TST/CLN: Remove more Panel tests

pandas/tests/api/test_api.py

@@ -53,10 +53,10 @@ class TestPDApi(Base):
                ]
 
     # these are already deprecated; awaiting removal
-    deprecated_classes = ['TimeGrouper']
+    deprecated_classes = ['TimeGrouper', 'Panel']
 
     # these should be deprecated in the future
-    deprecated_classes_in_future = ['Panel']
+    deprecated_classes_in_future = []
 
     # external modules exposed in pandas namespace
     modules = ['np', 'datetime']

pandas/tests/computation/test_eval.py

@@ -14,7 +14,7 @@
 from pandas.core.dtypes.common import is_bool, is_list_like, is_scalar
 
 import pandas as pd
-from pandas import DataFrame, Panel, Series, date_range
+from pandas import DataFrame, Series, date_range
 from pandas.core.computation import pytables
 from pandas.core.computation.check import _NUMEXPR_VERSION
 from pandas.core.computation.engines import NumExprClobberingError, _engines
@@ -1112,14 +1112,6 @@ def test_bool_ops_with_constants(self):
             exp = eval(ex)
             assert res == exp
 
-    @pytest.mark.filterwarnings("ignore::FutureWarning")
-    def test_panel_fails(self):
-        x = Panel(randn(3, 4, 5))
-        y = Series(randn(10))
-        with pytest.raises(NotImplementedError):
-            self.eval('x + y',
-                      local_dict={'x': x, 'y': y})
-
     def test_4d_ndarray_fails(self):
         x = randn(3, 4, 5, 6)
         y = Series(randn(10))

pandas/tests/dtypes/test_inference.py

@@ -11,7 +11,6 @@
 from fractions import Fraction
 from numbers import Number
 import re
-from warnings import catch_warnings, simplefilter
 
 import numpy as np
 import pytest
@@ -30,8 +29,8 @@
 
 import pandas as pd
 from pandas import (
-    Categorical, DataFrame, DateOffset, DatetimeIndex, Index, Interval, Panel,
-    Period, Series, Timedelta, TimedeltaIndex, Timestamp, compat, isna)
+    Categorical, DataFrame, DateOffset, DatetimeIndex, Index, Interval, Period,
+    Series, Timedelta, TimedeltaIndex, Timestamp, compat, isna)
 from pandas.util import testing as tm
 
 
@@ -1305,10 +1304,6 @@ def test_is_scalar_pandas_containers(self):
         assert not is_scalar(Series([1]))
         assert not is_scalar(DataFrame())
         assert not is_scalar(DataFrame([[1]]))
-        with catch_warnings(record=True):
-            simplefilter("ignore", FutureWarning)
-            assert not is_scalar(Panel())
-            assert not is_scalar(Panel([[[1]]]))
         assert not is_scalar(Index([]))
         assert not is_scalar(Index([1]))
 

pandas/tests/generic/test_generic.py

@@ -2,7 +2,6 @@
 # pylint: disable-msg=E1101,W0612
 
 from copy import copy, deepcopy
-from warnings import catch_warnings, simplefilter
 
 import numpy as np
 import pytest
@@ -12,7 +11,7 @@
 from pandas.core.dtypes.common import is_scalar
 
 import pandas as pd
-from pandas import DataFrame, MultiIndex, Panel, Series, date_range
+from pandas import DataFrame, MultiIndex, Series, date_range
 import pandas.util.testing as tm
 from pandas.util.testing import assert_frame_equal, assert_series_equal
 
@@ -238,12 +237,6 @@ def test_metadata_propagation(self):
         o2 = self._construct(shape=3)
         o2.name = 'bar'
 
-        # TODO
-        # Once panel can do non-trivial combine operations
-        # (currently there is an a raise in the Panel arith_ops to prevent
-        # this, though it actually does work)
-        # can remove all of these try: except: blocks on the actual operations
-
         # ----------
         # preserving
         # ----------
@@ -255,63 +248,37 @@ def test_metadata_propagation(self):
 
         # ops with like
         for op in ['__add__', '__sub__', '__truediv__', '__mul__']:
-            try:
-                result = getattr(o, op)(o)
-                self.check_metadata(o, result)
-            except (ValueError, AttributeError):
-                pass
+            result = getattr(o, op)(o)
+            self.check_metadata(o, result)
 
         # simple boolean
         for op in ['__eq__', '__le__', '__ge__']:
             v1 = getattr(o, op)(o)
             self.check_metadata(o, v1)
-
-            try:
-                self.check_metadata(o, v1 & v1)
-            except (ValueError):
-                pass
-
-            try:
-                self.check_metadata(o, v1 | v1)
-            except (ValueError):
-                pass
+            self.check_metadata(o, v1 & v1)
+            self.check_metadata(o, v1 | v1)
 
         # combine_first
-        try:
-            result = o.combine_first(o2)
-            self.check_metadata(o, result)
-        except (AttributeError):
-            pass
+        result = o.combine_first(o2)
+        self.check_metadata(o, result)
 
         # ---------------------------
         # non-preserving (by default)
         # ---------------------------
 
         # add non-like
-        try:
-            result = o + o2
-            self.check_metadata(result)
-        except (ValueError, AttributeError):
-            pass
+        result = o + o2
+        self.check_metadata(result)
 
         # simple boolean
         for op in ['__eq__', '__le__', '__ge__']:
 
             # this is a name matching op
             v1 = getattr(o, op)(o)
-
             v2 = getattr(o, op)(o2)
             self.check_metadata(v2)
-
-            try:
-                self.check_metadata(v1 & v2)
-            except (ValueError):
-                pass
-
-            try:
-                self.check_metadata(v1 | v2)
-            except (ValueError):
-                pass
+            self.check_metadata(v1 & v2)
+            self.check_metadata(v1 | v2)
 
     def test_head_tail(self):
         # GH5370
@@ -325,12 +292,7 @@ def test_head_tail(self):
             axis = o._get_axis_name(0)
             setattr(o, axis, index(len(getattr(o, axis))))
 
-            # Panel + dims
-            try:
-                o.head()
-            except (NotImplementedError):
-                pytest.skip('not implemented on {0}'.format(
-                    o.__class__.__name__))
+            o.head()
 
             self._compare(o.head(), o.iloc[:5])
             self._compare(o.tail(), o.iloc[-5:])
@@ -639,19 +601,12 @@ def test_sample(sel):
         sample1 = df.sample(n=1, weights='easyweights')
         assert_frame_equal(sample1, df.iloc[5:6])
 
-        # Ensure proper error if string given as weight for Series, panel, or
+        # Ensure proper error if string given as weight for Series or
         # DataFrame with axis = 1.
         s = Series(range(10))
         with pytest.raises(ValueError):
             s.sample(n=3, weights='weight_column')
 
-        with catch_warnings(record=True):
-            simplefilter("ignore", FutureWarning)
-            panel = Panel(items=[0, 1, 2], major_axis=[2, 3, 4],
-                          minor_axis=[3, 4, 5])
-            with pytest.raises(ValueError):
-                panel.sample(n=1, weights='weight_column')
-
         with pytest.raises(ValueError):
             df.sample(n=1, weights='weight_column', axis=1)
 
@@ -754,12 +709,9 @@ def test_squeeze(self):
         # don't fail with 0 length dimensions GH11229 & GH8999
         empty_series = Series([], name='five')
         empty_frame = DataFrame([empty_series])
-        with catch_warnings(record=True):
-            simplefilter("ignore", FutureWarning)
-            empty_panel = Panel({'six': empty_frame})
 
         [tm.assert_series_equal(empty_series, higher_dim.squeeze())
-         for higher_dim in [empty_series, empty_frame, empty_panel]]
+         for higher_dim in [empty_series, empty_frame]]
 
         # axis argument
         df = tm.makeTimeDataFrame(nper=1).iloc[:, :1]

pandas/tests/generic/test_label_or_level_utils.py

@@ -3,7 +3,6 @@
 from pandas.core.dtypes.missing import array_equivalent
 
 import pandas as pd
-import pandas.util.testing as tm
 
 
 # Fixtures
@@ -46,13 +45,6 @@ def df_duplabels(df):
     return df
 
 
-@pytest.fixture
-def panel():
-    with tm.assert_produces_warning(FutureWarning,
-                                    check_stacklevel=False):
-        return pd.Panel()
-
-
 # Test is label/level reference
 # =============================
 def get_labels_levels(df_levels):
@@ -134,32 +126,6 @@ def test_is_level_reference_series_axis1_error(df):
         s._is_level_reference('L1', axis=1)
 
 
-# Panel
-# -----
-def test_is_level_reference_panel_error(panel):
-    msg = ("_is_level_reference is not implemented for {type}"
-           .format(type=type(panel)))
-
-    with pytest.raises(NotImplementedError, match=msg):
-        panel._is_level_reference('L1', axis=0)
-
-
-def test_is_label_reference_panel_error(panel):
-    msg = ("_is_label_reference is not implemented for {type}"
-           .format(type=type(panel)))
-
-    with pytest.raises(NotImplementedError, match=msg):
-        panel._is_label_reference('L1', axis=0)
-
-
-def test_is_label_or_level_reference_panel_error(panel):
-    msg = ("_is_label_or_level_reference is not implemented for {type}"
-           .format(type=type(panel)))
-
-    with pytest.raises(NotImplementedError, match=msg):
-        panel._is_label_or_level_reference('L1', axis=0)
-
-
 # Test _check_label_or_level_ambiguity_df
 # =======================================
 
@@ -215,16 +181,6 @@ def test_check_label_or_level_ambiguity_series_axis1_error(df):
         s._check_label_or_level_ambiguity('L1', axis=1)
 
 
-# Panel
-# -----
-def test_check_label_or_level_ambiguity_panel_error(panel):
-    msg = ("_check_label_or_level_ambiguity is not implemented for {type}"
-           .format(type=type(panel)))
-
-    with pytest.raises(NotImplementedError, match=msg):
-        panel._check_label_or_level_ambiguity("L1", axis=0)
-
-
 # Test _get_label_or_level_values
 # ===============================
 def assert_label_values(frame, labels, axis):
@@ -322,16 +278,6 @@ def test_get_label_or_level_values_series_axis1_error(df):
         s._get_label_or_level_values('L1', axis=1)
 
 
-# Panel
-# -----
-def test_get_label_or_level_values_panel_error(panel):
-    msg = ("_get_label_or_level_values is not implemented for {type}"
-           .format(type=type(panel)))
-
-    with pytest.raises(NotImplementedError, match=msg):
-        panel._get_label_or_level_values('L1', axis=0)
-
-
 # Test _drop_labels_or_levels
 # ===========================
 def assert_labels_dropped(frame, labels, axis):
@@ -394,13 +340,3 @@ def test_drop_labels_or_levels_series(df):
 
     with pytest.raises(ValueError, match="not valid labels or levels"):
         s._drop_labels_or_levels('L4', axis=0)
-
-
-# Panel
-# -----
-def test_drop_labels_or_levels_panel_error(panel):
-    msg = ("_drop_labels_or_levels is not implemented for {type}"
-           .format(type=type(panel)))
-
-    with pytest.raises(NotImplementedError, match=msg):
-        panel._drop_labels_or_levels('L1', axis=0)

pandas/tests/indexing/test_iloc.py

@@ -217,7 +217,6 @@ def test_iloc_getitem_neg_int_can_reach_first_index(self):
 
     def test_iloc_getitem_dups(self):
 
-        # no dups in panel (bug?)
         self.check_result('list int (dups)', 'iloc', [0, 1, 1, 3], 'ix',
                           {0: [0, 2, 2, 6], 1: [0, 3, 3, 9]},
                           objs=['series', 'frame'], typs=['ints', 'uints'])

pandas/tests/reshape/merge/test_join.py

@@ -17,7 +17,6 @@
 a_ = np.array
 
 
-@pytest.mark.filterwarnings("ignore:\\nPanel:FutureWarning")
 class TestJoin(object):
 
     def setup_method(self, method):

pandas/tests/test_base.py

@@ -21,7 +21,7 @@
 import pandas as pd
 from pandas import (
     CategoricalIndex, DataFrame, DatetimeIndex, Index, Interval, IntervalIndex,
-    Panel, PeriodIndex, Series, Timedelta, TimedeltaIndex, Timestamp)
+    PeriodIndex, Series, Timedelta, TimedeltaIndex, Timestamp)
 from pandas.core.accessor import PandasDelegate
 from pandas.core.arrays import DatetimeArray, PandasArray, TimedeltaArray
 from pandas.core.base import NoNewAttributesMixin, PandasObject
@@ -239,7 +239,7 @@ def check_ops_properties(self, props, filter=None, ignore_failures=False):
                     with pytest.raises(err):
                         getattr(o, op)
 
-    @pytest.mark.parametrize('klass', [Series, DataFrame, Panel])
+    @pytest.mark.parametrize('klass', [Series, DataFrame])
     def test_binary_ops_docs(self, klass):
         op_map = {'add': '+',
                   'sub': '-',