113 lines
		
	
	
		
			3.3 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
			
		
		
	
	
			113 lines
		
	
	
		
			3.3 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
import numpy as np
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import pytest
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import pandas as pd
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from pandas import MultiIndex
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import pandas._testing as tm
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def test_fillna(idx):
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    # GH 11343
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    msg = "isna is not defined for MultiIndex"
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    with pytest.raises(NotImplementedError, match=msg):
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        idx.fillna(idx[0])
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def test_dropna():
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    # GH 6194
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    idx = MultiIndex.from_arrays(
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        [
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            [1, np.nan, 3, np.nan, 5],
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            [1, 2, np.nan, np.nan, 5],
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            ["a", "b", "c", np.nan, "e"],
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        ]
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    )
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    exp = MultiIndex.from_arrays([[1, 5], [1, 5], ["a", "e"]])
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    tm.assert_index_equal(idx.dropna(), exp)
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    tm.assert_index_equal(idx.dropna(how="any"), exp)
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    exp = MultiIndex.from_arrays(
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        [[1, np.nan, 3, 5], [1, 2, np.nan, 5], ["a", "b", "c", "e"]]
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    )
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    tm.assert_index_equal(idx.dropna(how="all"), exp)
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    msg = "invalid how option: xxx"
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    with pytest.raises(ValueError, match=msg):
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        idx.dropna(how="xxx")
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    # GH26408
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    # test if missing values are dropped for multiindex constructed
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    # from codes and values
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    idx = MultiIndex(
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        levels=[[np.nan, None, pd.NaT, "128", 2], [np.nan, None, pd.NaT, "128", 2]],
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        codes=[[0, -1, 1, 2, 3, 4], [0, -1, 3, 3, 3, 4]],
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    )
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    expected = MultiIndex.from_arrays([["128", 2], ["128", 2]])
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    tm.assert_index_equal(idx.dropna(), expected)
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    tm.assert_index_equal(idx.dropna(how="any"), expected)
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    expected = MultiIndex.from_arrays(
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        [[np.nan, np.nan, "128", 2], ["128", "128", "128", 2]]
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    )
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    tm.assert_index_equal(idx.dropna(how="all"), expected)
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def test_nulls(idx):
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    # this is really a smoke test for the methods
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    # as these are adequately tested for function elsewhere
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    msg = "isna is not defined for MultiIndex"
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    with pytest.raises(NotImplementedError, match=msg):
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        idx.isna()
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@pytest.mark.xfail(reason="isna is not defined for MultiIndex")
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def test_hasnans_isnans(idx):
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    # GH 11343, added tests for hasnans / isnans
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    index = idx.copy()
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    # cases in indices doesn't include NaN
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    expected = np.array([False] * len(index), dtype=bool)
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    tm.assert_numpy_array_equal(index._isnan, expected)
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    assert index.hasnans is False
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    index = idx.copy()
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    values = index.values
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    values[1] = np.nan
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    index = type(idx)(values)
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    expected = np.array([False] * len(index), dtype=bool)
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    expected[1] = True
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    tm.assert_numpy_array_equal(index._isnan, expected)
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    assert index.hasnans is True
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def test_nan_stays_float():
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    # GH 7031
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    idx0 = MultiIndex(levels=[["A", "B"], []], codes=[[1, 0], [-1, -1]], names=[0, 1])
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    idx1 = MultiIndex(levels=[["C"], ["D"]], codes=[[0], [0]], names=[0, 1])
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    idxm = idx0.join(idx1, how="outer")
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    assert pd.isna(idx0.get_level_values(1)).all()
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    # the following failed in 0.14.1
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    assert pd.isna(idxm.get_level_values(1)[:-1]).all()
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    df0 = pd.DataFrame([[1, 2]], index=idx0)
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    df1 = pd.DataFrame([[3, 4]], index=idx1)
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    dfm = df0 - df1
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    assert pd.isna(df0.index.get_level_values(1)).all()
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    # the following failed in 0.14.1
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    assert pd.isna(dfm.index.get_level_values(1)[:-1]).all()
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def test_tuples_have_na():
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    index = MultiIndex(
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        levels=[[1, 0], [0, 1, 2, 3]],
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        codes=[[1, 1, 1, 1, -1, 0, 0, 0], [0, 1, 2, 3, 0, 1, 2, 3]],
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    )
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    assert pd.isna(index[4][0])
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    assert pd.isna(index.values[4][0])
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