demo + utils venv
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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 DataFrame, Interval, IntervalIndex, Series
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import pandas.util.testing as tm
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class TestIntervalIndex(object):
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def setup_method(self, method):
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self.s = Series(np.arange(5), IntervalIndex.from_breaks(np.arange(6)))
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# To be removed, replaced by test_interval_new.py (see #16316, #16386)
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def test_loc_with_scalar(self):
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s = self.s
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expected = s.iloc[:3]
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tm.assert_series_equal(expected, s.loc[:3])
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tm.assert_series_equal(expected, s.loc[:2.5])
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tm.assert_series_equal(expected, s.loc[0.1:2.5])
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tm.assert_series_equal(expected, s.loc[-1:3])
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expected = s.iloc[1:4]
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tm.assert_series_equal(expected, s.loc[[1.5, 2.5, 3.5]])
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tm.assert_series_equal(expected, s.loc[[2, 3, 4]])
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tm.assert_series_equal(expected, s.loc[[1.5, 3, 4]])
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expected = s.iloc[2:5]
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tm.assert_series_equal(expected, s.loc[s >= 2])
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# TODO: check this behavior is consistent with test_interval_new.py
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def test_getitem_with_scalar(self):
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s = self.s
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expected = s.iloc[:3]
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tm.assert_series_equal(expected, s[:3])
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tm.assert_series_equal(expected, s[:2.5])
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tm.assert_series_equal(expected, s[0.1:2.5])
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tm.assert_series_equal(expected, s[-1:3])
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expected = s.iloc[1:4]
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tm.assert_series_equal(expected, s[[1.5, 2.5, 3.5]])
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tm.assert_series_equal(expected, s[[2, 3, 4]])
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tm.assert_series_equal(expected, s[[1.5, 3, 4]])
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expected = s.iloc[2:5]
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tm.assert_series_equal(expected, s[s >= 2])
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# TODO: check this behavior is consistent with test_interval_new.py
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@pytest.mark.parametrize('direction', ['increasing', 'decreasing'])
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def test_nonoverlapping_monotonic(self, direction, closed):
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tpls = [(0, 1), (2, 3), (4, 5)]
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if direction == 'decreasing':
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tpls = tpls[::-1]
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idx = IntervalIndex.from_tuples(tpls, closed=closed)
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s = Series(list('abc'), idx)
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for key, expected in zip(idx.left, s):
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if idx.closed_left:
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assert s[key] == expected
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assert s.loc[key] == expected
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else:
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with pytest.raises(KeyError):
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s[key]
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with pytest.raises(KeyError):
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s.loc[key]
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for key, expected in zip(idx.right, s):
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if idx.closed_right:
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assert s[key] == expected
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assert s.loc[key] == expected
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else:
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with pytest.raises(KeyError):
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s[key]
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with pytest.raises(KeyError):
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s.loc[key]
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for key, expected in zip(idx.mid, s):
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assert s[key] == expected
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assert s.loc[key] == expected
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# To be removed, replaced by test_interval_new.py (see #16316, #16386)
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def test_with_interval(self):
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s = self.s
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expected = 0
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result = s.loc[Interval(0, 1)]
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assert result == expected
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result = s[Interval(0, 1)]
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assert result == expected
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expected = s.iloc[3:5]
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result = s.loc[Interval(3, 6)]
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tm.assert_series_equal(expected, result)
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expected = s.iloc[3:5]
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result = s.loc[[Interval(3, 6)]]
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tm.assert_series_equal(expected, result)
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expected = s.iloc[3:5]
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result = s.loc[[Interval(3, 5)]]
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tm.assert_series_equal(expected, result)
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# missing
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with pytest.raises(KeyError):
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s.loc[Interval(-2, 0)]
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with pytest.raises(KeyError):
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s[Interval(-2, 0)]
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with pytest.raises(KeyError):
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s.loc[Interval(5, 6)]
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with pytest.raises(KeyError):
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s[Interval(5, 6)]
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# To be removed, replaced by test_interval_new.py (see #16316, #16386)
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def test_with_slices(self):
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s = self.s
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# slice of interval
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with pytest.raises(NotImplementedError):
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s.loc[Interval(3, 6):]
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with pytest.raises(NotImplementedError):
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s[Interval(3, 6):]
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expected = s.iloc[3:5]
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result = s[[Interval(3, 6)]]
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tm.assert_series_equal(expected, result)
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# slice of scalar with step != 1
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with pytest.raises(ValueError):
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s[0:4:2]
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# To be removed, replaced by test_interval_new.py (see #16316, #16386)
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def test_with_overlaps(self):
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s = self.s
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expected = s.iloc[[3, 4, 3, 4]]
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result = s.loc[[Interval(3, 6), Interval(3, 6)]]
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tm.assert_series_equal(expected, result)
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idx = IntervalIndex.from_tuples([(1, 5), (3, 7)])
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s = Series(range(len(idx)), index=idx)
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result = s[4]
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expected = s
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tm.assert_series_equal(expected, result)
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result = s[[4]]
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expected = s
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tm.assert_series_equal(expected, result)
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result = s.loc[[4]]
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expected = s
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tm.assert_series_equal(expected, result)
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result = s[Interval(3, 5)]
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expected = s
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tm.assert_series_equal(expected, result)
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result = s.loc[Interval(3, 5)]
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expected = s
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tm.assert_series_equal(expected, result)
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# doesn't intersect unique set of intervals
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with pytest.raises(KeyError):
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s[[Interval(3, 5)]]
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with pytest.raises(KeyError):
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s.loc[[Interval(3, 5)]]
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# To be removed, replaced by test_interval_new.py (see #16316, #16386)
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def test_non_unique(self):
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idx = IntervalIndex.from_tuples([(1, 3), (3, 7)])
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s = Series(range(len(idx)), index=idx)
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result = s.loc[Interval(1, 3)]
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assert result == 0
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result = s.loc[[Interval(1, 3)]]
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expected = s.iloc[0:1]
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tm.assert_series_equal(expected, result)
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# To be removed, replaced by test_interval_new.py (see #16316, #16386)
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def test_non_unique_moar(self):
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idx = IntervalIndex.from_tuples([(1, 3), (1, 3), (3, 7)])
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s = Series(range(len(idx)), index=idx)
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result = s.loc[Interval(1, 3)]
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expected = s.iloc[[0, 1]]
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tm.assert_series_equal(expected, result)
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# non-unique index and slices not allowed
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with pytest.raises(ValueError):
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s.loc[Interval(1, 3):]
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with pytest.raises(ValueError):
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s[Interval(1, 3):]
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# non-unique
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with pytest.raises(ValueError):
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s[[Interval(1, 3)]]
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# TODO: check this behavior is consistent with test_interval_new.py
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def test_non_matching(self):
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s = self.s
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# this is a departure from our current
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# indexin scheme, but simpler
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with pytest.raises(KeyError):
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s.loc[[-1, 3, 4, 5]]
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with pytest.raises(KeyError):
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s.loc[[-1, 3]]
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def test_large_series(self):
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s = Series(np.arange(1000000),
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index=IntervalIndex.from_breaks(np.arange(1000001)))
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result1 = s.loc[:80000]
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result2 = s.loc[0:80000]
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result3 = s.loc[0:80000:1]
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tm.assert_series_equal(result1, result2)
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tm.assert_series_equal(result1, result3)
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def test_loc_getitem_frame(self):
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df = DataFrame({'A': range(10)})
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s = pd.cut(df.A, 5)
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df['B'] = s
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df = df.set_index('B')
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result = df.loc[4]
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expected = df.iloc[4:6]
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tm.assert_frame_equal(result, expected)
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with pytest.raises(KeyError):
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df.loc[10]
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# single list-like
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result = df.loc[[4]]
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expected = df.iloc[4:6]
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tm.assert_frame_equal(result, expected)
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# non-unique
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result = df.loc[[4, 5]]
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expected = df.take([4, 5, 4, 5])
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tm.assert_frame_equal(result, expected)
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with pytest.raises(KeyError):
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df.loc[[10]]
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# partial missing
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with pytest.raises(KeyError):
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df.loc[[10, 4]]
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+246
@@ -0,0 +1,246 @@
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import numpy as np
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import pytest
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from pandas import Interval, IntervalIndex, Series
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import pandas.util.testing as tm
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pytestmark = pytest.mark.skip(reason="new indexing tests for issue 16316")
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class TestIntervalIndex(object):
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def setup_method(self, method):
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self.s = Series(np.arange(5), IntervalIndex.from_breaks(np.arange(6)))
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def test_loc_with_interval(self):
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# loc with single label / list of labels:
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# - Intervals: only exact matches
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# - scalars: those that contain it
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s = self.s
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expected = 0
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result = s.loc[Interval(0, 1)]
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assert result == expected
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result = s[Interval(0, 1)]
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assert result == expected
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expected = s.iloc[3:5]
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result = s.loc[[Interval(3, 4), Interval(4, 5)]]
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tm.assert_series_equal(expected, result)
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result = s[[Interval(3, 4), Interval(4, 5)]]
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tm.assert_series_equal(expected, result)
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# missing or not exact
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with pytest.raises(KeyError):
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s.loc[Interval(3, 5, closed='left')]
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with pytest.raises(KeyError):
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s[Interval(3, 5, closed='left')]
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with pytest.raises(KeyError):
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s[Interval(3, 5)]
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with pytest.raises(KeyError):
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s.loc[Interval(3, 5)]
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with pytest.raises(KeyError):
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s[Interval(3, 5)]
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with pytest.raises(KeyError):
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s.loc[Interval(-2, 0)]
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with pytest.raises(KeyError):
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s[Interval(-2, 0)]
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with pytest.raises(KeyError):
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s.loc[Interval(5, 6)]
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with pytest.raises(KeyError):
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s[Interval(5, 6)]
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def test_loc_with_scalar(self):
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# loc with single label / list of labels:
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# - Intervals: only exact matches
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# - scalars: those that contain it
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s = self.s
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assert s.loc[1] == 0
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assert s.loc[1.5] == 1
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assert s.loc[2] == 1
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# TODO with __getitem__ same rules as loc, or positional ?
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# assert s[1] == 0
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# assert s[1.5] == 1
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# assert s[2] == 1
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expected = s.iloc[1:4]
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tm.assert_series_equal(expected, s.loc[[1.5, 2.5, 3.5]])
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tm.assert_series_equal(expected, s.loc[[2, 3, 4]])
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tm.assert_series_equal(expected, s.loc[[1.5, 3, 4]])
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expected = s.iloc[[1, 1, 2, 1]]
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tm.assert_series_equal(expected, s.loc[[1.5, 2, 2.5, 1.5]])
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expected = s.iloc[2:5]
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tm.assert_series_equal(expected, s.loc[s >= 2])
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def test_loc_with_slices(self):
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# loc with slices:
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# - Interval objects: only works with exact matches
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# - scalars: only works for non-overlapping, monotonic intervals,
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# and start/stop select location based on the interval that
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# contains them:
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# (slice_loc(start, stop) == (idx.get_loc(start), idx.get_loc(stop))
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s = self.s
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# slice of interval
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expected = s.iloc[:3]
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result = s.loc[Interval(0, 1):Interval(2, 3)]
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tm.assert_series_equal(expected, result)
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result = s[Interval(0, 1):Interval(2, 3)]
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tm.assert_series_equal(expected, result)
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expected = s.iloc[4:]
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result = s.loc[Interval(3, 4):]
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tm.assert_series_equal(expected, result)
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result = s[Interval(3, 4):]
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tm.assert_series_equal(expected, result)
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with pytest.raises(KeyError):
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s.loc[Interval(3, 6):]
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with pytest.raises(KeyError):
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s[Interval(3, 6):]
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with pytest.raises(KeyError):
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s.loc[Interval(3, 4, closed='left'):]
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with pytest.raises(KeyError):
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s[Interval(3, 4, closed='left'):]
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# TODO with non-existing intervals ?
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# s.loc[Interval(-1, 0):Interval(2, 3)]
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# slice of scalar
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expected = s.iloc[:3]
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tm.assert_series_equal(expected, s.loc[:3])
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tm.assert_series_equal(expected, s.loc[:2.5])
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tm.assert_series_equal(expected, s.loc[0.1:2.5])
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# TODO should this work? (-1 is not contained in any of the Intervals)
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# tm.assert_series_equal(expected, s.loc[-1:3])
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# TODO with __getitem__ same rules as loc, or positional ?
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# tm.assert_series_equal(expected, s[:3])
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# tm.assert_series_equal(expected, s[:2.5])
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# tm.assert_series_equal(expected, s[0.1:2.5])
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# slice of scalar with step != 1
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with pytest.raises(NotImplementedError):
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s[0:4:2]
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def test_loc_with_overlap(self):
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idx = IntervalIndex.from_tuples([(1, 5), (3, 7)])
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s = Series(range(len(idx)), index=idx)
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# scalar
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expected = s
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result = s.loc[4]
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tm.assert_series_equal(expected, result)
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result = s[4]
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tm.assert_series_equal(expected, result)
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result = s.loc[[4]]
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tm.assert_series_equal(expected, result)
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result = s[[4]]
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tm.assert_series_equal(expected, result)
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# interval
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expected = 0
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result = s.loc[Interval(1, 5)]
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tm.assert_series_equal(expected, result)
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result = s[Interval(1, 5)]
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tm.assert_series_equal(expected, result)
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expected = s
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result = s.loc[[Interval(1, 5), Interval(3, 7)]]
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tm.assert_series_equal(expected, result)
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result = s[[Interval(1, 5), Interval(3, 7)]]
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tm.assert_series_equal(expected, result)
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with pytest.raises(KeyError):
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s.loc[Interval(3, 5)]
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with pytest.raises(KeyError):
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s.loc[[Interval(3, 5)]]
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with pytest.raises(KeyError):
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s[Interval(3, 5)]
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with pytest.raises(KeyError):
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s[[Interval(3, 5)]]
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# slices with interval (only exact matches)
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expected = s
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result = s.loc[Interval(1, 5):Interval(3, 7)]
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tm.assert_series_equal(expected, result)
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result = s[Interval(1, 5):Interval(3, 7)]
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tm.assert_series_equal(expected, result)
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with pytest.raises(KeyError):
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s.loc[Interval(1, 6):Interval(3, 8)]
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with pytest.raises(KeyError):
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s[Interval(1, 6):Interval(3, 8)]
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# slices with scalar raise for overlapping intervals
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# TODO KeyError is the appropriate error?
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with pytest.raises(KeyError):
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s.loc[1:4]
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def test_non_unique(self):
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idx = IntervalIndex.from_tuples([(1, 3), (3, 7)])
|
||||
s = Series(range(len(idx)), index=idx)
|
||||
|
||||
result = s.loc[Interval(1, 3)]
|
||||
assert result == 0
|
||||
|
||||
result = s.loc[[Interval(1, 3)]]
|
||||
expected = s.iloc[0:1]
|
||||
tm.assert_series_equal(expected, result)
|
||||
|
||||
def test_non_unique_moar(self):
|
||||
|
||||
idx = IntervalIndex.from_tuples([(1, 3), (1, 3), (3, 7)])
|
||||
s = Series(range(len(idx)), index=idx)
|
||||
|
||||
expected = s.iloc[[0, 1]]
|
||||
result = s.loc[Interval(1, 3)]
|
||||
tm.assert_series_equal(expected, result)
|
||||
|
||||
expected = s
|
||||
result = s.loc[Interval(1, 3):]
|
||||
tm.assert_series_equal(expected, result)
|
||||
|
||||
expected = s
|
||||
result = s[Interval(1, 3):]
|
||||
tm.assert_series_equal(expected, result)
|
||||
|
||||
expected = s.iloc[[0, 1]]
|
||||
result = s[[Interval(1, 3)]]
|
||||
tm.assert_series_equal(expected, result)
|
||||
Reference in New Issue
Block a user