@@ -694,9 +694,19 @@ def f(arg, *args, **kwargs):
694
694
return self ._wrap_results (results , blocks , obj )
695
695
696
696
_agg_doc = dedent ("""
697
- Examples
697
+ See Also
698
698
--------
699
+ pandas.DataFrame.rolling.aggregate
700
+ pandas.DataFrame.aggregate
701
+
702
+ Notes
703
+ -----
704
+ `agg` is an alias for `aggregate`. Use the alias.
699
705
706
+ A passed user-defined-function will be passed a Series for evaluation.
707
+
708
+ Examples
709
+ --------
700
710
>>> df = pd.DataFrame(np.random.randn(10, 3), columns=['A', 'B', 'C'])
701
711
>>> df
702
712
A B C
@@ -723,12 +733,6 @@ def f(arg, *args, **kwargs):
723
733
7 0.906020 1.283573 0.085482
724
734
8 -0.096361 0.818139 0.472290
725
735
9 0.070889 0.134399 -0.031308
726
-
727
- See Also
728
- --------
729
- pandas.DataFrame.rolling.aggregate
730
- pandas.DataFrame.aggregate
731
-
732
736
""" )
733
737
734
738
@Appender (_agg_doc )
@@ -1598,12 +1602,17 @@ def _validate_freq(self):
1598
1602
_agg_doc = dedent ("""
1599
1603
See Also
1600
1604
--------
1601
- pandas.Series.rolling
1602
- pandas.DataFrame.rolling
1605
+ Series.rolling
1606
+ DataFrame.rolling
1607
+
1608
+ Notes
1609
+ -----
1610
+ `agg` is an alias for `aggregate`. Use the alias.
1611
+
1612
+ A passed user-defined-function will be passed a Series for evaluation.
1603
1613
1604
1614
Examples
1605
1615
--------
1606
-
1607
1616
>>> df = pd.DataFrame(np.random.randn(10, 3), columns=['A', 'B', 'C'])
1608
1617
>>> df
1609
1618
A B C
@@ -1631,7 +1640,7 @@ def _validate_freq(self):
1631
1640
8 -0.289082 2.454418 1.416871
1632
1641
9 0.212668 0.403198 -0.093924
1633
1642
1634
- >>> df.rolling(3).agg({'A':'sum', 'B':'min'})
1643
+ >>> df.rolling(3).agg({'A': 'sum', 'B': 'min'})
1635
1644
A B
1636
1645
0 NaN NaN
1637
1646
1 NaN NaN
@@ -1645,11 +1654,11 @@ def _validate_freq(self):
1645
1654
9 0.212668 -1.647453
1646
1655
""" )
1647
1656
1657
+ @Appender (_agg_doc )
1648
1658
@Appender (_shared_docs ['aggregate' ] % dict (
1649
1659
versionadded = '' ,
1650
1660
klass = 'Series/DataFrame' ,
1651
1661
axis = '' ))
1652
- @Appender (_agg_doc )
1653
1662
def aggregate (self , arg , * args , ** kwargs ):
1654
1663
return super (Rolling , self ).aggregate (arg , * args , ** kwargs )
1655
1664
@@ -1886,13 +1895,18 @@ def _get_window(self, other=None):
1886
1895
_agg_doc = dedent ("""
1887
1896
See Also
1888
1897
--------
1889
- pandas.DataFrame.expanding.aggregate
1890
- pandas.DataFrame.rolling.aggregate
1891
- pandas.DataFrame.aggregate
1898
+ DataFrame.expanding.aggregate
1899
+ DataFrame.rolling.aggregate
1900
+ DataFrame.aggregate
1901
+
1902
+ Notes
1903
+ -----
1904
+ `agg` is an alias for `aggregate`. Use the alias.
1905
+
1906
+ A passed user-defined-function will be passed a Series for evaluation.
1892
1907
1893
1908
Examples
1894
1909
--------
1895
-
1896
1910
>>> df = pd.DataFrame(np.random.randn(10, 3), columns=['A', 'B', 'C'])
1897
1911
>>> df
1898
1912
A B C
@@ -1921,11 +1935,11 @@ def _get_window(self, other=None):
1921
1935
9 -0.286980 0.618493 -0.694496
1922
1936
""" )
1923
1937
1938
+ @Appender (_agg_doc )
1924
1939
@Appender (_shared_docs ['aggregate' ] % dict (
1925
1940
versionadded = '' ,
1926
1941
klass = 'Series/DataFrame' ,
1927
1942
axis = '' ))
1928
- @Appender (_agg_doc )
1929
1943
def aggregate (self , arg , * args , ** kwargs ):
1930
1944
return super (Expanding , self ).aggregate (arg , * args , ** kwargs )
1931
1945
@@ -2185,9 +2199,18 @@ def _constructor(self):
2185
2199
return EWM
2186
2200
2187
2201
_agg_doc = dedent ("""
2188
- Examples
2202
+ See Also
2189
2203
--------
2204
+ pandas.DataFrame.rolling.aggregate
2190
2205
2206
+ Notes
2207
+ -----
2208
+ `agg` is an alias for `aggregate`. Use the alias.
2209
+
2210
+ A passed user-defined-function will be passed a Series for evaluation.
2211
+
2212
+ Examples
2213
+ --------
2191
2214
>>> df = pd.DataFrame(np.random.randn(10, 3), columns=['A', 'B', 'C'])
2192
2215
>>> df
2193
2216
A B C
@@ -2214,10 +2237,6 @@ def _constructor(self):
2214
2237
7 0.680292 0.132049 0.548693
2215
2238
8 0.067236 0.948257 0.163353
2216
2239
9 -0.286980 0.618493 -0.694496
2217
-
2218
- See Also
2219
- --------
2220
- pandas.DataFrame.rolling.aggregate
2221
2240
""" )
2222
2241
2223
2242
@Appender (_agg_doc )
0 commit comments