ENH: DataFrame.pivot accepts a list of values

doc/source/enhancingperf.rst

@@ -94,8 +94,7 @@ hence we'll concentrate our efforts cythonizing these two functions.
 Plain cython
 ~~~~~~~~~~~~
 
-First we're going to need to import the cython magic function to ipython (for
-cython versions  < 0.21 you can use ``%load_ext cythonmagic``):
+First we're going to need to import the cython magic function to ipython:
 
 .. ipython:: python
    :okwarning:

doc/source/install.rst

@@ -228,7 +228,7 @@ Optional Dependencies
 ~~~~~~~~~~~~~~~~~~~~~
 
 * `Cython <http://www.cython.org>`__: Only necessary to build development
-  version. Version 0.23 or higher.
+  version. Version 0.24 or higher.
 * `SciPy <http://www.scipy.org>`__: miscellaneous statistical functions, Version 0.14.0 or higher
 * `xarray <http://xarray.pydata.org>`__: pandas like handling for > 2 dims, needed for converting Panels to xarray objects. Version 0.7.0 or higher is recommended.
 * `PyTables <http://www.pytables.org>`__: necessary for HDF5-based storage. Version 3.0.0 or higher required, Version 3.2.1 or higher highly recommended.

doc/source/whatsnew/v0.22.0.txt

@@ -77,16 +77,13 @@ Other Enhancements
 - :func:`Series.fillna` now accepts a Series or a dict as a ``value`` for a categorical dtype (:issue:`17033`)
 - :func:`pandas.read_clipboard` updated to use qtpy, falling back to PyQt5 and then PyQt4, adding compatibility with Python3 and multiple python-qt bindings (:issue:`17722`)
 - Improved wording of ``ValueError`` raised in :func:`read_csv` when the ``usecols`` argument cannot match all columns. (:issue:`17301`)
+- :func:`DataFrame.pivot` now accepts a list of values (:issue:`17160`).
 
 .. _whatsnew_0220.api_breaking:
 
 Backwards incompatible API changes
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
-- :func:`Series.fillna` now raises a ``TypeError`` instead of a ``ValueError`` when passed a list, tuple or DataFrame as a ``value`` (:issue:`18293`)
-- :func:`pandas.DataFrame.merge` no longer casts a ``float`` column to ``object`` when merging on ``int`` and ``float`` columns (:issue:`16572`)
-- The default NA value for :class:`UInt64Index` has changed from 0 to ``NaN``, which impacts methods that mask with NA, such as ``UInt64Index.where()`` (:issue:`18398`)
-
 .. _whatsnew_0220.api_breaking.deps:
 
 Dependencies have increased minimum versions
@@ -104,8 +101,6 @@ If installed, we now require:
    +-----------------+-----------------+----------+
 
 
-
-
 .. _whatsnew_0220.api:
 
 Other API Changes
@@ -129,6 +124,10 @@ Other API Changes
 - :func:`DataFrame.from_items` provides a more informative error message when passed scalar values (:issue:`17312`)
 - When created with duplicate labels, ``MultiIndex`` now raises a ``ValueError``. (:issue:`17464`)
 - Building from source now explicity requires ``setuptools`` in ``setup.py`` (:issue:`18113`)
+- :func:`Series.fillna` now raises a ``TypeError`` instead of a ``ValueError`` when passed a list, tuple or DataFrame as a ``value`` (:issue:`18293`)
+- :func:`pandas.DataFrame.merge` no longer casts a ``float`` column to ``object`` when merging on ``int`` and ``float`` columns (:issue:`16572`)
+- The default NA value for :class:`UInt64Index` has changed from 0 to ``NaN``, which impacts methods that mask with NA, such as ``UInt64Index.where()`` (:issue:`18398`)
+- Building pandas for development now requires ``cython >= 0.24`` (:issue:`18613`)
 
 .. _whatsnew_0220.deprecations:
 

pandas/core/reshape/reshape.py

@@ -374,15 +374,17 @@ def pivot(self, index=None, columns=None, values=None):
         cols = [columns] if index is None else [index, columns]
         append = index is None
         indexed = self.set_index(cols, append=append)
-        return indexed.unstack(columns)
     else:
-        if index is None:
-            index = self.index
+        index = self.index if index is None else self[index]
+        index = MultiIndex.from_arrays([index, self[columns]])
+        if isinstance(values, list):
+            indexed = DataFrame(self[values].values,
+                                index=index,
+                                columns=values)
         else:
-            index = self[index]
-        indexed = Series(self[values].values,
-                         index=MultiIndex.from_arrays([index, self[columns]]))
-        return indexed.unstack(columns)
+            indexed = Series(self[values].values,
+                             index=index)
+    return indexed.unstack(columns)
 
 
 def pivot_simple(index, columns, values):

pandas/tests/reshape/test_pivot.py

@@ -353,6 +353,29 @@ def test_pivot_periods(self):
         pv = df.pivot(index='p1', columns='p2', values='data1')
         tm.assert_frame_equal(pv, expected)
 
+    def test_pivot_with_multi_values(self):
+        df = pd.DataFrame({'foo': ['one', 'one', 'one', 'two', 'two', 'two'],
+                           'bar': ['A', 'B', 'C', 'A', 'B', 'C'],
+                           'baz': [1, 2, 3, 4, 5, 6],
+                           'zoo': ['x', 'y', 'z', 'q', 'w', 't']})
+
+        results = df.pivot(index='zoo', columns='foo', values=['bar', 'baz'])
+
+        data = [[None, 'A', None, 4],
+                [None, 'C', None, 6],
+                [None, 'B', None, 5],
+                ['A', None, 1, None],
+                ['B', None, 2, None],
+                ['C', None, 3, None]]
+        index = Index(data=['q', 't', 'w', 'x', 'y', 'z'], name='zoo')
+        columns = MultiIndex(levels=[['bar', 'baz'], ['one', 'two']],
+                             labels=[[0, 0, 1, 1], [0, 1, 0, 1]],
+                             names=[None, 'foo'])
+        expected = DataFrame(data=data, index=index,
+                             columns=columns, dtype='object')
+
+        tm.assert_frame_equal(results, expected)
+
     def test_margins(self):
         def _check_output(result, values_col, index=['A', 'B'],
                           columns=['C'],