done

lib/python3.11/site-packages/pandas/tests/indexes/multi/test_conversion.py

@@ -0,0 +1,201 @@
+import numpy as np
+import pytest
+
+from pandas.compat.numpy import np_version_gt2
+
+import pandas as pd
+from pandas import (
+    DataFrame,
+    MultiIndex,
+)
+import pandas._testing as tm
+
+
+def test_to_numpy(idx):
+    result = idx.to_numpy()
+    exp = idx.values
+    tm.assert_numpy_array_equal(result, exp)
+
+
+def test_array_interface(idx):
+    # https://github.com/pandas-dev/pandas/pull/60046
+    result = np.asarray(idx)
+    expected = np.empty((6,), dtype=object)
+    expected[:] = [
+        ("foo", "one"),
+        ("foo", "two"),
+        ("bar", "one"),
+        ("baz", "two"),
+        ("qux", "one"),
+        ("qux", "two"),
+    ]
+    tm.assert_numpy_array_equal(result, expected)
+
+    # it always gives a copy by default, but the values are cached, so results
+    # are still sharing memory
+    result_copy1 = np.asarray(idx)
+    result_copy2 = np.asarray(idx)
+    assert np.may_share_memory(result_copy1, result_copy2)
+
+    # with explicit copy=True, then it is an actual copy
+    result_copy1 = np.array(idx, copy=True)
+    result_copy2 = np.array(idx, copy=True)
+    assert not np.may_share_memory(result_copy1, result_copy2)
+
+    if not np_version_gt2:
+        # copy=False semantics are only supported in NumPy>=2.
+        return
+
+    # for MultiIndex, copy=False is never allowed
+    msg = "Starting with NumPy 2.0, the behavior of the 'copy' keyword has changed"
+    with tm.assert_produces_warning(FutureWarning, match=msg):
+        np.array(idx, copy=False)
+
+
+def test_to_frame():
+    tuples = [(1, "one"), (1, "two"), (2, "one"), (2, "two")]
+
+    index = MultiIndex.from_tuples(tuples)
+    result = index.to_frame(index=False)
+    expected = DataFrame(tuples)
+    tm.assert_frame_equal(result, expected)
+
+    result = index.to_frame()
+    expected.index = index
+    tm.assert_frame_equal(result, expected)
+
+    tuples = [(1, "one"), (1, "two"), (2, "one"), (2, "two")]
+    index = MultiIndex.from_tuples(tuples, names=["first", "second"])
+    result = index.to_frame(index=False)
+    expected = DataFrame(tuples)
+    expected.columns = ["first", "second"]
+    tm.assert_frame_equal(result, expected)
+
+    result = index.to_frame()
+    expected.index = index
+    tm.assert_frame_equal(result, expected)
+
+    # See GH-22580
+    index = MultiIndex.from_tuples(tuples)
+    result = index.to_frame(index=False, name=["first", "second"])
+    expected = DataFrame(tuples)
+    expected.columns = ["first", "second"]
+    tm.assert_frame_equal(result, expected)
+
+    result = index.to_frame(name=["first", "second"])
+    expected.index = index
+    expected.columns = ["first", "second"]
+    tm.assert_frame_equal(result, expected)
+
+    msg = "'name' must be a list / sequence of column names."
+    with pytest.raises(TypeError, match=msg):
+        index.to_frame(name="first")
+
+    msg = "'name' should have same length as number of levels on index."
+    with pytest.raises(ValueError, match=msg):
+        index.to_frame(name=["first"])
+
+    # Tests for datetime index
+    index = MultiIndex.from_product([range(5), pd.date_range("20130101", periods=3)])
+    result = index.to_frame(index=False)
+    expected = DataFrame(
+        {
+            0: np.repeat(np.arange(5, dtype="int64"), 3),
+            1: np.tile(pd.date_range("20130101", periods=3), 5),
+        }
+    )
+    tm.assert_frame_equal(result, expected)
+
+    result = index.to_frame()
+    expected.index = index
+    tm.assert_frame_equal(result, expected)
+
+    # See GH-22580
+    result = index.to_frame(index=False, name=["first", "second"])
+    expected = DataFrame(
+        {
+            "first": np.repeat(np.arange(5, dtype="int64"), 3),
+            "second": np.tile(pd.date_range("20130101", periods=3), 5),
+        }
+    )
+    tm.assert_frame_equal(result, expected)
+
+    result = index.to_frame(name=["first", "second"])
+    expected.index = index
+    tm.assert_frame_equal(result, expected)
+
+
+def test_to_frame_dtype_fidelity():
+    # GH 22420
+    mi = MultiIndex.from_arrays(
+        [
+            pd.date_range("19910905", periods=6, tz="US/Eastern"),
+            [1, 1, 1, 2, 2, 2],
+            pd.Categorical(["a", "a", "b", "b", "c", "c"], ordered=True),
+            ["x", "x", "y", "z", "x", "y"],
+        ],
+        names=["dates", "a", "b", "c"],
+    )
+    original_dtypes = {name: mi.levels[i].dtype for i, name in enumerate(mi.names)}
+
+    expected_df = DataFrame(
+        {
+            "dates": pd.date_range("19910905", periods=6, tz="US/Eastern"),
+            "a": [1, 1, 1, 2, 2, 2],
+            "b": pd.Categorical(["a", "a", "b", "b", "c", "c"], ordered=True),
+            "c": ["x", "x", "y", "z", "x", "y"],
+        }
+    )
+    df = mi.to_frame(index=False)
+    df_dtypes = df.dtypes.to_dict()
+
+    tm.assert_frame_equal(df, expected_df)
+    assert original_dtypes == df_dtypes
+
+
+def test_to_frame_resulting_column_order():
+    # GH 22420
+    expected = ["z", 0, "a"]
+    mi = MultiIndex.from_arrays(
+        [["a", "b", "c"], ["x", "y", "z"], ["q", "w", "e"]], names=expected
+    )
+    result = mi.to_frame().columns.tolist()
+    assert result == expected
+
+
+def test_to_frame_duplicate_labels():
+    # GH 45245
+    data = [(1, 2), (3, 4)]
+    names = ["a", "a"]
+    index = MultiIndex.from_tuples(data, names=names)
+    with pytest.raises(ValueError, match="Cannot create duplicate column labels"):
+        index.to_frame()
+
+    result = index.to_frame(allow_duplicates=True)
+    expected = DataFrame(data, index=index, columns=names)
+    tm.assert_frame_equal(result, expected)
+
+    names = [None, 0]
+    index = MultiIndex.from_tuples(data, names=names)
+    with pytest.raises(ValueError, match="Cannot create duplicate column labels"):
+        index.to_frame()
+
+    result = index.to_frame(allow_duplicates=True)
+    expected = DataFrame(data, index=index, columns=[0, 0])
+    tm.assert_frame_equal(result, expected)
+
+
+def test_to_flat_index(idx):
+    expected = pd.Index(
+        (
+            ("foo", "one"),
+            ("foo", "two"),
+            ("bar", "one"),
+            ("baz", "two"),
+            ("qux", "one"),
+            ("qux", "two"),
+        ),
+        tupleize_cols=False,
+    )
+    result = idx.to_flat_index()
+    tm.assert_index_equal(result, expected)