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adding DoseAnalysisTest

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frankknoll
2022-02-01 23:56:40 +01:00
parent 0380ec9092
commit 0317d25a90
2 changed files with 117 additions and 12 deletions
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124
HowBadIsMyBatch.ipynb
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@@ -210,6 +210,27 @@
" return BatchCodeTableHelper(severeEffectsDataFrame).createSevereEffectsBatchCodeTable()\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "41d4fa30",
"metadata": {},
"outputs": [],
"source": [
"class DoseAnalysis:\n",
" \n",
" def getNthDoseTable(dataFrame, dose):\n",
" nthDoseDataFrame = DataFrameFilter(dataFrame).filterBy(dose = dose)\n",
" dict = {\n",
" 'Total reports': len(nthDoseDataFrame.index),\n",
" 'Deaths': len(nthDoseDataFrame[nthDoseDataFrame['DIED'] == 'Y']),\n",
" 'Disabilities': len(nthDoseDataFrame[nthDoseDataFrame['DISABLE'] == 'Y']),\n",
" 'Life Threatening Illnesses': len(nthDoseDataFrame[nthDoseDataFrame['L_THREAT'] == 'Y'])\n",
" }\n",
" dict['Severe reports'] = (dict['Deaths'] + dict['Disabilities'] + dict['Life Threatening Illnesses'])/dict['Total reports'] * 100\n",
" return pd.Series(dict)"
]
},
{
"cell_type": "code",
"execution_count": null,
@@ -247,7 +268,7 @@
" 'VAERSVAX': self.createDataFrame(\n",
" columns = ['VAX_TYPE', 'VAX_MANU', 'VAX_LOT', 'VAX_DOSE_SERIES'],\n",
" data = [ ['COVID19', 'MODERNA', '037K20A', '1'],\n",
" ['COVID19', 'MODERNA', '025L20A', '1']],\n",
" ['COVID19', 'MODERNA', '025L20A', '1']],\n",
" index = [\n",
" \"0916600\",\n",
" \"0916601\"],\n",
@@ -257,14 +278,14 @@
" 'VAERSDATA': self.createDataFrame(\n",
" columns = ['DIED', 'L_THREAT', 'DISABLE'],\n",
" data = [ [np.NaN, np.NaN, np.NaN],\n",
" [np.NaN, np.NaN, 'Y']],\n",
" [np.NaN, np.NaN, 'Y']],\n",
" index = [\n",
" \"1996873\",\n",
" \"1996874\"]),\n",
" 'VAERSVAX': self.createDataFrame(\n",
" columns = ['VAX_TYPE', 'VAX_MANU', 'VAX_LOT', 'VAX_DOSE_SERIES'],\n",
" data = [ ['HPV9', 'MERCK & CO. INC.', 'R017624', 'UNK'],\n",
" ['COVID19', 'MODERNA', '025L20A', '1']],\n",
" ['COVID19', 'MODERNA', '025L20A', '1']],\n",
" index = [\n",
" \"1996873\",\n",
" \"1996874\"],\n",
@@ -340,7 +361,7 @@
" 'VAERSVAX': self.createDataFrame(\n",
" columns = ['VAX_TYPE', 'VAX_MANU', 'VAX_LOT', 'VAX_DOSE_SERIES'],\n",
" data = [ ['COVID19', 'MODERNA', '016M20A', '2'],\n",
" ['COVID19', 'MODERNA', '030L20A', '1']],\n",
" ['COVID19', 'MODERNA', '030L20A', '1']],\n",
" index = [\n",
" \"1048786\",\n",
" \"1048786\"],\n",
@@ -354,7 +375,7 @@
" # Then\n",
" dataFrameExpected = self.createDataFrame(\n",
" columns = ['DIED', 'L_THREAT', 'DISABLE', 'VAX_TYPE', 'VAX_MANU', 'VAX_LOT', 'VAX_DOSE_SERIES'],\n",
" data = [ ['Y', np.NaN, np.NaN, 'COVID19', 'MODERNA', '030L20A', '1']],\n",
" data = [ ['Y', np.NaN, np.NaN, 'COVID19', 'MODERNA', '030L20A', '1']],\n",
" index = [\n",
" \"1048786\"],\n",
" dtypes = {'VAX_DOSE_SERIES': \"string\"})\n",
@@ -374,7 +395,7 @@
" 'VAERSVAX': self.createDataFrame(\n",
" columns = ['VAX_TYPE', 'VAX_MANU', 'VAX_LOT', 'VAX_DOSE_SERIES'],\n",
" data = [ ['COVID19', 'MODERNA', '016M20A', '2'],\n",
" ['COVID19', 'MODERNA', '030L20A', '1']],\n",
" ['COVID19', 'MODERNA', '030L20A', '1']],\n",
" index = [\n",
" \"1048786\",\n",
" \"1048786\"],\n",
@@ -388,7 +409,7 @@
" # Then\n",
" dataFrameExpected = self.createDataFrame(\n",
" columns = ['DIED', 'L_THREAT', 'DISABLE', 'VAX_TYPE', 'VAX_MANU', 'VAX_LOT', 'VAX_DOSE_SERIES'],\n",
" data = [ ['Y', np.NaN, np.NaN, 'COVID19', 'MODERNA', '016M20A', '2']],\n",
" data = [ ['Y', np.NaN, np.NaN, 'COVID19', 'MODERNA', '016M20A', '2']],\n",
" index = [\n",
" \"1048786\"],\n",
" dtypes = {'VAX_DOSE_SERIES': \"string\"})\n",
@@ -417,14 +438,14 @@
" 'VAERSDATA': self.createDataFrame(\n",
" columns = ['DIED', 'L_THREAT', 'DISABLE', 'HOSPITAL', 'ER_VISIT'],\n",
" data = [ ['Y', 'Y', np.NaN, 'Y', 'Y'],\n",
" [np.NaN, np.NaN, 'Y', np.NaN, 'Y']],\n",
" [np.NaN, np.NaN, 'Y', np.NaN, 'Y']],\n",
" index = [\n",
" \"0916600\",\n",
" \"0916601\"]),\n",
" 'VAERSVAX': self.createDataFrame(\n",
" columns = ['VAX_TYPE', 'VAX_MANU', 'VAX_LOT', 'VAX_DOSE_SERIES'],\n",
" data = [ ['COVID19', 'MODERNA', '037K20A', '1'],\n",
" ['COVID19', 'PFIZER\\BIONTECH', '025L20A', '1']],\n",
" ['COVID19', 'PFIZER\\BIONTECH', '025L20A', '1']],\n",
" index = [\n",
" \"0916600\",\n",
" \"0916601\"],\n",
@@ -513,6 +534,75 @@
" return pd.DataFrame(index = index, columns = columns, data = data).astype(dtypes)\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "44c121ec",
"metadata": {},
"outputs": [],
"source": [
"from pandas.testing import assert_series_equal\n",
"\n",
"class DoseAnalysisTest(unittest.TestCase):\n",
"\n",
" def test_getFirstDoseTable(self):\n",
" # Given\n",
" dataFrame = self.createDataFrame(\n",
" columns = ['DIED', 'L_THREAT', 'DISABLE', 'VAX_TYPE', 'VAX_MANU', 'VAX_LOT', 'VAX_DOSE_SERIES'],\n",
" data = [ ['Y', np.NaN, np.NaN,\t 'COVID19', 'MODERNA', '016M20A', '2'],\n",
" ['Y', np.NaN, np.NaN, 'COVID19', 'MODERNA', '030L20A', '1'],\n",
" ['Y', 'Y', 'Y', 'COVID19', 'MODERNA', '030L20B', '1']],\n",
" index = [\n",
" \"1048786\",\n",
" \"1048786\",\n",
" \"4711\"],\n",
" dtypes = {'VAX_DOSE_SERIES': \"string\"})\n",
" \n",
" # When\n",
" doseTable = DoseAnalysis.getNthDoseTable(dataFrame, dose = '1')\n",
" \n",
" # Then\n",
" doseTableExpected = pd.Series(\n",
" {\n",
" 'Total reports': 2,\n",
" 'Deaths': 2,\n",
" 'Disabilities': 1,\n",
" 'Life Threatening Illnesses': 1,\n",
" 'Severe reports': (2 + 1 + 1)/2 * 100\n",
" })\n",
" assert_series_equal(doseTable, doseTableExpected)\n",
"\n",
" def test_getSecondDoseTable(self):\n",
" # Given\n",
" dataFrame = self.createDataFrame(\n",
" columns = ['DIED', 'L_THREAT', 'DISABLE', 'VAX_TYPE', 'VAX_MANU', 'VAX_LOT', 'VAX_DOSE_SERIES'],\n",
" data = [ ['Y', np.NaN, np.NaN,\t 'COVID19', 'MODERNA', '016M20A', '2'],\n",
" ['Y', np.NaN, np.NaN, 'COVID19', 'MODERNA', '030L20A', '1'],\n",
" ['Y', 'Y', 'Y', 'COVID19', 'MODERNA', '030L20B', '1']],\n",
" index = [\n",
" \"1048786\",\n",
" \"1048786\",\n",
" \"4711\"],\n",
" dtypes = {'VAX_DOSE_SERIES': \"string\"})\n",
" \n",
" # When\n",
" doseTable = DoseAnalysis.getNthDoseTable(dataFrame, dose = '2')\n",
" \n",
" # Then\n",
" doseTableExpected = pd.Series(\n",
" {\n",
" 'Total reports': 1,\n",
" 'Deaths': 1,\n",
" 'Disabilities': 0,\n",
" 'Life Threatening Illnesses': 0,\n",
" 'Severe reports': (1 + 0 + 0)/1 * 100\n",
" })\n",
" assert_series_equal(doseTable, doseTableExpected)\n",
"\n",
" def createDataFrame(self, index, columns, data, dtypes = {}):\n",
" return pd.DataFrame(index = index, columns = columns, data = data).astype(dtypes)\n"
]
},
{
"cell_type": "code",
"execution_count": null,
@@ -574,6 +664,22 @@
"source": [
"saveSevereEffectsBatchCodeTable('results/severeEffects.xlsx')"
]
},
{
"cell_type": "markdown",
"id": "1b228a16",
"metadata": {},
"source": [
"### Variation in Effect of First and Second Doses"
]
},
{
"cell_type": "markdown",
"id": "202f7c3f",
"metadata": {},
"source": [
"see https://www.howbadismybatch.com/firstsecond.html"
]
}
],
"metadata": {