Minor fix to outputVar json creation.

Author: smlindauer

examples/data/hmeqModels/DecisionTreeClassifier/outputVar.json

@@ -1,14 +1,14 @@
 [
     {
         "name": "EM_EVENTPROBABILITY",
-        "length": 8,
-        "type": "decimal",
-        "level": "interval"
-    },
-    {
-        "name": "EM_CLASSIFICATION",
         "length": 1,
         "type": "string",
         "level": "nominal"
+    },
+    {
+        "name": "EM_CLASSIFICATION",
+        "length": 8,
+        "type": "decimal",
+        "level": "interval"
     }
 ]

examples/data/hmeqModels/GradientBoosting/outputVar.json

@@ -1,14 +1,14 @@
 [
     {
         "name": "EM_EVENTPROBABILITY",
-        "length": 8,
-        "type": "decimal",
-        "level": "interval"
-    },
-    {
-        "name": "EM_CLASSIFICATION",
         "length": 1,
         "type": "string",
         "level": "nominal"
+    },
+    {
+        "name": "EM_CLASSIFICATION",
+        "length": 8,
+        "type": "decimal",
+        "level": "interval"
     }
 ]

examples/data/hmeqModels/RandomForest/outputVar.json

@@ -1,14 +1,14 @@
 [
     {
         "name": "EM_EVENTPROBABILITY",
-        "length": 8,
-        "type": "decimal",
-        "level": "interval"
-    },
-    {
-        "name": "EM_CLASSIFICATION",
         "length": 1,
         "type": "string",
         "level": "nominal"
+    },
+    {
+        "name": "EM_CLASSIFICATION",
+        "length": 8,
+        "type": "decimal",
+        "level": "interval"
     }
 ]

examples/pzmmModelImportExample.ipynb

@@ -635,7 +635,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 20,
    "metadata": {
     "Collapsed": "false"
    },
@@ -667,9 +667,7 @@
     "    J.writeVarJSON(data[predict], isInput=True, jPath=zipFolder)\n",
     "    \n",
     "    # Set output variables and assign an event threshold, then write output variable mapping\n",
-    "    outputVar = pd.DataFrame(columns=['EM_EVENTPROBABILITY', 'EM_CLASSIFICATION'])\n",
-    "    outputVar['EM_CLASSIFICATION'].loc[1] = 'A'#yTrain.astype('category').cat.categories.astype('str')\n",
-    "    outputVar['EM_EVENTPROBABILITY'].loc[1] = 0.5 # Event threshold\n",
+    "    outputVar = pd.DataFrame(columns=['EM_EVENTPROBABILITY', 'EM_CLASSIFICATION'], data=[['A', 0.5]]) # data argument includes example expected types for columns\n",
     "    J.writeVarJSON(outputVar, isInput=False, jPath=zipFolder)\n",
     "    \n",
     "    # Write model properties to a json file\n",