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.venv/Lib/site-packages/pandas/tests/indexes/multi/test_join.py

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+import numpy as np
+import pytest
+
+from pandas import (
+    Index,
+    Interval,
+    MultiIndex,
+)
+import pandas._testing as tm
+
+
+@pytest.mark.parametrize(
+    "other", [Index(["three", "one", "two"]), Index(["one"]), Index(["one", "three"])]
+)
+def test_join_level(idx, other, join_type):
+    join_index, lidx, ridx = other.join(
+        idx, how=join_type, level="second", return_indexers=True
+    )
+
+    exp_level = other.join(idx.levels[1], how=join_type)
+    assert join_index.levels[0].equals(idx.levels[0])
+    assert join_index.levels[1].equals(exp_level)
+
+    # pare down levels
+    mask = np.array([x[1] in exp_level for x in idx], dtype=bool)
+    exp_values = idx.values[mask]
+    tm.assert_numpy_array_equal(join_index.values, exp_values)
+
+    if join_type in ("outer", "inner"):
+        join_index2, ridx2, lidx2 = idx.join(
+            other, how=join_type, level="second", return_indexers=True
+        )
+
+        assert join_index.equals(join_index2)
+        tm.assert_numpy_array_equal(lidx, lidx2)
+        tm.assert_numpy_array_equal(ridx, ridx2)
+        tm.assert_numpy_array_equal(join_index2.values, exp_values)
+
+
+def test_join_level_corner_case(idx):
+    # some corner cases
+    index = Index(["three", "one", "two"])
+    result = index.join(idx, level="second")
+    assert isinstance(result, MultiIndex)
+
+    with pytest.raises(TypeError, match="Join.*MultiIndex.*ambiguous"):
+        idx.join(idx, level=1)
+
+
+def test_join_self(idx, join_type):
+    joined = idx.join(idx, how=join_type)
+    tm.assert_index_equal(joined, idx)
+
+
+def test_join_multi():
+    # GH 10665
+    midx = MultiIndex.from_product([np.arange(4), np.arange(4)], names=["a", "b"])
+    idx = Index([1, 2, 5], name="b")
+
+    # inner
+    jidx, lidx, ridx = midx.join(idx, how="inner", return_indexers=True)
+    exp_idx = MultiIndex.from_product([np.arange(4), [1, 2]], names=["a", "b"])
+    exp_lidx = np.array([1, 2, 5, 6, 9, 10, 13, 14], dtype=np.intp)
+    exp_ridx = np.array([0, 1, 0, 1, 0, 1, 0, 1], dtype=np.intp)
+    tm.assert_index_equal(jidx, exp_idx)
+    tm.assert_numpy_array_equal(lidx, exp_lidx)
+    tm.assert_numpy_array_equal(ridx, exp_ridx)
+    # flip
+    jidx, ridx, lidx = idx.join(midx, how="inner", return_indexers=True)
+    tm.assert_index_equal(jidx, exp_idx)
+    tm.assert_numpy_array_equal(lidx, exp_lidx)
+    tm.assert_numpy_array_equal(ridx, exp_ridx)
+
+    # keep MultiIndex
+    jidx, lidx, ridx = midx.join(idx, how="left", return_indexers=True)
+    exp_ridx = np.array(
+        [-1, 0, 1, -1, -1, 0, 1, -1, -1, 0, 1, -1, -1, 0, 1, -1], dtype=np.intp
+    )
+    tm.assert_index_equal(jidx, midx)
+    assert lidx is None
+    tm.assert_numpy_array_equal(ridx, exp_ridx)
+    # flip
+    jidx, ridx, lidx = idx.join(midx, how="right", return_indexers=True)
+    tm.assert_index_equal(jidx, midx)
+    assert lidx is None
+    tm.assert_numpy_array_equal(ridx, exp_ridx)
+
+
+def test_join_self_unique(idx, join_type):
+    if idx.is_unique:
+        joined = idx.join(idx, how=join_type)
+        assert (idx == joined).all()
+
+
+def test_join_multi_wrong_order():
+    # GH 25760
+    # GH 28956
+
+    midx1 = MultiIndex.from_product([[1, 2], [3, 4]], names=["a", "b"])
+    midx2 = MultiIndex.from_product([[1, 2], [3, 4]], names=["b", "a"])
+
+    join_idx, lidx, ridx = midx1.join(midx2, return_indexers=True)
+
+    exp_ridx = np.array([-1, -1, -1, -1], dtype=np.intp)
+
+    tm.assert_index_equal(midx1, join_idx)
+    assert lidx is None
+    tm.assert_numpy_array_equal(ridx, exp_ridx)
+
+
+def test_join_multi_return_indexers():
+    # GH 34074
+
+    midx1 = MultiIndex.from_product([[1, 2], [3, 4], [5, 6]], names=["a", "b", "c"])
+    midx2 = MultiIndex.from_product([[1, 2], [3, 4]], names=["a", "b"])
+
+    result = midx1.join(midx2, return_indexers=False)
+    tm.assert_index_equal(result, midx1)
+
+
+def test_join_overlapping_interval_level():
+    # GH 44096
+    idx_1 = MultiIndex.from_tuples(
+        [
+            (1, Interval(0.0, 1.0)),
+            (1, Interval(1.0, 2.0)),
+            (1, Interval(2.0, 5.0)),
+            (2, Interval(0.0, 1.0)),
+            (2, Interval(1.0, 3.0)),  # interval limit is here at 3.0, not at 2.0
+            (2, Interval(3.0, 5.0)),
+        ],
+        names=["num", "interval"],
+    )
+
+    idx_2 = MultiIndex.from_tuples(
+        [
+            (1, Interval(2.0, 5.0)),
+            (1, Interval(0.0, 1.0)),
+            (1, Interval(1.0, 2.0)),
+            (2, Interval(3.0, 5.0)),
+            (2, Interval(0.0, 1.0)),
+            (2, Interval(1.0, 3.0)),
+        ],
+        names=["num", "interval"],
+    )
+
+    expected = MultiIndex.from_tuples(
+        [
+            (1, Interval(0.0, 1.0)),
+            (1, Interval(1.0, 2.0)),
+            (1, Interval(2.0, 5.0)),
+            (2, Interval(0.0, 1.0)),
+            (2, Interval(1.0, 3.0)),
+            (2, Interval(3.0, 5.0)),
+        ],
+        names=["num", "interval"],
+    )
+    result = idx_1.join(idx_2, how="outer")
+
+    tm.assert_index_equal(result, expected)