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fix: Fix output type for
list.eval in certain cases (#18570)
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py-polars/tests/unit/operations/namespaces/list/test_eval.py
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,132 @@ | ||
| from __future__ import annotations | ||
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| from typing import Any | ||
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| import pytest | ||
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| import polars as pl | ||
| from polars.exceptions import ( | ||
| StructFieldNotFoundError, | ||
| ) | ||
| from polars.testing import assert_frame_equal, assert_series_equal | ||
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| def test_list_eval_dtype_inference() -> None: | ||
| grades = pl.DataFrame( | ||
| { | ||
| "student": ["bas", "laura", "tim", "jenny"], | ||
| "arithmetic": [10, 5, 6, 8], | ||
| "biology": [4, 6, 2, 7], | ||
| "geography": [8, 4, 9, 7], | ||
| } | ||
| ) | ||
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| rank_pct = pl.col("").rank(descending=True) / pl.col("").count().cast(pl.UInt16) | ||
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| # the .list.first() would fail if .list.eval did not correctly infer the output type | ||
| assert grades.with_columns( | ||
| pl.concat_list(pl.all().exclude("student")).alias("all_grades") | ||
| ).select( | ||
| pl.col("all_grades") | ||
| .list.eval(rank_pct, parallel=True) | ||
| .alias("grades_rank") | ||
| .list.first() | ||
| ).to_series().to_list() == [ | ||
| 0.3333333333333333, | ||
| 0.6666666666666666, | ||
| 0.6666666666666666, | ||
| 0.3333333333333333, | ||
| ] | ||
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| def test_list_eval_categorical() -> None: | ||
| df = pl.DataFrame({"test": [["a", None]]}, schema={"test": pl.List(pl.Categorical)}) | ||
| df = df.select( | ||
| pl.col("test").list.eval(pl.element().filter(pl.element().is_not_null())) | ||
| ) | ||
| assert_series_equal( | ||
| df.get_column("test"), pl.Series("test", [["a"]], dtype=pl.List(pl.Categorical)) | ||
| ) | ||
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| def test_list_eval_type_coercion() -> None: | ||
| last_non_null_value = pl.element().fill_null(3).last() | ||
| df = pl.DataFrame({"array_cols": [[1, None]]}) | ||
|
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| assert df.select( | ||
| pl.col("array_cols") | ||
| .list.eval(last_non_null_value, parallel=False) | ||
| .alias("col_last") | ||
| ).to_dict(as_series=False) == {"col_last": [[3]]} | ||
|
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| def test_list_eval_all_null() -> None: | ||
| df = pl.DataFrame({"foo": [1, 2, 3], "bar": [None, None, None]}).with_columns( | ||
| pl.col("bar").cast(pl.List(pl.String)) | ||
| ) | ||
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| assert df.select(pl.col("bar").list.eval(pl.element())).to_dict( | ||
| as_series=False | ||
| ) == {"bar": [None, None, None]} | ||
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| def test_empty_eval_dtype_5546() -> None: | ||
| # https://github.com/pola-rs/polars/issues/5546 | ||
| df = pl.DataFrame([{"a": [{"name": 1}, {"name": 2}]}]) | ||
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| dtype = df.dtypes[0] | ||
|
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| assert ( | ||
| df.limit(0).with_columns( | ||
| pl.col("a") | ||
| .list.eval(pl.element().filter(pl.first().struct.field("name") == 1)) | ||
| .alias("a_filtered") | ||
| ) | ||
| ).dtypes == [dtype, dtype] | ||
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| def test_list_eval_gather_every_13410() -> None: | ||
| df = pl.DataFrame({"a": [[1, 2, 3], [4, 5, 6]]}) | ||
| out = df.with_columns(result=pl.col("a").list.eval(pl.element().gather_every(2))) | ||
| expected = pl.DataFrame({"a": [[1, 2, 3], [4, 5, 6]], "result": [[1, 3], [4, 6]]}) | ||
| assert_frame_equal(out, expected) | ||
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| def test_list_eval_err_raise_15653() -> None: | ||
| df = pl.DataFrame({"foo": [[]]}) | ||
| with pytest.raises(StructFieldNotFoundError): | ||
| df.with_columns(bar=pl.col("foo").list.eval(pl.element().struct.field("baz"))) | ||
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| def test_list_eval_type_cast_11188() -> None: | ||
| df = pl.DataFrame( | ||
| [ | ||
| {"a": None}, | ||
| ], | ||
| schema={"a": pl.List(pl.Int64)}, | ||
| ) | ||
| assert df.select( | ||
| pl.col("a").list.eval(pl.element().cast(pl.String)).alias("a_str") | ||
| ).schema == {"a_str": pl.List(pl.String)} | ||
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| @pytest.mark.parametrize( | ||
| "data", | ||
| [ | ||
| {"a": [["0"], ["1"]]}, | ||
| {"a": [["0", "1"], ["2", "3"]]}, | ||
| {"a": [["0", "1"]]}, | ||
| {"a": [["0"]]}, | ||
| ], | ||
| ) | ||
| @pytest.mark.parametrize( | ||
| "expr", | ||
| [ | ||
| pl.lit(""), | ||
| pl.format("test: {}", pl.element()), | ||
| ], | ||
| ) | ||
| def test_list_eval_list_output_18510(data: dict[str, Any], expr: pl.Expr) -> None: | ||
| df = pl.DataFrame(data) | ||
| result = df.select(pl.col("a").list.eval(pl.lit(""))) | ||
| assert result.to_series().dtype == pl.List(pl.String) |
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