ENH: added parameter "positional" in DataFrame.reorder_levels (GH30289)

Author: fujiaxiang

doc/source/whatsnew/v1.0.0.rst

@@ -207,6 +207,7 @@ Other enhancements
 - The ``partition_cols`` argument in :meth:`DataFrame.to_parquet` now accepts a string (:issue:`27117`)
 - :func:`to_parquet` now appropriately handles the ``schema`` argument for user defined schemas in the pyarrow engine. (:issue: `30270`)
 - DataFrame constructor preserve `ExtensionArray` dtype with `ExtensionArray` (:issue:`11363`)
+- Added `positional` optional parameter in :meth:`DataFrame.reorder_levels` to specify the type of levels to use, labels or positions or both (:issue:`30289`)
 - Added `positional` optional parameter in :meth:`MultiIndex.reorder_levels` to specify the type of levels to use, labels or positions or both (:issue:`30289`)
 
 

pandas/core/frame.py

@@ -5040,7 +5040,7 @@ def swaplevel(self, i=-2, j=-1, axis=0):
             result.columns = result.columns.swaplevel(i, j)
         return result
 
-    def reorder_levels(self, order, axis=0):
+    def reorder_levels(self, order, axis=0, positional=None):
         """
         Rearrange index levels using input order. May not drop or duplicate levels.
 
@@ -5051,6 +5051,14 @@ def reorder_levels(self, order, axis=0):
             (position) or by key (label).
         axis : int
             Where to reorder levels.
+        positional : bool, optional
+            How to interpret integer values in `order`.
+
+              * None (default): prefer treating the values as labels,
+                but fall back to positional if no label with that
+                value is value.
+              * True : only treat integer values as positions.
+              * False : only treat integer values as labels.
 
         Returns
         -------
@@ -5063,9 +5071,9 @@ def reorder_levels(self, order, axis=0):
         result = self.copy()
 
         if axis == 0:
-            result.index = result.index.reorder_levels(order, positional=True)
+            result.index = result.index.reorder_levels(order, positional=positional)
         else:
-            result.columns = result.columns.reorder_levels(order, positional=True)
+            result.columns = result.columns.reorder_levels(order, positional=positional)
         return result
 
     # ----------------------------------------------------------------------