diff --git a/pandas/tests/test_common.py b/pandas/tests/test_common.py index 2c32b5d0310db..3b3b2becc82db 100644 --- a/pandas/tests/test_common.py +++ b/pandas/tests/test_common.py @@ -800,7 +800,7 @@ def test_1d_bool(self): result = com.take_1d(arr, [0, 2, 2, 1]) expected = arr.take([0, 2, 2, 1]) - self.assert_(np.array_equal(result, expected)) + self.assert_numpy_array_equal(result, expected) result = com.take_1d(arr, [0, 2, -1]) self.assertEqual(result.dtype, np.object_) @@ -812,11 +812,11 @@ def test_2d_bool(self): result = com.take_nd(arr, [0, 2, 2, 1]) expected = arr.take([0, 2, 2, 1], axis=0) - self.assert_(np.array_equal(result, expected)) + self.assert_numpy_array_equal(result, expected) result = com.take_nd(arr, [0, 2, 2, 1], axis=1) expected = arr.take([0, 2, 2, 1], axis=1) - self.assert_(np.array_equal(result, expected)) + self.assert_numpy_array_equal(result, expected) result = com.take_nd(arr, [0, 2, -1]) self.assertEqual(result.dtype, np.object_) diff --git a/pandas/tests/test_generic.py b/pandas/tests/test_generic.py index 6c7e455bb1c03..d694efff9b351 100644 --- a/pandas/tests/test_generic.py +++ b/pandas/tests/test_generic.py @@ -447,7 +447,7 @@ def test_interpolate(self): ts_copy[5:10] = np.NaN linear_interp = ts_copy.interpolate(method='linear') - self.assert_(np.array_equal(linear_interp, ts)) + self.assert_numpy_array_equal(linear_interp, ts) ord_ts = Series([d.toordinal() for d in self.ts.index], index=self.ts.index).astype(float) @@ -456,7 +456,7 @@ def test_interpolate(self): ord_ts_copy[5:10] = np.NaN time_interp = ord_ts_copy.interpolate(method='time') - self.assert_(np.array_equal(time_interp, ord_ts)) + self.assert_numpy_array_equal(time_interp, ord_ts) # try time interpolation on a non-TimeSeries self.assertRaises(ValueError, self.series.interpolate, method='time') diff --git a/pandas/tests/test_groupby.py b/pandas/tests/test_groupby.py index ba06cebd20080..fa7a2b2d24636 100644 --- a/pandas/tests/test_groupby.py +++ b/pandas/tests/test_groupby.py @@ -1720,7 +1720,7 @@ def test_apply_frame_to_series(self): result = grouped.apply(len) expected = grouped.count()['C'] self.assert_(result.index.equals(expected.index)) - self.assert_(np.array_equal(result.values, expected.values)) + self.assert_numpy_array_equal(result.values, expected.values) def test_apply_frame_concat_series(self): def trans(group): @@ -2198,17 +2198,17 @@ def test_panel_groupby(self): tm.assert_panel_equal(agged, agged2) - self.assert_(np.array_equal(agged.items, [0, 1])) + self.assert_numpy_array_equal(agged.items, [0, 1]) grouped = self.panel.groupby(lambda x: x.month, axis='major') agged = grouped.mean() - self.assert_(np.array_equal(agged.major_axis, [1, 2])) + self.assert_numpy_array_equal(agged.major_axis, [1, 2]) grouped = self.panel.groupby({'A': 0, 'B': 0, 'C': 1, 'D': 1}, axis='minor') agged = grouped.mean() - self.assert_(np.array_equal(agged.minor_axis, [0, 1])) + self.assert_numpy_array_equal(agged.minor_axis, [0, 1]) def test_numpy_groupby(self): from pandas.core.groupby import numpy_groupby @@ -2234,8 +2234,8 @@ def test_groupby_2d_malformed(self): d['label'] = ['l1', 'l2'] tmp = d.groupby(['group']).mean() res_values = np.array([[0., 1.], [0., 1.]]) - self.assert_(np.array_equal(tmp.columns, ['zeros', 'ones'])) - self.assert_(np.array_equal(tmp.values, res_values)) + self.assert_numpy_array_equal(tmp.columns, ['zeros', 'ones']) + self.assert_numpy_array_equal(tmp.values, res_values) def test_int32_overflow(self): B = np.concatenate((np.arange(10000), np.arange(10000), @@ -2290,19 +2290,19 @@ def test_groupby_sort_multi(self): tups = lmap(tuple, df[['a', 'b', 'c']].values) tups = com._asarray_tuplesafe(tups) result = df.groupby(['a', 'b', 'c'], sort=True).sum() - self.assert_(np.array_equal(result.index.values, - tups[[1, 2, 0]])) + self.assert_numpy_array_equal(result.index.values, + tups[[1, 2, 0]]) tups = lmap(tuple, df[['c', 'a', 'b']].values) tups = com._asarray_tuplesafe(tups) result = df.groupby(['c', 'a', 'b'], sort=True).sum() - self.assert_(np.array_equal(result.index.values, tups)) + self.assert_numpy_array_equal(result.index.values, tups) tups = lmap(tuple, df[['b', 'c', 'a']].values) tups = com._asarray_tuplesafe(tups) result = df.groupby(['b', 'c', 'a'], sort=True).sum() - self.assert_(np.array_equal(result.index.values, - tups[[2, 1, 0]])) + self.assert_numpy_array_equal(result.index.values, + tups[[2, 1, 0]]) df = DataFrame({'a': [0, 1, 2, 0, 1, 2], 'b': [0, 0, 0, 1, 1, 1], @@ -2452,7 +2452,7 @@ def test_agg_multiple_functions_maintain_order(self): result = self.df.groupby('A')['C'].agg(funcs) exp_cols = ['mean', 'max', 'min'] - self.assert_(np.array_equal(result.columns, exp_cols)) + self.assert_numpy_array_equal(result.columns, exp_cols) def test_multiple_functions_tuples_and_non_tuples(self): # #1359 @@ -2651,10 +2651,10 @@ def test_multiindex_columns_empty_level(self): df = DataFrame([[long(1), 'A']], columns=midx) grouped = df.groupby('to filter').groups - self.assert_(np.array_equal(grouped['A'], [0])) + self.assert_numpy_array_equal(grouped['A'], [0]) grouped = df.groupby([('to filter', '')]).groups - self.assert_(np.array_equal(grouped['A'], [0])) + self.assert_numpy_array_equal(grouped['A'], [0]) df = DataFrame([[long(1), 'A'], [long(2), 'B']], columns=midx) diff --git a/pandas/tests/test_multilevel.py b/pandas/tests/test_multilevel.py index b997d1fff9e9b..492f681a72541 100644 --- a/pandas/tests/test_multilevel.py +++ b/pandas/tests/test_multilevel.py @@ -1509,7 +1509,7 @@ def test_int_series_slicing(self): exp = self.ymd['A'].copy() s[5:] = 0 exp.values[5:] = 0 - self.assert_(np.array_equal(s.values, exp.values)) + self.assert_numpy_array_equal(s.values, exp.values) result = self.ymd[5:] expected = self.ymd.reindex(s.index[5:]) diff --git a/pandas/tests/test_panel.py b/pandas/tests/test_panel.py index 2727d0b5b0881..702307c8b7109 100644 --- a/pandas/tests/test_panel.py +++ b/pandas/tests/test_panel.py @@ -754,8 +754,8 @@ def test_comp(func): # versus same index result = func(p1, p2) - self.assert_(np.array_equal(result.values, - func(p1.values, p2.values))) + self.assert_numpy_array_equal(result.values, + func(p1.values, p2.values)) # versus non-indexed same objs self.assertRaises(Exception, func, p1, tp) @@ -765,8 +765,8 @@ def test_comp(func): # versus scalar result3 = func(self.panel, 0) - self.assert_(np.array_equal(result3.values, - func(self.panel.values, 0))) + self.assert_numpy_array_equal(result3.values, + func(self.panel.values, 0)) test_comp(operator.eq) test_comp(operator.ne) @@ -2155,7 +2155,7 @@ def test_axis_dummies(self): transformed = make_axis_dummies(self.panel, 'minor', transform=mapping.get) self.assertEqual(len(transformed.columns), 2) - self.assert_(np.array_equal(transformed.columns, ['one', 'two'])) + self.assert_numpy_array_equal(transformed.columns, ['one', 'two']) # TODO: test correctness @@ -2165,7 +2165,7 @@ def test_get_dummies(self): self.panel['Label'] = self.panel.index.labels[1] minor_dummies = make_axis_dummies(self.panel, 'minor') dummies = get_dummies(self.panel['Label']) - self.assert_(np.array_equal(dummies.values, minor_dummies.values)) + self.assert_numpy_array_equal(dummies.values, minor_dummies.values) def test_mean(self): means = self.panel.mean(level='minor') diff --git a/pandas/tests/test_strings.py b/pandas/tests/test_strings.py index d6a1f4f0341b7..ad55ce5c3aec5 100644 --- a/pandas/tests/test_strings.py +++ b/pandas/tests/test_strings.py @@ -133,7 +133,7 @@ def test_cat(self): # Multiple arrays result = strings.str_cat(one, [two], na_rep='NA') exp = ['aa', 'aNA', 'bb', 'bd', 'cfoo', 'NANA'] - self.assert_(np.array_equal(result, exp)) + self.assert_numpy_array_equal(result, exp) result = strings.str_cat(one, two) exp = ['aa', NA, 'bb', 'bd', 'cfoo', NA]