CLN: Removed SparsePanel

doc/source/sparse.rst

@@ -15,13 +15,15 @@
 Sparse data structures
 **********************
 
-We have implemented "sparse" versions of Series, DataFrame, and Panel. These
-are not sparse in the typical "mostly 0". You can view these objects as being
-"compressed" where any data matching a specific value (NaN/missing by default,
-though any value can be chosen) is omitted. A special ``SparseIndex`` object
-tracks where data has been "sparsified". This will make much more sense in an
-example. All of the standard pandas data structures have a ``to_sparse``
-method:
+.. note:: The ``SparsePanel`` class has been removed in 0.19.0
+
+We have implemented "sparse" versions of Series and DataFrame (there used to be
+one for Panel but was removed in 0.19.0). These are not sparse in the typical
+"mostly 0". You can view these objects as being "compressed" where any data matching
+a specific value (NaN/missing by default, though any value can be chosen) is omitted.
+A special ``SparseIndex`` object tracks where data has been "sparsified". This will
+make much more sense in an example. All of the standard pandas data structures have
+a ``to_sparse`` method:
 
 .. ipython:: python
 
@@ -77,9 +79,8 @@ distinct from the ``fill_value``:
    sparr = pd.SparseArray(arr)
    sparr
 
-Like the indexed objects (SparseSeries, SparseDataFrame, SparsePanel), a
-``SparseArray`` can be converted back to a regular ndarray by calling
-``to_dense``:
+Like the indexed objects (SparseSeries, SparseDataFrame), a ``SparseArray``
+can be converted back to a regular ndarray by calling ``to_dense``:
 
 .. ipython:: python
 

doc/source/whatsnew/v0.19.0.txt

@@ -330,6 +330,7 @@ API changes
 ~~~~~~~~~~~
 
 
+- ``Panel.to_sparse`` will raise a ``NotImplementedError`` exception when called (:issue:`13778`)
 - ``Index.reshape`` will raise a ``NotImplementedError`` exception when called (:issue:`12882`)
 - Non-convertible dates in an excel date column will be returned without conversion and the column will be ``object`` dtype, rather than raising an exception  (:issue:`10001`)
 - ``eval``'s upcasting rules for ``float32`` types have been updated to be more consistent with NumPy's rules.  New behavior will not upcast to ``float64`` if you multiply a pandas ``float32`` object by a scalar float64. (:issue:`12388`)
@@ -619,6 +620,7 @@ Deprecations
 
 Removal of prior version deprecations/changes
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+- The ``SparsePanel`` class has been removed (:issue:`13778`)
 - The ``pd.sandbox`` module has been removed in favor of the external library ``pandas-qt`` (:issue:`13670`)
 - The ``pandas.io.data`` and ``pandas.io.wb`` modules are removed in favor of
   the `pandas-datareader package <https://github.com/pydata/pandas-datareader>`__ (:issue:`13724`).

pandas/api/tests/test_api.py

@@ -57,7 +57,7 @@ class TestPDApi(Base, tm.TestCase):
                'TimedeltaIndex', 'Timestamp']
 
     # these are already deprecated; awaiting removal
-    deprecated_classes = ['SparsePanel', 'TimeSeries', 'WidePanel',
+    deprecated_classes = ['TimeSeries', 'WidePanel',
                           'SparseTimeSeries', 'Panel4D']
 
     # these should be deperecated in the future

pandas/core/panel.py

@@ -393,25 +393,15 @@ def _get_plane_axes(self, axis):
 
     fromDict = from_dict
 
-    def to_sparse(self, fill_value=None, kind='block'):
+    def to_sparse(self, *args, **kwargs):
         """
-        Convert to SparsePanel
-
-        Parameters
-        ----------
-        fill_value : float, default NaN
-        kind : {'block', 'integer'}
+        NOT IMPLEMENTED: do not call this method, as sparsifying is not
+        supported for Panel objects and will raise an error.
 
-        Returns
-        -------
-        y : SparseDataFrame
+        Convert to SparsePanel
         """
-        from pandas.core.sparse import SparsePanel
-        frames = dict(self.iteritems())
-        return SparsePanel(frames, items=self.items,
-                           major_axis=self.major_axis,
-                           minor_axis=self.minor_axis, default_kind=kind,
-                           default_fill_value=fill_value)
+        raise NotImplementedError("sparsifying is not supported "
+                                  "for Panel objects")
 
     def to_excel(self, path, na_rep='', engine=None, **kwargs):
         """

pandas/core/sparse.py

@@ -8,4 +8,3 @@
 
 from pandas.sparse.series import SparseSeries
 from pandas.sparse.frame import SparseDataFrame
-from pandas.sparse.panel import SparsePanel

pandas/io/packers.py

@@ -56,7 +56,7 @@
                     Panel, RangeIndex, PeriodIndex, DatetimeIndex, NaT,
                     Categorical)
 from pandas.tslib import NaTType
-from pandas.sparse.api import SparseSeries, SparseDataFrame, SparsePanel
+from pandas.sparse.api import SparseSeries, SparseDataFrame
 from pandas.sparse.array import BlockIndex, IntIndex
 from pandas.core.generic import NDFrame
 from pandas.core.common import PerformanceWarning
@@ -447,18 +447,6 @@ def encode(obj):
             # d['data'] = dict([(name, ss)
             #                 for name, ss in compat.iteritems(obj)])
             # return d
-        elif isinstance(obj, SparsePanel):
-            raise NotImplementedError(
-                'msgpack sparse frame is not implemented'
-            )
-            # d = {'typ': 'sparse_panel',
-            #     'klass': obj.__class__.__name__,
-            #     'items': obj.items}
-            # for f in ['default_fill_value', 'default_kind']:
-            #    d[f] = getattr(obj, f, None)
-            # d['data'] = dict([(name, df)
-            #                 for name, df in compat.iteritems(obj)])
-            # return d
         else:
 
             data = obj._data

pandas/io/pytables.py

@@ -29,7 +29,7 @@
                     MultiIndex, Int64Index, isnull)
 from pandas.core import config
 from pandas.io.common import _stringify_path
-from pandas.sparse.api import SparseSeries, SparseDataFrame, SparsePanel
+from pandas.sparse.api import SparseSeries, SparseDataFrame
 from pandas.sparse.array import BlockIndex, IntIndex
 from pandas.tseries.api import PeriodIndex, DatetimeIndex
 from pandas.tseries.tdi import TimedeltaIndex
@@ -169,7 +169,6 @@ class DuplicateWarning(Warning):
     SparseDataFrame: u('sparse_frame'),
     Panel: u('wide'),
     Panel4D: u('ndim'),
-    SparsePanel: u('sparse_panel')
 }
 
 # storer class map
@@ -183,7 +182,6 @@ class DuplicateWarning(Warning):
     u('frame'): 'FrameFixed',
     u('sparse_frame'): 'SparseFrameFixed',
     u('wide'): 'PanelFixed',
-    u('sparse_panel'): 'SparsePanelFixed',
 }
 
 # table class map
@@ -2777,39 +2775,6 @@ def write(self, obj, **kwargs):
         self.write_index('columns', obj.columns)
 
 
-class SparsePanelFixed(SparseFixed):
-    pandas_kind = u('sparse_panel')
-    attributes = ['default_kind', 'default_fill_value']
-
-    def read(self, **kwargs):
-        kwargs = self.validate_read(kwargs)
-        items = self.read_index('items')
-
-        sdict = {}
-        for name in items:
-            key = 'sparse_frame_%s' % name
-            s = SparseFrameFixed(self.parent, getattr(self.group, key))
-            s.infer_axes()
-            sdict[name] = s.read()
-        return SparsePanel(sdict, items=items, default_kind=self.default_kind,
-                           default_fill_value=self.default_fill_value)
-
-    def write(self, obj, **kwargs):
-        super(SparsePanelFixed, self).write(obj, **kwargs)
-        self.attrs.default_fill_value = obj.default_fill_value
-        self.attrs.default_kind = obj.default_kind
-        self.write_index('items', obj.items)
-
-        for name, sdf in obj.iteritems():
-            key = 'sparse_frame_%s' % name
-            if key not in self.group._v_children:
-                node = self._handle.create_group(self.group, key)
-            else:
-                node = getattr(self.group, key)
-            s = SparseFrameFixed(self.parent, node)
-            s.write(sdf)
-
-
 class BlockManagerFixed(GenericFixed):
     attributes = ['ndim', 'nblocks']
     is_shape_reversed = False

pandas/io/tests/test_packers.py

@@ -542,26 +542,6 @@ def test_sparse_frame(self):
         self._check_roundtrip(ss3, tm.assert_frame_equal,
                               check_frame_type=True)
 
-    def test_sparse_panel(self):
-
-        with tm.assert_produces_warning(FutureWarning,
-                                        check_stacklevel=False):
-
-            items = ['x', 'y', 'z']
-            p = Panel(dict((i, tm.makeDataFrame().ix[:2, :2]) for i in items))
-            sp = p.to_sparse()
-
-            self._check_roundtrip(sp, tm.assert_panel_equal,
-                                  check_panel_type=True)
-
-            sp2 = p.to_sparse(kind='integer')
-            self._check_roundtrip(sp2, tm.assert_panel_equal,
-                                  check_panel_type=True)
-
-            sp3 = p.to_sparse(fill_value=0)
-            self._check_roundtrip(sp3, tm.assert_panel_equal,
-                                  check_panel_type=True)
-
 
 class TestCompression(TestPackers):
     """See https://github.com/pydata/pandas/pull/9783

pandas/io/tests/test_pytables.py

@@ -2688,23 +2688,6 @@ def test_sparse_frame(self):
         self._check_double_roundtrip(ss3, tm.assert_frame_equal,
                                      check_frame_type=True)
 
-    def test_sparse_panel(self):
-
-        items = ['x', 'y', 'z']
-        p = Panel(dict((i, tm.makeDataFrame().ix[:2, :2]) for i in items))
-        sp = p.to_sparse()
-
-        self._check_double_roundtrip(sp, assert_panel_equal,
-                                     check_panel_type=True)
-
-        sp2 = p.to_sparse(kind='integer')
-        self._check_double_roundtrip(sp2, assert_panel_equal,
-                                     check_panel_type=True)
-
-        sp3 = p.to_sparse(fill_value=0)
-        self._check_double_roundtrip(sp3, assert_panel_equal,
-                                     check_panel_type=True)
-
     def test_float_index(self):
 
         # GH #454

pandas/sparse/api.py

@@ -4,4 +4,3 @@
 from pandas.sparse.list import SparseList
 from pandas.sparse.series import SparseSeries, SparseTimeSeries
 from pandas.sparse.frame import SparseDataFrame
-from pandas.sparse.panel import SparsePanel