diff --git a/python/cudf/cudf/_lib/parquet.pyx b/python/cudf/cudf/_lib/parquet.pyx
index 6eaf0536d9..68bb4ae1b4 100644
--- a/python/cudf/cudf/_lib/parquet.pyx
+++ b/python/cudf/cudf/_lib/parquet.pyx
@@ -222,25 +222,28 @@ cpdef read_parquet(filepaths_or_buffers, columns=None, row_groups=None,
 
     column_names = [x.decode() for x in c_out_table.metadata.column_names]
 
-    # Access the Parquet user_data json to find the index
     index_col = None
-    cdef map[string, string] user_data = c_out_table.metadata.user_data
-    json_str = user_data[b'pandas'].decode('utf-8')
-    meta = None
-    if json_str != "":
-        meta = json.loads(json_str)
-        if 'index_columns' in meta and len(meta['index_columns']) > 0:
-            index_col = meta['index_columns']
-            if isinstance(index_col[0], dict) and \
-                    index_col[0]['kind'] == 'range':
-                is_range_index = True
-            else:
-                is_range_index = False
-                index_col_names = OrderedDict()
-                for idx_col in index_col:
-                    for c in meta['columns']:
-                        if c['field_name'] == idx_col:
-                            index_col_names[idx_col] = c['name']
+    cdef map[string, string] user_data
+    if use_pandas_metadata:
+        # Access the Parquet user_data json to find the index
+        user_data = c_out_table.metadata.user_data
+        json_str = user_data[b'pandas'].decode('utf-8')
+        meta = None
+        if json_str != "":
+            meta = json.loads(json_str)
+            if 'index_columns' in meta and len(meta['index_columns']) > 0:
+                index_col = meta['index_columns']
+                if isinstance(index_col[0], dict) and \
+                        index_col[0]['kind'] == 'range':
+                    is_range_index = True
+                else:
+                    is_range_index = False
+                    index_col_names = OrderedDict()
+                    for idx_col in index_col:
+                        for c in meta['columns']:
+                            if c['field_name'] == idx_col:
+                                index_col_names[idx_col] = c['name']
+
     df = cudf.DataFrame._from_table(
         Table.from_unique_ptr(
             move(c_out_table.tbl),