refactoring

2023-01-23 08:07:23 +01:00
parent 28e71af7af
commit b6eb929a7b
2 changed files with 18 additions and 18 deletions
--- a/src/SymptomByBatchcodeTableFactory.py
+++ b/src/SymptomByBatchcodeTableFactory.py
@@ -0,0 +1,58 @@
+import pandas as pd
+import numpy as np
+
+class SymptomByBatchcodeTableFactory:
+
+    @staticmethod
+    def createSymptomByBatchcodeTable(VAERSVAX, VAERSSYMPTOMS):
+        index_columns = SymptomByBatchcodeTableFactory._getIndexColumns(VAERSVAX)
+        symptomColumn = 'SYMPTOM'
+        return pd.merge(
+            SymptomByBatchcodeTableFactory._get_VAERSVAX_WITH_VAX_LOTS(VAERSVAX, index_columns),
+            SymptomByBatchcodeTableFactory._getSymptomsTable(VAERSSYMPTOMS, symptomColumn),
+            on = 'VAERS_ID').set_index(index_columns)[[symptomColumn]]
+    
+    @staticmethod
+    def _getIndexColumns(VAERSVAX):
+        return [f"VAX_LOT{num}" for num in range(1, SymptomByBatchcodeTableFactory._getMaxNumShots(VAERSVAX) + 1)]
+
+    @staticmethod
+    def _getMaxNumShots(VAERSVAX):
+        return VAERSVAX.index.value_counts().iloc[0]
+
+    @staticmethod
+    def _get_VAERSVAX_WITH_VAX_LOTS(VAERSVAX, index_columns):
+        return pd.concat(
+            [VAERSVAX, SymptomByBatchcodeTableFactory._getVaxLotsTable(VAERSVAX, index_columns)],
+            axis='columns').reset_index().drop_duplicates(subset = ['VAERS_ID'] + index_columns)
+
+    @staticmethod
+    def _getVaxLotsTable(VAERSVAX, index_columns):       
+        VAX_LOT_LIST_Table = VAERSVAX.groupby("VAERS_ID").agg(
+            VAX_LOT_LIST = pd.NamedAgg(
+                column = 'VAX_LOT',
+                aggfunc = lambda VAX_LOT_series: list(VAX_LOT_series.sort_values())))
+        return pd.DataFrame(
+            fillLsts(
+                lsts = VAX_LOT_LIST_Table['VAX_LOT_LIST'].tolist(),
+                desiredLen = len(index_columns),
+                fillValue = str(np.nan)),
+            columns = index_columns,
+            index = VAX_LOT_LIST_Table.index)
+
+    @staticmethod
+    def _getSymptomsTable(VAERSSYMPTOMS, symptomColumn):
+        return pd.concat(
+            [
+                VAERSSYMPTOMS['SYMPTOM1'],
+                VAERSSYMPTOMS['SYMPTOM2'],
+                VAERSSYMPTOMS['SYMPTOM3'],
+                VAERSSYMPTOMS['SYMPTOM4'],
+                VAERSSYMPTOMS['SYMPTOM5']
+            ]).dropna().to_frame(name = symptomColumn).reset_index()
+
+def fillLsts(lsts, desiredLen, fillValue):
+    return [fillLst(lst, desiredLen, fillValue) for lst in lsts]
+
+def fillLst(lst, desiredLen, fillValue):
+    return lst + [fillValue] * (max(desiredLen - len(lst), 0))