diff --git a/doc/source/comparison_with_r.rst b/doc/source/comparison_with_r.rst
index 7de0b85ede51f..84bba77e0dfa3 100644
--- a/doc/source/comparison_with_r.rst
+++ b/doc/source/comparison_with_r.rst
@@ -171,7 +171,7 @@ In ``pandas`` we may use :meth:`~pandas.pivot_table` method to handle this:
       'player': random.sample(list(string.ascii_lowercase),25),
       'batting avg': np.random.uniform(.200, .400, 25)
       })
-   baseball.pivot_table(values='batting avg', cols='team', aggfunc=np.max)
+   baseball.pivot_table(values='batting avg', columns='team', aggfunc=np.max)
 
 For more details and examples see :ref:`the reshaping documentation
 <reshaping.pivot>`.
@@ -402,8 +402,8 @@ In Python the best way is to make use of :meth:`~pandas.pivot_table`:
         'week': [1,2]*6
    })
    mdf = pd.melt(df, id_vars=['month', 'week'])
-   pd.pivot_table(mdf, values='value', rows=['variable','week'],
-                    cols=['month'], aggfunc=np.mean)
+   pd.pivot_table(mdf, values='value', index=['variable','week'],
+                    columns=['month'], aggfunc=np.mean)
 
 Similarly for ``dcast`` which uses a data.frame called ``df`` in R to
 aggregate information based on ``Animal`` and ``FeedType``:
@@ -433,7 +433,7 @@ using :meth:`~pandas.pivot_table`:
        'Amount': [10, 7, 4, 2, 5, 6, 2],
    })
 
-   df.pivot_table(values='Amount', rows='Animal', cols='FeedType', aggfunc='sum')
+   df.pivot_table(values='Amount', index='Animal', columns='FeedType', aggfunc='sum')
 
 The second approach is to use the :meth:`~pandas.DataFrame.groupby` method:
 
diff --git a/doc/source/release.rst b/doc/source/release.rst
index df0f472c390c7..6d7751266036b 100644
--- a/doc/source/release.rst
+++ b/doc/source/release.rst
@@ -129,11 +129,6 @@ API Changes
     ``DataFrame.stack`` operations where the name of the column index is used as
     the name of the inserted column containing the pivoted data.
 
-- The :func:`pivot_table`/:meth:`DataFrame.pivot_table` and :func:`crosstab` functions
-  now take arguments ``index`` and ``columns`` instead of ``rows`` and ``cols``.  A
-  ``FutureWarning`` is raised  to alert that the old ``rows`` and ``cols`` arguments
-  will not be supported in a future release (:issue:`5505`)
-
 - Allow specification of a more complex groupby, via ``pd.Grouper`` (:issue:`3794`)
 
 - A tuple passed to ``DataFame.sort_index`` will be interpreted as the levels of
@@ -149,6 +144,21 @@ API Changes
 Deprecations
 ~~~~~~~~~~~~
 
+- The :func:`pivot_table`/:meth:`DataFrame.pivot_table` and :func:`crosstab` functions
+  now take arguments ``index`` and ``columns`` instead of ``rows`` and ``cols``.  A
+  ``FutureWarning`` is raised  to alert that the old ``rows`` and ``cols`` arguments
+  will not be supported in a future release (:issue:`5505`)
+
+- The :meth:`DataFrame.drop_duplicates` and :meth:`DataFrame.duplicated` methods
+  now take argument ``subset`` instead of ``cols`` to better align with
+  :meth:`DataFrame.dropna`.  A ``FutureWarning`` is raised  to alert that the old
+  ``cols`` arguments will not be supported in a future release (:issue:`6680`)
+
+- The :meth:`DataFrame.to_csv` and :meth:`DataFrame.to_excel` functions
+  now takes argument ``columns`` instead of ``cols``.  A
+  ``FutureWarning`` is raised  to alert that the old ``cols`` arguments
+  will not be supported in a future release (:issue:`6645`)
+
 Prior Version Deprecations/Changes
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
diff --git a/doc/source/reshaping.rst b/doc/source/reshaping.rst
index 9aab5543aff92..274a2341c1a9f 100644
--- a/doc/source/reshaping.rst
+++ b/doc/source/reshaping.rst
@@ -283,9 +283,9 @@ We can produce pivot tables from this data very easily:
 
 .. ipython:: python
 
-   pivot_table(df, values='D', rows=['A', 'B'], cols=['C'])
-   pivot_table(df, values='D', rows=['B'], cols=['A', 'C'], aggfunc=np.sum)
-   pivot_table(df, values=['D','E'], rows=['B'], cols=['A', 'C'], aggfunc=np.sum)
+   pivot_table(df, values='D', index=['A', 'B'], columns=['C'])
+   pivot_table(df, values='D', index=['B'], columns=['A', 'C'], aggfunc=np.sum)
+   pivot_table(df, values=['D','E'], index=['B'], columns=['A', 'C'], aggfunc=np.sum)
 
 The result object is a DataFrame having potentially hierarchical indexes on the
 rows and columns. If the ``values`` column name is not given, the pivot table
@@ -294,14 +294,14 @@ hierarchy in the columns:
 
 .. ipython:: python
 
-   pivot_table(df, rows=['A', 'B'], cols=['C'])
+   pivot_table(df, index=['A', 'B'], columns=['C'])
 
 You can render a nice output of the table omitting the missing values by
 calling ``to_string`` if you wish:
 
 .. ipython:: python
 
-   table = pivot_table(df, rows=['A', 'B'], cols=['C'])
+   table = pivot_table(df, index=['A', 'B'], columns=['C'])
    print(table.to_string(na_rep=''))
 
 Note that ``pivot_table`` is also available as an instance method on DataFrame.
@@ -315,8 +315,8 @@ unless an array of values and an aggregation function are passed.
 
 It takes a number of arguments
 
-- ``rows``: array-like, values to group by in the rows
-- ``cols``: array-like, values to group by in the columns
+- ``index``: array-like, values to group by in the rows
+- ``columns``: array-like, values to group by in the columns
 - ``values``: array-like, optional, array of values to aggregate according to
   the factors
 - ``aggfunc``: function, optional, If no values array is passed, computes a
@@ -350,7 +350,7 @@ rows and columns:
 
 .. ipython:: python
 
-   df.pivot_table(rows=['A', 'B'], cols='C', margins=True, aggfunc=np.std)
+   df.pivot_table(index=['A', 'B'], columns='C', margins=True, aggfunc=np.std)
 
 .. _reshaping.tile:
 
diff --git a/doc/source/v0.14.0.txt b/doc/source/v0.14.0.txt
index a2990644fa124..d845d0511815c 100644
--- a/doc/source/v0.14.0.txt
+++ b/doc/source/v0.14.0.txt
@@ -173,11 +173,6 @@ These are out-of-bounds selections
     # New output, 4-level MultiIndex
     df_multi.set_index([df_multi.index, df_multi.index])
 
-- The :func:`pivot_table`/:meth:`DataFrame.pivot_table` and :func:`crosstab` functions
-  now take arguments ``index`` and ``columns`` instead of ``rows`` and ``cols``.  A
-  ``FutureWarning`` is raised  to alert that the old ``rows`` and ``cols`` arguments
-  will not be supported in a future release (:issue:`5505`)
-
 - Following keywords are now acceptable for :meth:`DataFrame.plot(kind='bar')` and :meth:`DataFrame.plot(kind='barh')`.
   - `width`: Specify the bar width. In previous versions, static value 0.5 was passed to matplotlib and it cannot be overwritten.
   - `position`: Specify relative alignments for bar plot layout. From 0 (left/bottom-end) to 1(right/top-end). Default is 0.5 (center). (:issue:`6604`)
@@ -313,8 +308,20 @@ Therse are prior version deprecations that are taking effect as of 0.14.0.
 
 Deprecations
 ~~~~~~~~~~~~
+- The :func:`pivot_table`/:meth:`DataFrame.pivot_table` and :func:`crosstab` functions
+  now take arguments ``index`` and ``columns`` instead of ``rows`` and ``cols``.  A
+  ``FutureWarning`` is raised  to alert that the old ``rows`` and ``cols`` arguments
+  will not be supported in a future release (:issue:`5505`)
+
+- The :meth:`DataFrame.drop_duplicates` and :meth:`DataFrame.duplicated` methods
+  now take argument ``subset`` instead of ``cols`` to better align with
+  :meth:`DataFrame.dropna`.  A ``FutureWarning`` is raised  to alert that the old
+  ``cols`` arguments will not be supported in a future release (:issue:`6680`)
 
-There are no deprecations of prior behavior in 0.14.0
+- The :meth:`DataFrame.to_csv` and :meth:`DataFrame.to_excel` functions
+  now takes argument ``columns`` instead of ``cols``.  A
+  ``FutureWarning`` is raised  to alert that the old ``cols`` arguments
+  will not be supported in a future release (:issue:`6645`)
 
 Enhancements
 ~~~~~~~~~~~~
diff --git a/pandas/core/frame.py b/pandas/core/frame.py
index 8cf164ba76c21..a410bb8be8c52 100644
--- a/pandas/core/frame.py
+++ b/pandas/core/frame.py
@@ -41,7 +41,8 @@
 from pandas.compat import(range, zip, lrange, lmap, lzip, StringIO, u,
                           OrderedDict, raise_with_traceback)
 from pandas import compat
-from pandas.util.decorators import deprecate, Appender, Substitution
+from pandas.util.decorators import deprecate, Appender, Substitution, \
+    deprecate_kwarg
 
 from pandas.tseries.period import PeriodIndex
 from pandas.tseries.index import DatetimeIndex
@@ -1067,8 +1068,9 @@ def to_panel(self):
 
     to_wide = deprecate('to_wide', to_panel)
 
+    @deprecate_kwarg(old_arg_name='cols', new_arg_name='columns')
     def to_csv(self, path_or_buf=None, sep=",", na_rep='', float_format=None,
-               cols=None, header=True, index=True, index_label=None,
+               columns=None, header=True, index=True, index_label=None,
                mode='w', nanRep=None, encoding=None, quoting=None,
                quotechar='"', line_terminator='\n', chunksize=None,
                tupleize_cols=False, date_format=None, doublequote=True,
@@ -1086,7 +1088,7 @@ def to_csv(self, path_or_buf=None, sep=",", na_rep='', float_format=None,
             Missing data representation
         float_format : string, default None
             Format string for floating point numbers
-        cols : sequence, optional
+        columns : sequence, optional
             Columns to write
         header : boolean or list of string, default True
             Write out column names. If a list of string is given it is assumed
@@ -1124,6 +1126,7 @@ def to_csv(self, path_or_buf=None, sep=",", na_rep='', float_format=None,
             or new (expanded format) if False)
         date_format : string, default None
             Format string for datetime objects
+        cols : kwarg only alias of columns [deprecated]
         """
         if nanRep is not None:  # pragma: no cover
             warnings.warn("nanRep is deprecated, use na_rep",
@@ -1134,7 +1137,7 @@ def to_csv(self, path_or_buf=None, sep=",", na_rep='', float_format=None,
                                      line_terminator=line_terminator,
                                      sep=sep, encoding=encoding,
                                      quoting=quoting, na_rep=na_rep,
-                                     float_format=float_format, cols=cols,
+                                     float_format=float_format, cols=columns,
                                      header=header, index=index,
                                      index_label=index_label, mode=mode,
                                      chunksize=chunksize, quotechar=quotechar,
@@ -1148,8 +1151,9 @@ def to_csv(self, path_or_buf=None, sep=",", na_rep='', float_format=None,
         if path_or_buf is None:
             return formatter.path_or_buf.getvalue()
 
+    @deprecate_kwarg(old_arg_name='cols', new_arg_name='columns')
     def to_excel(self, excel_writer, sheet_name='Sheet1', na_rep='',
-                 float_format=None, cols=None, header=True, index=True,
+                 float_format=None, columns=None, header=True, index=True,
                  index_label=None, startrow=0, startcol=0, engine=None,
                  merge_cells=True, encoding=None):
         """
@@ -1189,6 +1193,7 @@ def to_excel(self, excel_writer, sheet_name='Sheet1', na_rep='',
         encoding: string, default None
             encoding of the resulting excel file. Only necessary for xlwt,
             other writers support unicode natively.
+        cols : kwarg only alias of columns [deprecated]
 
         Notes
         -----
@@ -1202,6 +1207,7 @@ def to_excel(self, excel_writer, sheet_name='Sheet1', na_rep='',
         >>> writer.save()
         """
         from pandas.io.excel import ExcelWriter
+        
         need_save = False
         if encoding == None:
             encoding = 'ascii'
@@ -1212,7 +1218,7 @@ def to_excel(self, excel_writer, sheet_name='Sheet1', na_rep='',
 
         formatter = fmt.ExcelFormatter(self,
                                        na_rep=na_rep,
-                                       cols=cols,
+                                       cols=columns,
                                        header=header,
                                        float_format=float_format,
                                        index=index,
@@ -2439,27 +2445,28 @@ def dropna(self, axis=0, how='any', thresh=None, subset=None,
         else:
             return result
 
-    def drop_duplicates(self, cols=None, take_last=False, inplace=False):
+    @deprecate_kwarg(old_arg_name='cols', new_arg_name='subset')
+    def drop_duplicates(self, subset=None, take_last=False, inplace=False):
         """
         Return DataFrame with duplicate rows removed, optionally only
         considering certain columns
 
         Parameters
         ----------
-        cols : column label or sequence of labels, optional
+        subset : column label or sequence of labels, optional
             Only consider certain columns for identifying duplicates, by
             default use all of the columns
         take_last : boolean, default False
             Take the last observed row in a row. Defaults to the first row
         inplace : boolean, default False
             Whether to drop duplicates in place or to return a copy
+        cols : kwargs only argument of subset [deprecated]
 
         Returns
         -------
         deduplicated : DataFrame
         """
-
-        duplicated = self.duplicated(cols, take_last=take_last)
+        duplicated = self.duplicated(subset, take_last=take_last)
 
         if inplace:
             inds, = (-duplicated).nonzero()
@@ -2468,18 +2475,20 @@ def drop_duplicates(self, cols=None, take_last=False, inplace=False):
         else:
             return self[-duplicated]
 
-    def duplicated(self, cols=None, take_last=False):
+    @deprecate_kwarg(old_arg_name='cols', new_arg_name='subset')
+    def duplicated(self, subset=None, take_last=False):
         """
         Return boolean Series denoting duplicate rows, optionally only
         considering certain columns
 
         Parameters
         ----------
-        cols : column label or sequence of labels, optional
+        subset : column label or sequence of labels, optional
             Only consider certain columns for identifying duplicates, by
             default use all of the columns
         take_last : boolean, default False
             Take the last observed row in a row. Defaults to the first row
+        cols : kwargs only argument of subset [deprecated]
 
         Returns
         -------
@@ -2491,19 +2500,19 @@ def _m8_to_i8(x):
                 return x.view(np.int64)
             return x
 
-        if cols is None:
+        if subset is None:
             values = list(_m8_to_i8(self.values.T))
         else:
-            if np.iterable(cols) and not isinstance(cols, compat.string_types):
-                if isinstance(cols, tuple):
-                    if cols in self.columns:
-                        values = [self[cols].values]
+            if np.iterable(subset) and not isinstance(subset, compat.string_types):
+                if isinstance(subset, tuple):
+                    if subset in self.columns:
+                        values = [self[subset].values]
                     else:
-                        values = [_m8_to_i8(self[x].values) for x in cols]
+                        values = [_m8_to_i8(self[x].values) for x in subset]
                 else:
-                    values = [_m8_to_i8(self[x].values) for x in cols]
+                    values = [_m8_to_i8(self[x].values) for x in subset]
             else:
-                values = [self[cols].values]
+                values = [self[subset].values]
 
         keys = lib.fast_zip_fillna(values)
         duplicated = lib.duplicated(keys, take_last=take_last)
diff --git a/pandas/io/tests/test_excel.py b/pandas/io/tests/test_excel.py
index e1d168b66420f..8ba2a5dfc3d9c 100644
--- a/pandas/io/tests/test_excel.py
+++ b/pandas/io/tests/test_excel.py
@@ -396,6 +396,14 @@ def test_excel_sheet_by_name_raise(self):
 
             self.assertRaises(xlrd.XLRDError, xl.parse, '0')
 
+    def test_excel_deprecated_options(self):
+        with ensure_clean(self.ext) as path:
+            with tm.assert_produces_warning(FutureWarning):
+                self.frame.to_excel(path, 'test1', cols=['A', 'B'])
+    
+            with tm.assert_produces_warning(False):
+                self.frame.to_excel(path, 'test1', columns=['A', 'B'])
+
     def test_excelwriter_contextmanager(self):
         _skip_if_no_xlrd()
 
@@ -417,7 +425,7 @@ def test_roundtrip(self):
             self.frame['A'][:5] = nan
 
             self.frame.to_excel(path, 'test1')
-            self.frame.to_excel(path, 'test1', cols=['A', 'B'])
+            self.frame.to_excel(path, 'test1', columns=['A', 'B'])
             self.frame.to_excel(path, 'test1', header=False)
             self.frame.to_excel(path, 'test1', index=False)
 
@@ -479,7 +487,7 @@ def test_basics_with_nan(self):
         with ensure_clean(self.ext) as path:
             self.frame['A'][:5] = nan
             self.frame.to_excel(path, 'test1')
-            self.frame.to_excel(path, 'test1', cols=['A', 'B'])
+            self.frame.to_excel(path, 'test1', columns=['A', 'B'])
             self.frame.to_excel(path, 'test1', header=False)
             self.frame.to_excel(path, 'test1', index=False)
 
@@ -537,7 +545,7 @@ def test_sheets(self):
             self.frame['A'][:5] = nan
 
             self.frame.to_excel(path, 'test1')
-            self.frame.to_excel(path, 'test1', cols=['A', 'B'])
+            self.frame.to_excel(path, 'test1', columns=['A', 'B'])
             self.frame.to_excel(path, 'test1', header=False)
             self.frame.to_excel(path, 'test1', index=False)
 
@@ -562,7 +570,7 @@ def test_colaliases(self):
             self.frame['A'][:5] = nan
 
             self.frame.to_excel(path, 'test1')
-            self.frame.to_excel(path, 'test1', cols=['A', 'B'])
+            self.frame.to_excel(path, 'test1', columns=['A', 'B'])
             self.frame.to_excel(path, 'test1', header=False)
             self.frame.to_excel(path, 'test1', index=False)
 
@@ -583,7 +591,7 @@ def test_roundtrip_indexlabels(self):
             self.frame['A'][:5] = nan
 
             self.frame.to_excel(path, 'test1')
-            self.frame.to_excel(path, 'test1', cols=['A', 'B'])
+            self.frame.to_excel(path, 'test1', columns=['A', 'B'])
             self.frame.to_excel(path, 'test1', header=False)
             self.frame.to_excel(path, 'test1', index=False)
 
@@ -630,7 +638,7 @@ def test_roundtrip_indexlabels(self):
 
             self.frame.to_excel(path,
                                 'test1',
-                                cols=['A', 'B', 'C', 'D'],
+                                columns=['A', 'B', 'C', 'D'],
                                 index=False, merge_cells=self.merge_cells)
             # take 'A' and 'B' as indexes (same row as cols 'C', 'D')
             df = self.frame.copy()
@@ -733,7 +741,7 @@ def test_to_excel_multiindex(self):
 
         with ensure_clean(self.ext) as path:
             frame.to_excel(path, 'test1', header=False)
-            frame.to_excel(path, 'test1', cols=['A', 'B'])
+            frame.to_excel(path, 'test1', columns=['A', 'B'])
 
             # round trip
             frame.to_excel(path, 'test1', merge_cells=self.merge_cells)
@@ -1020,7 +1028,7 @@ def test_swapped_columns(self):
         with ensure_clean(self.ext) as path:
             write_frame = DataFrame({'A': [1, 1, 1],
                                      'B': [2, 2, 2]})
-            write_frame.to_excel(path, 'test1', cols=['B', 'A'])
+            write_frame.to_excel(path, 'test1', columns=['B', 'A'])
 
             read_frame = read_excel(path, 'test1', header=0)
 
diff --git a/pandas/tests/test_format.py b/pandas/tests/test_format.py
index 80234c9c81023..3ce65c81592a9 100644
--- a/pandas/tests/test_format.py
+++ b/pandas/tests/test_format.py
@@ -725,7 +725,7 @@ def test_to_html_regression_GH6098(self):
                            'données1': np.random.randn(5),
                            'données2': np.random.randn(5)})
         # it works
-        df.pivot_table(rows=[u('clé1')], cols=[u('clé2')])._repr_html_()
+        df.pivot_table(index=[u('clé1')], columns=[u('clé2')])._repr_html_()
 
     def test_nonunicode_nonascii_alignment(self):
         df = DataFrame([["aa\xc3\xa4\xc3\xa4", 1], ["bbbb", 2]])
diff --git a/pandas/tests/test_frame.py b/pandas/tests/test_frame.py
index 32805d47821f4..2101c732893e3 100644
--- a/pandas/tests/test_frame.py
+++ b/pandas/tests/test_frame.py
@@ -5439,6 +5439,13 @@ def test_to_csv_deprecated_options(self):
             self.tsframe.to_csv(path, nanRep='foo')
             recons = read_csv(path,index_col=0,parse_dates=[0],na_values=['foo'])
             assert_frame_equal(self.tsframe, recons)
+        
+        with tm.assert_produces_warning(FutureWarning):
+            self.frame.to_csv(path, cols=['A', 'B'])
+
+        with tm.assert_produces_warning(False):
+            self.frame.to_csv(path, columns=['A', 'B'])
+            
 
     def test_to_csv_from_csv(self):
 
@@ -5448,7 +5455,7 @@ def test_to_csv_from_csv(self):
              self.frame['A'][:5] = nan
 
              self.frame.to_csv(path)
-             self.frame.to_csv(path, cols=['A', 'B'])
+             self.frame.to_csv(path, columns=['A', 'B'])
              self.frame.to_csv(path, header=False)
              self.frame.to_csv(path, index=False)
 
@@ -5522,9 +5529,9 @@ def test_to_csv_cols_reordering(self):
 
         def _check_df(df,cols=None):
             with ensure_clean() as path:
-                df.to_csv(path,cols = cols,engine='python')
+                df.to_csv(path,columns = cols,engine='python')
                 rs_p = pd.read_csv(path,index_col=0)
-                df.to_csv(path,cols = cols,chunksize=chunksize)
+                df.to_csv(path,columns = cols,chunksize=chunksize)
                 rs_c = pd.read_csv(path,index_col=0)
 
             if cols:
@@ -5550,7 +5557,7 @@ def test_to_csv_new_dupe_cols(self):
         import pandas as pd
         def _check_df(df,cols=None):
             with ensure_clean() as path:
-                df.to_csv(path,cols = cols,chunksize=chunksize)
+                df.to_csv(path,columns = cols,chunksize=chunksize)
                 rs_c = pd.read_csv(path,index_col=0)
 
                 # we wrote them in a different order
@@ -5807,7 +5814,7 @@ def test_to_csv_multiindex(self):
         with ensure_clean(pname) as path:
 
              frame.to_csv(path, header=False)
-             frame.to_csv(path, cols=['A', 'B'])
+             frame.to_csv(path, columns=['A', 'B'])
 
              # round trip
              frame.to_csv(path)
@@ -5925,7 +5932,7 @@ def _make_frame(names=None):
 
             # write with cols
             with assertRaisesRegexp(TypeError, 'cannot specify cols with a MultiIndex'):
-                df.to_csv(path, tupleize_cols=False, cols=['foo', 'bar'])
+                df.to_csv(path, tupleize_cols=False, columns=['foo', 'bar'])
 
         with ensure_clean(pname) as path:
             # empty
@@ -6937,6 +6944,32 @@ def test_drop_duplicates(self):
         expected = df2.drop_duplicates(['AAA', 'B'], take_last=True)
         assert_frame_equal(result, expected)
 
+    def test_drop_duplicates_deprecated_warning(self):
+        df = DataFrame({'AAA': ['foo', 'bar', 'foo', 'bar',
+                                'foo', 'bar', 'bar', 'foo'],
+                        'B': ['one', 'one', 'two', 'two',
+                              'two', 'two', 'one', 'two'],
+                        'C': [1, 1, 2, 2, 2, 2, 1, 2],
+                        'D': lrange(8)})
+        expected = df[:2]
+
+        # Raises warning
+        with tm.assert_produces_warning(False):
+            result = df.drop_duplicates(subset='AAA')
+        assert_frame_equal(result, expected)
+
+        with tm.assert_produces_warning(FutureWarning):
+            result = df.drop_duplicates(cols='AAA')
+        assert_frame_equal(result, expected)
+
+        # Does not allow both subset and cols
+        self.assertRaises(TypeError, df.drop_duplicates,
+                          kwargs={'cols': 'AAA', 'subset': 'B'})
+
+        # Does not allow unknown kwargs
+        self.assertRaises(TypeError, df.drop_duplicates,
+                          kwargs={'subset': 'AAA', 'bad_arg': True})
+
     def test_drop_duplicates_tuple(self):
         df = DataFrame({('AA', 'AB'): ['foo', 'bar', 'foo', 'bar',
                                        'foo', 'bar', 'bar', 'foo'],
@@ -7062,6 +7095,29 @@ def test_drop_duplicates_inplace(self):
         result = df2
         assert_frame_equal(result, expected)
 
+    def test_duplicated_deprecated_warning(self):
+        df = DataFrame({'AAA': ['foo', 'bar', 'foo', 'bar',
+                                'foo', 'bar', 'bar', 'foo'],
+                        'B': ['one', 'one', 'two', 'two',
+                              'two', 'two', 'one', 'two'],
+                        'C': [1, 1, 2, 2, 2, 2, 1, 2],
+                        'D': lrange(8)})
+
+        # Raises warning
+        with tm.assert_produces_warning(False):
+            result = df.duplicated(subset='AAA')
+
+        with tm.assert_produces_warning(FutureWarning):
+            result = df.duplicated(cols='AAA')
+
+        # Does not allow both subset and cols
+        self.assertRaises(TypeError, df.duplicated,
+                          kwargs={'cols': 'AAA', 'subset': 'B'})
+
+        # Does not allow unknown kwargs
+        self.assertRaises(TypeError, df.duplicated,
+                          kwargs={'subset': 'AAA', 'bad_arg': True})
+
     def test_drop_col_still_multiindex(self):
         arrays = [['a', 'b', 'c', 'top'],
                   ['', '', '', 'OD'],
diff --git a/pandas/tools/pivot.py b/pandas/tools/pivot.py
index 59f1bf3453b1b..6c4f55ae8a3b5 100644
--- a/pandas/tools/pivot.py
+++ b/pandas/tools/pivot.py
@@ -7,13 +7,15 @@
 from pandas.tools.merge import concat
 from pandas.tools.util import cartesian_product
 from pandas.compat import range, lrange, zip
+from pandas.util.decorators import deprecate_kwarg
 from pandas import compat
 import pandas.core.common as com
 import numpy as np
 
-
+@deprecate_kwarg(old_arg_name='cols', new_arg_name='columns')
+@deprecate_kwarg(old_arg_name='rows', new_arg_name='index')
 def pivot_table(data, values=None, index=None, columns=None, aggfunc='mean',
-                fill_value=None, margins=False, dropna=True, **kwarg):
+                fill_value=None, margins=False, dropna=True):
     """
     Create a spreadsheet-style pivot table as a DataFrame. The levels in the
     pivot table will be stored in MultiIndex objects (hierarchical indexes) on
@@ -67,28 +69,6 @@ def pivot_table(data, values=None, index=None, columns=None, aggfunc='mean',
     -------
     table : DataFrame
     """
-    # Parse old-style keyword arguments
-    rows = kwarg.pop('rows', None)
-    if rows is not None:
-        warnings.warn("rows is deprecated, use index", FutureWarning)
-        if index is None:
-            index = rows
-        else:
-            msg = "Can only specify either 'rows' or 'index'"
-            raise TypeError(msg)
-
-    cols = kwarg.pop('cols', None)
-    if cols is not None:
-        warnings.warn("cols is deprecated, use columns", FutureWarning)
-        if columns is None:
-            columns = cols
-        else:
-            msg = "Can only specify either 'cols' or 'columns'"
-            raise TypeError(msg)
-    
-    if kwarg:
-        raise TypeError("Unexpected argument(s): %s" % kwarg.keys())
-    
     index = _convert_by(index)
     columns = _convert_by(columns)
 
@@ -324,9 +304,10 @@ def _convert_by(by):
         by = list(by)
     return by
 
-
+@deprecate_kwarg(old_arg_name='cols', new_arg_name='columns')
+@deprecate_kwarg(old_arg_name='rows', new_arg_name='index')
 def crosstab(index, columns, values=None, rownames=None, colnames=None,
-             aggfunc=None, margins=False, dropna=True, **kwarg):
+             aggfunc=None, margins=False, dropna=True):
     """
     Compute a simple cross-tabulation of two (or more) factors. By default
     computes a frequency table of the factors unless an array of values and an
@@ -381,27 +362,6 @@ def crosstab(index, columns, values=None, rownames=None, colnames=None,
     -------
     crosstab : DataFrame
     """
-    # Parse old-style keyword arguments
-    rows = kwarg.pop('rows', None)
-    if rows is not None:
-        warnings.warn("rows is deprecated, use index", FutureWarning)
-        if index is None:
-            index = rows
-        else:
-            msg = "Can only specify either 'rows' or 'index'"
-            raise TypeError(msg)
-
-    cols = kwarg.pop('cols', None)
-    if cols is not None:
-        warnings.warn("cols is deprecated, use columns", FutureWarning)
-        if columns is None:
-            columns = cols
-        else:
-            msg = "Can only specify either 'cols' or 'columns'"
-            raise TypeError(msg)
-
-    if kwarg:
-        raise TypeError("Unexpected argument(s): %s" % kwarg.keys())
 
     index = com._maybe_make_list(index)
     columns = com._maybe_make_list(columns)
diff --git a/pandas/tools/tests/test_pivot.py b/pandas/tools/tests/test_pivot.py
index 12f0ffa6e8aa5..2255fdebc9fe3 100644
--- a/pandas/tools/tests/test_pivot.py
+++ b/pandas/tools/tests/test_pivot.py
@@ -430,7 +430,7 @@ def test_crosstab_pass_values(self):
 
         df = DataFrame({'foo': a, 'bar': b, 'baz': c, 'values': values})
 
-        expected = df.pivot_table('values', index=['foo', 'bar'], cols='baz',
+        expected = df.pivot_table('values', index=['foo', 'bar'], columns='baz',
                                   aggfunc=np.sum)
         tm.assert_frame_equal(table, expected)
 
diff --git a/pandas/util/decorators.py b/pandas/util/decorators.py
index 56a90b9ba1d17..476a643b34ff7 100644
--- a/pandas/util/decorators.py
+++ b/pandas/util/decorators.py
@@ -2,6 +2,7 @@
 from pandas.lib import cache_readonly
 import sys
 import warnings
+from functools import wraps
 
 
 def deprecate(name, alternative, alt_name=None):
@@ -13,6 +14,54 @@ def wrapper(*args, **kwargs):
         return alternative(*args, **kwargs)
     return wrapper
 
+
+def deprecate_kwarg(old_arg_name, new_arg_name):
+    """Decorator to deprecate a keyword argument of a function
+
+    Parameters
+    ----------
+    old_arg_name : str
+        Name of argument in function to deprecate
+    new_arg_name : str
+        Name of prefered argument in function
+
+    Examples
+    --------
+    The following deprecates 'cols', using 'columns' instead
+
+    >>> @deprecate_kwarg(old_arg_name='cols', new_arg_name='columns')
+    ... def f(columns=''):
+    ...     print columns
+    ...
+    >>> f(columns='should work ok')
+    should work ok
+    >>> f(cols='should raise warning')
+    FutureWarning: cols is deprecated, use columns instead
+      warnings.warn(msg, FutureWarning)
+    should raise warning
+    >>> f(cols='should error', columns="can't pass do both")
+    TypeError: Can only specify 'cols' or 'columns', not both
+
+    """
+    def _deprecate_kwarg(func):
+        @wraps(func)
+        def wrapper(*args, **kwargs):
+            old_arg_value = kwargs.pop(old_arg_name, None)
+            if old_arg_value is not None:
+                msg = "%s is deprecated, use %s instead" % \
+                      (old_arg_name, new_arg_name)
+                warnings.warn(msg, FutureWarning)
+                if kwargs.get(new_arg_name, None) is not None:
+                    msg = "Can only specify '%s' or '%s', not both" % \
+                      (old_arg_name, new_arg_name)
+                    raise TypeError(msg)
+                else:
+                    kwargs[new_arg_name] = old_arg_value
+            return func(*args, **kwargs)
+        return wrapper
+    return _deprecate_kwarg
+
+
 # Substitution and Appender are derived from matplotlib.docstring (1.1.0)
 # module http://matplotlib.sourceforge.net/users/license.html