76 lines
2.3 KiB
Python
76 lines
2.3 KiB
Python
import pytest
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import pandas as pd
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import pandas._testing as tm
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@pytest.mark.parametrize(
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"values, dtype",
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[
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([], "object"),
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([1, 2, 3], "int64"),
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([1.0, 2.0, 3.0], "float64"),
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(["a", "b", "c"], "object"),
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(["a", "b", "c"], "string"),
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([1, 2, 3], "datetime64[ns]"),
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([1, 2, 3], "datetime64[ns, CET]"),
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([1, 2, 3], "timedelta64[ns]"),
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(["2000", "2001", "2002"], "Period[D]"),
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([1, 0, 3], "Sparse"),
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([pd.Interval(0, 1), pd.Interval(1, 2), pd.Interval(3, 4)], "interval"),
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],
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)
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@pytest.mark.parametrize(
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"mask", [[True, False, False], [True, True, True], [False, False, False]]
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)
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@pytest.mark.parametrize("indexer_class", [list, pd.array, pd.Index, pd.Series])
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@pytest.mark.parametrize("frame", [True, False])
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def test_series_mask_boolean(values, dtype, mask, indexer_class, frame):
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# In case len(values) < 3
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index = ["a", "b", "c"][: len(values)]
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mask = mask[: len(values)]
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obj = pd.Series(values, dtype=dtype, index=index)
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if frame:
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if len(values) == 0:
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# Otherwise obj is an empty DataFrame with shape (0, 1)
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obj = pd.DataFrame(dtype=dtype, index=index)
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else:
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obj = obj.to_frame()
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if indexer_class is pd.array:
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mask = pd.array(mask, dtype="boolean")
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elif indexer_class is pd.Series:
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mask = pd.Series(mask, index=obj.index, dtype="boolean")
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else:
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mask = indexer_class(mask)
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expected = obj[mask]
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result = obj[mask]
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tm.assert_equal(result, expected)
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if indexer_class is pd.Series:
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msg = "iLocation based boolean indexing cannot use an indexable as a mask"
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with pytest.raises(ValueError, match=msg):
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result = obj.iloc[mask]
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tm.assert_equal(result, expected)
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else:
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result = obj.iloc[mask]
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tm.assert_equal(result, expected)
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result = obj.loc[mask]
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tm.assert_equal(result, expected)
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def test_na_treated_as_false(frame_or_series, indexer_sli):
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# https://github.com/pandas-dev/pandas/issues/31503
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obj = frame_or_series([1, 2, 3])
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mask = pd.array([True, False, None], dtype="boolean")
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result = indexer_sli(obj)[mask]
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expected = indexer_sli(obj)[mask.fillna(False)]
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tm.assert_equal(result, expected)
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