@@ -910,7 +910,38 @@ def max(self, *args, **kwargs):
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return self ._apply ('roll_max' , 'max' , ** kwargs )
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_shared_docs ['min' ] = dedent ("""
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- %(name)s minimum
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+ Calculate the %(name)s minimum.
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+
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+ Parameters
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+ ----------
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+ **kwargs
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+ Under Review.
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+
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+ Returns
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+ -------
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+ Series or DataFrame
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+ Returned object type is determined by the caller of the %(name)s
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+ calculation.
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+
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+ See Also
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+ --------
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+ Series.%(name)s : Calling object with a Series
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+ DataFrame.%(name)s : Calling object with a DataFrame
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+ Series.min : Similar method for Series
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+ DataFrame.min : Similar method for DataFrame
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+
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+ Examples
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+ --------
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+ Performing a rolling minimum with a window size of 3.
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+
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+ >>> s = pd.Series([4, 3, 5, 2, 6])
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+ >>> s.rolling(3).min()
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+ 0 NaN
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+ 1 NaN
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+ 2 3.0
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+ 3 2.0
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+ 4 2.0
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+ dtype: float64
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""" )
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def min (self , * args , ** kwargs ):
@@ -1410,7 +1441,6 @@ def max(self, *args, **kwargs):
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return super (Rolling , self ).max (* args , ** kwargs )
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@Substitution (name = 'rolling' )
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- @Appender (_doc_template )
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@Appender (_shared_docs ['min' ])
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def min (self , * args , ** kwargs ):
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nv .validate_rolling_func ('min' , args , kwargs )
@@ -1671,7 +1701,6 @@ def max(self, *args, **kwargs):
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return super (Expanding , self ).max (* args , ** kwargs )
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@Substitution (name = 'expanding' )
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- @Appender (_doc_template )
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@Appender (_shared_docs ['min' ])
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def min (self , * args , ** kwargs ):
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nv .validate_expanding_func ('min' , args , kwargs )
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