DOC: update the DataFrame.reindex_like docstring

pandas/core/frame.py

@@ -3926,22 +3926,36 @@ def shift(self, periods=1, freq=None, axis=0):
     def set_index(self, keys, drop=True, append=False, inplace=False,
                   verify_integrity=False):
         """
+        Set the DataFrame index using existing columns.
+
         Set the DataFrame index (row labels) using one or more existing
-        columns. By default yields a new object.
+        columns. The index can replace the existing index or expand on it.
 
         Parameters
         ----------
-        keys : column label or list of column labels / arrays
-        drop : boolean, default True
-            Delete columns to be used as the new index
-        append : boolean, default False
-            Whether to append columns to existing index
-        inplace : boolean, default False
-            Modify the DataFrame in place (do not create a new object)
-        verify_integrity : boolean, default False
+        keys : label or list of label
+            Name or names of the columns that will be used as the index.
+        drop : bool, default True
+            Delete columns to be used as the new index.
+        append : bool, default False
+            Whether to append columns to existing index.
+        inplace : bool, default False
+            Modify the DataFrame in place (do not create a new object).
+        verify_integrity : bool, default False
             Check the new index for duplicates. Otherwise defer the check until
             necessary. Setting to False will improve the performance of this
-            method
+            method.
+
+        Returns
+        -------
+        DataFrame
+            Changed row labels.
+
+        See Also
+        --------
+        DataFrame.reset_index : Opposite of set_index.
+        DataFrame.reindex : Change to new indices or expand indices.
+        DataFrame.reindex_like : Change to same indices as other DataFrame.
 
         Returns
         -------
@@ -3951,22 +3965,23 @@ def set_index(self, keys, drop=True, append=False, inplace=False,
         --------
         >>> df = pd.DataFrame({'month': [1, 4, 7, 10],
         ...                    'year': [2012, 2014, 2013, 2014],
-        ...                    'sale':[55, 40, 84, 31]})
-           month  sale  year
-        0  1      55    2012
-        1  4      40    2014
-        2  7      84    2013
-        3  10     31    2014
+        ...                    'sale': [55, 40, 84, 31]})
+        >>> df
+           month  year  sale
+        0      1  2012    55
+        1      4  2014    40
+        2      7  2013    84
+        3     10  2014    31
 
         Set the index to become the 'month' column:
 
         >>> df.set_index('month')
-               sale  year
+               year  sale
         month
-        1      55    2012
-        4      40    2014
-        7      84    2013
-        10     31    2014
+        1      2012    55
+        4      2014    40
+        7      2013    84
+        10     2014    31
 
         Create a multi-index using columns 'year' and 'month':
 
@@ -4074,22 +4089,22 @@ def set_index(self, keys, drop=True, append=False, inplace=False,
     def reset_index(self, level=None, drop=False, inplace=False, col_level=0,
                     col_fill=''):
         """
-        For DataFrame with multi-level index, return new DataFrame with
-        labeling information in the columns under the index names, defaulting
-        to 'level_0', 'level_1', etc. if any are None. For a standard index,
-        the index name will be used (if set), otherwise a default 'index' or
-        'level_0' (if 'index' is already taken) will be used.
+        Reset the index, or a level of it.
+
+        Reset the index of the DataFrame, and use the default one instead.
+        If the DataFrame has a MultiIndex, this method can remove one or more
+        of them.
 
         Parameters
         ----------
         level : int, str, tuple, or list, default None
             Only remove the given levels from the index. Removes all levels by
-            default
-        drop : boolean, default False
+            default.
+        drop : bool, default False
             Do not try to insert index into dataframe columns. This resets
             the index to the default integer index.
-        inplace : boolean, default False
-            Modify the DataFrame in place (do not create a new object)
+        inplace : bool, default False
+            Modify the DataFrame in place (do not create a new object).
         col_level : int or str, default 0
             If the columns have multiple levels, determines which level the
             labels are inserted into. By default it is inserted into the first
@@ -4100,13 +4115,20 @@ def reset_index(self, level=None, drop=False, inplace=False, col_level=0,
 
         Returns
         -------
-        resetted : DataFrame
+        DataFrame
+            DataFrame with the new index.
+
+        See Also
+        --------
+        DataFrame.set_index : Opposite of reset_index.
+        DataFrame.reindex : Change to new indices or expand indices.
+        DataFrame.reindex_like : Change to same indices as other DataFrame.
 
         Examples
         --------
-        >>> df = pd.DataFrame([('bird',    389.0),
-        ...                    ('bird',     24.0),
-        ...                    ('mammal',   80.5),
+        >>> df = pd.DataFrame([('bird', 389.0),
+        ...                    ('bird', 24.0),
+        ...                    ('mammal', 80.5),
         ...                    ('mammal', np.nan)],
         ...                   index=['falcon', 'parrot', 'lion', 'monkey'],
         ...                   columns=('class', 'max_speed'))