Commit some historic pathology transformation.

scripts/transform_pathology_historic.py

+#!/usr/bin/env python3
+
+'''Generate Pathology Table historic'''
+
+import argparse
+import datetime
+import os
+import pandas as pd
+
+
+def main():
+    args = get_args()
+    surgery = args.file
+    date = args.date
+    surgery_map = args.surgery
+    out_path = args.out
+
+    # Make output files
+    surgery_table = os.path.join(out_path + 'surgery_table.csv')
+    surgery_procedure_table = os.path.join(out_path + 'surgery_procedure_table.csv')
+    unmapped_table = os.path.join(out_path + 'unmapped_surgery_table.csv')
+
+    # Read in files
+    surgery_df = pd.read_csv(surgery)
+    date_shift = pd.read_csv(date)
+    surgery_map = pd.read_csv(surgery_map, sep='\t')
+
+    # Reformat data
+    surgery_reformat = reformat_record(surgery_df)
+
+    # Convert Surgery
+    surgery_convert, conflicting_surgery = convert_surgery(surgery_reformat, surgery_map)
+
+    # Calculate Date Shift
+    shifted_df = calculate_shift(surgery_convert, date_shift)
+
+    # Write out surgery table
+    shifted_df.to_csv(surgery_table, index=False)
+    conflicting_surgery.to_csv(unmapped_table, index=False)
+
+if __name__ == '__main__':
+    main()