update,

vihuwach/task1/archive/task3.py

@@ -0,0 +1,48 @@
+# https://api.data.gov.hk/v1/carpark-info-vacancy?data=vacancy&vehicleTypes=privateCar
+import requests
+from pprint import pprint
+
+url = "https://api.data.gov.hk/v1/carpark-info-vacancy"
+params = {
+    "data": "vacancy",
+    "vehicleTypes": "privateCar"
+}
+
+response = requests.get(url, params=params)
+js_result = response.json()['results']
+
+output = []
+for js_row in js_result:
+  if ((type(js_row.get('privateCar')) == type([]) ) and len(js_row.get('privateCar'))> 0):
+      if (js_row.get('privateCar')[0].get("vacancy_type",'-')== "A"):
+        output.append(js_row)
+
+test_json = [{
+    'park_Id': '10',
+    'privateCar': [{
+        'vacancy_type': 'A',
+        'vacancy': 29,
+        'lastupdate': '2024-10-18 16:04:59'
+    }]
+}]
+
+import pandas as pd
+
+# Create a DataFrame from the test_json
+df = pd.json_normalize(test_json, record_path=['privateCar'], meta='park_Id')
+
+
+# Extract the 'vacancy' column and flatten it
+vacancy_df = df[['park_Id', 'vacancy']]
+
+print(vacancy_df)
+
+
+pprint(output[0])
+pprint("length of json: "+str(len(output)))
+
+import json
+
+# Store output into task3_output.json
+with open('task3_output.json', 'w') as outfile:
+    json.dump(output, outfile, indent=2)