| 44 | class TestSorting: |
| 45 | @pytest.mark.slow |
| 46 | def test_int64_overflow(self): |
| 47 | B = np.concatenate((np.arange(1000), np.arange(1000), np.arange(500))) |
| 48 | A = np.arange(2500) |
| 49 | df = DataFrame( |
| 50 | { |
| 51 | "A": A, |
| 52 | "B": B, |
| 53 | "C": A, |
| 54 | "D": B, |
| 55 | "E": A, |
| 56 | "F": B, |
| 57 | "G": A, |
| 58 | "H": B, |
| 59 | "values": np.random.default_rng(2).standard_normal(2500), |
| 60 | } |
| 61 | ) |
| 62 | |
| 63 | lg = df.groupby(["A", "B", "C", "D", "E", "F", "G", "H"]) |
| 64 | rg = df.groupby(["H", "G", "F", "E", "D", "C", "B", "A"]) |
| 65 | |
| 66 | left = lg.sum()["values"] |
| 67 | right = rg.sum()["values"] |
| 68 | |
| 69 | exp_index, _ = left.index.sortlevel() |
| 70 | tm.assert_index_equal(left.index, exp_index) |
| 71 | |
| 72 | exp_index, _ = right.index.sortlevel(0) |
| 73 | tm.assert_index_equal(right.index, exp_index) |
| 74 | |
| 75 | tups = list(map(tuple, df[["A", "B", "C", "D", "E", "F", "G", "H"]].values)) |
| 76 | tups = com.asarray_tuplesafe(tups) |
| 77 | |
| 78 | expected = df.groupby(tups).sum()["values"] |
| 79 | |
| 80 | for k, v in expected.items(): |
| 81 | assert left[k] == right[k[::-1]] |
| 82 | assert left[k] == v |
| 83 | assert len(left) == len(right) |
| 84 | |
| 85 | def test_int64_overflow_groupby_large_range(self): |
| 86 | # GH9096 |