ENH: Set index of returned dataframe in DatetimeIndex.isocalendar

doc/source/user_guide/timeseries.rst

@@ -793,6 +793,7 @@ You may obtain the year, week and day components of the ISO year from the ISO 86
 .. ipython:: python
 
    idx = pd.date_range(start='2019-12-29', freq='D', periods=4)
+   idx.isocalendar()
    idx.to_series().dt.isocalendar()
 
 .. _timeseries.offsets:

pandas/core/arrays/datetimes.py

@@ -1272,17 +1272,17 @@ def isocalendar(self):
         --------
         >>> idx = pd.date_range(start='2019-12-29', freq='D', periods=4)
         >>> idx.isocalendar()
-           year  week  day
-        0  2019    52    7
-        1  2020     1    1
-        2  2020     1    2
-        3  2020     1    3
+                    year  week  day
+        2019-12-29  2019    52    7
+        2019-12-30  2020     1    1
+        2019-12-31  2020     1    2
+        2020-01-01  2020     1    3
         >>> idx.isocalendar().week
-        0    52
-        1     1
-        2     1
-        3     1
-        Name: week, dtype: UInt32
+        2019-12-29    52
+        2019-12-30     1
+        2019-12-31     1
+        2020-01-01     1
+        Freq: D, Name: week, dtype: UInt32
         """
         from pandas import DataFrame
 

pandas/core/indexes/datetimes.py

@@ -66,7 +66,7 @@ def _new_DatetimeIndex(cls, d):
 
 
 @inherit_names(
-    ["to_period", "to_perioddelta", "to_julian_date", "strftime"]
+    ["to_period", "to_perioddelta", "to_julian_date", "strftime", "isocalendar"]
     + DatetimeArray._field_ops
     + DatetimeArray._datetimelike_methods,
     DatetimeArray,
@@ -90,7 +90,6 @@ def _new_DatetimeIndex(cls, d):
         "date",
         "time",
         "timetz",
-        "isocalendar",
     ]
     + DatetimeArray._bool_ops,
     DatetimeArray,

pandas/core/indexes/extension.py

@@ -10,7 +10,7 @@
 from pandas.util._decorators import cache_readonly, doc
 
 from pandas.core.dtypes.common import is_dtype_equal, is_object_dtype
-from pandas.core.dtypes.generic import ABCSeries
+from pandas.core.dtypes.generic import ABCDataFrame, ABCSeries
 
 from pandas.core.arrays import ExtensionArray
 from pandas.core.indexers import deprecate_ndim_indexing
@@ -55,6 +55,8 @@ def fget(self):
                 if wrap:
                     if isinstance(result, type(self._data)):
                         return type(self)._simple_new(result, name=self.name)
+                    elif isinstance(result, ABCDataFrame):
+                        return result.set_index(self)
                     return Index(result, name=self.name)
                 return result
 
@@ -77,6 +79,8 @@ def method(self, *args, **kwargs):
             if wrap:
                 if isinstance(result, type(self._data)):
                     return type(self)._simple_new(result, name=self.name)
+                elif isinstance(result, ABCDataFrame):
+                    return result.set_index(self)
                 return Index(result, name=self.name)
             return result
 

pandas/tests/groupby/transform/test_transform.py

@@ -1022,7 +1022,7 @@ def test_groupby_transform_with_datetimes(func, values):
     dates = pd.date_range("1/1/2011", periods=10, freq="D")
 
     stocks = pd.DataFrame({"price": np.arange(10.0)}, index=dates)
-    stocks["week_id"] = dates.isocalendar().set_index(dates).week
+    stocks["week_id"] = dates.isocalendar().week
 
     result = stocks.groupby(stocks["week_id"])["price"].transform(func)
 

pandas/tests/indexes/datetimes/test_misc.py

@@ -404,6 +404,7 @@ def test_isocalendar_returns_correct_values_close_to_new_year_with_tz():
     expected_data_frame = pd.DataFrame(
         [[2013, 52, 7], [2014, 1, 1], [2014, 1, 2]],
         columns=["year", "week", "day"],
+        index=dates,
         dtype="UInt32",
     )
     tm.assert_frame_equal(result, expected_data_frame)