updating ipython json export routine

ipython/CSV to JSON Tree.ipynb

@@ -23,7 +23,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 25,
    "metadata": {
     "collapsed": false
    },
@@ -76,8 +76,14 @@
     "    # Populate the JSON skeleton\n",
     "    \n",
     "    for k,v in zip(bcl_groups.keys(),bcl_groups.values()):\n",
+    "        dfvalue = df.ix[v][value_label].values[0]\n",
+    "        if type(dfvalue)==type('asdf'):\n",
+    "            tree[k[0]][k[1]][k[2]] = float(df.ix[v][value_label].values[0][1:])\n",
+    "        else:\n",
+    "            tree[k[0]][k[1]][k[2]] = dfvalue\n",
     "        #tree[k[0]][k[1]][k[2]] = df.ix[v][value_label].values[0]\n",
-    "        tree[k[0]][k[1]][k[2]] = float(df.ix[v][value_label].values[0][1:])\n",
+    "\n",
+    "        \n",
     "    \n",
     "    #print json.dumps(tree, indent=4, separators=(',', ': '))\n",
     "\n",
@@ -113,7 +119,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 26,
    "metadata": {
     "collapsed": false
    },
@@ -130,24 +136,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 28,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [
-    {
-     "ename": "IndexError",
-     "evalue": "invalid index to scalar variable.",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mIndexError\u001b[0m                                Traceback (most recent call last)",
-      "\u001b[0;32m<ipython-input-17-18fc238f31e7>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0mgroupby_groups\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m'Fund'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'Department'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'BCL Name'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0mvalue_label\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m'2013 Expenditure Allowance'\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m \u001b[0mtree_json\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtreeify_dataframe\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdf\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mgroupby_groups\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mvalue_label\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      5\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      6\u001b[0m \u001b[0;32mwith\u001b[0m \u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'budget2013.json'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'w'\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m<ipython-input-15-1d515b754da2>\u001b[0m in \u001b[0;36mtreeify_dataframe\u001b[0;34m(df, groupby_groups, value_label)\u001b[0m\n\u001b[1;32m     47\u001b[0m     \u001b[0;32mfor\u001b[0m \u001b[0mk\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mv\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mzip\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbcl_groups\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mkeys\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mbcl_groups\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     48\u001b[0m         \u001b[0;31m#tree[k[0]][k[1]][k[2]] = df.ix[v][value_label].values[0]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 49\u001b[0;31m         \u001b[0mtree\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfloat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mix\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mv\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mvalue_label\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     50\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     51\u001b[0m     \u001b[0;31m#print json.dumps(tree, indent=4, separators=(',', ': '))\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;31mIndexError\u001b[0m: invalid index to scalar variable."
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "df = pd.read_csv('budget2013.csv')\n",
     "groupby_groups = ['Fund','Department','BCL Name']\n",
@@ -160,7 +153,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 29,
    "metadata": {
     "collapsed": false
    },