diff --git a/src/HowBadIsMyBatch.ipynb b/src/HowBadIsMyBatch.ipynb
index fa16e57ea61..2feb0b0ffc2 100644
--- a/src/HowBadIsMyBatch.ipynb
+++ b/src/HowBadIsMyBatch.ipynb
@@ -202,13 +202,13 @@
     "        summationTable = SummationTableFactory.createSummationTable(\n",
     "            dataFrame,\n",
     "            columnNameMappingsDict = {\n",
-    "                \"DIED_size\": \"Total reports\",\n",
+    "                \"DIED_size\": \"Total Number of Adverse Reaction Reports\",\n",
     "                \"DIED_sum\": \"Deaths\",\n",
     "                \"L_THREAT_sum\": \"Life Threatening Illnesses\",\n",
     "                \"DISABLE_sum\": \"Disabilities\"\n",
     "            })\n",
-    "        summationTable['Severe reports (%)'] = (summationTable['Deaths'] + summationTable['Disabilities'] + summationTable['Life Threatening Illnesses']) / summationTable['Total reports'] * 100\n",
-    "        summationTable = summationTable[['Total reports', 'Deaths', 'Disabilities', 'Life Threatening Illnesses', 'Severe reports (%)']]\n",
+    "        summationTable['Severe reports (%)'] = (summationTable['Deaths'] + summationTable['Disabilities'] + summationTable['Life Threatening Illnesses']) / summationTable['Total Number of Adverse Reaction Reports'] * 100\n",
+    "        summationTable = summationTable[['Total Number of Adverse Reaction Reports', 'Deaths', 'Disabilities', 'Life Threatening Illnesses', 'Severe reports (%)']]\n",
     "        return summationTable\n",
     "\n",
     "    @staticmethod\n",
@@ -797,11 +797,11 @@
     "            doseTable,\n",
     "            pd.DataFrame(\n",
     "                data = {\n",
-    "                    'Total reports':              [2,                   1],\n",
-    "                    'Deaths':                     [2,                   1],\n",
-    "                    'Disabilities':               [1,                   0],\n",
-    "                    'Life Threatening Illnesses': [1,                   0],\n",
-    "                    'Severe reports (%)':         [(2 + 1 + 1)/2 * 100, (1 + 0 + 0)/1 * 100]\n",
+    "                    'Total Number of Adverse Reaction Reports': [2,                   1],\n",
+    "                    'Deaths':                                   [2,                   1],\n",
+    "                    'Disabilities':                             [1,                   0],\n",
+    "                    'Life Threatening Illnesses':               [1,                   0],\n",
+    "                    'Severe reports (%)':                       [(2 + 1 + 1)/2 * 100, (1 + 0 + 0)/1 * 100]\n",
     "                },\n",
     "                index = pd.Index(['1', '2'], dtype = \"string\", name = 'Dose')))\n",
     "                \n",
@@ -827,11 +827,11 @@
     "            doseByMonthTable,\n",
     "            pd.DataFrame(\n",
     "                data = {\n",
-    "                    'Total reports':              [2,                   1],\n",
-    "                    'Deaths':                     [2,                   1],\n",
-    "                    'Disabilities':               [1,                   0],\n",
-    "                    'Life Threatening Illnesses': [1,                   0],\n",
-    "                    'Severe reports (%)':         [(2 + 1 + 1)/2 * 100, (1 + 0 + 0)/1 * 100]\n",
+    "                    'Total Number of Adverse Reaction Reports': [2,                   1],\n",
+    "                    'Deaths':                                   [2,                   1],\n",
+    "                    'Disabilities':                             [1,                   0],\n",
+    "                    'Life Threatening Illnesses':               [1,                   0],\n",
+    "                    'Severe reports (%)':                       [(2 + 1 + 1)/2 * 100, (1 + 0 + 0)/1 * 100]\n",
     "                },\n",
     "                index = pd.MultiIndex.from_tuples(\n",
     "                    [\n",
@@ -876,10 +876,10 @@
     "        assert_frame_equal(\n",
     "            internationalLotTable,\n",
     "            TestHelper.createDataFrame(\n",
-    "                columns = ['Total reports', 'Deaths', 'Disabilities', 'Life Threatening Illnesses', 'Severe reports (%)'],\n",
-    "                data = [  [2,               2,        1,              1,                            (2 + 1 + 1) / 2 * 100],\n",
-    "                          [1,               1,        0,              0,                            (1 + 0 + 0) / 1 * 100],\n",
-    "                          [2,               0,        0,              0,                            (0 + 0 + 0) / 2 * 100]],\n",
+    "                columns = ['Total Number of Adverse Reaction Reports', 'Deaths', 'Disabilities', 'Life Threatening Illnesses', 'Severe reports (%)'],\n",
+    "                data = [  [2,                                          2,        1,              1,                            (2 + 1 + 1) / 2 * 100],\n",
+    "                          [1,                                          1,        0,              0,                            (1 + 0 + 0) / 1 * 100],\n",
+    "                          [2,                                          0,        0,              0,                            (0 + 0 + 0) / 2 * 100]],\n",
     "                index = pd.Index(\n",
     "                    [\n",
     "                        'France',\n",
@@ -910,9 +910,9 @@
     "        assert_frame_equal(\n",
     "            batchCodeTable,\n",
     "            TestHelper.createDataFrame(\n",
-    "                columns = ['Total reports', 'Deaths', 'Disabilities', 'Life Threatening Illnesses', 'Severe reports (%)'],\n",
-    "                data = [  [2,               1,        2,              2,                            (1 + 2 + 2) / 2 * 100],\n",
-    "                          [1,               1,        0,              0,                            (1 + 0 + 0) / 1 * 100]],\n",
+    "                columns = ['Total Number of Adverse Reaction Reports', 'Deaths', 'Disabilities', 'Life Threatening Illnesses', 'Severe reports (%)'],\n",
+    "                data = [  [2,                                          1,        2,              2,                            (1 + 2 + 2) / 2 * 100],\n",
+    "                          [1,                                          1,        0,              0,                            (1 + 0 + 0) / 1 * 100]],\n",
     "                index = pd.Index(\n",
     "                    [\n",
     "                        '030L20B',\n",
@@ -1115,7 +1115,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "internationalLotTable = internationalLotTable[internationalLotTable['Total reports'] > 50]\n",
+    "internationalLotTable = internationalLotTable[internationalLotTable['Total Number of Adverse Reaction Reports'] > 50]\n",
     "IOUtils.saveDataFrame(internationalLotTable, 'results/international/International_Deadly_Lots')\n",
     "internationalLotTable"
    ]
@@ -1129,7 +1129,7 @@
    "source": [
     "def createAndSaveAndDisplayBatchCodeTableByCountry(nonDomesticVaers, country):\n",
     "    batchCodeTable = InternationalLotTableFactory.createBatchCodeTableByCountry(nonDomesticVaers, country)\n",
-    "    batchCodeTable = batchCodeTable[batchCodeTable['Total reports'] > 50]\n",
+    "    batchCodeTable = batchCodeTable[batchCodeTable['Total Number of Adverse Reaction Reports'] > 50]\n",
     "    IOUtils.saveDataFrame(batchCodeTable, 'results/international/' + country)\n",
     "    display(country + \":\", batchCodeTable)\n",
     "\n",