like(index)
         else:
             cols = []
 
-        append = index is lib.NoDefault
+        append = index is lib.no_default
         # error: Unsupported operand types for + ("List[Any]" and "ExtensionArray")
         # error: Unsupported left operand type for + ("ExtensionArray")
         indexed = data.set_index(
             cols + columns_listlike, append=append  # type: ignore[operator]
         )
     else:
-        if index is lib.NoDefault:
+        if index is lib.no_default:
             if isinstance(data.index, MultiIndex):
                 # GH 23955
                 index_list = [
@@ -569,7 +569,7 @@ def pivot(
     # "Hashable"
     result = indexed.unstack(columns_listlike)  # type: ignore[arg-type]
     result.index.names = [
-        name if name is not lib.NoDefault else None for name in result.index.names
+        name if name is not lib.no_default else None for name in result.index.names
     ]
 
     return result

pandas/tests/reshape/test_pivot_multilevel.py

@@ -35,7 +35,7 @@
         (
             ["lev4"],
             "lev3",
-            lib.NoDefault,
+            lib.no_default,
             [
                 [1.0, np.nan, 1.0, np.nan, 0.0, np.nan],
                 [np.nan, 1.0, np.nan, 1.0, np.nan, 1.0],
@@ -72,7 +72,7 @@
         (
             ["lev1", "lev2"],
             "lev3",
-            lib.NoDefault,
+            lib.no_default,
             [[1, 2, 0, 1], [3, 4, 2, 3], [5, 6, 4, 5], [7, 8, 6, 7]],
             MultiIndex.from_tuples(
                 [("lev4", 1), ("lev4", 2), ("values", 1), ("values", 2)],