MAINT: Remove np.array_equal calls in tests

Author: gfyoung

pandas/tests/dtypes/test_cast.py

@@ -38,17 +38,17 @@ def test_downcast_conv(self):
 
         arr = np.array([8.5, 8.6, 8.7, 8.8, 8.9999999999995])
         result = maybe_downcast_to_dtype(arr, 'infer')
-        assert (np.array_equal(result, arr))
+        tm.assert_numpy_array_equal(result, arr)
 
         arr = np.array([8., 8., 8., 8., 8.9999999999995])
         result = maybe_downcast_to_dtype(arr, 'infer')
         expected = np.array([8, 8, 8, 8, 9])
-        assert (np.array_equal(result, expected))
+        tm.assert_numpy_array_equal(result, expected)
 
         arr = np.array([8., 8., 8., 8., 9.0000000000005])
         result = maybe_downcast_to_dtype(arr, 'infer')
         expected = np.array([8, 8, 8, 8, 9])
-        assert (np.array_equal(result, expected))
+        tm.assert_numpy_array_equal(result, expected)
 
         # GH16875 coercing of bools
         ser = Series([True, True, False])

pandas/tests/frame/test_constructors.py

@@ -1913,10 +1913,11 @@ def test_from_records_len0_with_columns(self):
         # #2633
         result = DataFrame.from_records([], index='foo',
                                         columns=['foo', 'bar'])
+        expected = Index(['bar'])
 
-        assert np.array_equal(result.columns, ['bar'])
         assert len(result) == 0
         assert result.index.name == 'foo'
+        tm.assert_index_equal(result.columns, expected)
 
     def test_to_frame_with_falsey_names(self):
         # GH 16114

pandas/tests/frame/test_nonunique_indexes.py

@@ -448,7 +448,7 @@ def test_as_matrix_duplicates(self):
         expected = np.array([[1, 2, 'a', 'b'], [1, 2, 'a', 'b']],
                             dtype=object)
 
-        assert np.array_equal(result, expected)
+        tm.assert_numpy_array_equal(result, expected)
 
     def test_set_value_by_index(self):
         # See gh-12344

pandas/tests/indexes/datetimes/test_date_range.py

@@ -22,7 +22,10 @@
 
 def eq_gen_range(kwargs, expected):
     rng = generate_range(**kwargs)
-    assert (np.array_equal(list(rng), expected))
+    result = np.asarray(list(rng))
+    expected = np.asarray(expected)
+
+    tm.assert_numpy_array_equal(result, expected)
 
 
 class TestDateRanges(TestData):

pandas/tests/io/parser/common.py

@@ -823,7 +823,7 @@ def test_parse_integers_above_fp_precision(self):
                                           17007000002000192,
                                           17007000002000194]})
 
-        assert np.array_equal(result['Numbers'], expected['Numbers'])
+        tm.assert_series_equal(result['Numbers'], expected['Numbers'])
 
     def test_chunks_have_consistent_numerical_type(self):
         integers = [str(i) for i in range(499999)]

pandas/tests/io/parser/test_textreader.py

@@ -161,9 +161,9 @@ def test_skip_bad_lines(self):
                             error_bad_lines=False,
                             warn_bad_lines=False)
         result = reader.read()
-        expected = {0: ['a', 'd', 'g', 'l'],
-                    1: ['b', 'e', 'h', 'm'],
-                    2: ['c', 'f', 'i', 'n']}
+        expected = {0: np.array(['a', 'd', 'g', 'l'], dtype=object),
+                    1: np.array(['b', 'e', 'h', 'm'], dtype=object),
+                    2: np.array(['c', 'f', 'i', 'n'], dtype=object)}
         assert_array_dicts_equal(result, expected)
 
         reader = TextReader(StringIO(data), delimiter=':',
@@ -225,7 +225,7 @@ def test_escapechar(self):
         reader = TextReader(StringIO(data), delimiter=',', header=None,
                             escapechar='\\')
         result = reader.read()
-        expected = {0: ['"hello world"'] * 3}
+        expected = {0: np.array(['"hello world"'] * 3, dtype=object)}
         assert_array_dicts_equal(result, expected)
 
     def test_eof_has_eol(self):
@@ -397,4 +397,5 @@ def test_empty_csv_input(self):
 
 def assert_array_dicts_equal(left, right):
     for k, v in compat.iteritems(left):
-        assert(np.array_equal(v, right[k]))
+        assert tm.assert_numpy_array_equal(np.asarray(v),
+                                           np.asarray(right[k]))

pandas/tests/reshape/test_concat.py

@@ -1594,7 +1594,9 @@ def test_concat_series_axis1_same_names_ignore_index(self):
         s2 = Series(randn(len(dates)), index=dates, name='value')
 
         result = concat([s1, s2], axis=1, ignore_index=True)
-        assert np.array_equal(result.columns, [0, 1])
+        expected = Index([0, 1])
+
+        tm.assert_index_equal(result.columns, expected)
 
     def test_concat_iterables(self):
         from collections import deque, Iterable

pandas/tests/series/test_missing.py

@@ -636,17 +636,21 @@ def test_valid(self):
 
     def test_isna(self):
         ser = Series([0, 5.4, 3, nan, -0.001])
-        np.array_equal(ser.isna(),
-                       Series([False, False, False, True, False]).values)
+        expected = Series([False, False, False, True, False])
+        tm.assert_series_equal(ser.isna(), expected)
+
         ser = Series(["hi", "", nan])
-        np.array_equal(ser.isna(), Series([False, False, True]).values)
+        expected = Series([False, False, True])
+        tm.assert_series_equal(ser.isna(), expected)
 
     def test_notna(self):
         ser = Series([0, 5.4, 3, nan, -0.001])
-        np.array_equal(ser.notna(),
-                       Series([True, True, True, False, True]).values)
+        expected = Series([True, True, True, False, True])
+        tm.assert_series_equal(ser.notna(), expected)
+
         ser = Series(["hi", "", nan])
-        np.array_equal(ser.notna(), Series([True, True, False]).values)
+        expected = Series([True, True, False])
+        tm.assert_series_equal(ser.notna(), expected)
 
     def test_pad_nan(self):
         x = Series([np.nan, 1., np.nan, 3., np.nan], ['z', 'a', 'b', 'c', 'd'],

pandas/tests/test_algos.py

@@ -1132,19 +1132,19 @@ def test_pad_backfill_object_segfault():
 
     result = libalgos.pad_object(old, new)
     expected = np.array([-1], dtype=np.int64)
-    assert (np.array_equal(result, expected))
+    tm.assert_numpy_array_equal(result, expected)
 
     result = libalgos.pad_object(new, old)
     expected = np.array([], dtype=np.int64)
-    assert (np.array_equal(result, expected))
+    tm.assert_numpy_array_equal(result, expected)
 
     result = libalgos.backfill_object(old, new)
     expected = np.array([-1], dtype=np.int64)
-    assert (np.array_equal(result, expected))
+    tm.assert_numpy_array_equal(result, expected)
 
     result = libalgos.backfill_object(new, old)
     expected = np.array([], dtype=np.int64)
-    assert (np.array_equal(result, expected))
+    tm.assert_numpy_array_equal(result, expected)
 
 
 def test_arrmap():
@@ -1235,15 +1235,6 @@ def test_is_lexsorted():
 
     assert (not libalgos.is_lexsorted(failure))
 
-# def test_get_group_index():
-#     a = np.array([0, 1, 2, 0, 2, 1, 0, 0], dtype=np.int64)
-#     b = np.array([1, 0, 3, 2, 0, 2, 3, 0], dtype=np.int64)
-#     expected = np.array([1, 4, 11, 2, 8, 6, 3, 0], dtype=np.int64)
-
-#     result = lib.get_group_index([a, b], (3, 4))
-
-#     assert(np.array_equal(result, expected))
-
 
 def test_groupsort_indexer():
     a = np.random.randint(0, 1000, 100).astype(np.int64)
@@ -1253,13 +1244,13 @@ def test_groupsort_indexer():
 
     # need to use a stable sort
     expected = np.argsort(a, kind='mergesort')
-    assert (np.array_equal(result, expected))
+    tm.assert_numpy_array_equal(result, expected)
 
     # compare with lexsort
     key = a * 1000 + b
     result = libalgos.groupsort_indexer(key, 1000000)[0]
     expected = np.lexsort((b, a))
-    assert (np.array_equal(result, expected))
+    tm.assert_numpy_array_equal(result, expected)
 
 
 def test_infinity_sort():

pandas/tests/test_join.py

@@ -53,7 +53,7 @@ def test_left_join_indexer_unique():
 
     result = _join.left_join_indexer_unique_int64(b, a)
     expected = np.array([1, 1, 2, 3, 3], dtype=np.int64)
-    assert (np.array_equal(result, expected))
+    tm.assert_numpy_array_equal(result, expected)
 
 
 def test_left_outer_join_bug():
@@ -74,8 +74,8 @@ def test_left_outer_join_bug():
     exp_ridx[left == 1] = 1
     exp_ridx[left == 3] = 0
 
-    assert (np.array_equal(lidx, exp_lidx))
-    assert (np.array_equal(ridx, exp_ridx))
+    tm.assert_numpy_array_equal(lidx, exp_lidx)
+    tm.assert_numpy_array_equal(ridx, exp_ridx)
 
 
 def test_inner_join_indexer():