import numpy as np import pytest 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_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 = pd.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 = pd.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_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)