import numpy as np import pytest from pandas import Categorical, CategoricalDtype, CategoricalIndex, Index, IntervalIndex import pandas._testing as tm class TestAstype: def test_astype(self): ci = CategoricalIndex(list("aabbca"), categories=list("cab"), ordered=False) result = ci.astype(object) tm.assert_index_equal(result, Index(np.array(ci))) # this IS equal, but not the same class assert result.equals(ci) assert isinstance(result, Index) assert not isinstance(result, CategoricalIndex) # interval ii = IntervalIndex.from_arrays(left=[-0.001, 2.0], right=[2, 4], closed="right") ci = CategoricalIndex( Categorical.from_codes([0, 1, -1], categories=ii, ordered=True) ) result = ci.astype("interval") expected = ii.take([0, 1, -1]) tm.assert_index_equal(result, expected) result = IntervalIndex(result.values) tm.assert_index_equal(result, expected) @pytest.mark.parametrize("name", [None, "foo"]) @pytest.mark.parametrize("dtype_ordered", [True, False]) @pytest.mark.parametrize("index_ordered", [True, False]) def test_astype_category(self, name, dtype_ordered, index_ordered): # GH#18630 index = CategoricalIndex( list("aabbca"), categories=list("cab"), ordered=index_ordered ) if name: index = index.rename(name) # standard categories dtype = CategoricalDtype(ordered=dtype_ordered) result = index.astype(dtype) expected = CategoricalIndex( index.tolist(), name=name, categories=index.categories, ordered=dtype_ordered, ) tm.assert_index_equal(result, expected) # non-standard categories dtype = CategoricalDtype(index.unique().tolist()[:-1], dtype_ordered) result = index.astype(dtype) expected = CategoricalIndex(index.tolist(), name=name, dtype=dtype) tm.assert_index_equal(result, expected) if dtype_ordered is False: # dtype='category' can't specify ordered, so only test once result = index.astype("category") expected = index tm.assert_index_equal(result, expected)