fix(skore-hub-project): Make feature_importance.coefficients return a Display

ci/requirements/skore-hub-project/python-3.10/scikit-learn-1.4/test-requirements.txt

@@ -248,7 +248,7 @@ six==1.17.0
     # via python-dateutil
 skops==0.13.0
     # via skore-hub-project (skore-hub-project/pyproject.toml)
-skore==0.10.1
+skore==0.10.2
     # via skore-hub-project (skore-hub-project/pyproject.toml)
 skore-local-project==0.0.3
     # via skore

ci/requirements/skore-hub-project/python-3.10/scikit-learn-1.7/test-requirements.txt

@@ -248,7 +248,7 @@ six==1.17.0
     # via python-dateutil
 skops==0.13.0
     # via skore-hub-project (skore-hub-project/pyproject.toml)
-skore==0.10.1
+skore==0.10.2
     # via skore-hub-project (skore-hub-project/pyproject.toml)
 skore-local-project==0.0.3
     # via skore

ci/requirements/skore-hub-project/python-3.11/scikit-learn-1.4/test-requirements.txt

@@ -246,7 +246,7 @@ six==1.17.0
     # via python-dateutil
 skops==0.13.0
     # via skore-hub-project (skore-hub-project/pyproject.toml)
-skore==0.10.1
+skore==0.10.2
     # via skore-hub-project (skore-hub-project/pyproject.toml)
 skore-local-project==0.0.3
     # via skore

ci/requirements/skore-hub-project/python-3.11/scikit-learn-1.7/test-requirements.txt

@@ -246,7 +246,7 @@ six==1.17.0
     # via python-dateutil
 skops==0.13.0
     # via skore-hub-project (skore-hub-project/pyproject.toml)
-skore==0.10.1
+skore==0.10.2
     # via skore-hub-project (skore-hub-project/pyproject.toml)
 skore-local-project==0.0.3
     # via skore

ci/requirements/skore-hub-project/python-3.12/scikit-learn-1.4/test-requirements.txt

@@ -246,7 +246,7 @@ six==1.17.0
     # via python-dateutil
 skops==0.13.0
     # via skore-hub-project (skore-hub-project/pyproject.toml)
-skore==0.10.1
+skore==0.10.2
     # via skore-hub-project (skore-hub-project/pyproject.toml)
 skore-local-project==0.0.3
     # via skore

ci/requirements/skore-hub-project/python-3.12/scikit-learn-1.7/test-requirements.txt

@@ -246,7 +246,7 @@ six==1.17.0
     # via python-dateutil
 skops==0.13.0
     # via skore-hub-project (skore-hub-project/pyproject.toml)
-skore==0.10.1
+skore==0.10.2
     # via skore-hub-project (skore-hub-project/pyproject.toml)
 skore-local-project==0.0.3
     # via skore

ci/requirements/skore-hub-project/python-3.13/scikit-learn-1.5/test-requirements.txt

@@ -246,7 +246,7 @@ six==1.17.0
     # via python-dateutil
 skops==0.13.0
     # via skore-hub-project (skore-hub-project/pyproject.toml)
-skore==0.10.1
+skore==0.10.2
     # via skore-hub-project (skore-hub-project/pyproject.toml)
 skore-local-project==0.0.3
     # via skore

ci/requirements/skore-hub-project/python-3.13/scikit-learn-1.6/test-requirements.txt

@@ -246,7 +246,7 @@ six==1.17.0
     # via python-dateutil
 skops==0.13.0
     # via skore-hub-project (skore-hub-project/pyproject.toml)
-skore==0.10.1
+skore==0.10.2
     # via skore-hub-project (skore-hub-project/pyproject.toml)
 skore-local-project==0.0.3
     # via skore

ci/requirements/skore-hub-project/python-3.13/scikit-learn-1.7/test-requirements.txt

@@ -246,7 +246,7 @@ six==1.17.0
     # via python-dateutil
 skops==0.13.0
     # via skore-hub-project (skore-hub-project/pyproject.toml)
-skore==0.10.1
+skore==0.10.2
     # via skore-hub-project (skore-hub-project/pyproject.toml)
 skore-local-project==0.0.3
     # via skore

skore-hub-project/src/skore_hub_project/media/feature_importance.py

@@ -5,14 +5,15 @@
 from inspect import signature
 from typing import ClassVar, Literal, cast
 
+from pandas import DataFrame
 from pydantic import Field, computed_field
-from skore import EstimatorReport
+from skore import CrossValidationReport, EstimatorReport
 
 from .media import Media, Representation
 
 
 class FeatureImportance(Media):  # noqa: D101
-    report: EstimatorReport = Field(repr=False, exclude=True)
+    report: EstimatorReport | CrossValidationReport = Field(repr=False, exclude=True)
     accessor: ClassVar[str]
     category: Literal["feature_importance"] = "feature_importance"
 
@@ -32,15 +33,18 @@ def representation(self) -> Representation | None:  # noqa: D102
             k: v for k, v in self.attributes.items() if k in function_parameters
         }
 
-        dataframe = function(**function_kwargs)
+        result = function(**function_kwargs)
+
+        if not isinstance(result, DataFrame):
+            result = result.frame()
+
+        serialized = result.fillna("NaN").to_dict(orient="tight")
 
-        return Representation(
-            media_type="application/vnd.dataframe",
-            value=dataframe.fillna("NaN").to_dict(orient="tight"),
-        )
+        return Representation(media_type="application/vnd.dataframe", value=serialized)
 
 
 class Permutation(FeatureImportance):  # noqa: D101
+    report: EstimatorReport = Field(repr=False, exclude=True)
     accessor: ClassVar[str] = "feature_importance.permutation"
     key: str = "permutation"
     verbose_name: str = "Feature importance - Permutation"
@@ -55,6 +59,7 @@ class PermutationTest(Permutation):  # noqa: D101
 
 
 class MeanDecreaseImpurity(FeatureImportance):  # noqa: D101
+    report: EstimatorReport = Field(repr=False, exclude=True)
     accessor: ClassVar[str] = "feature_importance.mean_decrease_impurity"
     key: str = "mean_decrease_impurity"
     verbose_name: str = "Feature importance - Mean Decrease Impurity (MDI)"

skore-hub-project/tests/unit/media/test_feature_importance.py

@@ -1,6 +1,7 @@
 from functools import partialmethod
 from inspect import signature
 
+from pandas import DataFrame
 from pydantic import ValidationError
 from pytest import fixture, mark, param, raises
 from skore_hub_project.media import (
@@ -11,10 +12,6 @@
 )
 
 
-def serialize(dataframe):
-    return dataframe.fillna("NaN").to_dict(orient="tight")
-
-
 @fixture(autouse=True)
 def monkeypatch_permutation(monkeypatch):
     import skore
@@ -63,6 +60,14 @@ def monkeypatch_permutation(monkeypatch):
             {"method": "coefficients"},
             id="Coefficients",
         ),
+        param(
+            Coefficients,
+            "cv_regression",
+            "coefficients",
+            "Feature importance - Coefficients",
+            {"method": "coefficients"},
+            id="Coefficients",
+        ),
     ),
 )
 def test_feature_importance(
@@ -79,8 +84,13 @@ def test_feature_importance(
     function = getattr(report.feature_importance, accessor)
     function_parameters = signature(function).parameters
     function_kwargs = {k: v for k, v in attributes.items() if k in function_parameters}
-    dataframe = function(**function_kwargs)
-    dataframe_serialized = serialize(dataframe)
+
+    result = function(**function_kwargs)
+
+    if not isinstance(result, DataFrame):
+        result = result.frame()
+
+    serialized = result.fillna("NaN").to_dict(orient="tight")
 
     # available accessor
     assert Media(report=report).model_dump() == {
@@ -91,7 +101,7 @@ def test_feature_importance(
         "parameters": {},
         "representation": {
             "media_type": "application/vnd.dataframe",
-            "value": dataframe_serialized,
+            "value": serialized,
         },
     }