diff --git a/.vscode/launch.json b/.vscode/launch.json
new file mode 100644
index 00000000000..b6e68446328
--- /dev/null
+++ b/.vscode/launch.json
@@ -0,0 +1,15 @@
+{
+    // Verwendet IntelliSense zum Ermitteln möglicher Attribute.
+    // Zeigen Sie auf vorhandene Attribute, um die zugehörigen Beschreibungen anzuzeigen.
+    // Weitere Informationen finden Sie unter https://go.microsoft.com/fwlink/?linkid=830387
+    "version": "0.2.0",
+    "configurations": [
+        {
+            "type": "pwa-chrome",
+            "request": "launch",
+            "name": "Launch Chrome against localhost",
+            "url": "http://localhost:8080",
+            "webRoot": "${workspaceFolder}"
+        }
+    ]
+}
\ No newline at end of file
diff --git a/HowBadIsMyBatch.ipynb b/HowBadIsMyBatch.ipynb
index ab6161eba56..20f7a5120e6 100644
--- a/HowBadIsMyBatch.ipynb
+++ b/HowBadIsMyBatch.ipynb
@@ -9,6 +9,7 @@
    "source": [
     "import numpy as np\n",
     "import pandas as pd\n",
+    "\n",
     "pd.set_option('display.max_rows', 100)\n",
     "pd.set_option('display.max_columns', None)"
    ]
@@ -20,15 +21,15 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "def createDataFrame(manufacturer):\n",
-    "    def read_csv(file):\n",
-    "        return pd.read_csv(file, index_col='VAERS_ID', encoding='latin1', low_memory=False)\n",
+    "def createDataFrame(baseDir, manufacturer):\n",
+    "    def read_csv(file, usecols):\n",
+    "        return pd.read_csv(file, index_col='VAERS_ID', encoding='latin1', low_memory=False, usecols=usecols)\n",
     "        \n",
     "    def createDataFrameForYear(year):\n",
-    "        folder = \"VAERS/\" + year + \"VAERSData/\"\n",
+    "        folder = baseDir + \"/VAERS/\" + year + \"VAERSData/\"\n",
     "        return pd.merge(\n",
-    "            read_csv(folder + year + \"VAERSDATA.csv\"),\n",
-    "            read_csv(folder + year + \"VAERSVAX.csv\"),\n",
+    "            read_csv(folder + year + \"VAERSDATA.csv\", ['VAERS_ID','DIED', 'L_THREAT', 'DISABLE']),\n",
+    "            read_csv(folder + year + \"VAERSVAX.csv\", ['VAERS_ID','VAX_TYPE', 'VAX_MANU', 'VAX_LOT']),\n",
     "            left_index=True,\n",
     "            right_index=True)\n",
     "        \n",
@@ -45,16 +46,15 @@
    "source": [
     "def createPivotTable(df):\n",
     "    def filter(df, col):\n",
-    "        return df[df[col]=='Y'][['VAX_LOT']]\n",
+    "        return df[df[col] == 'Y'][['VAX_LOT']]\n",
     "\n",
-    "    return pd.concat(\n",
-    "        {\n",
-    "            'ADRs': df[['VAX_LOT']].value_counts(),\n",
-    "            'DEATHS': filter(df, 'DIED').value_counts(),\n",
-    "            'DISABILITIES': filter(df, 'DISABLE').value_counts(),\n",
-    "            'LIFE THREATENING ILLNESSES': filter(df, 'L_THREAT').value_counts()\n",
-    "        },\n",
-    "        axis=1)"
+    "    pivotTableDict = {\n",
+    "        'ADRs': df[['VAX_LOT']].value_counts(),\n",
+    "        'DEATHS': filter(df, 'DIED').value_counts(),\n",
+    "        'DISABILITIES': filter(df, 'DISABLE').value_counts(),\n",
+    "        'LIFE THREATENING ILLNESSES': filter(df, 'L_THREAT').value_counts()\n",
+    "    }\n",
+    "    return pd.concat(pivotTableDict, axis=1).replace(to_replace=np.nan, value=0)\n"
    ]
   },
   {
@@ -64,7 +64,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "df_moderna = createDataFrame(\"MODERNA\")"
+    "df_moderna = createDataFrame(\".\", \"MODERNA\")"
    ]
   },
   {
@@ -91,11 +91,65 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "bb7b2963",
-   "metadata": {},
+   "metadata": {
+    "scrolled": false
+   },
    "outputs": [],
    "source": [
     "pivotTable"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "9f506ac8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import unittest"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e14465d7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from pandas.testing import assert_frame_equal\n",
+    "\n",
+    "\n",
+    "class HowBadIsMyBatchTest(unittest.TestCase):\n",
+    "\n",
+    "    def test_createPivotTable(self):\n",
+    "        # Given\n",
+    "        pivotTable = createPivotTable(createDataFrame(\"test\", \"MODERNA\"))\n",
+    "\n",
+    "        # When\n",
+    "        pivotTableExpected = pd.DataFrame(\n",
+    "            {\n",
+    "                'ADRs': [2, 1],\n",
+    "                'DEATHS': [0, 1],\n",
+    "                'DISABILITIES': [2, 0],\n",
+    "                'LIFE THREATENING ILLNESSES': [0.0, 0.0]\n",
+    "            },\n",
+    "            index=pd.MultiIndex.from_arrays([['025L20A', '037K20A']], names=('VAX_LOT',)))\n",
+    "        display(\"actual:\", pivotTable)\n",
+    "        display(\"expected:\", pivotTableExpected)\n",
+    "\n",
+    "        # Then\n",
+    "        assert_frame_equal(pivotTable, pivotTableExpected, check_dtype=False)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ef8f99c4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "unittest.main(argv=[''], verbosity=2, exit=False)"
+   ]
   }
  ],
  "metadata": {