DEPR: remove assert_panel_equal

pandas/tests/generic/test_generic.py

@@ -14,8 +14,7 @@
 import pandas as pd
 from pandas import DataFrame, MultiIndex, Panel, Series, date_range
 import pandas.util.testing as tm
-from pandas.util.testing import (
-    assert_frame_equal, assert_panel_equal, assert_series_equal)
+from pandas.util.testing import assert_frame_equal, assert_series_equal
 
 import pandas.io.formats.printing as printing
 
@@ -701,16 +700,9 @@ def test_sample(sel):
         assert_frame_equal(sample1, df[['colString']])
 
         # Test default axes
-        with catch_warnings(record=True):
-            simplefilter("ignore", FutureWarning)
-            p = Panel(items=['a', 'b', 'c'], major_axis=[2, 4, 6],
-                      minor_axis=[1, 3, 5])
-            assert_panel_equal(
-                p.sample(n=3, random_state=42), p.sample(n=3, axis=1,
-                                                         random_state=42))
-            assert_frame_equal(
-                df.sample(n=3, random_state=42), df.sample(n=3, axis=0,
-                                                           random_state=42))
+        assert_frame_equal(
+            df.sample(n=3, random_state=42), df.sample(n=3, axis=0,
+                                                       random_state=42))
 
         # Test that function aligns weights with frame
         df = DataFrame(
@@ -950,22 +942,6 @@ def test_pipe_tuple_error(self):
         with pytest.raises(ValueError):
             df.A.pipe((f, 'y'), x=1, y=0)
 
-    def test_pipe_panel(self):
-        with catch_warnings(record=True):
-            simplefilter("ignore", FutureWarning)
-            wp = Panel({'r1': DataFrame({"A": [1, 2, 3]})})
-            f = lambda x, y: x + y
-            result = wp.pipe(f, 2)
-            expected = wp + 2
-            assert_panel_equal(result, expected)
-
-            result = wp.pipe((f, 'y'), x=1)
-            expected = wp + 1
-            assert_panel_equal(result, expected)
-
-            with pytest.raises(ValueError):
-                wp.pipe((f, 'y'), x=1, y=1)
-
     @pytest.mark.parametrize('box', [pd.Series, pd.DataFrame])
     def test_axis_classmethods(self, box):
         obj = box()

pandas/tests/indexing/common.py

@@ -233,8 +233,6 @@ def _print(result, error=None):
                         tm.assert_series_equal(rs, xp)
                     elif xp.ndim == 2:
                         tm.assert_frame_equal(rs, xp)
-                    elif xp.ndim == 3:
-                        tm.assert_panel_equal(rs, xp)
                     result = 'ok'
                 except AssertionError as e:
                     detail = str(e)

pandas/tests/indexing/multiindex/test_panel.py

@@ -55,49 +55,3 @@ def test_iloc_getitem_panel_multiindex(self):
 
         result = p.loc[:, (1, 'y'), 'u']
         tm.assert_series_equal(result, expected)
-
-    def test_panel_setitem_with_multiindex(self):
-
-        # 10360
-        # failing with a multi-index
-        arr = np.array([[[1, 2, 3], [0, 0, 0]],
-                        [[0, 0, 0], [0, 0, 0]]],
-                       dtype=np.float64)
-
-        # reg index
-        axes = dict(items=['A', 'B'], major_axis=[0, 1],
-                    minor_axis=['X', 'Y', 'Z'])
-        p1 = Panel(0., **axes)
-        p1.iloc[0, 0, :] = [1, 2, 3]
-        expected = Panel(arr, **axes)
-        tm.assert_panel_equal(p1, expected)
-
-        # multi-indexes
-        axes['items'] = MultiIndex.from_tuples(
-            [('A', 'a'), ('B', 'b')])
-        p2 = Panel(0., **axes)
-        p2.iloc[0, 0, :] = [1, 2, 3]
-        expected = Panel(arr, **axes)
-        tm.assert_panel_equal(p2, expected)
-
-        axes['major_axis'] = MultiIndex.from_tuples(
-            [('A', 1), ('A', 2)])
-        p3 = Panel(0., **axes)
-        p3.iloc[0, 0, :] = [1, 2, 3]
-        expected = Panel(arr, **axes)
-        tm.assert_panel_equal(p3, expected)
-
-        axes['minor_axis'] = MultiIndex.from_product(
-            [['X'], range(3)])
-        p4 = Panel(0., **axes)
-        p4.iloc[0, 0, :] = [1, 2, 3]
-        expected = Panel(arr, **axes)
-        tm.assert_panel_equal(p4, expected)
-
-        arr = np.array(
-            [[[1, 0, 0], [2, 0, 0]], [[0, 0, 0], [0, 0, 0]]],
-            dtype=np.float64)
-        p5 = Panel(0., **axes)
-        p5.iloc[0, :, 0] = [1, 2]
-        expected = Panel(arr, **axes)
-        tm.assert_panel_equal(p5, expected)

pandas/tests/indexing/test_panel.py

@@ -3,7 +3,7 @@
 import numpy as np
 import pytest
 
-from pandas import DataFrame, Panel, date_range
+from pandas import Panel, date_range
 from pandas.util import testing as tm
 
 
@@ -31,30 +31,6 @@ def test_iloc_getitem_panel(self):
             expected = p.loc['B', 'b', 'two']
             assert result == expected
 
-            # slice
-            result = p.iloc[1:3]
-            expected = p.loc[['B', 'C']]
-            tm.assert_panel_equal(result, expected)
-
-            result = p.iloc[:, 0:2]
-            expected = p.loc[:, ['a', 'b']]
-            tm.assert_panel_equal(result, expected)
-
-            # list of integers
-            result = p.iloc[[0, 2]]
-            expected = p.loc[['A', 'C']]
-            tm.assert_panel_equal(result, expected)
-
-            # neg indices
-            result = p.iloc[[-1, 1], [-1, 1]]
-            expected = p.loc[['D', 'B'], ['c', 'b']]
-            tm.assert_panel_equal(result, expected)
-
-            # dups indices
-            result = p.iloc[[-1, -1, 1], [-1, 1]]
-            expected = p.loc[['D', 'D', 'B'], ['c', 'b']]
-            tm.assert_panel_equal(result, expected)
-
             # combined
             result = p.iloc[0, [True, True], [0, 1]]
             expected = p.loc['A', ['a', 'b'], ['one', 'two']]
@@ -110,18 +86,6 @@ def test_iloc_panel_issue(self):
     def test_panel_getitem(self):
 
         with catch_warnings(record=True):
-            # GH4016, date selection returns a frame when a partial string
-            # selection
-            ind = date_range(start="2000", freq="D", periods=1000)
-            df = DataFrame(
-                np.random.randn(
-                    len(ind), 5), index=ind, columns=list('ABCDE'))
-            panel = Panel({'frame_' + c: df for c in list('ABC')})
-
-            test2 = panel.loc[:, "2002":"2002-12-31"]
-            test1 = panel.loc[:, "2002"]
-            tm.assert_panel_equal(test1, test2)
-
             # with an object-like
             # GH 9140
             class TestObject(object):
@@ -138,55 +102,3 @@ def __str__(self):
             expected = p.iloc[0]
             result = p[obj]
             tm.assert_frame_equal(result, expected)
-
-    def test_panel_setitem(self):
-
-        with catch_warnings(record=True):
-            # GH 7763
-            # loc and setitem have setting differences
-            np.random.seed(0)
-            index = range(3)
-            columns = list('abc')
-
-            panel = Panel({'A': DataFrame(np.random.randn(3, 3),
-                                          index=index, columns=columns),
-                           'B': DataFrame(np.random.randn(3, 3),
-                                          index=index, columns=columns),
-                           'C': DataFrame(np.random.randn(3, 3),
-                                          index=index, columns=columns)})
-
-            replace = DataFrame(np.eye(3, 3), index=range(3), columns=columns)
-            expected = Panel({'A': replace, 'B': replace, 'C': replace})
-
-            p = panel.copy()
-            for idx in list('ABC'):
-                p[idx] = replace
-            tm.assert_panel_equal(p, expected)
-
-            p = panel.copy()
-            for idx in list('ABC'):
-                p.loc[idx, :, :] = replace
-            tm.assert_panel_equal(p, expected)
-
-    def test_panel_assignment(self):
-
-        with catch_warnings(record=True):
-            # GH3777
-            wp = Panel(np.random.randn(2, 5, 4), items=['Item1', 'Item2'],
-                       major_axis=date_range('1/1/2000', periods=5),
-                       minor_axis=['A', 'B', 'C', 'D'])
-            wp2 = Panel(np.random.randn(2, 5, 4), items=['Item1', 'Item2'],
-                        major_axis=date_range('1/1/2000', periods=5),
-                        minor_axis=['A', 'B', 'C', 'D'])
-
-            # TODO: unused?
-            # expected = wp.loc[['Item1', 'Item2'], :, ['A', 'B']]
-
-            with pytest.raises(NotImplementedError):
-                wp.loc[['Item1', 'Item2'], :, ['A', 'B']] = wp2.loc[
-                    ['Item1', 'Item2'], :, ['A', 'B']]
-
-            # to_assign = wp2.loc[['Item1', 'Item2'], :, ['A', 'B']]
-            # wp.loc[['Item1', 'Item2'], :, ['A', 'B']] = to_assign
-            # result = wp.loc[['Item1', 'Item2'], :, ['A', 'B']]
-            # tm.assert_panel_equal(result,expected)

pandas/tests/indexing/test_partial.py

@@ -10,13 +10,12 @@
 import pytest
 
 import pandas as pd
-from pandas import DataFrame, Index, Panel, Series, date_range
+from pandas import DataFrame, Index, Series, date_range
 from pandas.util import testing as tm
 
 
 class TestPartialSetting(object):
 
-    @pytest.mark.filterwarnings("ignore:\\nPanel:FutureWarning")
     @pytest.mark.filterwarnings("ignore:\\n.ix:DeprecationWarning")
     def test_partial_setting(self):
 
@@ -116,35 +115,6 @@ def test_partial_setting(self):
             df.ix[:, 'C'] = df.ix[:, 'A']
         tm.assert_frame_equal(df, expected)
 
-        with catch_warnings(record=True):
-            # ## panel ##
-            p_orig = Panel(np.arange(16).reshape(2, 4, 2),
-                           items=['Item1', 'Item2'],
-                           major_axis=pd.date_range('2001/1/12', periods=4),
-                           minor_axis=['A', 'B'], dtype='float64')
-
-            # panel setting via item
-            p_orig = Panel(np.arange(16).reshape(2, 4, 2),
-                           items=['Item1', 'Item2'],
-                           major_axis=pd.date_range('2001/1/12', periods=4),
-                           minor_axis=['A', 'B'], dtype='float64')
-            expected = p_orig.copy()
-            expected['Item3'] = expected['Item1']
-            p = p_orig.copy()
-            p.loc['Item3'] = p['Item1']
-            tm.assert_panel_equal(p, expected)
-
-            # panel with aligned series
-            expected = p_orig.copy()
-            expected = expected.transpose(2, 1, 0)
-            expected['C'] = DataFrame({'Item1': [30, 30, 30, 30],
-                                       'Item2': [32, 32, 32, 32]},
-                                      index=p_orig.major_axis)
-            expected = expected.transpose(2, 1, 0)
-            p = p_orig.copy()
-            p.loc[:, :, 'C'] = Series([30, 32], index=p_orig.items)
-            tm.assert_panel_equal(p, expected)
-
         # GH 8473
         dates = date_range('1/1/2000', periods=8)
         df_orig = DataFrame(np.random.randn(8, 4), index=dates,

pandas/tests/io/generate_legacy_storage_files.py

@@ -41,15 +41,14 @@
 import os
 import platform as pl
 import sys
-from warnings import catch_warnings, filterwarnings
 
 import numpy as np
 
 from pandas.compat import u
 
 import pandas
 from pandas import (
-    Categorical, DataFrame, Index, MultiIndex, NaT, Panel, Period, Series,
+    Categorical, DataFrame, Index, MultiIndex, NaT, Period, Series,
     SparseDataFrame, SparseSeries, Timestamp, bdate_range, date_range,
     period_range, timedelta_range, to_msgpack)
 
@@ -187,18 +186,6 @@ def create_data():
                      u'C': Timestamp('20130603', tz='UTC')}, index=range(5))
                  )
 
-    with catch_warnings(record=True):
-        filterwarnings("ignore", "\\nPanel", FutureWarning)
-        mixed_dup_panel = Panel({u'ItemA': frame[u'float'],
-                                 u'ItemB': frame[u'int']})
-        mixed_dup_panel.items = [u'ItemA', u'ItemA']
-        panel = dict(float=Panel({u'ItemA': frame[u'float'],
-                                  u'ItemB': frame[u'float'] + 1}),
-                     dup=Panel(
-                         np.arange(30).reshape(3, 5, 2).astype(np.float64),
-                         items=[u'A', u'B', u'A']),
-                     mixed_dup=mixed_dup_panel)
-
     cat = dict(int8=Categorical(list('abcdefg')),
                int16=Categorical(np.arange(1000)),
                int32=Categorical(np.arange(10000)))
@@ -241,7 +228,6 @@ def create_data():
 
     return dict(series=series,
                 frame=frame,
-                panel=panel,
                 index=index,
                 scalars=scalars,
                 mi=mi,