diff --git a/pandas/core/groupby/groupby.py b/pandas/core/groupby/groupby.py index 3749ee26820dde..62883b6af30fd3 100644 --- a/pandas/core/groupby/groupby.py +++ b/pandas/core/groupby/groupby.py @@ -80,7 +80,8 @@ class providing the base-class of operations. See Also -------- Series.%(name)s : Apply a function %(name)s to a Series. - DataFrame.%(name)s : Apply a function %(name)s to each row or column of a DataFrame. + DataFrame.%(name)s : Apply a function %(name)s + to each row or column of a DataFrame. """ _apply_docs = dict( diff --git a/pandas/core/resample.py b/pandas/core/resample.py index 913dc7478718ee..a286443ef207aa 100644 --- a/pandas/core/resample.py +++ b/pandas/core/resample.py @@ -131,7 +131,7 @@ def __iter__(self): See Also -------- - GroupBy.__iter__ : Generator yielding sequence of (name, subset object) for each group + GroupBy.__iter__ : Generator yielding sequence for each group """ self._set_binner() return super().__iter__() @@ -235,9 +235,12 @@ def pipe(self, func, *args, **kwargs): """ See Also -------- - DataFrame.groupby.aggregate : Aggregate using callable, string, dict, or list of string/callables - DataFrame.resample.transform : Transforms the Series on each group based on the given function. - DataFrame.aggregate: Aggregate using one or more operations over the specified axis. + DataFrame.groupby.aggregate : + Aggregate using callable, string, dict, or list of string/callables + DataFrame.resample.transform : + Transforms the Series on each group based on the given function. + DataFrame.aggregate: + Aggregate using one or more operations over the specified axis. """ ) @@ -917,9 +920,11 @@ def quantile(self, q=0.5, **kwargs): Series.quantile Return a series, where the index is q and the values are the quantiles DataFrame.quantile - Return a DataFrame, where the columns are the columns of self, and the values are the quantiles. + Return a DataFrame, where the columns are the columns of self, + and the values are the quantiles. DataFrameGroupBy.quantile - Return a DataFrame, where the coulmns are groupby columns, and the values are its quantiles. + Return a DataFrame, where the coulmns are groupby columns, + and the values are its quantiles. """ return self._downsample("quantile", q=q, **kwargs)