diff --git a/HowBadIsMyBatch.ipynb b/HowBadIsMyBatch.ipynb
index 3687098d3cd..a56e8a30030 100644
--- a/HowBadIsMyBatch.ipynb
+++ b/HowBadIsMyBatch.ipynb
@@ -40,6 +40,7 @@
     "            'VAERSDATA':\n",
     "                self._read_csv(\n",
     "                    folder + year + \"VAERSDATA.csv\",\n",
+    "                    # FK-TODO: use Column enum\n",
     "                    ['VAERS_ID', 'DIED', 'L_THREAT', 'DISABLE', 'HOSPITAL', 'ER_VISIT']),\n",
     "            'VAERSVAX':\n",
     "                    self._read_csv(\n",
@@ -122,51 +123,59 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "def createBatchCodeTable(df : pd.DataFrame):\n",
-    "    def filterDataFrame(df, col):\n",
-    "        return df[df[col] == 'Y'][['VAX_LOT']]\n",
+    "import pandas as pd\n",
     "\n",
-    "    batchCodeTableDict = {\n",
-    "        'ADRs': df[['VAX_LOT']].value_counts(),\n",
-    "        'DEATHS': filterDataFrame(df, 'DIED').value_counts(),\n",
-    "        'DISABILITIES': filterDataFrame(df, 'DISABLE').value_counts(),\n",
-    "        'LIFE THREATENING ILLNESSES': filterDataFrame(df, 'L_THREAT').value_counts()\n",
-    "    }\n",
-    "    return pd.concat(batchCodeTableDict, axis = 'columns').replace(to_replace = np.nan, value = 0)\n",
+    "class BatchCodeTableFactory:\n",
+    "    \n",
+    "    @staticmethod\n",
+    "    def createBatchCodeTable(df : pd.DataFrame):\n",
+    "        def filterDataFrame(df, col):\n",
+    "            return df[df[col] == 'Y'][['VAX_LOT']]\n",
     "\n",
-    "def createManufacturerByBatchCodeTable(df):\n",
-    "    manufacturerByBatchCodeTable = df[['VAX_LOT', 'VAX_MANU']]\n",
-    "    manufacturerByBatchCodeTable = manufacturerByBatchCodeTable.drop_duplicates(subset = ['VAX_LOT'])\n",
-    "    return manufacturerByBatchCodeTable.set_index('VAX_LOT')\n",
+    "        batchCodeTableDict = {\n",
+    "            'ADRs': df[['VAX_LOT']].value_counts(),\n",
+    "            'DEATHS': filterDataFrame(df, 'DIED').value_counts(),\n",
+    "            'DISABILITIES': filterDataFrame(df, 'DISABLE').value_counts(),\n",
+    "            'LIFE THREATENING ILLNESSES': filterDataFrame(df, 'L_THREAT').value_counts()\n",
+    "        }\n",
+    "        return pd.concat(batchCodeTableDict, axis = 'columns').replace(to_replace = np.nan, value = 0)\n",
     "\n",
-    "def createCompanyByBatchCodeTable(df):\n",
-    "    return createManufacturerByBatchCodeTable(df).rename(columns = {\"VAX_MANU\": \"COMPANY\"})\n",
+    "    # create table from https://www.howbadismybatch.com/combined.html\n",
+    "    # FK-TODO: DRY with createBatchCodeTable()\n",
+    "    @staticmethod\n",
+    "    def createSevereEffectsBatchCodeTable(df : pd.DataFrame):\n",
+    "        def filterDataFrame(df, col):\n",
+    "            return df[df[col] == 'Y']['VAX_LOT']\n",
     "\n",
-    "# create table from https://www.howbadismybatch.com/combined.html\n",
-    "# FK-TODO: DRY with createBatchCodeTable()\n",
-    "def createSevereEffectsBatchCodeTable(df):\n",
-    "    def filterDataFrame(df, col):\n",
-    "        return df[df[col] == 'Y']['VAX_LOT']\n",
+    "        batchCodeTableDict = {\n",
+    "            'ADRs': df['VAX_LOT'].value_counts(),\n",
+    "            'DEATHS': filterDataFrame(df, 'DIED').value_counts(),\n",
+    "            'DISABILITIES': filterDataFrame(df, 'DISABLE').value_counts(),\n",
+    "            'LIFE THREATENING ILLNESSES': filterDataFrame(df, 'L_THREAT').value_counts(),\n",
+    "            'HOSPITALISATIONS': filterDataFrame(df, 'HOSPITAL').value_counts(),\n",
+    "            'EMERGENCY ROOM OR DOCTOR VISITS': filterDataFrame(df, 'ER_VISIT').value_counts()\n",
+    "        }\n",
+    "        batchCodeTable = pd.concat(batchCodeTableDict, axis = 'columns')\n",
+    "        batchCodeTable.index.name = 'VAX_LOT'\n",
+    "        # add Company column:\n",
+    "        batchCodeTable = pd.merge(\n",
+    "                batchCodeTable,\n",
+    "                BatchCodeTableFactory._createCompanyByBatchCodeTable(df),\n",
+    "                how = 'left',\n",
+    "                left_index = True,\n",
+    "                right_index = True,\n",
+    "                validate = 'one_to_one')\n",
+    "        return batchCodeTable.replace(to_replace = np.nan, value = 0)\n",
     "\n",
-    "    batchCodeTableDict = {\n",
-    "        'ADRs': df['VAX_LOT'].value_counts(),\n",
-    "        'DEATHS': filterDataFrame(df, 'DIED').value_counts(),\n",
-    "        'DISABILITIES': filterDataFrame(df, 'DISABLE').value_counts(),\n",
-    "        'LIFE THREATENING ILLNESSES': filterDataFrame(df, 'L_THREAT').value_counts(),\n",
-    "        'HOSPITALISATIONS': filterDataFrame(df, 'HOSPITAL').value_counts(),\n",
-    "        'EMERGENCY ROOM OR DOCTOR VISITS': filterDataFrame(df, 'ER_VISIT').value_counts()\n",
-    "    }\n",
-    "    batchCodeTable = pd.concat(batchCodeTableDict, axis = 'columns')\n",
-    "    batchCodeTable.index.name = 'VAX_LOT'\n",
-    "    # add Company column:\n",
-    "    batchCodeTable = pd.merge(\n",
-    "            batchCodeTable,\n",
-    "            createCompanyByBatchCodeTable(df),\n",
-    "            how = 'left',\n",
-    "            left_index = True,\n",
-    "            right_index = True,\n",
-    "            validate = 'one_to_one')\n",
-    "    return batchCodeTable.replace(to_replace = np.nan, value = 0)\n"
+    "    @staticmethod\n",
+    "    def _createManufacturerByBatchCodeTable(df):\n",
+    "        manufacturerByBatchCodeTable = df[['VAX_LOT', 'VAX_MANU']]\n",
+    "        manufacturerByBatchCodeTable = manufacturerByBatchCodeTable.drop_duplicates(subset = ['VAX_LOT'])\n",
+    "        return manufacturerByBatchCodeTable.set_index('VAX_LOT')\n",
+    "\n",
+    "    @staticmethod\n",
+    "    def _createCompanyByBatchCodeTable(df):\n",
+    "        return BatchCodeTableFactory._createManufacturerByBatchCodeTable(df).rename(columns = {\"VAX_MANU\": \"COMPANY\"})\n"
    ]
   },
   {
@@ -415,7 +424,7 @@
     "\n",
     "    def _test_createBatchCodeTable(self, dataFrame):\n",
     "        # When\n",
-    "        batchCodeTable = createBatchCodeTable(dataFrame)\n",
+    "        batchCodeTable = BatchCodeTableFactory.createBatchCodeTable(dataFrame)\n",
     "\n",
     "        # Then\n",
     "        batchCodeTableExpected = pd.DataFrame(\n",
@@ -469,7 +478,7 @@
     "        dataFrame = DataFrameFilter(dataFrame).filterForSevereEffects(dose = '1')\n",
     "\n",
     "        # When\n",
-    "        batchCodeTable = createSevereEffectsBatchCodeTable(dataFrame)\n",
+    "        batchCodeTable = BatchCodeTableFactory.createSevereEffectsBatchCodeTable(dataFrame)\n",
     "\n",
     "        # Then\n",
     "        batchCodeTableExpected = pd.DataFrame(\n",
@@ -510,7 +519,7 @@
     "    vaersDescrs = VaersDescrReader(\"VAERS\").readAllVaersDescrs()\n",
     "    dataFrame = VaersDescr2DataFrameConverter.createDataFrameFromDescrs(vaersDescrs)\n",
     "    dataFrameFilter = DataFrameFilter(dataFrame)\n",
-    "    batchCodeTable = createBatchCodeTable(dataFrameFilter.filterBy(manufacturer = manufacturer, dose = '1'))\n",
+    "    batchCodeTable = BatchCodeTableFactory.createBatchCodeTable(dataFrameFilter.filterBy(manufacturer = manufacturer, dose = '1'))\n",
     "    display(manufacturer, batchCodeTable)\n",
     "    batchCodeTable.to_excel(excelFile)"
    ]
@@ -538,7 +547,7 @@
     "    vaersDescrs = VaersDescrReader(\"VAERS\").readAllVaersDescrs()\n",
     "    dataFrame = VaersDescr2DataFrameConverter.createDataFrameFromDescrs(vaersDescrs)\n",
     "    dataFrameFilter = DataFrameFilter(dataFrame)\n",
-    "    severeEffectsBatchCodeTable = createSevereEffectsBatchCodeTable(dataFrameFilter.filterForSevereEffects(dose = '1'))\n",
+    "    severeEffectsBatchCodeTable = BatchCodeTableFactory.createSevereEffectsBatchCodeTable(dataFrameFilter.filterForSevereEffects(dose = '1'))\n",
     "    display('severeEffectsBatchCodeTable', severeEffectsBatchCodeTable)\n",
     "    severeEffectsBatchCodeTable.to_excel(excelFile)"
    ]