add match messages

pandas/core/arrays/categorical.py

@@ -339,8 +339,8 @@ def __init__(self, values, categories=None, ordered=None, dtype=None,
                     msg = "Unknown `dtype` {dtype}"
                     raise ValueError(msg.format(dtype=dtype))
             elif categories is not None or ordered is not None:
-                raise ValueError("Cannot specify both `dtype` and `categories`"
-                                 " or `ordered`.")
+                raise ValueError("Cannot specify `categories` or `ordered` "
+                                 "together with `dtype`.")
 
             categories = dtype.categories
 
@@ -673,8 +673,8 @@ def from_codes(cls, codes, categories=None, ordered=None, dtype=None):
         """
         if dtype is not None:
             if categories is not None or ordered is not None:
-                raise ValueError("Cannot specify both `dtype` and `categories`"
-                                 " or `ordered`.")
+                raise ValueError("Cannot specify `categories` or `ordered` "
+                                 "together with `dtype`.")
         else:
             dtype = CategoricalDtype(categories, ordered)
 

pandas/tests/arrays/categorical/test_constructors.py

@@ -77,7 +77,9 @@ def test_constructor_unsortable(self):
         assert not factor.ordered
 
         # this however will raise as cannot be sorted
-        with pytest.raises(TypeError):
+        msg = ("'values' is not ordered, please explicitly specify the "
+               "categories order by passing in a categories argument.")
+        with pytest.raises(TypeError, match=msg):
             Categorical(arr, ordered=True)
 
     def test_constructor_interval(self):
@@ -99,10 +101,11 @@ def test_constructor(self):
         tm.assert_numpy_array_equal(c2.__array__(), exp_arr)
 
         # categories must be unique
-        with pytest.raises(ValueError):
+        msg = "Categorical categories must be unique"
+        with pytest.raises(ValueError, match=msg):
             Categorical([1, 2], [1, 2, 2])
 
-        with pytest.raises(ValueError):
+        with pytest.raises(ValueError, match=msg):
             Categorical(["a", "b"], ["a", "b", "b"])
 
         # The default should be unordered
@@ -211,21 +214,23 @@ def test_constructor(self):
 
     def test_constructor_not_sequence(self):
         # https://github.com/pandas-dev/pandas/issues/16022
-        with pytest.raises(TypeError):
+        msg = r"^Index\(\.\.\.\) must be called with a collection of some kind"
+        with pytest.raises(TypeError, match=msg):
             Categorical(['a', 'b'], categories='a')
 
     def test_constructor_with_null(self):
 
         # Cannot have NaN in categories
-        with pytest.raises(ValueError):
+        msg = "Categorial categories cannot be null"
+        with pytest.raises(ValueError, match=msg):
             Categorical([np.nan, "a", "b", "c"],
                         categories=[np.nan, "a", "b", "c"])
 
-        with pytest.raises(ValueError):
+        with pytest.raises(ValueError, match=msg):
             Categorical([None, "a", "b", "c"],
                         categories=[None, "a", "b", "c"])
 
-        with pytest.raises(ValueError):
+        with pytest.raises(ValueError, match=msg):
             Categorical(DatetimeIndex(['nat', '20160101']),
                         categories=[NaT, Timestamp('20160101')])
 
@@ -347,13 +352,14 @@ def test_constructor_with_dtype(self, ordered):
 
     def test_constructor_dtype_and_others_raises(self):
         dtype = CategoricalDtype(['a', 'b'], ordered=True)
-        with pytest.raises(ValueError, match="Cannot"):
+        msg = "Cannot specify `categories` or `ordered` together with `dtype`."
+        with pytest.raises(ValueError, match=msg):
             Categorical(['a', 'b'], categories=['a', 'b'], dtype=dtype)
 
-        with pytest.raises(ValueError, match="Cannot"):
+        with pytest.raises(ValueError, match=msg):
             Categorical(['a', 'b'], ordered=True, dtype=dtype)
 
-        with pytest.raises(ValueError, match="Cannot"):
+        with pytest.raises(ValueError, match=msg):
             Categorical(['a', 'b'], ordered=False, dtype=dtype)
 
     @pytest.mark.parametrize('categories', [
@@ -418,30 +424,35 @@ def test_from_codes(self):
 
         # too few categories
         dtype = CategoricalDtype(categories=[1, 2])
-        with pytest.raises(ValueError):
+        msg = "codes need to be between "
+        with pytest.raises(ValueError, match=msg):
             Categorical.from_codes([1, 2], categories=dtype.categories)
-        with pytest.raises(ValueError):
+        with pytest.raises(ValueError, match=msg):
             Categorical.from_codes([1, 2], dtype=dtype)
 
         # no int codes
-        with pytest.raises(ValueError):
+        msg = "codes need to be array-like integers"
+        with pytest.raises(ValueError, match=msg):
             Categorical.from_codes(["a"], categories=dtype.categories)
-        with pytest.raises(ValueError):
+        with pytest.raises(ValueError, match=msg):
             Categorical.from_codes(["a"], dtype=dtype)
 
         # no unique categories
-        with pytest.raises(ValueError):
+        with pytest.raises(ValueError,
+                           match="Categorical categories must be unique"):
             Categorical.from_codes([0, 1, 2], categories=["a", "a", "b"])
 
         # NaN categories included
-        with pytest.raises(ValueError):
+        with pytest.raises(ValueError,
+                           match="Categorial categories cannot be null"):
             Categorical.from_codes([0, 1, 2], categories=["a", "b", np.nan])
 
         # too negative
         dtype = CategoricalDtype(categories=["a", "b", "c"])
-        with pytest.raises(ValueError):
+        msg = r"codes need to be between -1 and len\(categories\)-1"
+        with pytest.raises(ValueError, match=msg):
             Categorical.from_codes([-2, 1, 2], categories=dtype.categories)
-        with pytest.raises(ValueError):
+        with pytest.raises(ValueError, match=msg):
             Categorical.from_codes([-2, 1, 2], dtype=dtype)
 
         exp = Categorical(["a", "b", "c"], ordered=False)
@@ -469,16 +480,19 @@ def test_from_codes_with_categorical_categories(self):
         tm.assert_categorical_equal(result, expected)
 
         # non-unique Categorical still raises
-        with pytest.raises(ValueError):
+        with pytest.raises(ValueError,
+                           match="Categorical categories must be unique"):
             Categorical.from_codes([0, 1], Categorical(['a', 'b', 'a']))
 
     def test_from_codes_with_nan_code(self):
         # GH21767
         codes = [1, 2, np.nan]
         dtype = CategoricalDtype(categories=['a', 'b', 'c'])
-        with pytest.raises(ValueError):
+        with pytest.raises(ValueError,
+                           match="codes need to be array-like integers"):
             Categorical.from_codes(codes, categories=dtype.categories)
-        with pytest.raises(ValueError):
+        with pytest.raises(ValueError,
+                           match="codes need to be array-like integers"):
             Categorical.from_codes(codes, dtype=dtype)
 
     def test_from_codes_with_float(self):
@@ -495,9 +509,11 @@ def test_from_codes_with_float(self):
         tm.assert_numpy_array_equal(cat.codes, np.array([1, 2, 0], dtype='i1'))
 
         codes = [1.1, 2.0, 0]  # non-integer
-        with pytest.raises(ValueError):
+        with pytest.raises(ValueError,
+                           match="codes need to be array-like integers"):
             Categorical.from_codes(codes, dtype.categories)
-        with pytest.raises(ValueError):
+        with pytest.raises(ValueError,
+                           match="codes need to be array-like integers"):
             Categorical.from_codes(codes, dtype=dtype)
 
     @pytest.mark.parametrize('dtype', [None, 'category'])

pandas/tests/indexes/test_category.py

@@ -156,7 +156,7 @@ def test_construction_with_categorical_dtype(self):
         tm.assert_index_equal(result, expected, exact=True)
 
         # error when combining categories/ordered and dtype kwargs
-        msg = 'Cannot specify both `dtype` and `categories` or `ordered`.'
+        msg = "Cannot specify `categories` or `ordered` together with `dtype`."
         with pytest.raises(ValueError, match=msg):
             CategoricalIndex(data, categories=cats, dtype=dtype)