521 lines
20 KiB
Python
521 lines
20 KiB
Python
import re
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import numpy as np
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import pytest
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from pandas import Categorical, CategoricalIndex, DataFrame, Index, Series
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import pandas._testing as tm
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from pandas.core.arrays.categorical import recode_for_categories
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from pandas.tests.arrays.categorical.common import TestCategorical
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class TestCategoricalAPI:
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def test_ordered_api(self):
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# GH 9347
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cat1 = Categorical(list("acb"), ordered=False)
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tm.assert_index_equal(cat1.categories, Index(["a", "b", "c"]))
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assert not cat1.ordered
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cat2 = Categorical(list("acb"), categories=list("bca"), ordered=False)
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tm.assert_index_equal(cat2.categories, Index(["b", "c", "a"]))
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assert not cat2.ordered
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cat3 = Categorical(list("acb"), ordered=True)
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tm.assert_index_equal(cat3.categories, Index(["a", "b", "c"]))
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assert cat3.ordered
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cat4 = Categorical(list("acb"), categories=list("bca"), ordered=True)
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tm.assert_index_equal(cat4.categories, Index(["b", "c", "a"]))
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assert cat4.ordered
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def test_set_ordered(self):
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cat = Categorical(["a", "b", "c", "a"], ordered=True)
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cat2 = cat.as_unordered()
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assert not cat2.ordered
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cat2 = cat.as_ordered()
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assert cat2.ordered
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cat2.as_unordered(inplace=True)
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assert not cat2.ordered
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cat2.as_ordered(inplace=True)
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assert cat2.ordered
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assert cat2.set_ordered(True).ordered
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assert not cat2.set_ordered(False).ordered
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cat2.set_ordered(True, inplace=True)
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assert cat2.ordered
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cat2.set_ordered(False, inplace=True)
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assert not cat2.ordered
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# removed in 0.19.0
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msg = "can't set attribute"
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with pytest.raises(AttributeError, match=msg):
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cat.ordered = True
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with pytest.raises(AttributeError, match=msg):
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cat.ordered = False
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def test_rename_categories(self):
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cat = Categorical(["a", "b", "c", "a"])
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# inplace=False: the old one must not be changed
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res = cat.rename_categories([1, 2, 3])
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tm.assert_numpy_array_equal(
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res.__array__(), np.array([1, 2, 3, 1], dtype=np.int64)
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)
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tm.assert_index_equal(res.categories, Index([1, 2, 3]))
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exp_cat = np.array(["a", "b", "c", "a"], dtype=np.object_)
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tm.assert_numpy_array_equal(cat.__array__(), exp_cat)
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exp_cat = Index(["a", "b", "c"])
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tm.assert_index_equal(cat.categories, exp_cat)
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# GH18862 (let rename_categories take callables)
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result = cat.rename_categories(lambda x: x.upper())
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expected = Categorical(["A", "B", "C", "A"])
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tm.assert_categorical_equal(result, expected)
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# and now inplace
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res = cat.rename_categories([1, 2, 3], inplace=True)
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assert res is None
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tm.assert_numpy_array_equal(
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cat.__array__(), np.array([1, 2, 3, 1], dtype=np.int64)
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)
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tm.assert_index_equal(cat.categories, Index([1, 2, 3]))
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@pytest.mark.parametrize("new_categories", [[1, 2, 3, 4], [1, 2]])
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def test_rename_categories_wrong_length_raises(self, new_categories):
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cat = Categorical(["a", "b", "c", "a"])
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msg = (
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"new categories need to have the same number of items as the "
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"old categories!"
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)
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with pytest.raises(ValueError, match=msg):
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cat.rename_categories(new_categories)
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def test_rename_categories_series(self):
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# https://github.com/pandas-dev/pandas/issues/17981
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c = Categorical(["a", "b"])
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result = c.rename_categories(Series([0, 1], index=["a", "b"]))
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expected = Categorical([0, 1])
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tm.assert_categorical_equal(result, expected)
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def test_rename_categories_dict(self):
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# GH 17336
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cat = Categorical(["a", "b", "c", "d"])
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res = cat.rename_categories({"a": 4, "b": 3, "c": 2, "d": 1})
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expected = Index([4, 3, 2, 1])
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tm.assert_index_equal(res.categories, expected)
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# Test for inplace
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res = cat.rename_categories({"a": 4, "b": 3, "c": 2, "d": 1}, inplace=True)
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assert res is None
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tm.assert_index_equal(cat.categories, expected)
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# Test for dicts of smaller length
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cat = Categorical(["a", "b", "c", "d"])
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res = cat.rename_categories({"a": 1, "c": 3})
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expected = Index([1, "b", 3, "d"])
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tm.assert_index_equal(res.categories, expected)
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# Test for dicts with bigger length
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cat = Categorical(["a", "b", "c", "d"])
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res = cat.rename_categories({"a": 1, "b": 2, "c": 3, "d": 4, "e": 5, "f": 6})
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expected = Index([1, 2, 3, 4])
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tm.assert_index_equal(res.categories, expected)
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# Test for dicts with no items from old categories
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cat = Categorical(["a", "b", "c", "d"])
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res = cat.rename_categories({"f": 1, "g": 3})
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expected = Index(["a", "b", "c", "d"])
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tm.assert_index_equal(res.categories, expected)
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def test_reorder_categories(self):
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cat = Categorical(["a", "b", "c", "a"], ordered=True)
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old = cat.copy()
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new = Categorical(
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["a", "b", "c", "a"], categories=["c", "b", "a"], ordered=True
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)
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# first inplace == False
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res = cat.reorder_categories(["c", "b", "a"])
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# cat must be the same as before
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tm.assert_categorical_equal(cat, old)
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# only res is changed
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tm.assert_categorical_equal(res, new)
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# inplace == True
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res = cat.reorder_categories(["c", "b", "a"], inplace=True)
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assert res is None
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tm.assert_categorical_equal(cat, new)
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@pytest.mark.parametrize(
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"new_categories",
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[
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["a"], # not all "old" included in "new"
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["a", "b", "d"], # still not all "old" in "new"
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["a", "b", "c", "d"], # all "old" included in "new", but too long
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],
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)
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def test_reorder_categories_raises(self, new_categories):
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cat = Categorical(["a", "b", "c", "a"], ordered=True)
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msg = "items in new_categories are not the same as in old categories"
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with pytest.raises(ValueError, match=msg):
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cat.reorder_categories(new_categories)
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def test_add_categories(self):
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cat = Categorical(["a", "b", "c", "a"], ordered=True)
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old = cat.copy()
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new = Categorical(
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["a", "b", "c", "a"], categories=["a", "b", "c", "d"], ordered=True
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)
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# first inplace == False
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res = cat.add_categories("d")
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tm.assert_categorical_equal(cat, old)
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tm.assert_categorical_equal(res, new)
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res = cat.add_categories(["d"])
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tm.assert_categorical_equal(cat, old)
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tm.assert_categorical_equal(res, new)
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# inplace == True
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res = cat.add_categories("d", inplace=True)
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tm.assert_categorical_equal(cat, new)
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assert res is None
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# GH 9927
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cat = Categorical(list("abc"), ordered=True)
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expected = Categorical(list("abc"), categories=list("abcde"), ordered=True)
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# test with Series, np.array, index, list
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res = cat.add_categories(Series(["d", "e"]))
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tm.assert_categorical_equal(res, expected)
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res = cat.add_categories(np.array(["d", "e"]))
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tm.assert_categorical_equal(res, expected)
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res = cat.add_categories(Index(["d", "e"]))
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tm.assert_categorical_equal(res, expected)
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res = cat.add_categories(["d", "e"])
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tm.assert_categorical_equal(res, expected)
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def test_add_categories_existing_raises(self):
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# new is in old categories
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cat = Categorical(["a", "b", "c", "d"], ordered=True)
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msg = re.escape("new categories must not include old categories: {'d'}")
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with pytest.raises(ValueError, match=msg):
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cat.add_categories(["d"])
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def test_set_categories(self):
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cat = Categorical(["a", "b", "c", "a"], ordered=True)
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exp_categories = Index(["c", "b", "a"])
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exp_values = np.array(["a", "b", "c", "a"], dtype=np.object_)
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res = cat.set_categories(["c", "b", "a"], inplace=True)
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tm.assert_index_equal(cat.categories, exp_categories)
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tm.assert_numpy_array_equal(cat.__array__(), exp_values)
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assert res is None
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res = cat.set_categories(["a", "b", "c"])
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# cat must be the same as before
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tm.assert_index_equal(cat.categories, exp_categories)
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tm.assert_numpy_array_equal(cat.__array__(), exp_values)
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# only res is changed
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exp_categories_back = Index(["a", "b", "c"])
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tm.assert_index_equal(res.categories, exp_categories_back)
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tm.assert_numpy_array_equal(res.__array__(), exp_values)
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# not all "old" included in "new" -> all not included ones are now
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# np.nan
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cat = Categorical(["a", "b", "c", "a"], ordered=True)
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res = cat.set_categories(["a"])
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tm.assert_numpy_array_equal(res.codes, np.array([0, -1, -1, 0], dtype=np.int8))
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# still not all "old" in "new"
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res = cat.set_categories(["a", "b", "d"])
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tm.assert_numpy_array_equal(res.codes, np.array([0, 1, -1, 0], dtype=np.int8))
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tm.assert_index_equal(res.categories, Index(["a", "b", "d"]))
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# all "old" included in "new"
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cat = cat.set_categories(["a", "b", "c", "d"])
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exp_categories = Index(["a", "b", "c", "d"])
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tm.assert_index_equal(cat.categories, exp_categories)
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# internals...
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c = Categorical([1, 2, 3, 4, 1], categories=[1, 2, 3, 4], ordered=True)
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tm.assert_numpy_array_equal(c._codes, np.array([0, 1, 2, 3, 0], dtype=np.int8))
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tm.assert_index_equal(c.categories, Index([1, 2, 3, 4]))
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exp = np.array([1, 2, 3, 4, 1], dtype=np.int64)
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tm.assert_numpy_array_equal(np.asarray(c), exp)
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# all "pointers" to '4' must be changed from 3 to 0,...
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c = c.set_categories([4, 3, 2, 1])
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# positions are changed
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tm.assert_numpy_array_equal(c._codes, np.array([3, 2, 1, 0, 3], dtype=np.int8))
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# categories are now in new order
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tm.assert_index_equal(c.categories, Index([4, 3, 2, 1]))
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# output is the same
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exp = np.array([1, 2, 3, 4, 1], dtype=np.int64)
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tm.assert_numpy_array_equal(np.asarray(c), exp)
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assert c.min() == 4
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assert c.max() == 1
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# set_categories should set the ordering if specified
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c2 = c.set_categories([4, 3, 2, 1], ordered=False)
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assert not c2.ordered
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tm.assert_numpy_array_equal(np.asarray(c), np.asarray(c2))
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# set_categories should pass thru the ordering
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c2 = c.set_ordered(False).set_categories([4, 3, 2, 1])
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assert not c2.ordered
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tm.assert_numpy_array_equal(np.asarray(c), np.asarray(c2))
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def test_to_dense_deprecated(self):
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cat = Categorical(["a", "b", "c", "a"], ordered=True)
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with tm.assert_produces_warning(FutureWarning):
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cat.to_dense()
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@pytest.mark.parametrize(
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"values, categories, new_categories",
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[
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# No NaNs, same cats, same order
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(["a", "b", "a"], ["a", "b"], ["a", "b"]),
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# No NaNs, same cats, different order
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(["a", "b", "a"], ["a", "b"], ["b", "a"]),
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# Same, unsorted
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(["b", "a", "a"], ["a", "b"], ["a", "b"]),
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# No NaNs, same cats, different order
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(["b", "a", "a"], ["a", "b"], ["b", "a"]),
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# NaNs
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(["a", "b", "c"], ["a", "b"], ["a", "b"]),
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(["a", "b", "c"], ["a", "b"], ["b", "a"]),
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(["b", "a", "c"], ["a", "b"], ["a", "b"]),
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(["b", "a", "c"], ["a", "b"], ["a", "b"]),
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# Introduce NaNs
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(["a", "b", "c"], ["a", "b"], ["a"]),
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(["a", "b", "c"], ["a", "b"], ["b"]),
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(["b", "a", "c"], ["a", "b"], ["a"]),
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(["b", "a", "c"], ["a", "b"], ["a"]),
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# No overlap
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(["a", "b", "c"], ["a", "b"], ["d", "e"]),
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],
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)
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@pytest.mark.parametrize("ordered", [True, False])
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def test_set_categories_many(self, values, categories, new_categories, ordered):
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c = Categorical(values, categories)
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expected = Categorical(values, new_categories, ordered)
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result = c.set_categories(new_categories, ordered=ordered)
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tm.assert_categorical_equal(result, expected)
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def test_set_categories_rename_less(self):
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# GH 24675
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cat = Categorical(["A", "B"])
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result = cat.set_categories(["A"], rename=True)
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expected = Categorical(["A", np.nan])
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tm.assert_categorical_equal(result, expected)
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def test_set_categories_private(self):
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cat = Categorical(["a", "b", "c"], categories=["a", "b", "c", "d"])
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cat._set_categories(["a", "c", "d", "e"])
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expected = Categorical(["a", "c", "d"], categories=list("acde"))
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tm.assert_categorical_equal(cat, expected)
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# fastpath
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cat = Categorical(["a", "b", "c"], categories=["a", "b", "c", "d"])
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cat._set_categories(["a", "c", "d", "e"], fastpath=True)
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expected = Categorical(["a", "c", "d"], categories=list("acde"))
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tm.assert_categorical_equal(cat, expected)
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def test_remove_categories(self):
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cat = Categorical(["a", "b", "c", "a"], ordered=True)
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old = cat.copy()
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new = Categorical(["a", "b", np.nan, "a"], categories=["a", "b"], ordered=True)
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# first inplace == False
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res = cat.remove_categories("c")
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tm.assert_categorical_equal(cat, old)
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tm.assert_categorical_equal(res, new)
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res = cat.remove_categories(["c"])
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tm.assert_categorical_equal(cat, old)
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tm.assert_categorical_equal(res, new)
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# inplace == True
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res = cat.remove_categories("c", inplace=True)
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tm.assert_categorical_equal(cat, new)
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assert res is None
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@pytest.mark.parametrize("removals", [["c"], ["c", np.nan], "c", ["c", "c"]])
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def test_remove_categories_raises(self, removals):
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cat = Categorical(["a", "b", "a"])
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message = re.escape("removals must all be in old categories: {'c'}")
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with pytest.raises(ValueError, match=message):
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cat.remove_categories(removals)
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def test_remove_unused_categories(self):
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c = Categorical(["a", "b", "c", "d", "a"], categories=["a", "b", "c", "d", "e"])
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exp_categories_all = Index(["a", "b", "c", "d", "e"])
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exp_categories_dropped = Index(["a", "b", "c", "d"])
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tm.assert_index_equal(c.categories, exp_categories_all)
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res = c.remove_unused_categories()
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tm.assert_index_equal(res.categories, exp_categories_dropped)
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tm.assert_index_equal(c.categories, exp_categories_all)
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with tm.assert_produces_warning(FutureWarning):
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# issue #37643 inplace kwarg deprecated
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res = c.remove_unused_categories(inplace=True)
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tm.assert_index_equal(c.categories, exp_categories_dropped)
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assert res is None
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# with NaN values (GH11599)
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c = Categorical(["a", "b", "c", np.nan], categories=["a", "b", "c", "d", "e"])
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res = c.remove_unused_categories()
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tm.assert_index_equal(res.categories, Index(np.array(["a", "b", "c"])))
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exp_codes = np.array([0, 1, 2, -1], dtype=np.int8)
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tm.assert_numpy_array_equal(res.codes, exp_codes)
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tm.assert_index_equal(c.categories, exp_categories_all)
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val = ["F", np.nan, "D", "B", "D", "F", np.nan]
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cat = Categorical(values=val, categories=list("ABCDEFG"))
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out = cat.remove_unused_categories()
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tm.assert_index_equal(out.categories, Index(["B", "D", "F"]))
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exp_codes = np.array([2, -1, 1, 0, 1, 2, -1], dtype=np.int8)
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tm.assert_numpy_array_equal(out.codes, exp_codes)
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assert out.tolist() == val
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alpha = list("abcdefghijklmnopqrstuvwxyz")
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val = np.random.choice(alpha[::2], 10000).astype("object")
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val[np.random.choice(len(val), 100)] = np.nan
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cat = Categorical(values=val, categories=alpha)
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out = cat.remove_unused_categories()
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assert out.tolist() == val.tolist()
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class TestCategoricalAPIWithFactor(TestCategorical):
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def test_describe(self):
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# string type
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desc = self.factor.describe()
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assert self.factor.ordered
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exp_index = CategoricalIndex(
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["a", "b", "c"], name="categories", ordered=self.factor.ordered
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)
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expected = DataFrame(
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{"counts": [3, 2, 3], "freqs": [3 / 8.0, 2 / 8.0, 3 / 8.0]}, index=exp_index
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)
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tm.assert_frame_equal(desc, expected)
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# check unused categories
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cat = self.factor.copy()
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cat.set_categories(["a", "b", "c", "d"], inplace=True)
|
|
desc = cat.describe()
|
|
|
|
exp_index = CategoricalIndex(
|
|
list("abcd"), ordered=self.factor.ordered, name="categories"
|
|
)
|
|
expected = DataFrame(
|
|
{"counts": [3, 2, 3, 0], "freqs": [3 / 8.0, 2 / 8.0, 3 / 8.0, 0]},
|
|
index=exp_index,
|
|
)
|
|
tm.assert_frame_equal(desc, expected)
|
|
|
|
# check an integer one
|
|
cat = Categorical([1, 2, 3, 1, 2, 3, 3, 2, 1, 1, 1])
|
|
desc = cat.describe()
|
|
exp_index = CategoricalIndex([1, 2, 3], ordered=cat.ordered, name="categories")
|
|
expected = DataFrame(
|
|
{"counts": [5, 3, 3], "freqs": [5 / 11.0, 3 / 11.0, 3 / 11.0]},
|
|
index=exp_index,
|
|
)
|
|
tm.assert_frame_equal(desc, expected)
|
|
|
|
# https://github.com/pandas-dev/pandas/issues/3678
|
|
# describe should work with NaN
|
|
cat = Categorical([np.nan, 1, 2, 2])
|
|
desc = cat.describe()
|
|
expected = DataFrame(
|
|
{"counts": [1, 2, 1], "freqs": [1 / 4.0, 2 / 4.0, 1 / 4.0]},
|
|
index=CategoricalIndex(
|
|
[1, 2, np.nan], categories=[1, 2], name="categories"
|
|
),
|
|
)
|
|
tm.assert_frame_equal(desc, expected)
|
|
|
|
def test_set_categories_inplace(self):
|
|
cat = self.factor.copy()
|
|
cat.set_categories(["a", "b", "c", "d"], inplace=True)
|
|
tm.assert_index_equal(cat.categories, Index(["a", "b", "c", "d"]))
|
|
|
|
|
|
class TestPrivateCategoricalAPI:
|
|
def test_codes_immutable(self):
|
|
|
|
# Codes should be read only
|
|
c = Categorical(["a", "b", "c", "a", np.nan])
|
|
exp = np.array([0, 1, 2, 0, -1], dtype="int8")
|
|
tm.assert_numpy_array_equal(c.codes, exp)
|
|
|
|
# Assignments to codes should raise
|
|
with pytest.raises(AttributeError, match="can't set attribute"):
|
|
c.codes = np.array([0, 1, 2, 0, 1], dtype="int8")
|
|
|
|
# changes in the codes array should raise
|
|
codes = c.codes
|
|
|
|
with pytest.raises(ValueError, match="assignment destination is read-only"):
|
|
codes[4] = 1
|
|
|
|
# But even after getting the codes, the original array should still be
|
|
# writeable!
|
|
c[4] = "a"
|
|
exp = np.array([0, 1, 2, 0, 0], dtype="int8")
|
|
tm.assert_numpy_array_equal(c.codes, exp)
|
|
c._codes[4] = 2
|
|
exp = np.array([0, 1, 2, 0, 2], dtype="int8")
|
|
tm.assert_numpy_array_equal(c.codes, exp)
|
|
|
|
@pytest.mark.parametrize(
|
|
"codes, old, new, expected",
|
|
[
|
|
([0, 1], ["a", "b"], ["a", "b"], [0, 1]),
|
|
([0, 1], ["b", "a"], ["b", "a"], [0, 1]),
|
|
([0, 1], ["a", "b"], ["b", "a"], [1, 0]),
|
|
([0, 1], ["b", "a"], ["a", "b"], [1, 0]),
|
|
([0, 1, 0, 1], ["a", "b"], ["a", "b", "c"], [0, 1, 0, 1]),
|
|
([0, 1, 2, 2], ["a", "b", "c"], ["a", "b"], [0, 1, -1, -1]),
|
|
([0, 1, -1], ["a", "b", "c"], ["a", "b", "c"], [0, 1, -1]),
|
|
([0, 1, -1], ["a", "b", "c"], ["b"], [-1, 0, -1]),
|
|
([0, 1, -1], ["a", "b", "c"], ["d"], [-1, -1, -1]),
|
|
([0, 1, -1], ["a", "b", "c"], [], [-1, -1, -1]),
|
|
([-1, -1], [], ["a", "b"], [-1, -1]),
|
|
([1, 0], ["b", "a"], ["a", "b"], [0, 1]),
|
|
],
|
|
)
|
|
def test_recode_to_categories(self, codes, old, new, expected):
|
|
codes = np.asanyarray(codes, dtype=np.int8)
|
|
expected = np.asanyarray(expected, dtype=np.int8)
|
|
old = Index(old)
|
|
new = Index(new)
|
|
result = recode_for_categories(codes, old, new)
|
|
tm.assert_numpy_array_equal(result, expected)
|
|
|
|
def test_recode_to_categories_large(self):
|
|
N = 1000
|
|
codes = np.arange(N)
|
|
old = Index(codes)
|
|
expected = np.arange(N - 1, -1, -1, dtype=np.int16)
|
|
new = Index(expected)
|
|
result = recode_for_categories(codes, old, new)
|
|
tm.assert_numpy_array_equal(result, expected)
|