Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

DOC: update the pandas.core.window.x.mean docstring #20265

Merged
merged 3 commits into from
Mar 17, 2018
Merged

DOC: update the pandas.core.window.x.mean docstring #20265

Changes from all commits
Commits
Show all changes
3 commits
Select commit Hold shift + click to select a range
1400b71
DOC: Improve the docstring of window mean functions.
johnnymetz Mar 10, 2018
a9a510c
DOC: Add line between examples for pandas.core.window.x.mean.
johnnymetz Mar 12, 2018
a09533c
DOC: Remove whitespace in blank line for pandas.core.window.x.mean.
johnnymetz Mar 12, 2018
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
46 changes: 42 additions & 4 deletions pandas/core/window.py
View file
Open in desktop
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