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