import numpy as np
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import pytest
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from pandas import (
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Categorical,
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CategoricalDtype,
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CategoricalIndex,
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Index,
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)
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import pandas._testing as tm
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class TestCategoricalIndexConstructors:
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def test_construction_disallows_scalar(self):
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msg = "must be called with a collection of some kind"
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with pytest.raises(TypeError, match=msg):
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CategoricalIndex(data=1, categories=list("abcd"), ordered=False)
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with pytest.raises(TypeError, match=msg):
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CategoricalIndex(categories=list("abcd"), ordered=False)
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def test_construction(self):
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ci = CategoricalIndex(list("aabbca"), categories=list("abcd"), ordered=False)
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categories = ci.categories
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result = Index(ci)
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tm.assert_index_equal(result, ci, exact=True)
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assert not result.ordered
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result = Index(ci.values)
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tm.assert_index_equal(result, ci, exact=True)
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assert not result.ordered
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# empty
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result = CategoricalIndex([], categories=categories)
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tm.assert_index_equal(result.categories, Index(categories))
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tm.assert_numpy_array_equal(result.codes, np.array([], dtype="int8"))
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assert not result.ordered
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# passing categories
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result = CategoricalIndex(list("aabbca"), categories=categories)
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tm.assert_index_equal(result.categories, Index(categories))
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tm.assert_numpy_array_equal(
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result.codes, np.array([0, 0, 1, 1, 2, 0], dtype="int8")
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)
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c = Categorical(list("aabbca"))
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result = CategoricalIndex(c)
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tm.assert_index_equal(result.categories, Index(list("abc")))
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tm.assert_numpy_array_equal(
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result.codes, np.array([0, 0, 1, 1, 2, 0], dtype="int8")
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)
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assert not result.ordered
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result = CategoricalIndex(c, categories=categories)
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tm.assert_index_equal(result.categories, Index(categories))
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tm.assert_numpy_array_equal(
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result.codes, np.array([0, 0, 1, 1, 2, 0], dtype="int8")
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)
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assert not result.ordered
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ci = CategoricalIndex(c, categories=list("abcd"))
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result = CategoricalIndex(ci)
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tm.assert_index_equal(result.categories, Index(categories))
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tm.assert_numpy_array_equal(
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result.codes, np.array([0, 0, 1, 1, 2, 0], dtype="int8")
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)
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assert not result.ordered
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result = CategoricalIndex(ci, categories=list("ab"))
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tm.assert_index_equal(result.categories, Index(list("ab")))
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tm.assert_numpy_array_equal(
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result.codes, np.array([0, 0, 1, 1, -1, 0], dtype="int8")
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)
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assert not result.ordered
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result = CategoricalIndex(ci, categories=list("ab"), ordered=True)
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tm.assert_index_equal(result.categories, Index(list("ab")))
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tm.assert_numpy_array_equal(
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result.codes, np.array([0, 0, 1, 1, -1, 0], dtype="int8")
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)
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assert result.ordered
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result = CategoricalIndex(ci, categories=list("ab"), ordered=True)
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expected = CategoricalIndex(
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ci, categories=list("ab"), ordered=True, dtype="category"
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)
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tm.assert_index_equal(result, expected, exact=True)
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# turn me to an Index
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result = Index(np.array(ci))
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assert isinstance(result, Index)
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assert not isinstance(result, CategoricalIndex)
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def test_construction_with_dtype(self):
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# specify dtype
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ci = CategoricalIndex(list("aabbca"), categories=list("abc"), ordered=False)
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result = Index(np.array(ci), dtype="category")
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tm.assert_index_equal(result, ci, exact=True)
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result = Index(np.array(ci).tolist(), dtype="category")
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tm.assert_index_equal(result, ci, exact=True)
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# these are generally only equal when the categories are reordered
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ci = CategoricalIndex(list("aabbca"), categories=list("cab"), ordered=False)
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result = Index(np.array(ci), dtype="category").reorder_categories(ci.categories)
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tm.assert_index_equal(result, ci, exact=True)
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# make sure indexes are handled
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idx = Index(range(3))
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expected = CategoricalIndex([0, 1, 2], categories=idx, ordered=True)
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result = CategoricalIndex(idx, categories=idx, ordered=True)
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tm.assert_index_equal(result, expected, exact=True)
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def test_construction_empty_with_bool_categories(self):
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# see GH#22702
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cat = CategoricalIndex([], categories=[True, False])
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categories = sorted(cat.categories.tolist())
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assert categories == [False, True]
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def test_construction_with_categorical_dtype(self):
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# construction with CategoricalDtype
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# GH#18109
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data, cats, ordered = "a a b b".split(), "c b a".split(), True
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dtype = CategoricalDtype(categories=cats, ordered=ordered)
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result = CategoricalIndex(data, dtype=dtype)
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expected = CategoricalIndex(data, categories=cats, ordered=ordered)
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tm.assert_index_equal(result, expected, exact=True)
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# GH#19032
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result = Index(data, dtype=dtype)
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tm.assert_index_equal(result, expected, exact=True)
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# error when combining categories/ordered and dtype kwargs
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msg = "Cannot specify `categories` or `ordered` together with `dtype`."
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with pytest.raises(ValueError, match=msg):
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CategoricalIndex(data, categories=cats, dtype=dtype)
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with pytest.raises(ValueError, match=msg):
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CategoricalIndex(data, ordered=ordered, dtype=dtype)
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