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46 changes: 42 additions & 4 deletions pandas/core/window.py
Original file line number Diff line number Diff line change
Expand Up @@ -323,7 +323,48 @@ def aggregate(self, arg, *args, **kwargs):
%(name)s sum""")

_shared_docs['mean'] = dedent("""
%(name)s mean""")
Calculate the %(name)s mean of the values.

Parameters
----------
*args
Under Review.
**kwargs
Under Review.

Returns
-------
Series or DataFrame
Returned object type is determined by the caller of the %(name)s
calculation.

See Also
--------
Series.%(name)s : Calling object with Series data
DataFrame.%(name)s : Calling object with DataFrames
Series.mean : Equivalent method for Series
DataFrame.mean : Equivalent method for DataFrame

Examples
--------
The below examples will show rolling mean calculations with window sizes of
two and three, respectively.

>>> s = pd.Series([1, 2, 3, 4])
>>> s.rolling(2).mean()
0 NaN
1 1.5
2 2.5
3 3.5
dtype: float64

>>> s.rolling(3).mean()
0 NaN
1 NaN
2 2.0
3 3.0
dtype: float64
""")


class Window(_Window):
Expand Down Expand Up @@ -646,7 +687,6 @@ def sum(self, *args, **kwargs):
return self._apply_window(mean=False, **kwargs)

@Substitution(name='window')
@Appender(_doc_template)
@Appender(_shared_docs['mean'])
def mean(self, *args, **kwargs):
nv.validate_window_func('mean', args, kwargs)
Expand Down Expand Up @@ -1237,7 +1277,6 @@ def min(self, *args, **kwargs):
return super(Rolling, self).min(*args, **kwargs)

@Substitution(name='rolling')
@Appender(_doc_template)
@Appender(_shared_docs['mean'])
def mean(self, *args, **kwargs):
nv.validate_rolling_func('mean', args, kwargs)
Expand Down Expand Up @@ -1476,7 +1515,6 @@ def min(self, *args, **kwargs):
return super(Expanding, self).min(*args, **kwargs)

@Substitution(name='expanding')
@Appender(_doc_template)
@Appender(_shared_docs['mean'])
def mean(self, *args, **kwargs):
nv.validate_expanding_func('mean', args, kwargs)
Expand Down