diff --git a/src/HowBadIsMyBatch.ipynb b/src/HowBadIsMyBatch.ipynb
index 4920d0f0491..9f720a10a60 100644
--- a/src/HowBadIsMyBatch.ipynb
+++ b/src/HowBadIsMyBatch.ipynb
@@ -151,6 +151,9 @@
     "        return dataFrame[dataFrame[countryColumnName] == country]\n",
     "\n",
     "    def filterBy(self, dataFrame, manufacturer = None, dose = None):\n",
+    "        if manufacturer is None and dose is None:\n",
+    "            return dataFrame\n",
+    "        \n",
     "        return dataFrame[self._isManufacturer(dataFrame, manufacturer) & self._isDose(dataFrame, dose)]\n",
     "\n",
     "    def _isCovid19(self, dataFrame):\n",
@@ -607,6 +610,20 @@
     "                \"801423\"])\n",
     "        assert_frame_equal(dataFrameActual, dataFrameExpected, check_dtype = False)\n",
     "\n",
+    "    def test_filterByNothing(self):\n",
+    "        # Given\n",
+    "        dataFrame = TestHelper.createDataFrame(\n",
+    "            columns = ['DIED', 'L_THREAT', 'DISABLE', 'VAX_TYPE',   'VAX_MANU',                    'VAX_LOT', 'VAX_DOSE_SERIES'],\n",
+    "            data = [  [0,       0,         0,         'FLU(H1N1)',  'GLAXOSMITHKLINE BIOLOGICALS', '5R3J5',   '1']],\n",
+    "            index = [\"801410\"])\n",
+    "        dataFrameFilter = DataFrameFilter()\n",
+    "            \n",
+    "        # When\n",
+    "        dataFrameActual = dataFrameFilter.filterBy(dataFrame, manufacturer = None, dose = None)\n",
+    "        \n",
+    "        # Then\n",
+    "        assert_frame_equal(dataFrameActual, dataFrame, check_dtype = True)\n",
+    "\n",
     "    def test_filterByCovid19_filterBy(self):\n",
     "        # Given\n",
     "        dataFrame = VaersDescr2DataFrameConverter.createDataFrameFromDescrs(\n",
@@ -1548,6 +1565,98 @@
    "source": [
     "see https://www.bitchute.com/video/4HlIyBmOEJeY/ and https://www.bitchute.com/video/8wJYP2NpGwN2/"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f4196935",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def getFluBatchCodeTable(vaers):\n",
+    "    dataFrame = DataFrameFilter().filterByFlu(vaers)\n",
+    "    return _getCovid19BatchCodeTable(dataFrame)\n",
+    "\n",
+    "def getCovid19BatchCodeTable(vaers, manufacturer = None):\n",
+    "    dataFrame = DataFrameFilter().filterByCovid19(vaers)\n",
+    "    dataFrame = DataFrameFilter().filterBy(dataFrame, manufacturer = manufacturer)\n",
+    "    return _getCovid19BatchCodeTable(dataFrame)\n",
+    "\n",
+    "def _getCovid19BatchCodeTable(dataFrame):\n",
+    "    batchCodeTable = BatchCodeTableFactory._createSummationTableByVAX_LOT(dataFrame)[\n",
+    "        [\n",
+    "            'Total Number of Adverse Reaction Reports',\n",
+    "            'Deaths',\n",
+    "            'Disabilities',\n",
+    "            'Life Threatening Illnesses',\n",
+    "            'Company',\n",
+    "            'Lethality'\n",
+    "        ]].reset_index()\n",
+    "    batchCodeTable = batchCodeTable.sort_values(by = 'VAX_LOT', ascending = True)\n",
+    "    return batchCodeTable\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "6eeab206",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "fluBatchCodeTable = getFluBatchCodeTable(vaers2019)\n",
+    "IOUtils.saveDataFrame(fluBatchCodeTable, 'results/flu/flu')\n",
+    "fluBatchCodeTable"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a66be712",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "covid19PfizerBatchCodeTable = getCovid19BatchCodeTable(vaers, manufacturer = 'PFIZER\\BIONTECH')\n",
+    "IOUtils.saveDataFrame(covid19PfizerBatchCodeTable, 'results/flu/covid19Pfizer')\n",
+    "covid19PfizerBatchCodeTable"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "9bcc91ab",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#import seaborn as sns\n",
+    "#\n",
+    "#sns.set(rc = {'figure.figsize': (11.7, 8.27)})\n",
+    "#sns.set_theme()\n",
+    "#chart = sns.stripplot(x = \"VAX_LOT\", y = \"Total Number of Adverse Reaction Reports\", data = covid19PfizerBatchCodeTable)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "622b454a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "covid19ModernaBatchCodeTable = getCovid19BatchCodeTable(vaers, manufacturer = 'MODERNA')\n",
+    "IOUtils.saveDataFrame(covid19ModernaBatchCodeTable, 'results/flu/covid19Moderna')\n",
+    "covid19ModernaBatchCodeTable"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "0a47dcb4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "covid19JanssenBatchCodeTable = getCovid19BatchCodeTable(vaers, manufacturer = 'JANSSEN')\n",
+    "IOUtils.saveDataFrame(covid19JanssenBatchCodeTable, 'results/flu/covid19Janssen')\n",
+    "covid19JanssenBatchCodeTable"
+   ]
   }
  ],
  "metadata": {
diff --git a/src/help.txt b/src/help.txt
index 50020c5eceb..9ece86bb4ed 100644
--- a/src/help.txt
+++ b/src/help.txt
@@ -13,6 +13,9 @@ FK-TODO:
   - https://www.bitchute.com/video/4HlIyBmOEJeY/
   - https://www.bitchute.com/video/8wJYP2NpGwN2/
   - https://www.howbad.info/expiry.html
+  - https://www.howbadismybatch.com/moderna20A21A.pdf
+  - https://www.howbadismybatch.com/deathbylottery.pdf
+  - https://dailyexpose.uk/2021/10/31/100-percent-of-covid-19-vaccine-deaths-caused-by-just-5-percent-of-the-batches-produced/?fbclid=IwAR0U4RWwoehj2mEQpDixoQYfo9JpRhZvuP_6w4z_At2Z-Tez-EVvToW4PX4
 - https://www.howbadismybatch.com/geography.html nachprogrammieren
 - handle VAX_DOSE_SERIES = 'UNK' or 'N/A' like '1'?
 - Format des jeweiligen Herstellers berücksichtigen und "verschmutzte" Einträge säubern, denn sie stellen alle dieselbe Charge dar: