Remove .ix method, part 1

Author: topper-123

pandas/tests/frame/test_indexing.py

@@ -393,85 +393,6 @@ def test_boolean_index_empty_corner(self):
         blah[k]
         blah[k] = 0
 
-    def test_getitem_ix_mixed_integer(self):
-        df = DataFrame(
-            np.random.randn(4, 3), index=[1, 10, "C", "E"], columns=[1, 2, 3]
-        )
-
-        result = df.iloc[:-1]
-        expected = df.loc[df.index[:-1]]
-        assert_frame_equal(result, expected)
-
-        with catch_warnings(record=True):
-            simplefilter("ignore", FutureWarning)
-            result = df.ix[[1, 10]]
-            expected = df.ix[Index([1, 10], dtype=object)]
-        assert_frame_equal(result, expected)
-
-        # 11320
-        df = pd.DataFrame(
-            {
-                "rna": (1.5, 2.2, 3.2, 4.5),
-                -1000: [11, 21, 36, 40],
-                0: [10, 22, 43, 34],
-                1000: [0, 10, 20, 30],
-            },
-            columns=["rna", -1000, 0, 1000],
-        )
-        result = df[[1000]]
-        expected = df.iloc[:, [3]]
-        assert_frame_equal(result, expected)
-        result = df[[-1000]]
-        expected = df.iloc[:, [1]]
-        assert_frame_equal(result, expected)
-
-    def test_getitem_setitem_ix_negative_integers(self, float_frame):
-        with catch_warnings(record=True):
-            simplefilter("ignore", FutureWarning)
-            result = float_frame.ix[:, -1]
-        assert_series_equal(result, float_frame["D"])
-
-        with catch_warnings(record=True):
-            simplefilter("ignore", FutureWarning)
-            result = float_frame.ix[:, [-1]]
-        assert_frame_equal(result, float_frame[["D"]])
-
-        with catch_warnings(record=True):
-            simplefilter("ignore", FutureWarning)
-            result = float_frame.ix[:, [-1, -2]]
-        assert_frame_equal(result, float_frame[["D", "C"]])
-
-        with catch_warnings(record=True):
-            simplefilter("ignore", FutureWarning)
-            float_frame.ix[:, [-1]] = 0
-        assert (float_frame["D"] == 0).all()
-
-        df = DataFrame(np.random.randn(8, 4))
-        # ix does label-based indexing when having an integer index
-        msg = "\"None of [Int64Index([-1], dtype='int64')] are in the [index]\""
-        with catch_warnings(record=True):
-            simplefilter("ignore", FutureWarning)
-            with pytest.raises(KeyError, match=re.escape(msg)):
-                df.ix[[-1]]
-
-        msg = "\"None of [Int64Index([-1], dtype='int64')] are in the [columns]\""
-        with catch_warnings(record=True):
-            simplefilter("ignore", FutureWarning)
-            with pytest.raises(KeyError, match=re.escape(msg)):
-                df.ix[:, [-1]]
-
-        # #1942
-        a = DataFrame(np.random.randn(20, 2), index=[chr(x + 65) for x in range(20)])
-        with catch_warnings(record=True):
-            simplefilter("ignore", FutureWarning)
-            a.ix[-1] = a.ix[-2]
-
-        with catch_warnings(record=True):
-            simplefilter("ignore", FutureWarning)
-            assert_series_equal(a.ix[-1], a.ix[-2], check_names=False)
-            assert a.ix[-1].name == "T"
-            assert a.ix[-2].name == "S"
-
     def test_getattr(self, float_frame):
         assert_series_equal(float_frame.A, float_frame["A"])
         msg = "'DataFrame' object has no attribute 'NONEXISTENT_NAME'"

pandas/tests/indexing/multiindex/test_slice.py

@@ -12,16 +12,15 @@
 from pandas.util import testing as tm
 
 
-@pytest.mark.filterwarnings("ignore:\\n.ix:FutureWarning")
 class TestMultiIndexSlicers:
     def test_per_axis_per_level_getitem(self):
 
         # GH6134
         # example test case
-        ix = MultiIndex.from_product(
+        midx = MultiIndex.from_product(
             [_mklbl("A", 5), _mklbl("B", 7), _mklbl("C", 4), _mklbl("D", 2)]
         )
-        df = DataFrame(np.arange(len(ix.to_numpy())), index=ix)
+        df = DataFrame(np.arange(len(midx)), index=midx)
 
         result = df.loc[(slice("A1", "A3"), slice(None), ["C1", "C3"]), :]
         expected = df.loc[
@@ -98,7 +97,7 @@ def test_per_axis_per_level_getitem(self):
         tm.assert_frame_equal(result, expected)
 
         # multi-level series
-        s = Series(np.arange(len(ix.to_numpy())), index=ix)
+        s = Series(np.arange(len(midx)), index=midx)
         result = s.loc["A1":"A3", :, ["C1", "C3"]]
         expected = s.loc[
             [
@@ -637,8 +636,6 @@ def test_multiindex_label_slicing_with_negative_step(self):
         def assert_slices_equivalent(l_slc, i_slc):
             tm.assert_series_equal(s.loc[l_slc], s.iloc[i_slc])
             tm.assert_series_equal(s[l_slc], s.iloc[i_slc])
-            with catch_warnings(record=True):
-                tm.assert_series_equal(s.ix[l_slc], s.iloc[i_slc])
 
         assert_slices_equivalent(SLC[::-1], SLC[::-1])