PERF: default_index

pandas/core/algorithms.py

@@ -947,7 +947,7 @@ def mode(values, dropna: bool = True) -> Series:
     mode : Series
     """
     from pandas import Series
-    import pandas.core.indexes.base as ibase
+    from pandas.core.indexes.api import default_index
 
     values = _ensure_arraylike(values)
     original = values
@@ -973,7 +973,7 @@ def mode(values, dropna: bool = True) -> Series:
 
     result = _reconstruct_data(npresult, original.dtype, original)
     # Ensure index is type stable (should always use int index)
-    return Series(result, index=ibase.default_index(len(result)))
+    return Series(result, index=default_index(len(result)))
 
 
 def rank(

pandas/core/arrays/sparse/accessor.py

@@ -360,16 +360,18 @@ def density(self) -> float:
 
     @staticmethod
     def _prep_index(data, index, columns):
-        from pandas.core.indexes.api import ensure_index
-        import pandas.core.indexes.base as ibase
+        from pandas.core.indexes.api import (
+            default_index,
+            ensure_index,
+        )
 
         N, K = data.shape
         if index is None:
-            index = ibase.default_index(N)
+            index = default_index(N)
         else:
             index = ensure_index(index)
         if columns is None:
-            columns = ibase.default_index(K)
+            columns = default_index(K)
         else:
             columns = ensure_index(columns)
 

pandas/core/frame.py

@@ -160,11 +160,11 @@
     _shared_docs,
 )
 from pandas.core.indexers import check_key_length
-from pandas.core.indexes import base as ibase
 from pandas.core.indexes.api import (
     DatetimeIndex,
     Index,
     PeriodIndex,
+    default_index,
     ensure_index,
     ensure_index_from_sequences,
 )
@@ -5780,7 +5780,7 @@ class    max    type
         else:
             new_obj = self.copy()
 
-        new_index = ibase.default_index(len(new_obj))
+        new_index = default_index(len(new_obj))
         if level is not None:
             if not isinstance(level, (tuple, list)):
                 level = [level]
@@ -6101,7 +6101,7 @@ def drop_duplicates(
 
         result = self[-duplicated]
         if ignore_index:
-            result.index = ibase.default_index(len(result))
+            result.index = default_index(len(result))
 
         if inplace:
             self._update_inplace(result)
@@ -6317,7 +6317,7 @@ def sort_values(  # type: ignore[override]
 
         if ignore_index:
             new_data.set_axis(
-                self._get_block_manager_axis(axis), ibase.default_index(len(indexer))
+                self._get_block_manager_axis(axis), default_index(len(indexer))
             )
 
         result = self._constructor(new_data)
@@ -8320,7 +8320,7 @@ def explode(
             result = DataFrame({c: df[c].explode() for c in columns})
         result = df.drop(columns, axis=1).join(result)
         if ignore_index:
-            result.index = ibase.default_index(len(result))
+            result.index = default_index(len(result))
         else:
             result.index = self.index.take(result.index)
         result = result.reindex(columns=self.columns, copy=False)
@@ -10286,7 +10286,7 @@ def f(s):
         data = data.apply(f, axis=axis)
         # Ensure index is type stable (should always use int index)
         if data.empty:
-            data.index = ibase.default_index(0)
+            data.index = default_index(0)
 
         return data
 

pandas/core/generic.py

@@ -125,13 +125,13 @@
 )
 from pandas.core.describe import describe_ndframe
 from pandas.core.flags import Flags
-from pandas.core.indexes import base as ibase
 from pandas.core.indexes.api import (
     DatetimeIndex,
     Index,
     MultiIndex,
     PeriodIndex,
     RangeIndex,
+    default_index,
     ensure_index,
 )
 from pandas.core.internals import (
@@ -4589,7 +4589,7 @@ def sort_index(
 
         if ignore_index:
             axis = 1 if isinstance(self, ABCDataFrame) else 0
-            new_data.set_axis(axis, ibase.default_index(len(indexer)))
+            new_data.set_axis(axis, default_index(len(indexer)))
 
         result = self._constructor(new_data)
 
@@ -5330,7 +5330,7 @@ def sample(
         result = self.take(sampled_indices, axis=axis)
 
         if ignore_index:
-            result.index = ibase.default_index(len(result))
+            result.index = default_index(len(result))
 
         return result
 

pandas/core/indexes/api.py

@@ -63,6 +63,7 @@
     "union_indexes",
     "get_unanimous_names",
     "all_indexes_same",
+    "default_index",
 ]
 
 
@@ -287,3 +288,8 @@ def all_indexes_same(indexes) -> bool:
     itr = iter(indexes)
     first = next(itr)
     return all(first.equals(index) for index in itr)
+
+
+def default_index(n: int) -> RangeIndex:
+    rng = range(0, n)
+    return RangeIndex._simple_new(rng, name=None)

pandas/core/indexes/base.py

@@ -168,7 +168,6 @@
         DataFrame,
         IntervalIndex,
         MultiIndex,
-        RangeIndex,
         Series,
     )
     from pandas.core.arrays import PeriodArray
@@ -6799,12 +6798,6 @@ def _validate_join_method(method: str) -> None:
         raise ValueError(f"do not recognize join method {method}")
 
 
-def default_index(n: int) -> RangeIndex:
-    from pandas.core.indexes.range import RangeIndex
-
-    return RangeIndex(0, n, name=None)
-
-
 def maybe_extract_name(name, obj, cls) -> Hashable:
     """
     If no name is passed, then extract it from data, validating hashability.

pandas/core/internals/construction.py

@@ -65,11 +65,11 @@
     range_to_ndarray,
     sanitize_array,
 )
-from pandas.core.indexes import base as ibase
 from pandas.core.indexes.api import (
     DatetimeIndex,
     Index,
     TimedeltaIndex,
+    default_index,
     ensure_index,
     get_objs_combined_axis,
     union_indexes,
@@ -502,9 +502,9 @@ def nested_data_to_arrays(
             index = _get_names_from_index(data)
         elif isinstance(data[0], Categorical):
             # GH#38845 hit in test_constructor_categorical
-            index = ibase.default_index(len(data[0]))
+            index = default_index(len(data[0]))
         else:
-            index = ibase.default_index(len(data))
+            index = default_index(len(data))
 
     return arrays, columns, index
 
@@ -665,7 +665,7 @@ def _extract_index(data) -> Index:
                     )
                     raise ValueError(msg)
             else:
-                index = ibase.default_index(lengths[0])
+                index = default_index(lengths[0])
 
     # error: Argument 1 to "ensure_index" has incompatible type "Optional[Index]";
     # expected "Union[Union[Union[ExtensionArray, ndarray], Index, Series],
@@ -707,7 +707,7 @@ def reorder_arrays(
 def _get_names_from_index(data) -> Index:
     has_some_name = any(getattr(s, "name", None) is not None for s in data)
     if not has_some_name:
-        return ibase.default_index(len(data))
+        return default_index(len(data))
 
     index: list[Hashable] = list(range(len(data)))
     count = 0
@@ -729,12 +729,12 @@ def _get_axes(
     # return axes or defaults
 
     if index is None:
-        index = ibase.default_index(N)
+        index = default_index(N)
     else:
         index = ensure_index(index)
 
     if columns is None:
-        columns = ibase.default_index(K)
+        columns = default_index(K)
     else:
         columns = ensure_index(columns)
     return index, columns
@@ -833,7 +833,7 @@ def to_arrays(
             stacklevel=4,
         )
         if columns is None:
-            columns = ibase.default_index(len(data))
+            columns = default_index(len(data))
         elif len(columns) > len(data):
             raise ValueError("len(columns) > len(data)")
         elif len(columns) < len(data):
@@ -890,7 +890,7 @@ def _list_of_series_to_arrays(
     for s in data:
         index = getattr(s, "index", None)
         if index is None:
-            index = ibase.default_index(len(s))
+            index = default_index(len(s))
 
         if id(index) in indexer_cache:
             indexer = indexer_cache[id(index)]
@@ -995,7 +995,7 @@ def _validate_or_indexify_columns(
         not equal to length of content
     """
     if columns is None:
-        columns = ibase.default_index(len(content))
+        columns = default_index(len(content))
     else:
 
         # Add mask for data which is composed of list of lists

pandas/core/reshape/concat.py

@@ -38,11 +38,11 @@
     Index,
     MultiIndex,
     all_indexes_same,
+    default_index,
     ensure_index,
     get_objs_combined_axis,
     get_unanimous_names,
 )
-import pandas.core.indexes.base as ibase
 from pandas.core.internals import concatenate_managers
 
 if TYPE_CHECKING:
@@ -619,7 +619,7 @@ def _get_concat_axis(self) -> Index:
             if self.bm_axis == 0:
                 indexes = [x.index for x in self.objs]
             elif self.ignore_index:
-                idx = ibase.default_index(len(self.objs))
+                idx = default_index(len(self.objs))
                 return idx
             elif self.keys is None:
                 names: list[Hashable] = [None] * len(self.objs)
@@ -640,14 +640,14 @@ def _get_concat_axis(self) -> Index:
                 if has_names:
                     return Index(names)
                 else:
-                    return ibase.default_index(len(self.objs))
+                    return default_index(len(self.objs))
             else:
                 return ensure_index(self.keys).set_names(self.names)
         else:
             indexes = [x.axes[self.axis] for x in self.objs]
 
         if self.ignore_index:
-            idx = ibase.default_index(sum(len(i) for i in indexes))
+            idx = default_index(sum(len(i) for i in indexes))
             return idx
 
         if self.keys is None:

pandas/core/series.py

@@ -122,6 +122,7 @@
     MultiIndex,
     PeriodIndex,
     TimedeltaIndex,
+    default_index,
     ensure_index,
 )
 import pandas.core.indexes.base as ibase
@@ -425,7 +426,7 @@ def __init__(
             if index is None:
                 if not is_list_like(data):
                     data = [data]
-                index = ibase.default_index(len(data))
+                index = default_index(len(data))
             elif is_list_like(data):
                 com.require_length_match(data, index)
 
@@ -1424,7 +1425,7 @@ def reset_index(self, level=None, drop=False, name=None, inplace=False):
         """
         inplace = validate_bool_kwarg(inplace, "inplace")
         if drop:
-            new_index = ibase.default_index(len(self))
+            new_index = default_index(len(self))
             if level is not None:
                 if not isinstance(level, (tuple, list)):
                     level = [level]
@@ -1745,7 +1746,7 @@ def to_frame(self, name=None) -> DataFrame:
             name = self.name
             if name is None:
                 # default to [0], same as we would get with DataFrame(self)
-                columns = ibase.default_index(1)
+                columns = default_index(1)
             else:
                 columns = Index([name])
         else:
@@ -3466,7 +3467,7 @@ def sort_values(
         )
 
         if ignore_index:
-            result.index = ibase.default_index(len(sorted_index))
+            result.index = default_index(len(sorted_index))
 
         if inplace:
             self._update_inplace(result)
@@ -4039,7 +4040,7 @@ def explode(self, ignore_index: bool = False) -> Series:
         values, counts = reshape.explode(np.asarray(self._values))
 
         if ignore_index:
-            index = ibase.default_index(len(values))
+            index = default_index(len(values))
         else:
             index = self.index.repeat(counts)