TST: fill with limit in sparse. BUG: limit in sparse frame. GH #1197 #993

Author: Chang She

pandas/sparse/frame.py

@@ -741,10 +741,10 @@ def apply(self, func, axis=0, broadcast=False):
                 return self._apply_broadcast(func, axis)
 
     @Appender(DataFrame.fillna.__doc__)
-    def fillna(self, value=None, method='pad', inplace=False):
+    def fillna(self, value=None, method='pad', inplace=False, limit=None):
         new_series = {}
         for k, v in self.iterkv():
-            new_series[k] = v.fillna(value=value, method=method)
+            new_series[k] = v.fillna(value=value, method=method, limit=limit)
 
         if inplace:
             self._series = new_series

pandas/tseries/tests/test_timeseries.py

@@ -211,6 +211,89 @@ def test_frame_fillna_limit(self):
         expected.values[:3] = np.nan
         tm.assert_frame_equal(result, expected)
 
+    def test_sparse_series_fillna_limit(self):
+        index = np.arange(10)
+        s = Series(np.random.randn(10), index=index)
+
+        ss = s[:2].reindex(index).to_sparse()
+        result = ss.fillna(method='pad', limit=5)
+        expected = ss.fillna(method='pad', limit=5)
+        expected = expected.to_dense()
+        expected[-3:] = np.nan
+        expected = expected.to_sparse()
+        assert_series_equal(result, expected)
+
+        ss = s[-2:].reindex(index).to_sparse()
+        result = ss.fillna(method='backfill', limit=5)
+        expected = ss.fillna(method='backfill')
+        expected = expected.to_dense()
+        expected[:3] = np.nan
+        expected = expected.to_sparse()
+        assert_series_equal(result, expected)
+
+    def test_sparse_series_pad_backfill_limit(self):
+        index = np.arange(10)
+        s = Series(np.random.randn(10), index=index)
+        s = s.to_sparse()
+
+        result = s[:2].reindex(index, method='pad', limit=5)
+        expected = s[:2].reindex(index).fillna(method='pad')
+        expected = expected.to_dense()
+        expected[-3:] = np.nan
+        expected = expected.to_sparse()
+        assert_series_equal(result, expected)
+
+        result = s[-2:].reindex(index, method='backfill', limit=5)
+        expected = s[-2:].reindex(index).fillna(method='backfill')
+        expected = expected.to_dense()
+        expected[:3] = np.nan
+        expected = expected.to_sparse()
+        assert_series_equal(result, expected)
+
+    def test_sparse_frame_pad_backfill_limit(self):
+        index = np.arange(10)
+        df = DataFrame(np.random.randn(10, 4), index=index)
+        sdf = df.to_sparse()
+
+        result = sdf[:2].reindex(index, method='pad', limit=5)
+
+        expected = sdf[:2].reindex(index).fillna(method='pad')
+        expected = expected.to_dense()
+        expected.values[-3:] = np.nan
+        expected = expected.to_sparse()
+        tm.assert_frame_equal(result, expected)
+
+        result = sdf[-2:].reindex(index, method='backfill', limit=5)
+
+        expected = sdf[-2:].reindex(index).fillna(method='backfill')
+        expected = expected.to_dense()
+        expected.values[:3] = np.nan
+        expected = expected.to_sparse()
+        tm.assert_frame_equal(result, expected)
+
+    def test_sparse_frame_fillna_limit(self):
+        index = np.arange(10)
+        df = DataFrame(np.random.randn(10, 4), index=index)
+        sdf = df.to_sparse()
+
+        result = sdf[:2].reindex(index)
+        result = result.fillna(method='pad', limit=5)
+
+        expected = sdf[:2].reindex(index).fillna(method='pad')
+        expected = expected.to_dense()
+        expected.values[-3:] = np.nan
+        expected = expected.to_sparse()
+        tm.assert_frame_equal(result, expected)
+
+        result = sdf[-2:].reindex(index)
+        result = result.fillna(method='backfill', limit=5)
+
+        expected = sdf[-2:].reindex(index).fillna(method='backfill')
+        expected = expected.to_dense()
+        expected.values[:3] = np.nan
+        expected = expected.to_sparse()
+        tm.assert_frame_equal(result, expected)
+
     def test_pad_require_monotonicity(self):
         rng = date_range('1/1/2000', '3/1/2000', freq='B')