with tests update is better

jeremiedbb · jeremiedbb · commit fb1a4e9f4add · 2018-06-20T10:40:15.000+02:00
diff --git a/sklearn/impute.py b/sklearn/impute.py
@@ -181,7 +181,7 @@ def _validate_input(self, X):
                 raise ve
 
         if X.dtype.kind not in ("i", "u", "f", "O"):
-            raise ValueError("SimpleImputer does not work on data with dtype "
+            raise ValueError("SimpleImputer does not support data with dtype "
                              "{0}. Please provide either a numeric array (with"
                              " a floating point or integer dtype) or "
                              "categorical data represented either as an array "
diff --git a/sklearn/tests/test_impute.py b/sklearn/tests/test_impute.py
@@ -217,7 +217,7 @@ def test_imputation_mean_median_error_invalid_type(strategy, dtype):
                   [4, "e", 6],
                   ["g", "h", 9]], dtype=dtype)
 
-    with pytest.raises(TypeError, match="non-numeric data"):
+    with pytest.raises(ValueError, match="non-numeric data"):
         imputer = SimpleImputer(strategy=strategy)
         imputer.fit_transform(X)
 
@@ -234,8 +234,8 @@ def test_imputation_const_mostf_error_invalid_types(strategy, dtype):
         [np.nan, "c", "d", "h"],
     ], dtype=dtype)
 
-    err_msg = "SimpleImputer does not support this datatype"
-    with pytest.raises(TypeError, match=err_msg):
+    err_msg = "SimpleImputer does not support data"
+    with pytest.raises(ValueError, match=err_msg):
         imputer = SimpleImputer(strategy=strategy)
         imputer.fit(X).transform(X)
 
