DOC: Add documentation for new melt() functionality.

Author: hoechenberger

doc/source/reshaping.rst

@@ -200,7 +200,9 @@ Reshaping by Melt
 The ``melt`` function found in ``pandas.core.reshape`` is useful to massage a
 DataFrame into a format where one or more columns are identifier variables,
 while all other columns, considered measured variables, are "pivoted" to the
-row axis, leaving just two non-identifier columns, "variable" and "value".
+row axis, leaving just two non-identifier columns, "variable" and "value". The
+names of those columns can be customized by supplying the ``var_name`` and
+``value_name`` parameters.
 
 For instance,
 
@@ -212,6 +214,7 @@ For instance,
                        'weight' : [130, 150]})
    cheese
    melt(cheese, id_vars=['first', 'last'])
+   melt(cheese, id_vars=['first', 'last'], var_name='quantity')
 
 Combining with stats and GroupBy
 --------------------------------

doc/source/v0.11.1.txt

@@ -138,6 +138,9 @@ Enhancements
        import os
        os.remove('mi.csv')
 
+  - ``pd.melt()`` now accepts the optional parameters ``var_name`` and ``value_name``
+    to specify custom column names of the returned DataFrame.
+
 Bug Fixes
 ~~~~~~~~~
 

pandas/core/reshape.py

@@ -609,8 +609,10 @@ def melt(frame, id_vars=None, value_vars=None,
     Parameters
     ----------
     frame : DataFrame
-    id_vars :
-    value_vars :
+    id_vars : tuple, list, or ndarray
+    value_vars : tuple, list, or ndarray
+    var_name : scalar
+    value_name : scalar
 
     Examples
     --------