diff --git a/docs/cruncher_demo.ipynb b/docs/cruncher_demo.ipynb
index 93fd262..7e93cb0 100644
--- a/docs/cruncher_demo.ipynb
+++ b/docs/cruncher_demo.ipynb
@@ -28,22 +28,7 @@
    "cell_type": "code",
    "execution_count": 2,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/Users/petermetz/anaconda3/envs/taxcrunch-env/lib/python3.7/site-packages/pandas/core/computation/expressions.py:68: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n",
-      "  return op(a, b)\n",
-      "/Users/petermetz/anaconda3/envs/taxcrunch-env/lib/python3.7/site-packages/pandas/core/computation/expressions.py:68: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n",
-      "  return op(a, b)\n",
-      "/Users/petermetz/anaconda3/envs/taxcrunch-env/lib/python3.7/site-packages/pandas/core/computation/expressions.py:68: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n",
-      "  return op(a, b)\n",
-      "/Users/petermetz/anaconda3/envs/taxcrunch-env/lib/python3.7/site-packages/pandas/core/computation/expressions.py:68: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n",
-      "  return op(a, b)\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "# path to input csv file\n",
     "CURRENT_PATH = os.path.abspath(os.path.dirname('file'))\n",
diff --git a/taxcrunch/cruncher.py b/taxcrunch/cruncher.py
index 783f304..dd3b374 100644
--- a/taxcrunch/cruncher.py
+++ b/taxcrunch/cruncher.py
@@ -151,7 +151,7 @@ def translate(self, ivar):
         # convert both Cruncher and Batch inputs (i.e. Single/Joint
         # and 0/1)
         mars = np.where(
-            np.logical_or(mstat == "Single", mstat == 1),
+            np.logical_or(mstat.astype(str) == "Single", mstat == 1),
             np.where(num_deps > 0, 4, 1),
             2,
         )