Bug: Raise ValueError with interpolate limit = 0

add whatsnew

Author: mroeschke

doc/source/whatsnew/v0.20.0.txt

@@ -238,6 +238,7 @@ Other API Changes
 - ``CParserError`` has been renamed to ``ParserError`` in ``pd.read_csv`` and will be removed in the future (:issue:`12665`)
 - ``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`)
+- ``interpolate()`` will raise a ``ValueError`` if the ``limit`` is not greater than 0.
 
 .. _whatsnew_0200.deprecations:
 

pandas/core/generic.py

@@ -3662,7 +3662,7 @@ 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.
@@ -3704,6 +3704,8 @@ def interpolate(self, method='linear', axis=0, limit=None, inplace=False,
         """
         Interpolate values according to different methods.
         """
+        if isinstance(limit, int) and not limit > 0:
+            raise ValueError("Interpolate `limit` must be greater than 0.")
 
         if self.ndim > 2:
             raise NotImplementedError("Interpolate has not been implemented "

pandas/tests/series/test_missing.py

@@ -730,6 +730,10 @@ def test_interp_limit(self):
         result = s.interpolate(method='linear', limit=2)
         assert_series_equal(result, expected)
 
+        # GH 9217
+        s = pd.Series([1, 2, np.nan, np.nan, 5])
+        tm.assertRaises(ValueError, lambda: s.interpolate(limit=0))
+
     def test_interp_limit_forward(self):
         s = Series([1, 3, np.nan, np.nan, np.nan, 11])