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| import numpy as np
| import pytest
|
| from pandas import (
| DataFrame,
| MultiIndex,
| Series,
| concat,
| )
| import pandas._testing as tm
|
|
| @pytest.mark.parametrize(
| "ops, names",
| [
| ([np.sqrt], ["sqrt"]),
| ([np.abs, np.sqrt], ["absolute", "sqrt"]),
| (np.array([np.sqrt]), ["sqrt"]),
| (np.array([np.abs, np.sqrt]), ["absolute", "sqrt"]),
| ],
| )
| def test_transform_listlike(string_series, ops, names):
| # GH 35964
| with np.errstate(all="ignore"):
| expected = concat([op(string_series) for op in ops], axis=1)
| expected.columns = names
| result = string_series.transform(ops)
| tm.assert_frame_equal(result, expected)
|
|
| @pytest.mark.parametrize("box", [dict, Series])
| def test_transform_dictlike(string_series, box):
| # GH 35964
| with np.errstate(all="ignore"):
| expected = concat([np.sqrt(string_series), np.abs(string_series)], axis=1)
| expected.columns = ["foo", "bar"]
| result = string_series.transform(box({"foo": np.sqrt, "bar": np.abs}))
| tm.assert_frame_equal(result, expected)
|
|
| def test_transform_dictlike_mixed():
| # GH 40018 - mix of lists and non-lists in values of a dictionary
| df = Series([1, 4])
| result = df.transform({"b": ["sqrt", "abs"], "c": "sqrt"})
| expected = DataFrame(
| [[1.0, 1, 1.0], [2.0, 4, 2.0]],
| columns=MultiIndex([("b", "c"), ("sqrt", "abs")], [(0, 0, 1), (0, 1, 0)]),
| )
| tm.assert_frame_equal(result, expected)
|
|
