diff --git a/numpy/ma/core.py b/numpy/ma/core.py
index 18e902bffb4c..e4f1a9584b38 100644
--- a/numpy/ma/core.py
+++ b/numpy/ma/core.py
@@ -2698,8 +2698,11 @@ class MaskedArray(ndarray):
     _defaultmask = nomask
     _defaulthardmask = False
     _baseclass = ndarray
-    # Maximum number of elements per axis used when printing an array.
+
+    # Maximum number of elements per axis used when printing an array. The
+    # 1d case is handled separately because we need more values in this case.
     _print_width = 100
+    _print_width_1d = 1500
 
     def __new__(cls, data=None, mask=nomask, dtype=None, copy=False,
                 subok=True, ndmin=0, fill_value=None, keep_mask=True,
@@ -3776,9 +3779,11 @@ def __str__(self):
                     mask = m
                     # For big arrays, to avoid a costly conversion to the
                     # object dtype, extract the corners before the conversion.
+                    print_width = (self._print_width if self.ndim > 1
+                                   else self._print_width_1d)
                     for axis in range(self.ndim):
-                        if data.shape[axis] > self._print_width:
-                            ind = self._print_width // 2
+                        if data.shape[axis] > print_width:
+                            ind = print_width // 2
                             arr = np.split(data, (ind, -ind), axis=axis)
                             data = np.concatenate((arr[0], arr[2]), axis=axis)
                             arr = np.split(mask, (ind, -ind), axis=axis)
diff --git a/numpy/ma/tests/test_core.py b/numpy/ma/tests/test_core.py
index 95afe4ce9972..7f9b36d543f7 100644
--- a/numpy/ma/tests/test_core.py
+++ b/numpy/ma/tests/test_core.py
@@ -451,6 +451,15 @@ def test_str_repr(self):
                               '             mask = [False  True False],\n'
                               '       fill_value = 999999)\n')
 
+        a = np.ma.arange(2000)
+        a[1:50] = np.ma.masked
+        assert_equal(
+            repr(a),
+            'masked_array(data = [0 -- -- ..., 1997 1998 1999],\n'
+            '             mask = [False  True  True ..., False False False],\n'
+            '       fill_value = 999999)\n'
+        )
+
     def test_pickling(self):
         # Tests pickling
         a = arange(10)