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DOC: update the window.Rolling.min docstring #20263

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Merged
merged 3 commits into from
Mar 17, 2018
Merged

DOC: update the window.Rolling.min docstring #20263

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81f5d97
DOC: Improve the doctring of window.Rolling.min()
gojandrooo Mar 10, 2018
eaaa162
Merge remote-tracking branch 'upstream/master' into gojandrooo-docstr…
jorisvandenbossche Mar 17, 2018
1a5c3cc
pep8
jorisvandenbossche Mar 17, 2018
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45 changes: 41 additions & 4 deletions pandas/core/window.py
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Original file line number Diff line number Diff line change
Expand Up @@ -838,9 +838,48 @@ def max(self, *args, **kwargs):
return self._apply('roll_max', 'max', **kwargs)

_shared_docs['min'] = dedent("""
%(name)s minimum
""")
Calculate the %(name)s minimum.

Parameters
----------
**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 a Series
DataFrame.%(name)s : Calling object with a DataFrame
Series.min : Similar method for Series
DataFrame.min : Similar method for DataFrame

Examples
--------
The below example will show a rolling calculation
with a window size of 3.

>>> s = pd.Series([4,3,5,2,6])
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spaces after comma for PEP8

>>> s
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The constructor here is simple enough that you don't need to explicitly print

0 4
1 3
2 5
3 2
4 6
dtype: int64
>>> s.rolling(3).min()
0 NaN
1 NaN
2 3.0
3 2.0
4 2.0
dtype: float64
""")

def min(self, *args, **kwargs):
nv.validate_window_func('min', args, kwargs)
return self._apply('roll_min', 'min', **kwargs)
Expand Down Expand Up @@ -1230,7 +1269,6 @@ def max(self, *args, **kwargs):
return super(Rolling, self).max(*args, **kwargs)

@Substitution(name='rolling')
@Appender(_doc_template)
@Appender(_shared_docs['min'])
def min(self, *args, **kwargs):
nv.validate_rolling_func('min', args, kwargs)
Expand Down Expand Up @@ -1469,7 +1507,6 @@ def max(self, *args, **kwargs):
return super(Expanding, self).max(*args, **kwargs)

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