Bug: Raise ValueError with interpolate limit = 0

add whatsnew

Add similar log to fillna

Update whatsnew with issue and fillna change

Add test for a negative limit

change if statements to assert

move limit check closer to where the variable is used

Author: mroeschke

doc/source/whatsnew/v0.20.0.txt

@@ -361,6 +361,7 @@ Other API Changes
 - ``SparseArray.cumsum()`` and ``SparseSeries.cumsum()`` will now always return ``SparseArray`` and ``SparseSeries`` respectively (:issue:`12855`)
 - ``DataFrame.applymap()`` with an empty ``DataFrame`` will return a copy of the empty ``DataFrame`` instead of a ``Series`` (:issue:`8222`)
 - ``.loc`` has compat with ``.ix`` for accepting iterators, and NamedTuples (:issue:`15120`)
+- ``interpolate()`` and ``fillna()`` will raise a ``ValueError`` if the ``limit`` keyword argument is not greater than 0. (:issue:`9217`)
 - ``pd.read_csv()`` will now issue a ``ParserWarning`` whenever there are conflicting values provided by the ``dialect`` parameter and the user (:issue:`14898`)
 - ``pd.read_csv()`` will now raise a ``ValueError`` for the C engine if the quote character is larger than than one byte (:issue:`11592`)
 - ``inplace`` arguments now require a boolean value, else a ``ValueError`` is thrown (:issue:`14189`)

pandas/core/generic.py

@@ -3248,7 +3248,7 @@ def convert_objects(self, convert_dates=True, convert_numeric=False,
             a gap with more than this number of consecutive NaNs, it will only
             be partially filled. If method is not specified, this is the
             maximum number of entries along the entire axis where NaNs will be
-            filled.
+            filled. Must be greater than 0 if not None.
         downcast : dict, default is None
             a dict of item->dtype of what to downcast if possible,
             or the string 'infer' which will try to downcast to an appropriate
@@ -3267,6 +3267,7 @@ def convert_objects(self, convert_dates=True, convert_numeric=False,
     def fillna(self, value=None, method=None, axis=None, inplace=False,
                limit=None, downcast=None):
         inplace = validate_bool_kwarg(inplace, 'inplace')
+
         if isinstance(value, (list, tuple)):
             raise TypeError('"value" parameter must be a scalar or dict, but '
                             'you passed a "{0}"'.format(type(value).__name__))
@@ -3278,7 +3279,6 @@ def fillna(self, value=None, method=None, axis=None, inplace=False,
             axis = 0
         axis = self._get_axis_number(axis)
         method = missing.clean_fill_method(method)
-
         from pandas import DataFrame
         if value is None:
             if method is None:
@@ -3673,7 +3673,7 @@ def replace(self, to_replace=None, value=None, inplace=False, limit=None,
             * 0: fill column-by-column
             * 1: fill row-by-row
         limit : int, default None.
-            Maximum number of consecutive NaNs to fill.
+            Maximum number of consecutive NaNs to fill. Must be greater than 0.
         limit_direction : {'forward', 'backward', 'both'}, default 'forward'
             If limit is specified, consecutive NaNs will be filled in this
             direction.

pandas/core/internals.py

@@ -372,6 +372,9 @@ 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):
+                assert limit > 0, ('`limit` keyword argument 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

@@ -12,7 +12,7 @@
                                  is_float_dtype, is_datetime64_dtype,
                                  is_datetime64tz_dtype, is_integer_dtype,
                                  _ensure_float64, is_scalar,
-                                 needs_i8_conversion)
+                                 needs_i8_conversion, is_integer)
 from pandas.types.missing import isnull
 
 
@@ -169,7 +169,10 @@ def _interp_limit(invalid, fw_limit, bw_limit):
     # the beginning (see issues #9218 and #10420)
     violate_limit = sorted(start_nans)
 
-    if limit:
+    if limit is not None:
+        if is_integer(limit):
+            assert limit > 0, ('`limit` keyword argument must be greater '
+                               'than 0.')
         if limit_direction == 'forward':
             violate_limit = sorted(start_nans | set(_interp_limit(invalid,
                                                                   limit, 0)))

pandas/tests/series/test_missing.py

@@ -297,6 +297,11 @@ 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(AssertionError, lambda: s.fillna(1, limit=limit))
+
     def test_fillna_nat(self):
         series = Series([0, 1, 2, tslib.iNaT], dtype='M8[ns]')
 
@@ -867,6 +872,11 @@ 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(AssertionError, lambda: s.interpolate(limit=limit))
+
     def test_interp_limit_forward(self):
         s = Series([1, 3, np.nan, np.nan, np.nan, 11])