Fix SS06 formatting errors (pandas-dev#29263)

Author: mcalingo

pandas/core/frame.py

@@ -5252,8 +5252,7 @@ def swaplevel(self, i=-2, j=-1, axis=0):
 
     def reorder_levels(self, order, axis=0):
         """
-        Rearrange index levels using input order. May not drop or
-        duplicate levels.
+        Rearrange index levels using input order. May not drop or duplicate levels.
 
         Parameters
         ----------
@@ -5855,9 +5854,10 @@ def pivot(self, index=None, columns=None, values=None):
     _shared_docs[
         "pivot_table"
     ] = """
-        Create a spreadsheet-style pivot table as a DataFrame. The levels in
-        the pivot table will be stored in MultiIndex objects (hierarchical
-        indexes) on the index and columns of the result DataFrame.
+        Create a spreadsheet-style pivot table as a DataFrame.
+
+        The levels in the pivot table will be stored in MultiIndex objects
+        (hierarchical indexes) on the index and columns of the result DataFrame.
 
         Parameters
         ----------%s
@@ -6250,8 +6250,9 @@ def explode(self, column: Union[str, Tuple]) -> "DataFrame":
 
     def unstack(self, level=-1, fill_value=None):
         """
-        Pivot a level of the (necessarily hierarchical) index labels, returning
-        a DataFrame having a new level of column labels whose inner-most level
+        Pivot a level of the (necessarily hierarchical) index labels.
+
+        Returns a DataFrame having a new level of column labels whose inner-most level
         consists of the pivoted index labels.
 
         If the index is not a MultiIndex, the output will be a Series
@@ -6313,8 +6314,7 @@ def unstack(self, level=-1, fill_value=None):
     _shared_docs[
         "melt"
     ] = """
-    Unpivot a DataFrame from wide format to long format, optionally
-    leaving identifier variables set.
+    Unpivot a DataFrame from wide to long format, optionally leaving identifiers set.
 
     This function is useful to massage a DataFrame into a format where one
     or more columns are identifier variables (`id_vars`), while all other
@@ -7910,6 +7910,7 @@ def nunique(self, axis=0, dropna=True):
     def idxmin(self, axis=0, skipna=True):
         """
         Return index of first occurrence of minimum over requested axis.
+
         NA/null values are excluded.
 
         Parameters
@@ -7947,6 +7948,7 @@ def idxmin(self, axis=0, skipna=True):
     def idxmax(self, axis=0, skipna=True):
         """
         Return index of first occurrence of maximum over requested axis.
+
         NA/null values are excluded.
 
         Parameters

pandas/core/generic.py

@@ -4353,8 +4353,9 @@ def sort_index(
 
     def reindex(self, *args, **kwargs):
         """
-        Conform %(klass)s to new index with optional filling logic, placing
-        NA/NaN in locations having no value in the previous index. A new object
+        Conform %(klass)s to new index with optional filling logic.
+
+        Places NA/NaN in locations having no value in the previous index. A new object
         is produced unless the new index is equivalent to the current one and
         ``copy=False``.
 
@@ -4669,8 +4670,7 @@ def _reindex_with_indexers(
 
     def filter(self, items=None, like=None, regex=None, axis=None):
         """
-        Subset rows or columns of dataframe according to labels in
-        the specified index.
+        Subset the dataframe rows or columns according to the specified index labels.
 
         Note that this routine does not filter a dataframe on its
         contents. The filter is applied to the labels of the index.
@@ -8497,8 +8497,7 @@ def resample(
 
     def first(self, offset):
         """
-        Convenience method for subsetting initial periods of time series data
-        based on a date offset.
+        Method to subset initial periods of time series data based on a date offset.
 
         Parameters
         ----------
@@ -8560,8 +8559,7 @@ def first(self, offset):
 
     def last(self, offset):
         """
-        Convenience method for subsetting final periods of time series data
-        based on a date offset.
+        Method to subset final periods of time series data based on a date offset.
 
         Parameters
         ----------