FIX PowerTransformer raise when "box-cox" has nan column (scikit-learn#26400)

Co-authored-by: Olivier Grisel <olivier.grisel@ensta.org>

Author: Charlie-XIAO

doc/whats_new/v1.3.rst

@@ -628,6 +628,10 @@ Changelog
   The `sample_interval_` attribute is deprecated and will be removed in 1.5.
   :pr:`25190` by :user:`Vincent Maladière <Vincent-Maladiere>`.
 
+- |Fix| :class:`preprocessing.PowerTransformer` now correcly raises error when
+  using `method="box-cox"` on data with a constant `np.nan` column.
+  :pr:`26400` by :user:`Yao Xiao <Charlie-XIAO>`.
+
 :mod:`sklearn.svm`
 ..................
 

sklearn/preprocessing/_data.py

@@ -3311,9 +3311,13 @@ def _box_cox_optimize(self, x):
 
         We here use scipy builtins which uses the brent optimizer.
         """
+        mask = np.isnan(x)
+        if np.all(mask):
+            raise ValueError("Column must not be all nan.")
+
         # the computation of lambda is influenced by NaNs so we need to
         # get rid of them
-        _, lmbda = stats.boxcox(x[~np.isnan(x)], lmbda=None)
+        _, lmbda = stats.boxcox(x[~mask], lmbda=None)
 
         return lmbda
 

sklearn/preprocessing/tests/test_data.py

@@ -2527,6 +2527,21 @@ def test_power_transformer_copy_False(method, standardize):
     assert X_trans is X_inv_trans
 
 
+def test_power_transformer_box_cox_raise_all_nans_col():
+    """Check that box-cox raises informative when a column contains all nans.
+
+    Non-regression test for gh-26303
+    """
+    X = rng.random_sample((4, 5))
+    X[:, 0] = np.nan
+
+    err_msg = "Column must not be all nan."
+
+    pt = PowerTransformer(method="box-cox")
+    with pytest.raises(ValueError, match=err_msg):
+        pt.fit_transform(X)
+
+
 @pytest.mark.parametrize(
     "X_2",
     [