Fixed SA04 errors in docstrings (pandas-dev pandas-dev#28792)

Author: suparnasnair

pandas/core/resample.py

@@ -119,7 +119,7 @@ def __iter__(self):
 
         See Also
         --------
-        GroupBy.__iter__
+        GroupBy.__iter__ : Groupby iterator.
         """
         self._set_binner()
         return super().__iter__()
@@ -224,9 +224,10 @@ def pipe(self, func, *args, **kwargs):
         """
     See Also
     --------
-    DataFrame.groupby.aggregate
-    DataFrame.resample.transform
-    DataFrame.aggregate
+    DataFrame.groupby.aggregate : Aggregate using callable, string, dict, or list of string/callables
+    DataFrame.resample.transform : Call function producing a like-indexed Series on each group and return a
+        Series with the transformed values.
+    DataFrame.aggregate : Aggregate using one or more operations over the specified axis.
     """
     )
 
@@ -432,8 +433,8 @@ def pad(self, limit=None):
 
         See Also
         --------
-        Series.fillna
-        DataFrame.fillna
+        Series.fillna : Fill NA/NaN values using the specified method in a Series.
+        DataFrame.fillna : Fill NA/NaN values using the specified method in a DataFrame.
         """
         return self._upsample("pad", limit=limit)
 
@@ -812,8 +813,8 @@ def asfreq(self, fill_value=None):
 
         See Also
         --------
-        Series.asfreq
-        DataFrame.asfreq
+        Series.asfreq : Convert TimeSeries to specified frequency in a Series.
+        DataFrame.asfreq : Convert TimeSeries to specified frequency in a DataFrame.
         """
         return self._upsample("asfreq", fill_value=fill_value)
 
@@ -879,9 +880,9 @@ def quantile(self, q=0.5, **kwargs):
 
         See Also
         --------
-        Series.quantile
-        DataFrame.quantile
-        DataFrameGroupBy.quantile
+        Series.quantile : Return value at the given quantile.
+        DataFrame.quantile : Return values at the given quantile over requested axis.
+        DataFrameGroupBy.quantile : Return group values at the given quantile, a la numpy.percentile.
         """
         return self._downsample("quantile", q=q, **kwargs)