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| import numpy as np
| import pytest
|
| from pandas import (
| DataFrame,
| MultiIndex,
| Series,
| )
| import pandas._testing as tm
|
|
| @pytest.fixture
| def simple_multiindex_dataframe():
| """
| Factory function to create simple 3 x 3 dataframe with
| both columns and row MultiIndex using supplied data or
| random data by default.
| """
|
| data = np.random.randn(3, 3)
| return DataFrame(
| data, columns=[[2, 2, 4], [6, 8, 10]], index=[[4, 4, 8], [8, 10, 12]]
| )
|
|
| @pytest.mark.parametrize(
| "indexer, expected",
| [
| (
| lambda df: df.iloc[0],
| lambda arr: Series(arr[0], index=[[2, 2, 4], [6, 8, 10]], name=(4, 8)),
| ),
| (
| lambda df: df.iloc[2],
| lambda arr: Series(arr[2], index=[[2, 2, 4], [6, 8, 10]], name=(8, 12)),
| ),
| (
| lambda df: df.iloc[:, 2],
| lambda arr: Series(arr[:, 2], index=[[4, 4, 8], [8, 10, 12]], name=(4, 10)),
| ),
| ],
| )
| def test_iloc_returns_series(indexer, expected, simple_multiindex_dataframe):
| df = simple_multiindex_dataframe
| arr = df.values
| result = indexer(df)
| expected = expected(arr)
| tm.assert_series_equal(result, expected)
|
|
| def test_iloc_returns_dataframe(simple_multiindex_dataframe):
| df = simple_multiindex_dataframe
| result = df.iloc[[0, 1]]
| expected = df.xs(4, drop_level=False)
| tm.assert_frame_equal(result, expected)
|
|
| def test_iloc_returns_scalar(simple_multiindex_dataframe):
| df = simple_multiindex_dataframe
| arr = df.values
| result = df.iloc[2, 2]
| expected = arr[2, 2]
| assert result == expected
|
|
| def test_iloc_getitem_multiple_items():
| # GH 5528
| tup = zip(*[["a", "a", "b", "b"], ["x", "y", "x", "y"]])
| index = MultiIndex.from_tuples(tup)
| df = DataFrame(np.random.randn(4, 4), index=index)
| result = df.iloc[[2, 3]]
| expected = df.xs("b", drop_level=False)
| tm.assert_frame_equal(result, expected)
|
|
| def test_iloc_getitem_labels():
| # this is basically regular indexing
| arr = np.random.randn(4, 3)
| df = DataFrame(
| arr,
| columns=[["i", "i", "j"], ["A", "A", "B"]],
| index=[["i", "i", "j", "k"], ["X", "X", "Y", "Y"]],
| )
| result = df.iloc[2, 2]
| expected = arr[2, 2]
| assert result == expected
|
|
| def test_frame_getitem_slice(multiindex_dataframe_random_data):
| df = multiindex_dataframe_random_data
| result = df.iloc[:4]
| expected = df[:4]
| tm.assert_frame_equal(result, expected)
|
|
| def test_frame_setitem_slice(multiindex_dataframe_random_data):
| df = multiindex_dataframe_random_data
| df.iloc[:4] = 0
|
| assert (df.values[:4] == 0).all()
| assert (df.values[4:] != 0).all()
|
|
| def test_indexing_ambiguity_bug_1678():
| # GH 1678
| columns = MultiIndex.from_tuples(
| [("Ohio", "Green"), ("Ohio", "Red"), ("Colorado", "Green")]
| )
| index = MultiIndex.from_tuples([("a", 1), ("a", 2), ("b", 1), ("b", 2)])
|
| df = DataFrame(np.arange(12).reshape((4, 3)), index=index, columns=columns)
|
| result = df.iloc[:, 1]
| expected = df.loc[:, ("Ohio", "Red")]
| tm.assert_series_equal(result, expected)
|
|
| def test_iloc_integer_locations():
| # GH 13797
| data = [
| ["str00", "str01"],
| ["str10", "str11"],
| ["str20", "srt21"],
| ["str30", "str31"],
| ["str40", "str41"],
| ]
|
| index = MultiIndex.from_tuples(
| [("CC", "A"), ("CC", "B"), ("CC", "B"), ("BB", "a"), ("BB", "b")]
| )
|
| expected = DataFrame(data)
| df = DataFrame(data, index=index)
|
| result = DataFrame([[df.iloc[r, c] for c in range(2)] for r in range(5)])
|
| tm.assert_frame_equal(result, expected)
|
|
| @pytest.mark.parametrize(
| "data, indexes, values, expected_k",
| [
| # test without indexer value in first level of MultiIndex
| ([[2, 22, 5], [2, 33, 6]], [0, -1, 1], [2, 3, 1], [7, 10]),
| # test like code sample 1 in the issue
| ([[1, 22, 555], [1, 33, 666]], [0, -1, 1], [200, 300, 100], [755, 1066]),
| # test like code sample 2 in the issue
| ([[1, 3, 7], [2, 4, 8]], [0, -1, 1], [10, 10, 1000], [17, 1018]),
| # test like code sample 3 in the issue
| ([[1, 11, 4], [2, 22, 5], [3, 33, 6]], [0, -1, 1], [4, 7, 10], [8, 15, 13]),
| ],
| )
| def test_iloc_setitem_int_multiindex_series(data, indexes, values, expected_k):
| # GH17148
| df = DataFrame(data=data, columns=["i", "j", "k"])
| df = df.set_index(["i", "j"])
|
| series = df.k.copy()
| for i, v in zip(indexes, values):
| series.iloc[i] += v
|
| df["k"] = expected_k
| expected = df.k
| tm.assert_series_equal(series, expected)
|
|
| def test_getitem_iloc(multiindex_dataframe_random_data):
| df = multiindex_dataframe_random_data
| result = df.iloc[2]
| expected = df.xs(df.index[2])
| tm.assert_series_equal(result, expected)
|
|
