fix: fix license classifier (#1751)

Author: MarcoGorelli

pyproject.toml

@@ -14,8 +14,8 @@ authors = [
 description = "Extremely lightweight compatibility layer between dataframe libraries"
 readme = "README.md"
 keywords = ["dataframes", "interoperability", "pandas", "polars", "pyarrow", "dask", "modin", "cudf"]
-license = {file = "LICENSE.md"}
 classifiers = [
+  "License :: OSI Approved :: MIT License",
   "Programming Language :: Python",
   "Operating System :: OS Independent",
 ]

tests/expr_and_series/rolling_mean_test.py

@@ -76,6 +76,7 @@ def test_rolling_mean_series(constructor_eager: ConstructorEager) -> None:
 @pytest.mark.skipif(PANDAS_VERSION < (1,), reason="too old for pyarrow")
 @pytest.mark.slow
 @pytest.mark.filterwarnings("ignore:.*:narwhals.exceptions.NarwhalsUnstableWarning")
+@pytest.mark.filterwarnings("ignore:.*is_sparse is deprecated:DeprecationWarning")
 def test_rolling_mean_hypothesis(center: bool, values: list[float]) -> None:  # noqa: FBT001
     s = pd.Series(values)
     n_missing = random.randint(0, len(s) - 1)  # noqa: S311

tests/expr_and_series/rolling_sum_test.py

@@ -194,6 +194,7 @@ def test_rolling_sum_series_invalid_params(
 )
 @pytest.mark.skipif(PANDAS_VERSION < (1,), reason="too old for pyarrow")
 @pytest.mark.filterwarnings("ignore:.*:narwhals.exceptions.NarwhalsUnstableWarning")
+@pytest.mark.filterwarnings("ignore:.*is_sparse is deprecated:DeprecationWarning")
 @pytest.mark.slow
 def test_rolling_sum_hypothesis(center: bool, values: list[float]) -> None:  # noqa: FBT001
     s = pd.Series(values)

tests/expr_and_series/rolling_var_test.py

@@ -105,6 +105,7 @@ def test_rolling_var_series(
 )
 @pytest.mark.skipif(PANDAS_VERSION < (1,), reason="too old for pyarrow")
 @pytest.mark.skipif(POLARS_VERSION < (1,), reason="different null behavior")
+@pytest.mark.filterwarnings("ignore:.*is_sparse is deprecated:DeprecationWarning")
 @pytest.mark.filterwarnings("ignore:.*:narwhals.exceptions.NarwhalsUnstableWarning")
 def test_rolling_var_hypothesis(center: bool, values: list[float]) -> None:  # noqa: FBT001
     s = pd.Series(values)