removing some unused analysis
This commit is contained in:
frankknoll
@@ -230,95 +230,6 @@
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" dataFrame.columns = [\"_\".join(a) for a in dataFrame.columns.to_flat_index()]\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "99945ca8",
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"metadata": {},
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"outputs": [],
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"source": [
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"import pandas as pd\n",
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"\n",
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"class BatchCodeTableFactory:\n",
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"\n",
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" @staticmethod\n",
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" def createBatchCodeTable(dataFrame : pd.DataFrame, minADRsForLethality = None):\n",
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" dataFrame = DataFrameFilter().filterByCovid19(dataFrame)\n",
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" batchCodeTable = BatchCodeTableFactory._createSummationTableByVAX_LOT(dataFrame)[\n",
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" [\n",
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" 'Adverse Reaction Reports',\n",
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" 'Deaths',\n",
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" 'Disabilities',\n",
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" 'Life Threatening Illnesses',\n",
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" 'Company',\n",
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" 'Lethality'\n",
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" ]]\n",
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" if minADRsForLethality is not None:\n",
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" batchCodeTable.loc[batchCodeTable['Adverse Reaction Reports'] < minADRsForLethality, 'Lethality'] = np.nan\n",
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" return batchCodeTable\n",
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"\n",
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" # create table from https://www.howbadismybatch.com/combined.html\n",
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" @staticmethod\n",
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" def createSevereEffectsBatchCodeTable(dataFrame : pd.DataFrame, dose):\n",
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" dataFrame = DataFrameFilter().filterByCovid19(dataFrame)\n",
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" dataFrame = DataFrameFilter().filterBy(dataFrame, dose = dose)\n",
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" return BatchCodeTableFactory._createSummationTableByVAX_LOT(dataFrame)[\n",
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" [\n",
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" 'Adverse Reaction Reports', \n",
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" 'Deaths',\n",
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" 'Disabilities',\n",
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" 'Life Threatening Illnesses',\n",
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" 'Hospitalisations',\n",
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" 'Emergency Room or Doctor Visits',\n",
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" 'Company'\n",
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" ]]\n",
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"\n",
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" @staticmethod\n",
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" def _createSummationTableByVAX_LOT(dataFrame):\n",
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" batchCodeTable = SummationTableFactory.createSummationTable(dataFrame.groupby('VAX_LOT'))\n",
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" batchCodeTable['Lethality'] = batchCodeTable['Deaths'] / batchCodeTable['Adverse Reaction Reports'] * 100\n",
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" batchCodeTable = batchCodeTable[\n",
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" [\n",
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" 'Adverse Reaction Reports',\n",
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" 'Deaths',\n",
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" 'Disabilities',\n",
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" 'Life Threatening Illnesses',\n",
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" 'Hospitalisations',\n",
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" 'Emergency Room or Doctor Visits',\n",
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" 'Lethality'\n",
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" ]]\n",
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" batchCodeTable = batchCodeTable.sort_values(by = 'Adverse Reaction Reports', ascending = False)\n",
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" return CompanyColumnAdder.addCompanyColumn(batchCodeTable, CompanyColumnAdder.createCompanyByBatchCodeTable(dataFrame))\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "41d4fa30",
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"metadata": {},
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"outputs": [],
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"source": [
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"class DoseTableFactory:\n",
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" \n",
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" @staticmethod\n",
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" def createDoseTable(dataFrame):\n",
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" dataFrame = DataFrameFilter().filterByCovid19(dataFrame)\n",
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" return SummationTableFactory.createSummationTableHavingSevereReportsColumn(\n",
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" dataFrame.groupby(\n",
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" dataFrame['VAX_DOSE_SERIES'].rename('Dose')))\n",
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"\n",
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" @staticmethod\n",
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" def createDoseByMonthTable(dataFrame):\n",
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" dataFrame = DataFrameFilter().filterByCovid19(dataFrame)\n",
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" return SummationTableFactory.createSummationTableHavingSevereReportsColumn(\n",
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" dataFrame.groupby(\n",
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" [\n",
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" dataFrame['RECVDATE'].dt.year.rename('Year'),\n",
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" dataFrame['RECVDATE'].dt.month.rename('Month'),\n",
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" dataFrame['VAX_DOSE_SERIES'].rename('Dose')\n",
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" ]))\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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@@ -861,263 +772,6 @@
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" assert_frame_equal(dataFrame, dataFrameExpected, check_dtype = False)\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "e14465d7",
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"metadata": {},
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"outputs": [],
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"source": [
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"from pandas.testing import assert_frame_equal\n",
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"\n",
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"class BatchCodeTableFactoryTest(unittest.TestCase):\n",
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"\n",
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" def test_createSevereEffectsBatchCodeTable(self):\n",
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" # Given\n",
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" dataFrame = VaersDescr2DataFrameConverter.createDataFrameFromDescrs(\n",
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" [\n",
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" {\n",
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" 'VAERSDATA': TestHelper.createDataFrame(\n",
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" columns = ['DIED', 'L_THREAT', 'DISABLE', 'HOSPITAL', 'ER_VISIT'],\n",
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" data = [ [1, 1, 0, 1, 1],\n",
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" [0, 0, 1, 0, 1]],\n",
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" index = [\n",
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" \"0916600\",\n",
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" \"0916601\"]),\n",
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" 'VAERSVAX': TestHelper.createDataFrame(\n",
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" columns = ['VAX_TYPE', 'VAX_MANU', 'VAX_LOT', 'VAX_DOSE_SERIES'],\n",
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" data = [ ['COVID19', 'MODERNA', '037K20A', '1'],\n",
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" ['COVID19', 'PFIZER\\BIONTECH', '025L20A', '1']],\n",
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" index = [\n",
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" \"0916600\",\n",
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" \"0916601\"],\n",
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" dtypes = {'VAX_DOSE_SERIES': \"string\"})\n",
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" }\n",
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" ])\n",
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" dataFrame = SevereColumnAdder.addSevereColumn(dataFrame)\n",
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"\n",
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" # When\n",
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" batchCodeTable = BatchCodeTableFactory.createSevereEffectsBatchCodeTable(dataFrame, '1')\n",
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"\n",
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" # Then\n",
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" batchCodeTableExpected = pd.DataFrame(\n",
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" data = {\n",
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" 'Adverse Reaction Reports': [1, 1],\n",
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" 'Deaths': [0, 1],\n",
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" 'Disabilities': [1, 0],\n",
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" 'Life Threatening Illnesses': [0, 1],\n",
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" 'Hospitalisations': [0, 1],\n",
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" 'Emergency Room or Doctor Visits': [1, 1],\n",
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" 'Company': ['PFIZER\\BIONTECH', 'MODERNA']\n",
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" },\n",
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" index = pd.Index(['025L20A', '037K20A'], name = 'VAX_LOT'))\n",
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" assert_frame_equal(batchCodeTable, batchCodeTableExpected, check_dtype = False)\n",
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"\n",
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" def test_createBatchCodeTable(self):\n",
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" # Given\n",
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" dataFrame = VaersDescr2DataFrameConverter.createDataFrameFromDescrs(\n",
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" [\n",
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" {\n",
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" 'VAERSDATA': TestHelper.createDataFrame(\n",
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" columns = ['DIED', 'L_THREAT', 'DISABLE', 'HOSPITAL', 'ER_VISIT'],\n",
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" data = [ [1, 0, 0, 0, 0],\n",
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" [0, 0, 1, 0, 0]],\n",
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" index = [\n",
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" \"0916600\",\n",
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" \"0916601\"]),\n",
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" 'VAERSVAX': TestHelper.createDataFrame(\n",
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" columns = ['VAX_TYPE', 'VAX_MANU', 'VAX_LOT', 'VAX_DOSE_SERIES'],\n",
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" data = [ ['COVID19', 'MODERNA', '037K20A', '1'],\n",
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" ['COVID19', 'MODERNA', '025L20A', '1']],\n",
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" index = [\n",
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" \"0916600\",\n",
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" \"0916601\"],\n",
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" dtypes = {'VAX_DOSE_SERIES': \"string\"})\n",
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" },\n",
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" {\n",
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" 'VAERSDATA': TestHelper.createDataFrame(\n",
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" columns = ['DIED', 'L_THREAT', 'DISABLE', 'HOSPITAL', 'ER_VISIT'],\n",
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" data = [ [0, 0, 0, 0, 0],\n",
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" [0, 0, 1, 0, 0]],\n",
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" index = [\n",
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" \"1996873\",\n",
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" \"1996874\"]),\n",
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" 'VAERSVAX': TestHelper.createDataFrame(\n",
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" columns = ['VAX_TYPE', 'VAX_MANU', 'VAX_LOT', 'VAX_DOSE_SERIES'],\n",
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" data = [ ['HPV9', 'MERCK & CO. INC.', 'R017624', 'UNK'],\n",
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" ['COVID19', 'MODERNA', '025L20A', '1']],\n",
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" index = [\n",
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" \"1996873\",\n",
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" \"1996874\"],\n",
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" dtypes = {'VAX_DOSE_SERIES': \"string\"})\n",
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" }\n",
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" ])\n",
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" self._test_createBatchCodeTable(dataFrame)\n",
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"\n",
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" def test_createBatchCodeTable_minADRsForLethality(self):\n",
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" # Given\n",
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" dataFrame = VaersDescr2DataFrameConverter.createDataFrameFromDescrs(\n",
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" [\n",
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" {\n",
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" 'VAERSDATA': TestHelper.createDataFrame(\n",
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" columns = ['DIED', 'L_THREAT', 'DISABLE', 'HOSPITAL', 'ER_VISIT'],\n",
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" data = [ [1, 0, 0, 0, 0],\n",
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" [0, 0, 1, 0, 0]],\n",
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" index = [\n",
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" \"0916600\",\n",
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" \"0916601\"]),\n",
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" 'VAERSVAX': TestHelper.createDataFrame(\n",
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" columns = ['VAX_TYPE', 'VAX_MANU', 'VAX_LOT', 'VAX_DOSE_SERIES'],\n",
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" data = [ ['COVID19', 'MODERNA', '037K20A', '1'],\n",
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" ['COVID19', 'MODERNA', '025L20A', '1']],\n",
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" index = [\n",
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" \"0916600\",\n",
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" \"0916601\"],\n",
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" dtypes = {'VAX_DOSE_SERIES': \"string\"})\n",
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" },\n",
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" {\n",
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" 'VAERSDATA': TestHelper.createDataFrame(\n",
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" columns = ['DIED', 'L_THREAT', 'DISABLE', 'HOSPITAL', 'ER_VISIT'],\n",
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" data = [ [0, 0, 0, 0, 0],\n",
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" [0, 0, 1, 0, 0]],\n",
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" index = [\n",
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" \"1996873\",\n",
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" \"1996874\"]),\n",
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" 'VAERSVAX': TestHelper.createDataFrame(\n",
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" columns = ['VAX_TYPE', 'VAX_MANU', 'VAX_LOT', 'VAX_DOSE_SERIES'],\n",
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" data = [ ['HPV9', 'MERCK & CO. INC.', 'R017624', 'UNK'],\n",
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" ['COVID19', 'MODERNA', '025L20A', '1']],\n",
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" index = [\n",
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" \"1996873\",\n",
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" \"1996874\"],\n",
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" dtypes = {'VAX_DOSE_SERIES': \"string\"})\n",
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" }\n",
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" ])\n",
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" dataFrame = SevereColumnAdder.addSevereColumn(dataFrame)\n",
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"\n",
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" # When\n",
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" batchCodeTable = BatchCodeTableFactory.createBatchCodeTable(dataFrame, minADRsForLethality = 2)\n",
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"\n",
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" # Then\n",
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" batchCodeTableExpected = pd.DataFrame(\n",
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" data = {\n",
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" 'Adverse Reaction Reports': [2, 1],\n",
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" 'Deaths': [0, 1],\n",
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" 'Disabilities': [2, 0],\n",
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" 'Life Threatening Illnesses': [0, 0],\n",
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" 'Company': ['MODERNA', 'MODERNA'],\n",
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" 'Lethality': [0/2 * 100, np.nan]\n",
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" },\n",
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" index = pd.Index(['025L20A', '037K20A'], name = 'VAX_LOT'))\n",
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" assert_frame_equal(batchCodeTable, batchCodeTableExpected, check_dtype = False)\n",
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"\n",
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" def test_createBatchCodeTableFromFiles(self):\n",
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" dataFrame = VaersDescr2DataFrameConverter.createDataFrameFromDescrs(\n",
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" VaersDescrReader(dataDir = \"test/VAERS\").readVaersDescrsForYears([2021, 2022]))\n",
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" DataFrameNormalizer.normalize(dataFrame)\n",
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" self._test_createBatchCodeTable(dataFrame)\n",
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"\n",
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" def _test_createBatchCodeTable(self, dataFrame):\n",
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" dataFrame = SevereColumnAdder.addSevereColumn(dataFrame)\n",
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"\n",
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" # When\n",
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" batchCodeTable = BatchCodeTableFactory.createBatchCodeTable(dataFrame)\n",
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"\n",
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" # Then\n",
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" batchCodeTableExpected = pd.DataFrame(\n",
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" data = {\n",
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" 'Adverse Reaction Reports': [2, 1],\n",
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" 'Deaths': [0, 1],\n",
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" 'Disabilities': [2, 0],\n",
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" 'Life Threatening Illnesses': [0, 0],\n",
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" 'Company': ['MODERNA', 'MODERNA'],\n",
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" 'Lethality': [0/2 * 100, 1/1 * 100]\n",
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" },\n",
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" index = pd.Index(['025L20A', '037K20A'], name = 'VAX_LOT'))\n",
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" assert_frame_equal(batchCodeTable, batchCodeTableExpected, check_dtype = False)\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "44c121ec",
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"metadata": {},
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"outputs": [],
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"source": [
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"from pandas.testing import assert_frame_equal\n",
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"\n",
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"class DoseTableFactoryTest(unittest.TestCase):\n",
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"\n",
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" def test_createDoseTable(self):\n",
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" # Given\n",
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" dataFrame = TestHelper.createDataFrame(\n",
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" columns = ['DIED', 'L_THREAT', 'DISABLE', 'VAX_TYPE', 'VAX_MANU', 'VAX_LOT', 'VAX_DOSE_SERIES', 'HOSPITAL', 'ER_VISIT'],\n",
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" data = [ [1, 0, 0, 'COVID19', 'MODERNA', '016M20A', '2', 0, 0],\n",
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" [1, 0, 0, 'COVID19', 'MODERNA', '030L20A', '1', 0, 0],\n",
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" [1, 1, 1, 'COVID19', 'MODERNA', '030L20B', '1', 0, 0]],\n",
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" index = [\n",
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" \"1048786\",\n",
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" \"1048786\",\n",
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" \"4711\"],\n",
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" dtypes = {'VAX_DOSE_SERIES': \"string\"})\n",
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" dataFrame = SevereColumnAdder.addSevereColumn(dataFrame)\n",
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" \n",
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" # When\n",
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" doseTable = DoseTableFactory.createDoseTable(dataFrame)\n",
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"\n",
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" # Then\n",
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" assert_frame_equal(\n",
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" doseTable,\n",
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" pd.DataFrame(\n",
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" data = {\n",
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" 'Adverse Reaction Reports': [2, 1],\n",
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" 'Deaths': [2, 1],\n",
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" 'Disabilities': [1, 0],\n",
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" 'Life Threatening Illnesses': [1, 0],\n",
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" 'Severe reports': [2/2 * 100, 1/1 * 100],\n",
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" 'Lethality': [2/2 * 100, 1/1 * 100]\n",
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" },\n",
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" index = pd.Index(['1', '2'], dtype = \"string\", name = 'Dose')))\n",
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" \n",
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" def test_createDoseByMonthTable(self):\n",
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" # Given\n",
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" parseDate = lambda dateStr: pd.to_datetime(dateStr, format = \"%m/%d/%Y\")\n",
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" dataFrame = TestHelper.createDataFrame(\n",
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" columns = ['RECVDATE', 'DIED', 'L_THREAT', 'DISABLE', 'VAX_TYPE', 'VAX_MANU', 'VAX_LOT', 'VAX_DOSE_SERIES', 'HOSPITAL', 'ER_VISIT'],\n",
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" data = [ [parseDate('01/01/2021'), 1, 0, 0, 'COVID19', 'MODERNA', '016M20A', '2', 0, 0],\n",
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" [parseDate('01/01/2021'), 1, 0, 0, 'COVID19', 'MODERNA', '030L20A', '1', 0, 0],\n",
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" [parseDate('01/01/2021'), 1, 1, 1, 'COVID19', 'MODERNA', '030L20B', '1', 0, 0]],\n",
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" index = [\n",
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" \"1048786\",\n",
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" \"1048786\",\n",
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" \"4711\"],\n",
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" dtypes = {'VAX_DOSE_SERIES': \"string\"})\n",
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" dataFrame = SevereColumnAdder.addSevereColumn(dataFrame)\n",
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" \n",
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" # When\n",
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" doseByMonthTable = DoseTableFactory.createDoseByMonthTable(dataFrame)\n",
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"\n",
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" # Then\n",
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" assert_frame_equal(\n",
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" doseByMonthTable,\n",
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" pd.DataFrame(\n",
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" data = {\n",
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" 'Adverse Reaction Reports': [2, 1],\n",
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" 'Deaths': [2, 1],\n",
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" 'Disabilities': [1, 0],\n",
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" 'Life Threatening Illnesses': [1, 0],\n",
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" 'Severe reports': [2/2 * 100, 1/1 * 100],\n",
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" 'Lethality': [2/2 * 100, 1/1 * 100]\n",
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" },\n",
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" index = pd.MultiIndex.from_tuples(\n",
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" [\n",
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" (2021, 1, '1'),\n",
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" (2021, 1, '2'),\n",
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" ],\n",
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" names = ('Year', 'Month', 'Dose'))),\n",
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" check_index_type = False)\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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@@ -1344,119 +998,6 @@
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"internationalVaers"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "dddde600",
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"metadata": {},
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"outputs": [],
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"source": [
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"vaers2019 = getVaersForYear(\"2019\")\n",
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"vaers2019"
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]
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},
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{
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||||
"cell_type": "markdown",
|
||||
"id": "f677b620",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"### Short-list of 2000 batches having severe effects"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "bc56831d",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"def saveSevereEffectsBatchCodeTable(vaers, file):\n",
|
||||
" severeEffectsBatchCodeTable = BatchCodeTableFactory.createSevereEffectsBatchCodeTable(vaers, dose = '1')\n",
|
||||
" display(severeEffectsBatchCodeTable)\n",
|
||||
" IOUtils.saveDataFrame(severeEffectsBatchCodeTable, file)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "ace3fed9",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"saveSevereEffectsBatchCodeTable(vaers, 'results/severeEffects')"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "1b228a16",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"### Variation in Effect of First and Second Doses"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "202f7c3f",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# https://www.howbadismybatch.com/firstsecond.html\n",
|
||||
"DoseTableFactory.createDoseTable(vaers)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "b333e5fb",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"doseByMonthTable = DoseTableFactory.createDoseByMonthTable(vaers)\n",
|
||||
"IOUtils.saveDataFrame(doseByMonthTable, 'results/firstsecond/doseByMonthTable')\n",
|
||||
"doseByMonthTable"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "075aa6c9",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"### International Deadly Lots"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "8f8880f4",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# https://www.howbadismybatch.com/international.html"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "54e03231",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"internationalLotTable = InternationalLotTableFactory(nonDomesticVaers).createInternationalLotTable()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "7e80e958",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"internationalLotTable = internationalLotTable[internationalLotTable['Adverse Reaction Reports'] > 50]\n",
|
||||
"IOUtils.saveDataFrame(internationalLotTable, 'results/international/International_Deadly_Lots')\n",
|
||||
"internationalLotTable"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
@@ -1499,16 +1040,7 @@
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"countries = sorted(internationalVaers['COUNTRY'].unique())"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "e3d09ffa",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"countries = sorted(internationalVaers['COUNTRY'].unique())\n",
|
||||
"printCountryOptions(countries)"
|
||||
]
|
||||
},
|
||||
@@ -1533,275 +1065,13 @@
|
||||
" minADRsForLethality = minADRsForLethality)\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "ba02139d",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"### Batch Clusters"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "9649a32d",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### Pfizer Batches"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "f6e460ab",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"see https://www.howbadismybatch.com/clusters.html"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "b769466d",
|
||||
"id": "376b9193",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"def createADRsByVAX_LOTTable(vaers, manufacturer):\n",
|
||||
" dataFrame = DataFrameFilter().filterByCovid19(vaers)\n",
|
||||
" dataFrame = DataFrameFilter().filterBy(dataFrame, manufacturer = manufacturer)\n",
|
||||
" batchCodeTable = BatchCodeTableFactory._createSummationTableByVAX_LOT(dataFrame)[['Adverse Reaction Reports']].reset_index()\n",
|
||||
" return batchCodeTable\n",
|
||||
"\n",
|
||||
"def filterColumnOfDataFrameWithRegexp(dataFrame, column, regexp):\n",
|
||||
" return dataFrame[dataFrame[column].apply(lambda columnValue: bool(regexp.match(columnValue)))]\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "020b0d90",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import re\n",
|
||||
"\n",
|
||||
"batchCodeTable = createADRsByVAX_LOTTable(vaers, \"PFIZER\\BIONTECH\")\n",
|
||||
"batchCodeTable['VAX_LOT_PREFIX'] = batchCodeTable['VAX_LOT'].str[:2]\n",
|
||||
"batchCodeTable = batchCodeTable.sort_values(by = 'VAX_LOT_PREFIX', ascending = True)\n",
|
||||
"twoLetterPrefix = re.compile(r'^[a-zA-Z]{2}')\n",
|
||||
"batchCodeTable = filterColumnOfDataFrameWithRegexp(dataFrame = batchCodeTable, column = 'VAX_LOT_PREFIX', regexp = twoLetterPrefix)\n",
|
||||
"batchCodeTable = batchCodeTable[batchCodeTable['VAX_LOT_PREFIX'].isin(['EN', 'EP', 'ER', 'EW', 'FA', 'FC', 'FD', 'FE', 'FH'])]\n",
|
||||
"batchCodeTable = batchCodeTable[batchCodeTable['Adverse Reaction Reports'] > 400]\n",
|
||||
"batchCodeTable"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "02201726",
|
||||
"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_PREFIX\", y = \"Adverse Reaction Reports\", data = batchCodeTable)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "d6000b48",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"sns.pointplot(x = \"VAX_LOT_PREFIX\", y = \"Adverse Reaction Reports\", data = batchCodeTable, estimator = np.mean)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "cf53c8c8",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import seaborn as sns\n",
|
||||
"sns.set_theme(style = \"ticks\", palette = \"pastel\")\n",
|
||||
"\n",
|
||||
"sns.boxplot(x = \"VAX_LOT_PREFIX\", y = \"Adverse Reaction Reports\", data = batchCodeTable)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "731c27a5",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### Moderna Batches"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "b4a9c489",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import re\n",
|
||||
"\n",
|
||||
"batchCodeTable = createADRsByVAX_LOTTable(vaers, \"MODERNA\")\n",
|
||||
"modernaBatchCodePrefix = re.compile(r'^[0-9]{3}[a-zA-Z]')\n",
|
||||
"batchCodeTable = filterColumnOfDataFrameWithRegexp(dataFrame = batchCodeTable, column = 'VAX_LOT', regexp = modernaBatchCodePrefix)\n",
|
||||
"batchCodeTable['CONCENTRATION'] = batchCodeTable['VAX_LOT'].str[3]\n",
|
||||
"batchCodeTable = batchCodeTable.sort_values(by = 'CONCENTRATION', ascending = True)\n",
|
||||
"batchCodeTable = batchCodeTable[batchCodeTable['Adverse Reaction Reports'] > 400]\n",
|
||||
"batchCodeTable"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "e26c9d85",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import seaborn as sns\n",
|
||||
"\n",
|
||||
"order = ['J', 'K', 'L', 'M', 'A', 'B', 'C', 'D', 'E', 'F', 'G', 'H']\n",
|
||||
"\n",
|
||||
"sns.set(rc = {'figure.figsize': (11.7, 8.27)})\n",
|
||||
"sns.set_theme()\n",
|
||||
"chart = sns.stripplot(x = \"CONCENTRATION\", y = \"Adverse Reaction Reports\", data = batchCodeTable, order = order)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "d1de13c7",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"sns.pointplot(x = \"CONCENTRATION\", y = \"Adverse Reaction Reports\", data = batchCodeTable, estimator = np.mean, order = order)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "29ae8ca2",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import seaborn as sns\n",
|
||||
"sns.set_theme(style = \"ticks\", palette = \"pastel\")\n",
|
||||
"\n",
|
||||
"sns.boxplot(x = \"CONCENTRATION\", y = \"Adverse Reaction Reports\", data = batchCodeTable, order = order)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "259b6474",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"### COVID-19 Vaccines vs. Flu Vaccines"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "fa5c8480",
|
||||
"metadata": {},
|
||||
"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",
|
||||
" '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 = \"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"
|
||||
]
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
|
||||
Reference in New Issue
Block a user