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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Index,
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)
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import pandas._testing as tm
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class TestCategoricalSort:
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def test_argsort(self):
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c = Categorical([5, 3, 1, 4, 2], ordered=True)
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expected = np.array([2, 4, 1, 3, 0])
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tm.assert_numpy_array_equal(
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c.argsort(ascending=True), expected, check_dtype=False
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)
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expected = expected[::-1]
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tm.assert_numpy_array_equal(
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c.argsort(ascending=False), expected, check_dtype=False
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)
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def test_numpy_argsort(self):
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c = Categorical([5, 3, 1, 4, 2], ordered=True)
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expected = np.array([2, 4, 1, 3, 0])
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tm.assert_numpy_array_equal(np.argsort(c), expected, check_dtype=False)
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tm.assert_numpy_array_equal(
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np.argsort(c, kind="mergesort"), expected, check_dtype=False
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)
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msg = "the 'axis' parameter is not supported"
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with pytest.raises(ValueError, match=msg):
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np.argsort(c, axis=0)
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msg = "the 'order' parameter is not supported"
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with pytest.raises(ValueError, match=msg):
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np.argsort(c, order="C")
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def test_sort_values(self):
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# unordered cats are sortable
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cat = Categorical(["a", "b", "b", "a"], ordered=False)
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cat.sort_values()
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cat = Categorical(["a", "c", "b", "d"], ordered=True)
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# sort_values
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res = cat.sort_values()
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exp = np.array(["a", "b", "c", "d"], dtype=object)
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tm.assert_numpy_array_equal(res.__array__(), exp)
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tm.assert_index_equal(res.categories, cat.categories)
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cat = Categorical(
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["a", "c", "b", "d"], categories=["a", "b", "c", "d"], ordered=True
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)
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res = cat.sort_values()
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exp = np.array(["a", "b", "c", "d"], dtype=object)
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tm.assert_numpy_array_equal(res.__array__(), exp)
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tm.assert_index_equal(res.categories, cat.categories)
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res = cat.sort_values(ascending=False)
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exp = np.array(["d", "c", "b", "a"], dtype=object)
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tm.assert_numpy_array_equal(res.__array__(), exp)
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tm.assert_index_equal(res.categories, cat.categories)
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# sort (inplace order)
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cat1 = cat.copy()
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orig_codes = cat1._codes
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cat1.sort_values(inplace=True)
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assert cat1._codes is orig_codes
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exp = np.array(["a", "b", "c", "d"], dtype=object)
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tm.assert_numpy_array_equal(cat1.__array__(), exp)
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tm.assert_index_equal(res.categories, cat.categories)
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# reverse
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cat = Categorical(["a", "c", "c", "b", "d"], ordered=True)
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res = cat.sort_values(ascending=False)
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exp_val = np.array(["d", "c", "c", "b", "a"], dtype=object)
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exp_categories = Index(["a", "b", "c", "d"])
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tm.assert_numpy_array_equal(res.__array__(), exp_val)
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tm.assert_index_equal(res.categories, exp_categories)
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def test_sort_values_na_position(self):
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# see gh-12882
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cat = Categorical([5, 2, np.nan, 2, np.nan], ordered=True)
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exp_categories = Index([2, 5])
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exp = np.array([2.0, 2.0, 5.0, np.nan, np.nan])
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res = cat.sort_values() # default arguments
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tm.assert_numpy_array_equal(res.__array__(), exp)
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tm.assert_index_equal(res.categories, exp_categories)
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exp = np.array([np.nan, np.nan, 2.0, 2.0, 5.0])
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res = cat.sort_values(ascending=True, na_position="first")
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tm.assert_numpy_array_equal(res.__array__(), exp)
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tm.assert_index_equal(res.categories, exp_categories)
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exp = np.array([np.nan, np.nan, 5.0, 2.0, 2.0])
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res = cat.sort_values(ascending=False, na_position="first")
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tm.assert_numpy_array_equal(res.__array__(), exp)
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tm.assert_index_equal(res.categories, exp_categories)
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exp = np.array([2.0, 2.0, 5.0, np.nan, np.nan])
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res = cat.sort_values(ascending=True, na_position="last")
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tm.assert_numpy_array_equal(res.__array__(), exp)
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tm.assert_index_equal(res.categories, exp_categories)
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exp = np.array([5.0, 2.0, 2.0, np.nan, np.nan])
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res = cat.sort_values(ascending=False, na_position="last")
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tm.assert_numpy_array_equal(res.__array__(), exp)
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tm.assert_index_equal(res.categories, exp_categories)
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cat = Categorical(["a", "c", "b", "d", np.nan], ordered=True)
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res = cat.sort_values(ascending=False, na_position="last")
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exp_val = np.array(["d", "c", "b", "a", np.nan], dtype=object)
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exp_categories = Index(["a", "b", "c", "d"])
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tm.assert_numpy_array_equal(res.__array__(), exp_val)
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tm.assert_index_equal(res.categories, exp_categories)
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cat = Categorical(["a", "c", "b", "d", np.nan], ordered=True)
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res = cat.sort_values(ascending=False, na_position="first")
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exp_val = np.array([np.nan, "d", "c", "b", "a"], dtype=object)
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exp_categories = Index(["a", "b", "c", "d"])
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tm.assert_numpy_array_equal(res.__array__(), exp_val)
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tm.assert_index_equal(res.categories, exp_categories)
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