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- # -*- coding: utf-8 -*-
- import collections
- import numpy as np
- import pytest
- from pandas.compat import lrange
- from pandas.core.dtypes.dtypes import CategoricalDtype
- from pandas import Categorical, Index, isna
- import pandas.util.testing as tm
- class TestCategoricalMissing(object):
- def test_na_flags_int_categories(self):
- # #1457
- categories = lrange(10)
- labels = np.random.randint(0, 10, 20)
- labels[::5] = -1
- cat = Categorical(labels, categories, fastpath=True)
- repr(cat)
- tm.assert_numpy_array_equal(isna(cat), labels == -1)
- def test_nan_handling(self):
- # Nans are represented as -1 in codes
- c = Categorical(["a", "b", np.nan, "a"])
- tm.assert_index_equal(c.categories, Index(["a", "b"]))
- tm.assert_numpy_array_equal(c._codes, np.array([0, 1, -1, 0],
- dtype=np.int8))
- c[1] = np.nan
- tm.assert_index_equal(c.categories, Index(["a", "b"]))
- tm.assert_numpy_array_equal(c._codes, np.array([0, -1, -1, 0],
- dtype=np.int8))
- # Adding nan to categories should make assigned nan point to the
- # category!
- c = Categorical(["a", "b", np.nan, "a"])
- tm.assert_index_equal(c.categories, Index(["a", "b"]))
- tm.assert_numpy_array_equal(c._codes, np.array([0, 1, -1, 0],
- dtype=np.int8))
- def test_set_dtype_nans(self):
- c = Categorical(['a', 'b', np.nan])
- result = c._set_dtype(CategoricalDtype(['a', 'c']))
- tm.assert_numpy_array_equal(result.codes, np.array([0, -1, -1],
- dtype='int8'))
- def test_set_item_nan(self):
- cat = Categorical([1, 2, 3])
- cat[1] = np.nan
- exp = Categorical([1, np.nan, 3], categories=[1, 2, 3])
- tm.assert_categorical_equal(cat, exp)
- @pytest.mark.parametrize('fillna_kwargs, msg', [
- (dict(value=1, method='ffill'),
- "Cannot specify both 'value' and 'method'."),
- (dict(),
- "Must specify a fill 'value' or 'method'."),
- (dict(method='bad'),
- "Invalid fill method. Expecting .* bad"),
- ])
- def test_fillna_raises(self, fillna_kwargs, msg):
- # https://github.com/pandas-dev/pandas/issues/19682
- cat = Categorical([1, 2, 3])
- with pytest.raises(ValueError, match=msg):
- cat.fillna(**fillna_kwargs)
- @pytest.mark.parametrize("named", [True, False])
- def test_fillna_iterable_category(self, named):
- # https://github.com/pandas-dev/pandas/issues/21097
- if named:
- Point = collections.namedtuple("Point", "x y")
- else:
- Point = lambda *args: args # tuple
- cat = Categorical([Point(0, 0), Point(0, 1), None])
- result = cat.fillna(Point(0, 0))
- expected = Categorical([Point(0, 0), Point(0, 1), Point(0, 0)])
- tm.assert_categorical_equal(result, expected)
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