Unify ValueError message and correct cython limits

Add stricter integer check with tests

Author: mroeschke

pandas/core/internals.py

@@ -372,9 +372,10 @@ def fillna(self, value, limit=None, inplace=False, downcast=None,
         original_value = value
         mask = isnull(self.values)
         if limit is not None:
-            if is_integer(limit) and limit < 1:
-                raise ValueError('`limit` keyword argument must be greater '
-                                 'than 0.')
+            if not is_integer(limit):
+                raise ValueError('Limit must be an integer')
+            if limit < 1:
+                raise ValueError('Limit must be greater than 0')
             if self.ndim > 2:
                 raise NotImplementedError("number of dimensions for 'fillna' "
                                           "is currently limited to 2")

pandas/core/missing.py

@@ -170,9 +170,10 @@ def _interp_limit(invalid, fw_limit, bw_limit):
     violate_limit = sorted(start_nans)
 
     if limit is not None:
-        if is_integer(limit) and limit < 1:
-            raise ValueError('`limit` keyword argument must be greater '
-                             'than 0.')
+        if not is_integer(limit):
+            raise ValueError('Limit must be an integer')
+        if limit < 1:
+            raise ValueError('Limit must be greater than 0')
         if limit_direction == 'forward':
             violate_limit = sorted(start_nans | set(_interp_limit(invalid,
                                                                   limit, 0)))

pandas/src/algos_common_helper.pxi.in

@@ -83,8 +83,10 @@ def pad_{{name}}(ndarray[{{c_type}}] old, ndarray[{{c_type}}] new,
     if limit is None:
         lim = nright
     else:
-        if limit < 0:
-            raise ValueError('Limit must be non-negative')
+        if not util.is_integer_object(limit):
+            raise ValueError('Limit must be an integer')
+        if limit < 1:
+            raise ValueError('Limit must be greater than 0')
         lim = limit
 
     if nleft == 0 or nright == 0 or new[nright - 1] < old[0]:
@@ -146,8 +148,10 @@ def pad_inplace_{{name}}(ndarray[{{c_type}}] values,
     if limit is None:
         lim = N
     else:
-        if limit < 0:
-            raise ValueError('Limit must be non-negative')
+        if not util.is_integer_object(limit):
+            raise ValueError('Limit must be an integer')
+        if limit < 1:
+            raise ValueError('Limit must be greater than 0')
         lim = limit
 
     val = values[0]
@@ -180,8 +184,10 @@ def pad_2d_inplace_{{name}}(ndarray[{{c_type}}, ndim=2] values,
     if limit is None:
         lim = N
     else:
-        if limit < 0:
-            raise ValueError('Limit must be non-negative')
+        if not util.is_integer_object(limit):
+            raise ValueError('Limit must be an integer')
+        if limit < 1:
+            raise ValueError('Limit must be greater than 0')
         lim = limit
 
     for j in range(K):
@@ -240,8 +246,10 @@ def backfill_{{name}}(ndarray[{{c_type}}] old, ndarray[{{c_type}}] new,
     if limit is None:
         lim = nright
     else:
-        if limit < 0:
-            raise ValueError('Limit must be non-negative')
+        if not util.is_integer_object(limit):
+            raise ValueError('Limit must be an integer')
+        if limit < 1:
+            raise ValueError('Limit must be greater than 0')
         lim = limit
 
     if nleft == 0 or nright == 0 or new[0] > old[nleft - 1]:
@@ -304,8 +312,10 @@ def backfill_inplace_{{name}}(ndarray[{{c_type}}] values,
     if limit is None:
         lim = N
     else:
-        if limit < 0:
-            raise ValueError('Limit must be non-negative')
+        if not util.is_integer_object(limit):
+            raise ValueError('Limit must be an integer')
+        if limit < 1:
+            raise ValueError('Limit must be greater than 0')
         lim = limit
 
     val = values[N - 1]
@@ -338,8 +348,10 @@ def backfill_2d_inplace_{{name}}(ndarray[{{c_type}}, ndim=2] values,
     if limit is None:
         lim = N
     else:
-        if limit < 0:
-            raise ValueError('Limit must be non-negative')
+        if not util.is_integer_object(limit):
+            raise ValueError('Limit must be an integer')
+        if limit < 1:
+            raise ValueError('Limit must be greater than 0')
         lim = limit
 
     for j in range(K):

pandas/tests/series/test_missing.py

@@ -295,10 +295,12 @@ def test_fillna_raise(self):
         self.assertRaises(TypeError, s.fillna, [1, 2])
         self.assertRaises(TypeError, s.fillna, (1, 2))
 
-        # related GH 9217, make sure limit is greater than 0
-        for limit in [-1, 0]:
-            s = Series([1, 2, 3, None])
-            tm.assertRaises(ValueError, lambda: s.fillna(1, limit=limit))
+        # related GH 9217, make sure limit is an int and greater than 0
+        s = Series([1, 2, 3, None])
+        for limit in [-1, 0, 1., 2.]:
+            for method in ['backfill', 'bfill', 'pad', 'ffill', None]:
+                with tm.assertRaises(ValueError):
+                    s.fillna(1, limit=limit, method=method)
 
     def test_fillna_nat(self):
         series = Series([0, 1, 2, tslib.iNaT], dtype='M8[ns]')
@@ -870,10 +872,16 @@ def test_interp_limit(self):
         result = s.interpolate(method='linear', limit=2)
         assert_series_equal(result, expected)
 
-        # GH 9217
-        for limit in [-1, 0]:
-            s = pd.Series([1, 2, np.nan, np.nan, 5])
-            tm.assertRaises(ValueError, lambda: s.interpolate(limit=limit))
+        # GH 9217, make sure limit is an int and greater than 0
+        methods = ['linear', 'time', 'index', 'values', 'nearest', 'zero',
+                   'slinear', 'quadratic', 'cubic', 'barycentric', 'krogh',
+                   'polynomial', 'spline', 'piecewise_polynomial', None,
+                   'from_derivatives', 'pchip', 'akima']
+        s = pd.Series([1, 2, np.nan, np.nan, 5])
+        for limit in [-1, 0, 1., 2.]:
+            for method in methods:
+                with tm.assertRaises(ValueError):
+                    s.interpolate(limit=limit, method=method)
 
     def test_interp_limit_forward(self):
         s = Series([1, 3, np.nan, np.nan, np.nan, 11])