Fix FeatureInputComponent bool range crash (#328)

Author: oegedijk

RELEASE_NOTES.md

@@ -1,6 +1,11 @@
 # Release Notes
 
 
+## Version 0.5.6:
+
+### Bug Fixes
+- Fix FeatureInputComponent range calculation for boolean columns (avoid np.round on bools) and add a regression test.
+
 ## Version 0.5.5:
 
 ### Bug Fixes

explainerdashboard/__init__.py

@@ -1,4 +1,4 @@
-__version__ = "0.5.5"
+__version__ = "0.5.6"
 
 from .explainers import ClassifierExplainer, RegressionExplainer  # noqa
 from .dashboards import ExplainerDashboard, ExplainerHub, InlineExplainer  # noqa

explainerdashboard/dashboard_components/overview_components.py

@@ -8,6 +8,7 @@
 from math import ceil
 
 import numpy as np
+from pandas.api.types import is_bool_dtype
 
 from dash import html, dcc, Input, Output
 from dash.exceptions import PreventUpdate
@@ -1212,12 +1213,13 @@ def _generate_dash_input(self, col, onehot_cols, onehot_dict, cat_dict):
                 ]
             )
         else:
-            min_range = np.round(
-                self.explainer.X[col][lambda x: x != self.explainer.na_fill].min(), 2
-            )
-            max_range = np.round(
-                self.explainer.X[col][lambda x: x != self.explainer.na_fill].max(), 2
-            )
+            col_values = self.explainer.X[col][lambda x: x != self.explainer.na_fill]
+            if is_bool_dtype(col_values):
+                min_range = int(col_values.min())
+                max_range = int(col_values.max())
+            else:
+                min_range = np.round(col_values.min(), 2)
+                max_range = np.round(col_values.max(), 2)
             return html.Div(
                 [
                     dbc.Label(col),

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "explainerdashboard"
-version = "0.5.5"
+version = "0.5.6"
 description = "Quickly build Explainable AI dashboards that show the inner workings of so-called \"blackbox\" machine learning models."
 readme = "README.md"
 requires-python = ">=3.10"

tests/test_feature_input_component.py

@@ -0,0 +1,26 @@
+from sklearn.ensemble import RandomForestClassifier
+
+from explainerdashboard import ClassifierExplainer
+from explainerdashboard.dashboard_components.overview_components import (
+    FeatureInputComponent,
+)
+
+
+def test_feature_input_component_handles_bool_columns(classifier_data):
+    X_train, y_train, X_test, y_test = classifier_data
+
+    X_train = X_train.copy()
+    X_test = X_test.copy()
+
+    cutoff = X_train["Age"].median()
+    X_train["is_older"] = X_train["Age"] > cutoff
+    X_test["is_older"] = X_test["Age"] > cutoff
+
+    model = RandomForestClassifier(n_estimators=5, max_depth=2)
+    model.fit(X_train, y_train)
+
+    explainer = ClassifierExplainer(model, X_test, y_test)
+    component = FeatureInputComponent(explainer)
+
+    layout = component.layout()
+    assert layout is not None