@@ -153,11 +153,23 @@ class providing the base-class of operations.
153153 transform : Apply function column-by-column to the GroupBy object.
154154 Series.apply : Apply a function to a Series.
155155 DataFrame.apply : Apply a function to each row or column of a DataFrame.
156+
157+ Notes
158+ -----
159+ In the current implementation `apply` calls `func` twice on the
160+ first group to decide whether it can take a fast or slow code
161+ path. This can lead to unexpected behavior if `func` has
162+ side-effects, as they will take effect twice for the first
163+ group.
164+
165+ Examples
166+ --------
167+ {examples}
156168 """ ,
157169 "dataframe_examples" : """
158170 >>> df = pd.DataFrame({'A': 'a a b'.split(),
159- 'B': [1,2,3],
160- 'C': [4,6, 5]})
171+ ... 'B': [1,2,3],
172+ ... 'C': [4,6, 5]})
161173 >>> g = df.groupby('A')
162174
163175 Notice that ``g`` has two groups, ``a`` and ``b``.
@@ -192,8 +204,7 @@ class providing the base-class of operations.
192204 A
193205 a 5
194206 b 2
195- dtype: int64
196- """ ,
207+ dtype: int64""" ,
197208 "series_examples" : """
198209 >>> s = pd.Series([0, 1, 2], index='a a b'.split())
199210 >>> g = s.groupby(s.index)
@@ -206,9 +217,9 @@ class providing the base-class of operations.
206217 each group together into a new Series:
207218
208219 >>> g.apply(lambda x: x*2 if x.name == 'b' else x/2)
209- 0 0.0
210- 1 0.5
211- 2 4.0
220+ a 0.0
221+ a 0.5
222+ b 4.0
212223 dtype: float64
213224
214225 Example 2: The function passed to `apply` takes a Series as
@@ -219,20 +230,7 @@ class providing the base-class of operations.
219230 >>> g.apply(lambda x: x.max() - x.min())
220231 a 1
221232 b 0
222- dtype: int64
223-
224- Notes
225- -----
226- In the current implementation `apply` calls `func` twice on the
227- first group to decide whether it can take a fast or slow code
228- path. This can lead to unexpected behavior if `func` has
229- side-effects, as they will take effect twice for the first
230- group.
231-
232- Examples
233- --------
234- {examples}
235- """ ,
233+ dtype: int64""" ,
236234}
237235
238236_groupby_agg_method_template = """
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