Added script to process any subset of socioeconomic features from the Boston buildings inventory

Author: anushkaray

scripts/process_socioeconomic.py

@@ -0,0 +1,68 @@
+import geopandas as gpd
+from shapely.geometry import Polygon
+import csv
+from tqdm import tqdm
+import pandas as pd
+import math
+import copy
+import argparse
+
+
+def parse_args():
+    parser = argparse.ArgumentParser(description='Process Socioeconomic Data for Boston')
+    parser.add_argument('--boston-building-path', required=True, help='File path to the Boston Buildings Inventory dataset')
+    parser.add_argument('--vulnerabilities', required=True, type=str, nargs='+', help = "Socioeconomic columns to process from the Boston buildings inventory")
+    parser.add_argument('--output-path',required=True, help='Output CSV path')
+    args = parser.parse_args()
+    return args
+
+def unique_census_tracts(building_inventory_df, census_tract_column_name):
+    unique_census_tracts = set()
+    unique_building_use_classes = set()
+    for index, row in building_inventory_df.iterrows():
+        row_census_tract = row[census_tract_column_name]
+        if (not math.isnan(row_census_tract)) and (row_census_tract not in unique_census_tracts):
+            unique_census_tracts.add(row_census_tract)
+    return unique_census_tracts
+
+def process_socioecon(unique_ct, vulnerable_pops, boston_df):
+    output = {}
+    non_percent = set()
+
+    for vulnerable in vulnerable_pops:
+        if 'pop' in vulnerable:
+            non_percent.add(vulnerable)
+    for ct in unique_ct:
+        int_ct = int(ct)
+        inner_dict = {}
+        for vulnerable in vulnerable_pops:
+            inner_dict[vulnerable] = 0
+        for pop in vulnerable_pops:
+            row = boston_df.loc[boston_df["census_tract_number"] == int_ct]
+            if pop in non_percent:
+                socio = row.iloc[0].loc[pop]
+            else:
+                socio = (row.iloc[0].loc[pop]) / 100
+            
+            inner_dict[pop] = socio
+        row_census_tract_str = str(int(ct))
+        row_census_tract_fixed = str(int(row_census_tract_str[5:9])) + "." + row_census_tract_str[-2:]
+        output[row_census_tract_fixed] = inner_dict
+    return output
+
+
+
+if __name__ == '__main__':
+    args = parse_args()
+    boston_building_inventory_path = args.boston_building_path
+    vulnerable_pops = args.vulnerabilities
+    output_file =args.output_path
+    boston_building_inventory_df = pd.read_csv(boston_building_inventory_path)
+    
+    unique_census_tracts = unique_census_tracts(boston_building_inventory_df, "census_tract_number")
+    output_dict = process_socioecon(unique_census_tracts, vulnerable_pops, boston_building_inventory_df)
+    
+    df = pd.DataFrame.from_dict(output_dict)
+    df = df.transpose()
+    df.to_csv(output_file)
+