update docstring running result; reformat code; update what's new

Author: auderson

doc/source/whatsnew/v1.5.0.rst

@@ -45,6 +45,7 @@ Other enhancements
 - Improved error message in :class:`~pandas.core.window.Rolling` when ``window`` is a frequency and ``NaT`` is in the rolling axis (:issue:`46087`)
 - :class:`Series` and :class:`DataFrame` with ``IntegerDtype`` now supports bitwise operations (:issue:`34463`)
 - Add ``milliseconds`` field support for :class:`~pandas.DateOffset` (:issue:`43371`)
+- :meth:`DataFrame.rolling.var`, :meth:`DataFrame.rolling.std`, :meth:`Series.rolling.var`, :meth:`Series.rolling.std` now generate correct result 0 for window containing same values (:issue:`42064`)
 -
 
 .. ---------------------------------------------------------------------------
@@ -251,10 +252,10 @@ Deprecations
 
 .. _whatsnew_150.deprecations.int_slicing_series:
 
-In a future version, integer slicing on a :class:`Series` with a :class:`Int64Index` or :class:`RangeIndex` will be treated as *label-based*, not positional. This will make the behavior consistent with other :meth:`Series.__getitem__` and :meth:`Series.__setitem__` behaviors (:issue:`45162`).
+In a future version, integer slicing on a :class:`Series` with a :class:`Int64Index` or :class:`RangeIndex` will be treated as *label-based*, not positional. This will make the behavior consisent with other :meth:`Series.__getitem__` and :meth:`Series.__setitem__` behaviors (:issue:`45162`).
 
 For example:
-
+t
 .. ipython:: python
 
    ser = pd.Series([1, 2, 3, 4, 5], index=[2, 3, 5, 7, 11])

pandas/core/_numba/kernels/var_.py

@@ -22,7 +22,7 @@ def add_var(
     ssqdm_x: float,
     compensation: float,
     num_consecutive_same_value: int,
-    prev_value: float
+    prev_value: float,
 ) -> tuple[int, float, float, float, int, float]:
     if not np.isnan(val):
 

pandas/core/window/rolling.py

@@ -2150,24 +2150,21 @@ def median(
         The default ``ddof`` of 1 used in :meth:`Series.std` is different
         than the default ``ddof`` of 0 in :func:`numpy.std`.
 
-        A minimum of one period is required for the rolling calculation.
-
-        The implementation is susceptible to floating point imprecision as
-        shown in the example below.\n
+        A minimum of one period is required for the rolling calculation.\n
         """
         ).replace("\n", "", 1),
         create_section_header("Examples"),
         dedent(
             """
         >>> s = pd.Series([5, 5, 6, 7, 5, 5, 5])
         >>> s.rolling(3).std()
-        0             NaN
-        1             NaN
-        2    5.773503e-01
-        3    1.000000e+00
-        4    1.000000e+00
-        5    1.154701e+00
-        6    2.580957e-08
+        0         NaN
+        1         NaN
+        2    0.577350
+        3    1.000000
+        4    1.000000
+        5    1.154701
+        6    0.000000
         dtype: float64
         """
         ).replace("\n", "", 1),
@@ -2212,24 +2209,21 @@ def std(
         The default ``ddof`` of 1 used in :meth:`Series.var` is different
         than the default ``ddof`` of 0 in :func:`numpy.var`.
 
-        A minimum of one period is required for the rolling calculation.
-
-        The implementation is susceptible to floating point imprecision as
-        shown in the example below.\n
+        A minimum of one period is required for the rolling calculation.\n
         """
         ).replace("\n", "", 1),
         create_section_header("Examples"),
         dedent(
             """
         >>> s = pd.Series([5, 5, 6, 7, 5, 5, 5])
         >>> s.rolling(3).var()
-        0             NaN
-        1             NaN
-        2    3.333333e-01
-        3    1.000000e+00
-        4    1.000000e+00
-        5    1.333333e+00
-        6    6.661338e-16
+        0         NaN
+        1         NaN
+        2    0.333333
+        3    1.000000
+        4    1.000000
+        5    1.333333
+        6    0.000000
         dtype: float64
         """
         ).replace("\n", "", 1),