requests_1.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import requests\n",
    "import json\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import dotenv\n",
    "import os\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "\n",
    "from datetime import datetime,timedelta"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'tsn': '2155384',\n",
       "  'time': '742877319',\n",
       "  'spots': '1004',\n",
       "  'zones': [{'spots': '152',\n",
       "    'zone_id': 'CPS-CUD1',\n",
       "    'occupancy': {'loop': None,\n",
       "     'total': '150',\n",
       "     'monthlies': None,\n",
       "     'open_gate': None,\n",
       "     'transients': None},\n",
       "    'zone_name': 'Tallawong Station At-Grade A Car Park',\n",
       "    'parent_zone_id': '0'},\n",
       "   {'spots': '455',\n",
       "    'zone_id': 'CPS-CUD2',\n",
       "    'occupancy': {'loop': None,\n",
       "     'total': '455',\n",
       "     'monthlies': None,\n",
       "     'open_gate': None,\n",
       "     'transients': None},\n",
       "    'zone_name': 'Tallawong Station At-Grade B Car Park',\n",
       "    'parent_zone_id': '0'},\n",
       "   {'spots': '397',\n",
       "    'zone_id': 'CPS-CUD3',\n",
       "    'occupancy': {'loop': None,\n",
       "     'total': '376',\n",
       "     'monthlies': None,\n",
       "     'open_gate': None,\n",
       "     'transients': None},\n",
       "    'zone_name': 'Tallawong Station At-Grade D Car Park',\n",
       "    'parent_zone_id': '0'}],\n",
       "  'ParkID': '1',\n",
       "  'occupancy': {'loop': None,\n",
       "   'total': '981',\n",
       "   'monthlies': None,\n",
       "   'open_gate': None,\n",
       "   'transients': None},\n",
       "  'MessageDate': '2023-07-17T12:48:39',\n",
       "  'facility_id': '1',\n",
       "  'facility_name': 'Tallawong Station Car Park',\n",
       "  'tfnsw_facility_id': '2155384CCP001'},\n",
       " {'tsn': '2101131',\n",
       "  'time': '760602185',\n",
       "  'spots': '244',\n",
       "  'zones': [{'spots': '244',\n",
       "    'zone_id': '1',\n",
       "    'occupancy': {'loop': None,\n",
       "     'total': '198',\n",
       "     'monthlies': None,\n",
       "     'open_gate': None,\n",
       "     'transients': None},\n",
       "    'zone_name': 'Warriewood Car Park',\n",
       "    'parent_zone_id': '0'}],\n",
       "  'ParkID': '1',\n",
       "  'occupancy': {'loop': None,\n",
       "   'total': '198',\n",
       "   'monthlies': None,\n",
       "   'open_gate': None,\n",
       "   'transients': None},\n",
       "  'MessageDate': '2024-02-07T17:23:05',\n",
       "  'facility_id': '10',\n",
       "  'facility_name': 'Warriewood Car Park',\n",
       "  'tfnsw_facility_id': '2101131TPR001'},\n",
       " {'tsn': '2101130',\n",
       "  'time': '760602224',\n",
       "  'spots': '46',\n",
       "  'zones': [{'spots': '46',\n",
       "    'zone_id': '1',\n",
       "    'occupancy': {'loop': '64068',\n",
       "     'total': '37',\n",
       "     'monthlies': None,\n",
       "     'open_gate': None,\n",
       "     'transients': None},\n",
       "    'zone_name': 'SYD312 Narrabeen Park&Ride',\n",
       "    'parent_zone_id': '0'}],\n",
       "  'ParkID': '1',\n",
       "  'occupancy': {'loop': '64068',\n",
       "   'total': '37',\n",
       "   'monthlies': None,\n",
       "   'open_gate': None,\n",
       "   'transients': None},\n",
       "  'MessageDate': '2024-02-07T17:23:44',\n",
       "  'facility_id': '11',\n",
       "  'facility_name': 'Narrabeen Car Park',\n",
       "  'tfnsw_facility_id': '2101130TPR001'},\n",
       " {'tsn': '2103108',\n",
       "  'time': '760600881',\n",
       "  'spots': '68',\n",
       "  'zones': [{'spots': '68',\n",
       "    'zone_id': '1',\n",
       "    'occupancy': {'loop': None,\n",
       "     'total': '64',\n",
       "     'monthlies': None,\n",
       "     'open_gate': None,\n",
       "     'transients': None},\n",
       "    'zone_name': 'Mona Vale Car Park',\n",
       "    'parent_zone_id': '0'}],\n",
       "  'ParkID': '1',\n",
       "  'occupancy': {'loop': None,\n",
       "   'total': '64',\n",
       "   'monthlies': None,\n",
       "   'open_gate': None,\n",
       "   'transients': None},\n",
       "  'MessageDate': '2024-02-07T17:01:21',\n",
       "  'facility_id': '12',\n",
       "  'facility_name': 'Mona Vale Car Park',\n",
       "  'tfnsw_facility_id': '2103108TPR001'},\n",
       " {'tsn': '2099207',\n",
       "  'time': '760602196',\n",
       "  'spots': '117',\n",
       "  'zones': [{'spots': '117',\n",
       "    'zone_id': '1',\n",
       "    'occupancy': {'loop': '53620',\n",
       "     'total': '87',\n",
       "     'monthlies': None,\n",
       "     'open_gate': None,\n",
       "     'transients': None},\n",
       "    'zone_name': 'SYD309 Dee Why Park&Ride',\n",
       "    'parent_zone_id': '0'}],\n",
       "  'ParkID': '1',\n",
       "  'occupancy': {'loop': '53620',\n",
       "   'total': '87',\n",
       "   'monthlies': None,\n",
       "   'open_gate': None,\n",
       "   'transients': None},\n",
       "  'MessageDate': '2024-02-07T17:23:16',\n",
       "  'facility_id': '13',\n",
       "  'facility_name': 'Dee Why Car Park',\n",
       "  'tfnsw_facility_id': '2099207TPR001'},\n",
       " {'tsn': '211420',\n",
       "  'time': '760602280',\n",
       "  'spots': '151',\n",
       "  'zones': [{'spots': '151',\n",
       "    'zone_id': '1',\n",
       "    'occupancy': {'loop': '228800',\n",
       "     'total': '95',\n",
       "     'monthlies': None,\n",
       "     'open_gate': None,\n",
       "     'transients': None},\n",
       "    'zone_name': 'SYD372 West Ryde Park&Ride',\n",
       "    'parent_zone_id': '0'}],\n",
       "  'ParkID': '1',\n",
       "  'occupancy': {'loop': '228800',\n",
       "   'total': '95',\n",
       "   'monthlies': None,\n",
       "   'open_gate': None,\n",
       "   'transients': None},\n",
       "  'MessageDate': '2024-02-07T17:24:40',\n",
       "  'facility_id': '14',\n",
       "  'facility_name': 'West Ryde Car Park',\n",
       "  'tfnsw_facility_id': '211420TPR001'},\n",
       " {'tsn': '223210',\n",
       "  'time': '760602198',\n",
       "  'spots': '373',\n",
       "  'zones': [{'spots': '373',\n",
       "    'zone_id': '1',\n",
       "    'occupancy': {'loop': None,\n",
       "     'total': '249',\n",
       "     'monthlies': None,\n",
       "     'open_gate': None,\n",
       "     'transients': None},\n",
       "    'zone_name': 'Sutherland East Parade Car Park',\n",
       "    'parent_zone_id': '0'}],\n",
       "  'ParkID': '1',\n",
       "  'occupancy': {'loop': None,\n",
       "   'total': '249',\n",
       "   'monthlies': None,\n",
       "   'open_gate': None,\n",
       "   'transients': None},\n",
       "  'MessageDate': '2024-02-07T17:23:18',\n",
       "  'facility_id': '15',\n",
       "  'facility_name': 'Sutherland East Parade Car Park',\n",
       "  'tfnsw_facility_id': '223210TPR001'},\n",
       " {'tsn': '217933',\n",
       "  'time': '760602304',\n",
       "  'spots': '1884',\n",
       "  'zones': [{'spots': '1884',\n",
       "    'zone_id': '1',\n",
       "    'occupancy': {'loop': '813955',\n",
       "     'total': '1036',\n",
       "     'monthlies': None,\n",
       "     'open_gate': None,\n",
       "     'transients': None},\n",
       "    'zone_name': 'SYD373 Leppington Park&Ride',\n",
       "    'parent_zone_id': '0'}],\n",
       "  'ParkID': '1',\n",
       "  'occupancy': {'loop': '813955',\n",
       "   'total': '1036',\n",
       "   'monthlies': None,\n",
       "   'open_gate': None,\n",
       "   'transients': None},\n",
       "  'MessageDate': '2024-02-07T17:25:04',\n",
       "  'facility_id': '16',\n",
       "  'facility_name': 'Leppington Car Park',\n",
       "  'tfnsw_facility_id': '217933TPR001'},\n",
       " {'tsn': '217426',\n",
       "  'time': '760602306',\n",
       "  'spots': '1429',\n",
       "  'zones': [{'spots': '1429',\n",
       "    'zone_id': '1',\n",
       "    'occupancy': {'loop': '744548',\n",
       "     'total': '669',\n",
       "     'monthlies': None,\n",
       "     'open_gate': None,\n",
       "     'transients': None},\n",
       "    'zone_name': 'SYD375 Edmondson Park Park&Ride',\n",
       "    'parent_zone_id': '0'}],\n",
       "  'ParkID': '1',\n",
       "  'occupancy': {'loop': '744548',\n",
       "   'total': '669',\n",
       "   'monthlies': None,\n",
       "   'open_gate': None,\n",
       "   'transients': None},\n",
       "  'MessageDate': '2024-02-07T17:25:06',\n",
       "  'facility_id': '17',\n",
       "  'facility_name': 'Edmondson Park South Car Park',\n",
       "  'tfnsw_facility_id': '217426TPR001'},\n",
       " {'tsn': '276010',\n",
       "  'time': '760602293',\n",
       "  'spots': '682',\n",
       "  'zones': [{'spots': '682',\n",
       "    'zone_id': '1',\n",
       "    'occupancy': {'loop': None,\n",
       "     'total': '384',\n",
       "     'monthlies': None,\n",
       "     'open_gate': None,\n",
       "     'transients': None},\n",
       "    'zone_name': 'St Marys Car Park',\n",
       "    'parent_zone_id': '0'}],\n",
       "  'ParkID': '1',\n",
       "  'occupancy': {'loop': None,\n",
       "   'total': '384',\n",
       "   'monthlies': None,\n",
       "   'open_gate': None,\n",
       "   'transients': None},\n",
       "  'MessageDate': '2024-02-07T17:24:53',\n",
       "  'facility_id': '18',\n",
       "  'facility_name': 'St Marys Car Park',\n",
       "  'tfnsw_facility_id': '276010TPR001'},\n",
       " {'tsn': '256020',\n",
       "  'time': '760602081',\n",
       "  'spots': '68',\n",
       "  'zones': [{'spots': '68',\n",
       "    'zone_id': '1',\n",
       "    'occupancy': {'loop': '147997',\n",
       "     'total': '50',\n",
       "     'monthlies': None,\n",
       "     'open_gate': None,\n",
       "     'transients': None},\n",
       "    'zone_name': 'SYD368D FRN Park&Ride',\n",
       "    'parent_zone_id': '0'}],\n",
       "  'ParkID': '1',\n",
       "  'occupancy': {'loop': '147997',\n",
       "   'total': '50',\n",
       "   'monthlies': None,\n",
       "   'open_gate': None,\n",
       "   'transients': None},\n",
       "  'MessageDate': '2024-02-07T17:21:21',\n",
       "  'facility_id': '19',\n",
       "  'facility_name': 'Campbelltown Farrow Rd North Car Park',\n",
       "  'tfnsw_facility_id': '256020TPR001'},\n",
       " {'tsn': '2155382',\n",
       "  'time': '742877319',\n",
       "  'spots': '1374',\n",
       "  'zones': [{'spots': '368',\n",
       "    'zone_id': 'CPS-KVE1',\n",
       "    'occupancy': {'loop': None,\n",
       "     'total': '357',\n",
       "     'monthlies': None,\n",
       "     'open_gate': None,\n",
       "     'transients': None},\n",
       "    'zone_name': 'Kellyville Station Northern At-Grade Car Park',\n",
       "    'parent_zone_id': '0'},\n",
       "   {'spots': '1006',\n",
       "    'zone_id': 'CPS-KVE2',\n",
       "    'occupancy': {'loop': None,\n",
       "     'total': '1006',\n",
       "     'monthlies': None,\n",
       "     'open_gate': None,\n",
       "     'transients': None},\n",
       "    'zone_name': 'Kellyville Station Southern Multi-Level Car Park',\n",
       "    'parent_zone_id': '0'}],\n",
       "  'ParkID': '1',\n",
       "  'occupancy': {'loop': None,\n",
       "   'total': '1363',\n",
       "   'monthlies': None,\n",
       "   'open_gate': None,\n",
       "   'transients': None},\n",
       "  'MessageDate': '2023-07-17T12:48:39',\n",
       "  'facility_id': '2',\n",
       "  'facility_name': 'Kellyville Station Car Park',\n",
       "  'tfnsw_facility_id': '2155382CCP001'},\n",
       " {'tsn': '256020',\n",
       "  'time': '760602253',\n",
       "  'spots': '118',\n",
       "  'zones': [{'spots': '118',\n",
       "    'zone_id': '1',\n",
       "    'occupancy': {'loop': '178354',\n",
       "     'total': '79',\n",
       "     'monthlies': None,\n",
       "     'open_gate': None,\n",
       "     'transients': None},\n",
       "    'zone_name': 'SYD368C HSS Park&Ride',\n",
       "    'parent_zone_id': '0'}],\n",
       "  'ParkID': '1',\n",
       "  'occupancy': {'loop': '178354',\n",
       "   'total': '79',\n",
       "   'monthlies': None,\n",
       "   'open_gate': None,\n",
       "   'transients': None},\n",
       "  'MessageDate': '2024-02-07T17:24:13',\n",
       "  'facility_id': '20',\n",
       "  'facility_name': 'Campbelltown Hurley Street South Car Park',\n",
       "  'tfnsw_facility_id': '25602TPR002'},\n",
       " {'tsn': '275010',\n",
       "  'time': '760602318',\n",
       "  'spots': '230',\n",
       "  'zones': [{'spots': '230',\n",
       "    'zone_id': '1',\n",
       "    'occupancy': {'loop': '74681',\n",
       "     'total': '86',\n",
       "     'monthlies': None,\n",
       "     'open_gate': None,\n",
       "     'transients': None},\n",
       "    'zone_name': 'SYD369A Penrith AG Park&Ride',\n",
       "    'parent_zone_id': '0'}],\n",
       "  'ParkID': '1',\n",
       "  'occupancy': {'loop': '74681',\n",
       "   'total': '86',\n",
       "   'monthlies': None,\n",
       "   'open_gate': None,\n",
       "   'transients': None},\n",
       "  'MessageDate': '2024-02-07T16:25:18',\n",
       "  'facility_id': '21',\n",
       "  'facility_name': 'Penrith Combewood At-Grade Car Park',\n",
       "  'tfnsw_facility_id': '275010TPR001'},\n",
       " {'tsn': '275010',\n",
       "  'time': '760602326',\n",
       "  'spots': '1144',\n",
       "  'zones': [{'spots': '1144',\n",
       "    'zone_id': '1',\n",
       "    'occupancy': {'loop': '523857',\n",
       "     'total': '466',\n",
       "     'monthlies': None,\n",
       "     'open_gate': None,\n",
       "     'transients': None},\n",
       "    'zone_name': 'SYD369B Penrith MSC Park&Ride',\n",
       "    'parent_zone_id': '0'}],\n",
       "  'ParkID': '1',\n",
       "  'occupancy': {'loop': '523857',\n",
       "   'total': '466',\n",
       "   'monthlies': None,\n",
       "   'open_gate': None,\n",
       "   'transients': None},\n",
       "  'MessageDate': '2024-02-07T16:25:26',\n",
       "  'facility_id': '22',\n",
       "  'facility_name': 'Penrith Combewood Multi-Level Car Park',\n",
       "  'tfnsw_facility_id': '275010TPR002'},\n",
       " {'tsn': '217010',\n",
       "  'time': '760602327',\n",
       "  'spots': '910',\n",
       "  'zones': [{'spots': '910',\n",
       "    'zone_id': '1',\n",
       "    'occupancy': {'loop': None,\n",
       "     'total': '427',\n",
       "     'monthlies': None,\n",
       "     'open_gate': None,\n",
       "     'transients': None},\n",
       "    'zone_name': 'Warwick Farm Car Park',\n",
       "    'parent_zone_id': '0'}],\n",
       "  'ParkID': '1',\n",
       "  'occupancy': {'loop': None,\n",
       "   'total': '427',\n",
       "   'monthlies': None,\n",
       "   'open_gate': None,\n",
       "   'transients': None},\n",
       "  'MessageDate': '2024-02-07T17:25:27',\n",
       "  'facility_id': '23',\n",
       "  'facility_name': 'Warwick Farm Car Park',\n",
       "  'tfnsw_facility_id': '217010TPR001'},\n",
       " {'tsn': '276220',\n",
       "  'time': '760602212',\n",
       "  'spots': '700',\n",
       "  'zones': [{'spots': '700',\n",
       "    'zone_id': '1',\n",
       "    'occupancy': {'loop': '480393',\n",
       "     'total': '522',\n",
       "     'monthlies': None,\n",
       "     'open_gate': None,\n",
       "     'transients': None},\n",
       "    'zone_name': 'SYD383 Schofields Commuter Car Park',\n",
       "    'parent_zone_id': '0'}],\n",
       "  'ParkID': '1',\n",
       "  'occupancy': {'loop': '480393',\n",
       "   'total': '522',\n",
       "   'monthlies': None,\n",
       "   'open_gate': None,\n",
       "   'transients': None},\n",
       "  'MessageDate': '2024-02-07T17:23:32',\n",
       "  'facility_id': '24',\n",
       "  'facility_name': 'Schofields Car Park',\n",
       "  'tfnsw_facility_id': '276220TPR001'},\n",
       " {'tsn': '207720',\n",
       "  'time': '760602144',\n",
       "  'spots': '145',\n",
       "  'zones': [{'spots': '145',\n",
       "    'zone_id': '1',\n",
       "    'occupancy': {'loop': '105217',\n",
       "     'total': '97',\n",
       "     'monthlies': None,\n",
       "     'open_gate': None,\n",
       "     'transients': None},\n",
       "    'zone_name': 'SYD386 Hornsby Commuter Car Park',\n",
       "    'parent_zone_id': '0'}],\n",
       "  'ParkID': '1',\n",
       "  'occupancy': {'loop': '105217',\n",
       "   'total': '97',\n",
       "   'monthlies': None,\n",
       "   'open_gate': None,\n",
       "   'transients': None},\n",
       "  'MessageDate': '2024-02-07T17:22:24',\n",
       "  'facility_id': '25',\n",
       "  'facility_name': 'Hornsby Jersey St Car Park',\n",
       "  'tfnsw_facility_id': '207720TPR001'},\n",
       " {'tsn': '2155384',\n",
       "  'time': '760602237',\n",
       "  'spots': '121',\n",
       "  'zones': [{'spots': '121',\n",
       "    'zone_id': '1',\n",
       "    'occupancy': {'loop': '91340',\n",
       "     'total': '73',\n",
       "     'monthlies': None,\n",
       "     'open_gate': None,\n",
       "     'transients': None},\n",
       "    'zone_name': 'SYD396A Tallawong P1 Car Park',\n",
       "    'parent_zone_id': '0'}],\n",
       "  'ParkID': '1',\n",
       "  'occupancy': {'loop': '91340',\n",
       "   'total': '73',\n",
       "   'monthlies': None,\n",
       "   'open_gate': None,\n",
       "   'transients': None},\n",
       "  'MessageDate': '2024-02-07T17:23:57',\n",
       "  'facility_id': '26',\n",
       "  'facility_name': 'Tallawong P1 Car Park',\n",
       "  'tfnsw_facility_id': '2155384TPR001'},\n",
       " {'tsn': '2155384',\n",
       "  'time': '760602232',\n",
       "  'spots': '455',\n",
       "  'zones': [{'spots': '455',\n",
       "    'zone_id': '1',\n",
       "    'occupancy': {'loop': '174538',\n",
       "     'total': '247',\n",
       "     'monthlies': None,\n",
       "     'open_gate': None,\n",
       "     'transients': None},\n",
       "    'zone_name': 'SYD396B Tallawong P2 Car Park',\n",
       "    'parent_zone_id': '0'}],\n",
       "  'ParkID': '1',\n",
       "  'occupancy': {'loop': '174538',\n",
       "   'total': '247',\n",
       "   'monthlies': None,\n",
       "   'open_gate': None,\n",
       "   'transients': None},\n",
       "  'MessageDate': '2024-02-07T17:23:52',\n",
       "  'facility_id': '27',\n",
       "  'facility_name': 'Tallawong P2 Car Park',\n",
       "  'tfnsw_facility_id': '2155384TPR002'},\n",
       " {'tsn': '2155384',\n",
       "  'time': '760602230',\n",
       "  'spots': '397',\n",
       "  'zones': [{'spots': '397',\n",
       "    'zone_id': '1',\n",
       "    'occupancy': {'loop': '103746',\n",
       "     'total': '311',\n",
       "     'monthlies': None,\n",
       "     'open_gate': None,\n",
       "     'transients': None},\n",
       "    'zone_name': 'SYD396C Tallawong P3 Car Park',\n",
       "    'parent_zone_id': '0'}],\n",
       "  'ParkID': '1',\n",
       "  'occupancy': {'loop': '103746',\n",
       "   'total': '311',\n",
       "   'monthlies': None,\n",
       "   'open_gate': None,\n",
       "   'transients': None},\n",
       "  'MessageDate': '2024-02-07T17:23:50',\n",
       "  'facility_id': '28',\n",
       "  'facility_name': 'Tallawong P3 Car Park',\n",
       "  'tfnsw_facility_id': '2155384TPR003'},\n",
       " {'tsn': '2155382',\n",
       "  'time': '760602313',\n",
       "  'spots': '351',\n",
       "  'zones': [{'spots': '351',\n",
       "    'zone_id': '1',\n",
       "    'occupancy': {'loop': '77920',\n",
       "     'total': '245',\n",
       "     'monthlies': None,\n",
       "     'open_gate': None,\n",
       "     'transients': None},\n",
       "    'zone_name': 'SYD395A Kellyville North Car Park',\n",
       "    'parent_zone_id': '0'}],\n",
       "  'ParkID': '1',\n",
       "  'occupancy': {'loop': '77920',\n",
       "   'total': '245',\n",
       "   'monthlies': None,\n",
       "   'open_gate': None,\n",
       "   'transients': None},\n",
       "  'MessageDate': '2024-02-07T17:25:13',\n",
       "  'facility_id': '29',\n",
       "  'facility_name': 'Kellyville North Car Park',\n",
       "  'tfnsw_facility_id': '2155382TPR001'},\n",
       " {'tsn': '2153478',\n",
       "  'time': '742877319',\n",
       "  'spots': '800',\n",
       "  'zones': [{'spots': '800',\n",
       "    'zone_id': 'CPS-BLV',\n",
       "    'occupancy': {'loop': None,\n",
       "     'total': '314',\n",
       "     'monthlies': None,\n",
       "     'open_gate': None,\n",
       "     'transients': None},\n",
       "    'zone_name': 'Bella Vista Station Multi-Level Car Park',\n",
       "    'parent_zone_id': '0'}],\n",
       "  'ParkID': '1',\n",
       "  'occupancy': {'loop': None,\n",
       "   'total': '314',\n",
       "   'monthlies': None,\n",
       "   'open_gate': None,\n",
       "   'transients': None},\n",
       "  'MessageDate': '2023-07-17T12:48:39',\n",
       "  'facility_id': '3',\n",
       "  'facility_name': 'Bella Vista Station Car Park',\n",
       "  'tfnsw_facility_id': '2153478CCP001'},\n",
       " {'tsn': '2155382',\n",
       "  'time': '760602343',\n",
       "  'spots': '964',\n",
       "  'zones': [{'spots': '964',\n",
       "    'zone_id': '1',\n",
       "    'occupancy': {'loop': '292551',\n",
       "     'total': '678',\n",
       "     'monthlies': None,\n",
       "     'open_gate': None,\n",
       "     'transients': None},\n",
       "    'zone_name': 'SYD395B Kellyville South Car Park',\n",
       "    'parent_zone_id': '0'}],\n",
       "  'ParkID': '1',\n",
       "  'occupancy': {'loop': '292551',\n",
       "   'total': '678',\n",
       "   'monthlies': None,\n",
       "   'open_gate': None,\n",
       "   'transients': None},\n",
       "  'MessageDate': '2024-02-07T17:25:43',\n",
       "  'facility_id': '30',\n",
       "  'facility_name': 'Kellyville South Car Park',\n",
       "  'tfnsw_facility_id': '2155382TPR002'},\n",
       " {'tsn': '2153478',\n",
       "  'time': '760602341',\n",
       "  'spots': '777',\n",
       "  'zones': [{'spots': '777',\n",
       "    'zone_id': '1',\n",
       "    'occupancy': {'loop': '246986',\n",
       "     'total': '518',\n",
       "     'monthlies': None,\n",
       "     'open_gate': None,\n",
       "     'transients': None},\n",
       "    'zone_name': 'SYD392 Bella Vista Car Park',\n",
       "    'parent_zone_id': '0'}],\n",
       "  'ParkID': '1',\n",
       "  'occupancy': {'loop': '246986',\n",
       "   'total': '518',\n",
       "   'monthlies': None,\n",
       "   'open_gate': None,\n",
       "   'transients': None},\n",
       "  'MessageDate': '2024-02-07T17:25:41',\n",
       "  'facility_id': '31',\n",
       "  'facility_name': 'Bella Vista Car Park',\n",
       "  'tfnsw_facility_id': '2153478TPR001'},\n",
       " {'tsn': '2154392',\n",
       "  'time': '760602340',\n",
       "  'spots': '584',\n",
       "  'zones': [{'spots': '584',\n",
       "    'zone_id': '1',\n",
       "    'occupancy': {'loop': '205110',\n",
       "     'total': '417',\n",
       "     'monthlies': None,\n",
       "     'open_gate': None,\n",
       "     'transients': None},\n",
       "    'zone_name': 'SYD394 Hills Showground Car Park',\n",
       "    'parent_zone_id': '0'}],\n",
       "  'ParkID': '1',\n",
       "  'occupancy': {'loop': '205110',\n",
       "   'total': '417',\n",
       "   'monthlies': None,\n",
       "   'open_gate': None,\n",
       "   'transients': None},\n",
       "  'MessageDate': '2024-02-07T17:25:40',\n",
       "  'facility_id': '32',\n",
       "  'facility_name': 'Hills Showground Car Park',\n",
       "  'tfnsw_facility_id': '2154392TPR001'},\n",
       " {'tsn': '2126158',\n",
       "  'time': '760602341',\n",
       "  'spots': '384',\n",
       "  'zones': [{'spots': '384',\n",
       "    'zone_id': '1',\n",
       "    'occupancy': {'loop': '142681',\n",
       "     'total': '273',\n",
       "     'monthlies': None,\n",
       "     'open_gate': None,\n",
       "     'transients': None},\n",
       "    'zone_name': 'SYD393 Cherrybrook Car Park',\n",
       "    'parent_zone_id': '0'}],\n",
       "  'ParkID': '1',\n",
       "  'occupancy': {'loop': '142681',\n",
       "   'total': '273',\n",
       "   'monthlies': None,\n",
       "   'open_gate': None,\n",
       "   'transients': None},\n",
       "  'MessageDate': '2024-02-07T17:25:41',\n",
       "  'facility_id': '33',\n",
       "  'facility_name': 'Cherrybrook Car Park',\n",
       "  'tfnsw_facility_id': '2126158TPR001'},\n",
       " {'tsn': '2154392',\n",
       "  'time': '742877319',\n",
       "  'spots': '600',\n",
       "  'zones': [{'spots': '600',\n",
       "    'zone_id': 'CPS-SHW',\n",
       "    'occupancy': {'loop': None,\n",
       "     'total': '532',\n",
       "     'monthlies': None,\n",
       "     'open_gate': None,\n",
       "     'transients': None},\n",
       "    'zone_name': 'Hills Showground Station Multi-Level Car Park',\n",
       "    'parent_zone_id': '0'}],\n",
       "  'ParkID': '1',\n",
       "  'occupancy': {'loop': None,\n",
       "   'total': '532',\n",
       "   'monthlies': None,\n",
       "   'open_gate': None,\n",
       "   'transients': None},\n",
       "  'MessageDate': '2023-07-17T12:48:39',\n",
       "  'facility_id': '4',\n",
       "  'facility_name': 'Hills Showground Station Car Park',\n",
       "  'tfnsw_facility_id': '2154392CCP001'},\n",
       " {'tsn': '213110',\n",
       "  'time': '760641955',\n",
       "  'spots': '228',\n",
       "  'zones': [{'spots': '228',\n",
       "    'zone_id': '1',\n",
       "    'occupancy': {'loop': '310122',\n",
       "     'total': None,\n",
       "     'monthlies': '0',\n",
       "     'open_gate': None,\n",
       "     'transients': '140'},\n",
       "    'zone_name': 'AshfieldCarPark',\n",
       "    'parent_zone_id': '0'}],\n",
       "  'ParkID': 1,\n",
       "  'occupancy': {'loop': None,\n",
       "   'total': '140',\n",
       "   'monthlies': '0',\n",
       "   'open_gate': '0',\n",
       "   'transients': '141'},\n",
       "  'MessageDate': '2024-02-07T17:25:55',\n",
       "  'facility_id': '486',\n",
       "  'facility_name': 'Ashfield Car Park',\n",
       "  'tfnsw_facility_id': '213110TPR001'},\n",
       " {'tsn': '221710',\n",
       "  'time': '760641856',\n",
       "  'spots': '259',\n",
       "  'zones': [{'spots': '259',\n",
       "    'zone_id': '2',\n",
       "    'occupancy': {'loop': '186',\n",
       "     'total': None,\n",
       "     'monthlies': '0',\n",
       "     'open_gate': None,\n",
       "     'transients': '141'},\n",
       "    'zone_name': 'SYD319 Kogarah Park and Ride',\n",
       "    'parent_zone_id': '0'},\n",
       "   {'spots': '0',\n",
       "    'zone_id': '0',\n",
       "    'occupancy': {'loop': '0',\n",
       "     'total': None,\n",
       "     'monthlies': '0',\n",
       "     'open_gate': None,\n",
       "     'transients': '0'},\n",
       "    'zone_name': '',\n",
       "    'parent_zone_id': '0'},\n",
       "   {'spots': '0',\n",
       "    'zone_id': '0',\n",
       "    'occupancy': {'loop': '0',\n",
       "     'total': None,\n",
       "     'monthlies': '0',\n",
       "     'open_gate': None,\n",
       "     'transients': '0'},\n",
       "    'zone_name': '',\n",
       "    'parent_zone_id': '0'},\n",
       "   {'spots': '0',\n",
       "    'zone_id': '0',\n",
       "    'occupancy': {'loop': '0',\n",
       "     'total': None,\n",
       "     'monthlies': '0',\n",
       "     'open_gate': None,\n",
       "     'transients': '0'},\n",
       "    'zone_name': '',\n",
       "    'parent_zone_id': '0'},\n",
       "   {'spots': '0',\n",
       "    'zone_id': '0',\n",
       "    'occupancy': {'loop': '0',\n",
       "     'total': None,\n",
       "     'monthlies': '0',\n",
       "     'open_gate': None,\n",
       "     'transients': '0'},\n",
       "    'zone_name': '',\n",
       "    'parent_zone_id': '0'},\n",
       "   {'spots': '0',\n",
       "    'zone_id': '0',\n",
       "    'occupancy': {'loop': '0',\n",
       "     'total': None,\n",
       "     'monthlies': '0',\n",
       "     'open_gate': None,\n",
       "     'transients': '0'},\n",
       "    'zone_name': '',\n",
       "    'parent_zone_id': '0'},\n",
       "   {'spots': '0',\n",
       "    'zone_id': '0',\n",
       "    'occupancy': {'loop': '0',\n",
       "     'total': None,\n",
       "     'monthlies': '0',\n",
       "     'open_gate': None,\n",
       "     'transients': '0'},\n",
       "    'zone_name': '',\n",
       "    'parent_zone_id': '0'}],\n",
       "  'ParkID': 3,\n",
       "  'occupancy': {'loop': None,\n",
       "   'total': '141',\n",
       "   'monthlies': '0',\n",
       "   'open_gate': '0',\n",
       "   'transients': '141'},\n",
       "  'MessageDate': '2024-02-07T17:24:16',\n",
       "  'facility_id': '487',\n",
       "  'facility_name': 'Kogarah Car Park',\n",
       "  'tfnsw_facility_id': '221710TPR001'},\n",
       " {'tsn': '214710',\n",
       "  'time': '760641955',\n",
       "  'spots': '1613',\n",
       "  'zones': [{'spots': '874',\n",
       "    'zone_id': '4',\n",
       "    'occupancy': {'loop': '17',\n",
       "     'total': None,\n",
       "     'monthlies': '0',\n",
       "     'open_gate': None,\n",
       "     'transients': '537'},\n",
       "    'zone_name': 'Multi Level',\n",
       "    'parent_zone_id': '0'},\n",
       "   {'spots': '739',\n",
       "    'zone_id': '5',\n",
       "    'occupancy': {'loop': '7',\n",
       "     'total': None,\n",
       "     'monthlies': '0',\n",
       "     'open_gate': None,\n",
       "     'transients': '102'},\n",
       "    'zone_name': 'on grade',\n",
       "    'parent_zone_id': '0'},\n",
       "   {'spots': '0',\n",
       "    'zone_id': '0',\n",
       "    'occupancy': {'loop': '0',\n",
       "     'total': None,\n",
       "     'monthlies': '0',\n",
       "     'open_gate': None,\n",
       "     'transients': '0'},\n",
       "    'zone_name': '',\n",
       "    'parent_zone_id': '0'},\n",
       "   {'spots': '0',\n",
       "    'zone_id': '0',\n",
       "    'occupancy': {'loop': '0',\n",
       "     'total': None,\n",
       "     'monthlies': '0',\n",
       "     'open_gate': None,\n",
       "     'transients': '0'},\n",
       "    'zone_name': '',\n",
       "    'parent_zone_id': '0'}],\n",
       "  'ParkID': 4,\n",
       "  'occupancy': {'loop': None,\n",
       "   'total': '639',\n",
       "   'monthlies': '0',\n",
       "   'open_gate': '0',\n",
       "   'transients': '648'},\n",
       "  'MessageDate': '2024-02-07T17:25:55',\n",
       "  'facility_id': '488',\n",
       "  'facility_name': 'Seven Hills Car Park',\n",
       "  'tfnsw_facility_id': '214710TPR001'},\n",
       " {'tsn': '2093117',\n",
       "  'time': '760641886',\n",
       "  'spots': '142',\n",
       "  'zones': [{'spots': '142',\n",
       "    'zone_id': '1',\n",
       "    'occupancy': {'loop': '0',\n",
       "     'total': None,\n",
       "     'monthlies': '0',\n",
       "     'open_gate': None,\n",
       "     'transients': '106'},\n",
       "    'zone_name': 'SYD326 Manly Vale Park and Ride',\n",
       "    'parent_zone_id': '0'}],\n",
       "  'ParkID': 1,\n",
       "  'occupancy': {'loop': None,\n",
       "   'total': '106',\n",
       "   'monthlies': '0',\n",
       "   'open_gate': '0',\n",
       "   'transients': '106'},\n",
       "  'MessageDate': '2024-02-07T17:24:46',\n",
       "  'facility_id': '489',\n",
       "  'facility_name': 'Manly Vale Car Park',\n",
       "  'tfnsw_facility_id': '2093117TPR001'},\n",
       " {'tsn': '210020',\n",
       "  'time': '760641922',\n",
       "  'spots': '246',\n",
       "  'zones': [{'spots': '246',\n",
       "    'zone_id': '1',\n",
       "    'occupancy': {'loop': '183',\n",
       "     'total': None,\n",
       "     'monthlies': '0',\n",
       "     'open_gate': None,\n",
       "     'transients': '57'},\n",
       "    'zone_name': 'MainArea',\n",
       "    'parent_zone_id': '0'}],\n",
       "  'ParkID': 1,\n",
       "  'occupancy': {'loop': None,\n",
       "   'total': '183',\n",
       "   'monthlies': '0',\n",
       "   'open_gate': '0',\n",
       "   'transients': '447'},\n",
       "  'MessageDate': '2024-02-07T17:25:22',\n",
       "  'facility_id': '490',\n",
       "  'facility_name': 'Brookvale Car Park',\n",
       "  'tfnsw_facility_id': '210020TPR001'},\n",
       " {'tsn': '2126158',\n",
       "  'time': '742877319',\n",
       "  'spots': '400',\n",
       "  'zones': [{'spots': '400',\n",
       "    'zone_id': 'CPS-CHE',\n",
       "    'occupancy': {'loop': None,\n",
       "     'total': '400',\n",
       "     'monthlies': None,\n",
       "     'open_gate': None,\n",
       "     'transients': None},\n",
       "    'zone_name': 'Cherrybrook Station Multi-Level Car Park',\n",
       "    'parent_zone_id': '0'}],\n",
       "  'ParkID': '1',\n",
       "  'occupancy': {'loop': None,\n",
       "   'total': '400',\n",
       "   'monthlies': None,\n",
       "   'open_gate': None,\n",
       "   'transients': None},\n",
       "  'MessageDate': '2023-07-17T12:48:39',\n",
       "  'facility_id': '5',\n",
       "  'facility_name': 'Cherrybrook Station Car Park',\n",
       "  'tfnsw_facility_id': '2126158CCP001'},\n",
       " {'tsn': '207210',\n",
       "  'time': '760602224',\n",
       "  'spots': '213',\n",
       "  'zones': [{'spots': '213',\n",
       "    'zone_id': '1',\n",
       "    'occupancy': {'loop': None,\n",
       "     'total': '139',\n",
       "     'monthlies': None,\n",
       "     'open_gate': None,\n",
       "     'transients': None},\n",
       "    'zone_name': 'Gordon Henry St North Car Park',\n",
       "    'parent_zone_id': '0'}],\n",
       "  'ParkID': '1',\n",
       "  'occupancy': {'loop': None,\n",
       "   'total': '139',\n",
       "   'monthlies': None,\n",
       "   'open_gate': None,\n",
       "   'transients': None},\n",
       "  'MessageDate': '2024-02-07T17:23:44',\n",
       "  'facility_id': '6',\n",
       "  'facility_name': 'Gordon Henry St North Car Park',\n",
       "  'tfnsw_facility_id': '207210TPR001'},\n",
       " {'tsn': '253330',\n",
       "  'time': '760602367',\n",
       "  'spots': '42',\n",
       "  'zones': [{'spots': '42',\n",
       "    'zone_id': '1',\n",
       "    'occupancy': {'loop': None,\n",
       "     'total': '1',\n",
       "     'monthlies': None,\n",
       "     'open_gate': None,\n",
       "     'transients': None},\n",
       "    'zone_name': 'Kiama Car Park',\n",
       "    'parent_zone_id': '0'}],\n",
       "  'ParkID': '1',\n",
       "  'occupancy': {'loop': None,\n",
       "   'total': '1',\n",
       "   'monthlies': None,\n",
       "   'open_gate': None,\n",
       "   'transients': None},\n",
       "  'MessageDate': '2024-02-07T17:26:07',\n",
       "  'facility_id': '7',\n",
       "  'facility_name': 'Kiama Car Park',\n",
       "  'tfnsw_facility_id': '253330TPR001'},\n",
       " {'tsn': '225040',\n",
       "  'time': '760602296',\n",
       "  'spots': '1057',\n",
       "  'zones': [{'spots': '1057',\n",
       "    'zone_id': '1',\n",
       "    'occupancy': {'loop': None,\n",
       "     'total': '748',\n",
       "     'monthlies': None,\n",
       "     'open_gate': None,\n",
       "     'transients': None},\n",
       "    'zone_name': 'Gosford Car Park',\n",
       "    'parent_zone_id': '0'}],\n",
       "  'ParkID': '1',\n",
       "  'occupancy': {'loop': None,\n",
       "   'total': '748',\n",
       "   'monthlies': None,\n",
       "   'open_gate': None,\n",
       "   'transients': None},\n",
       "  'MessageDate': '2024-02-07T17:24:56',\n",
       "  'facility_id': '8',\n",
       "  'facility_name': 'Gosford Car Park',\n",
       "  'tfnsw_facility_id': '225040TPR001'},\n",
       " {'tsn': '221210',\n",
       "  'time': '760602271',\n",
       "  'spots': '934',\n",
       "  'zones': [{'spots': '934',\n",
       "    'zone_id': '1',\n",
       "    'occupancy': {'loop': '323483',\n",
       "     'total': '370',\n",
       "     'monthlies': None,\n",
       "     'open_gate': None,\n",
       "     'transients': None},\n",
       "    'zone_name': 'SYD364 Revesby Commuter Carpark',\n",
       "    'parent_zone_id': '0'}],\n",
       "  'ParkID': '1',\n",
       "  'occupancy': {'loop': '323483',\n",
       "   'total': '370',\n",
       "   'monthlies': None,\n",
       "   'open_gate': None,\n",
       "   'transients': None},\n",
       "  'MessageDate': '2024-02-07T17:24:31',\n",
       "  'facility_id': '9',\n",
       "  'facility_name': 'Revesby Car Park',\n",
       "  'tfnsw_facility_id': '221210TPR001'}]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Load secret file\n",
    "dotenv.load_dotenv('.env')\n",
    "\n",
    "headers = {\n",
    "  \"Authorization\":f\"apikey {os.environ.get('apikey')}\"\n",
    "}\n",
    "url_carparks = 'https://api.transport.nsw.gov.au/v1/carpark'\n",
    "# url_carpark_history = 'https://api.transport.nsw.gov.au/v1/carpark/history'\n",
    "\n",
    "list_of_carparks = requests.get(url_carparks, headers=headers).json()\n",
    "\n",
    "# Create a json file and write the data if it doesn't exist\n",
    "if not os.path.exists('./data/carparks.json'):\n",
    "  with open('./data/carparks.json', 'w') as f:\n",
    "    json.dumps(list_of_carparks, f)\n",
    "\n",
    "# The format of the file itself is a dictionary, thus requiring some creativity to read\n",
    "with open('./data/carparks.json') as f:\n",
    "  data = json.load(f)\n",
    "\n",
    "# Convert the dictionary to a dataframe\n",
    "df_carparks = pd.DataFrame.from_dict(data, orient='index')\n",
    "# Resetting the index to label the columns afterwards\n",
    "df_carparks = df_carparks.reset_index()\n",
    "df_carparks.columns = ['facility_id', 'CarParkName']\n",
    "\n",
    "df_carparks\n",
    "\n",
    "carpark_details_array=[]\n",
    "for index, row in df_carparks.iterrows():\n",
    "  facility = row['facility_id']\n",
    "  url = f'https://api.transport.nsw.gov.au/v1/carpark?facility={facility}'\n",
    "\n",
    "\n",
    "  # Make request\n",
    "  response = requests.get(url, headers=headers).json()\n",
    "\n",
    "  # Add to array\n",
    "  carpark_details_array.append(response)\n",
    "\n",
    "carpark_details_array"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tsn</th>\n",
       "      <th>time</th>\n",
       "      <th>spots</th>\n",
       "      <th>zones</th>\n",
       "      <th>ParkID</th>\n",
       "      <th>occupancy</th>\n",
       "      <th>MessageDate</th>\n",
       "      <th>facility_id</th>\n",
       "      <th>facility_name</th>\n",
       "      <th>tfnsw_facility_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2155384</td>\n",
       "      <td>742877319</td>\n",
       "      <td>1004</td>\n",
       "      <td>[{'spots': '152', 'zone_id': 'CPS-CUD1', 'occu...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '981', 'monthlies': No...</td>\n",
       "      <td>2023-07-17T12:48:39</td>\n",
       "      <td>1</td>\n",
       "      <td>Tallawong Station Car Park</td>\n",
       "      <td>2155384CCP001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2101131</td>\n",
       "      <td>760523635</td>\n",
       "      <td>244</td>\n",
       "      <td>[{'spots': '244', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '60', 'monthlies': Non...</td>\n",
       "      <td>2024-02-06T19:33:55</td>\n",
       "      <td>10</td>\n",
       "      <td>Warriewood Car Park</td>\n",
       "      <td>2101131TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2101130</td>\n",
       "      <td>760523847</td>\n",
       "      <td>46</td>\n",
       "      <td>[{'spots': '46', 'zone_id': '1', 'occupancy': ...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '63981', 'total': '6', 'monthlies': N...</td>\n",
       "      <td>2024-02-06T19:37:27</td>\n",
       "      <td>11</td>\n",
       "      <td>Narrabeen Car Park</td>\n",
       "      <td>2101130TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2103108</td>\n",
       "      <td>760523782</td>\n",
       "      <td>68</td>\n",
       "      <td>[{'spots': '68', 'zone_id': '1', 'occupancy': ...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '37', 'monthlies': Non...</td>\n",
       "      <td>2024-02-06T19:36:22</td>\n",
       "      <td>12</td>\n",
       "      <td>Mona Vale Car Park</td>\n",
       "      <td>2103108TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2099207</td>\n",
       "      <td>760523886</td>\n",
       "      <td>117</td>\n",
       "      <td>[{'spots': '117', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '53474', 'total': '37', 'monthlies': ...</td>\n",
       "      <td>2024-02-06T19:38:06</td>\n",
       "      <td>13</td>\n",
       "      <td>Dee Why Car Park</td>\n",
       "      <td>2099207TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>211420</td>\n",
       "      <td>760523565</td>\n",
       "      <td>151</td>\n",
       "      <td>[{'spots': '151', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '228460', 'total': '23', 'monthlies':...</td>\n",
       "      <td>2024-02-06T19:32:45</td>\n",
       "      <td>14</td>\n",
       "      <td>West Ryde Car Park</td>\n",
       "      <td>211420TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>223210</td>\n",
       "      <td>760523415</td>\n",
       "      <td>373</td>\n",
       "      <td>[{'spots': '373', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '35', 'monthlies': Non...</td>\n",
       "      <td>2024-02-06T19:30:15</td>\n",
       "      <td>15</td>\n",
       "      <td>Sutherland East Parade Car Park</td>\n",
       "      <td>223210TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>217933</td>\n",
       "      <td>760523838</td>\n",
       "      <td>1884</td>\n",
       "      <td>[{'spots': '1884', 'zone_id': '1', 'occupancy'...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '811983', 'total': '312', 'monthlies'...</td>\n",
       "      <td>2024-02-06T19:37:18</td>\n",
       "      <td>16</td>\n",
       "      <td>Leppington Car Park</td>\n",
       "      <td>217933TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>217426</td>\n",
       "      <td>760523875</td>\n",
       "      <td>1429</td>\n",
       "      <td>[{'spots': '1429', 'zone_id': '1', 'occupancy'...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '742989', 'total': '108', 'monthlies'...</td>\n",
       "      <td>2024-02-06T19:37:55</td>\n",
       "      <td>17</td>\n",
       "      <td>Edmondson Park South Car Park</td>\n",
       "      <td>217426TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>276010</td>\n",
       "      <td>760523931</td>\n",
       "      <td>682</td>\n",
       "      <td>[{'spots': '682', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '107', 'monthlies': No...</td>\n",
       "      <td>2024-02-06T19:38:51</td>\n",
       "      <td>18</td>\n",
       "      <td>St Marys Car Park</td>\n",
       "      <td>276010TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>256020</td>\n",
       "      <td>760523930</td>\n",
       "      <td>68</td>\n",
       "      <td>[{'spots': '68', 'zone_id': '1', 'occupancy': ...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '147734', 'total': '33', 'monthlies':...</td>\n",
       "      <td>2024-02-06T19:38:50</td>\n",
       "      <td>19</td>\n",
       "      <td>Campbelltown Farrow Rd North Car Park</td>\n",
       "      <td>256020TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2155382</td>\n",
       "      <td>742877319</td>\n",
       "      <td>1374</td>\n",
       "      <td>[{'spots': '368', 'zone_id': 'CPS-KVE1', 'occu...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '1363', 'monthlies': N...</td>\n",
       "      <td>2023-07-17T12:48:39</td>\n",
       "      <td>2</td>\n",
       "      <td>Kellyville Station Car Park</td>\n",
       "      <td>2155382CCP001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>256020</td>\n",
       "      <td>760523758</td>\n",
       "      <td>118</td>\n",
       "      <td>[{'spots': '118', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '178056', 'total': '33', 'monthlies':...</td>\n",
       "      <td>2024-02-06T19:35:58</td>\n",
       "      <td>20</td>\n",
       "      <td>Campbelltown Hurley Street South Car Park</td>\n",
       "      <td>25602TPR002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>275010</td>\n",
       "      <td>760523880</td>\n",
       "      <td>230</td>\n",
       "      <td>[{'spots': '230', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '74516', 'total': '19', 'monthlies': ...</td>\n",
       "      <td>2024-02-06T18:38:00</td>\n",
       "      <td>21</td>\n",
       "      <td>Penrith Combewood At-Grade Car Park</td>\n",
       "      <td>275010TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>275010</td>\n",
       "      <td>760523926</td>\n",
       "      <td>1144</td>\n",
       "      <td>[{'spots': '1144', 'zone_id': '1', 'occupancy'...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '522646', 'total': '91', 'monthlies':...</td>\n",
       "      <td>2024-02-06T18:38:46</td>\n",
       "      <td>22</td>\n",
       "      <td>Penrith Combewood Multi-Level Car Park</td>\n",
       "      <td>275010TPR002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>217010</td>\n",
       "      <td>760523792</td>\n",
       "      <td>910</td>\n",
       "      <td>[{'spots': '910', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '110', 'monthlies': No...</td>\n",
       "      <td>2024-02-06T19:36:32</td>\n",
       "      <td>23</td>\n",
       "      <td>Warwick Farm Car Park</td>\n",
       "      <td>217010TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>276220</td>\n",
       "      <td>760523939</td>\n",
       "      <td>700</td>\n",
       "      <td>[{'spots': '700', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '478766', 'total': '49', 'monthlies':...</td>\n",
       "      <td>2024-02-06T19:38:59</td>\n",
       "      <td>24</td>\n",
       "      <td>Schofields Car Park</td>\n",
       "      <td>276220TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>207720</td>\n",
       "      <td>760523683</td>\n",
       "      <td>145</td>\n",
       "      <td>[{'spots': '145', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '104953', 'total': '25', 'monthlies':...</td>\n",
       "      <td>2024-02-06T19:34:43</td>\n",
       "      <td>25</td>\n",
       "      <td>Hornsby Jersey St Car Park</td>\n",
       "      <td>207720TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2155384</td>\n",
       "      <td>760523850</td>\n",
       "      <td>121</td>\n",
       "      <td>[{'spots': '121', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '90929', 'total': '14', 'monthlies': ...</td>\n",
       "      <td>2024-02-06T19:37:30</td>\n",
       "      <td>26</td>\n",
       "      <td>Tallawong P1 Car Park</td>\n",
       "      <td>2155384TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2155384</td>\n",
       "      <td>760523907</td>\n",
       "      <td>455</td>\n",
       "      <td>[{'spots': '455', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '173680', 'total': '28', 'monthlies':...</td>\n",
       "      <td>2024-02-06T19:38:27</td>\n",
       "      <td>27</td>\n",
       "      <td>Tallawong P2 Car Park</td>\n",
       "      <td>2155384TPR002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2155384</td>\n",
       "      <td>760523862</td>\n",
       "      <td>397</td>\n",
       "      <td>[{'spots': '397', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '103032', 'total': '51', 'monthlies':...</td>\n",
       "      <td>2024-02-06T19:37:42</td>\n",
       "      <td>28</td>\n",
       "      <td>Tallawong P3 Car Park</td>\n",
       "      <td>2155384TPR003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2155382</td>\n",
       "      <td>760523894</td>\n",
       "      <td>351</td>\n",
       "      <td>[{'spots': '351', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '77329', 'total': '45', 'monthlies': ...</td>\n",
       "      <td>2024-02-06T19:38:14</td>\n",
       "      <td>29</td>\n",
       "      <td>Kellyville North Car Park</td>\n",
       "      <td>2155382TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2153478</td>\n",
       "      <td>742877319</td>\n",
       "      <td>800</td>\n",
       "      <td>[{'spots': '800', 'zone_id': 'CPS-BLV', 'occup...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '314', 'monthlies': No...</td>\n",
       "      <td>2023-07-17T12:48:39</td>\n",
       "      <td>3</td>\n",
       "      <td>Bella Vista Station Car Park</td>\n",
       "      <td>2153478CCP001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2155382</td>\n",
       "      <td>760523751</td>\n",
       "      <td>964</td>\n",
       "      <td>[{'spots': '964', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '290767', 'total': '100', 'monthlies'...</td>\n",
       "      <td>2024-02-06T19:35:51</td>\n",
       "      <td>30</td>\n",
       "      <td>Kellyville South Car Park</td>\n",
       "      <td>2155382TPR002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2153478</td>\n",
       "      <td>760523891</td>\n",
       "      <td>777</td>\n",
       "      <td>[{'spots': '777', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '245560', 'total': '110', 'monthlies'...</td>\n",
       "      <td>2024-02-06T19:38:11</td>\n",
       "      <td>31</td>\n",
       "      <td>Bella Vista Car Park</td>\n",
       "      <td>2153478TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>2154392</td>\n",
       "      <td>760523962</td>\n",
       "      <td>584</td>\n",
       "      <td>[{'spots': '584', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '204073', 'total': '69', 'monthlies':...</td>\n",
       "      <td>2024-02-06T19:39:22</td>\n",
       "      <td>32</td>\n",
       "      <td>Hills Showground Car Park</td>\n",
       "      <td>2154392TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>2126158</td>\n",
       "      <td>760523931</td>\n",
       "      <td>384</td>\n",
       "      <td>[{'spots': '384', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '141861', 'total': '65', 'monthlies':...</td>\n",
       "      <td>2024-02-06T19:38:51</td>\n",
       "      <td>33</td>\n",
       "      <td>Cherrybrook Car Park</td>\n",
       "      <td>2126158TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>2154392</td>\n",
       "      <td>742877319</td>\n",
       "      <td>600</td>\n",
       "      <td>[{'spots': '600', 'zone_id': 'CPS-SHW', 'occup...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '532', 'monthlies': No...</td>\n",
       "      <td>2023-07-17T12:48:39</td>\n",
       "      <td>4</td>\n",
       "      <td>Hills Showground Station Car Park</td>\n",
       "      <td>2154392CCP001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>213110</td>\n",
       "      <td>760563564</td>\n",
       "      <td>228</td>\n",
       "      <td>[{'spots': '228', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '53', 'monthlies': '0'...</td>\n",
       "      <td>2024-02-06T19:39:24</td>\n",
       "      <td>486</td>\n",
       "      <td>Ashfield Car Park</td>\n",
       "      <td>213110TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>221710</td>\n",
       "      <td>760563536</td>\n",
       "      <td>259</td>\n",
       "      <td>[{'spots': '259', 'zone_id': '2', 'occupancy':...</td>\n",
       "      <td>3</td>\n",
       "      <td>{'loop': None, 'total': '29', 'monthlies': '0'...</td>\n",
       "      <td>2024-02-06T19:38:56</td>\n",
       "      <td>487</td>\n",
       "      <td>Kogarah Car Park</td>\n",
       "      <td>221710TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>214710</td>\n",
       "      <td>760563564</td>\n",
       "      <td>1613</td>\n",
       "      <td>[{'spots': '874', 'zone_id': '4', 'occupancy':...</td>\n",
       "      <td>4</td>\n",
       "      <td>{'loop': None, 'total': '152', 'monthlies': '0...</td>\n",
       "      <td>2024-02-06T19:39:24</td>\n",
       "      <td>488</td>\n",
       "      <td>Seven Hills Car Park</td>\n",
       "      <td>214710TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>2093117</td>\n",
       "      <td>760563408</td>\n",
       "      <td>142</td>\n",
       "      <td>[{'spots': '142', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '26', 'monthlies': '0'...</td>\n",
       "      <td>2024-02-06T19:36:48</td>\n",
       "      <td>489</td>\n",
       "      <td>Manly Vale Car Park</td>\n",
       "      <td>2093117TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>210020</td>\n",
       "      <td>760563578</td>\n",
       "      <td>246</td>\n",
       "      <td>[{'spots': '246', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '27', 'monthlies': '0'...</td>\n",
       "      <td>2024-02-06T19:39:38</td>\n",
       "      <td>490</td>\n",
       "      <td>Brookvale Car Park</td>\n",
       "      <td>210020TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>2126158</td>\n",
       "      <td>742877319</td>\n",
       "      <td>400</td>\n",
       "      <td>[{'spots': '400', 'zone_id': 'CPS-CHE', 'occup...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '400', 'monthlies': No...</td>\n",
       "      <td>2023-07-17T12:48:39</td>\n",
       "      <td>5</td>\n",
       "      <td>Cherrybrook Station Car Park</td>\n",
       "      <td>2126158CCP001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>207210</td>\n",
       "      <td>760523866</td>\n",
       "      <td>213</td>\n",
       "      <td>[{'spots': '213', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '25', 'monthlies': Non...</td>\n",
       "      <td>2024-02-06T19:37:46</td>\n",
       "      <td>6</td>\n",
       "      <td>Gordon Henry St North Car Park</td>\n",
       "      <td>207210TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>253330</td>\n",
       "      <td>760523985</td>\n",
       "      <td>42</td>\n",
       "      <td>[{'spots': '42', 'zone_id': '1', 'occupancy': ...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '-2', 'monthlies': Non...</td>\n",
       "      <td>2024-02-06T19:39:45</td>\n",
       "      <td>7</td>\n",
       "      <td>Kiama Car Park</td>\n",
       "      <td>253330TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>225040</td>\n",
       "      <td>760523776</td>\n",
       "      <td>1057</td>\n",
       "      <td>[{'spots': '1057', 'zone_id': '1', 'occupancy'...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '188', 'monthlies': No...</td>\n",
       "      <td>2024-02-06T19:36:16</td>\n",
       "      <td>8</td>\n",
       "      <td>Gosford Car Park</td>\n",
       "      <td>225040TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>221210</td>\n",
       "      <td>760523963</td>\n",
       "      <td>934</td>\n",
       "      <td>[{'spots': '934', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '322681', 'total': '98', 'monthlies':...</td>\n",
       "      <td>2024-02-06T19:39:23</td>\n",
       "      <td>9</td>\n",
       "      <td>Revesby Car Park</td>\n",
       "      <td>221210TPR001</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        tsn       time  spots  \\\n",
       "0   2155384  742877319   1004   \n",
       "1   2101131  760523635    244   \n",
       "2   2101130  760523847     46   \n",
       "3   2103108  760523782     68   \n",
       "4   2099207  760523886    117   \n",
       "5    211420  760523565    151   \n",
       "6    223210  760523415    373   \n",
       "7    217933  760523838   1884   \n",
       "8    217426  760523875   1429   \n",
       "9    276010  760523931    682   \n",
       "10   256020  760523930     68   \n",
       "11  2155382  742877319   1374   \n",
       "12   256020  760523758    118   \n",
       "13   275010  760523880    230   \n",
       "14   275010  760523926   1144   \n",
       "15   217010  760523792    910   \n",
       "16   276220  760523939    700   \n",
       "17   207720  760523683    145   \n",
       "18  2155384  760523850    121   \n",
       "19  2155384  760523907    455   \n",
       "20  2155384  760523862    397   \n",
       "21  2155382  760523894    351   \n",
       "22  2153478  742877319    800   \n",
       "23  2155382  760523751    964   \n",
       "24  2153478  760523891    777   \n",
       "25  2154392  760523962    584   \n",
       "26  2126158  760523931    384   \n",
       "27  2154392  742877319    600   \n",
       "28   213110  760563564    228   \n",
       "29   221710  760563536    259   \n",
       "30   214710  760563564   1613   \n",
       "31  2093117  760563408    142   \n",
       "32   210020  760563578    246   \n",
       "33  2126158  742877319    400   \n",
       "34   207210  760523866    213   \n",
       "35   253330  760523985     42   \n",
       "36   225040  760523776   1057   \n",
       "37   221210  760523963    934   \n",
       "\n",
       "                                                zones  ParkID  \\\n",
       "0   [{'spots': '152', 'zone_id': 'CPS-CUD1', 'occu...       1   \n",
       "1   [{'spots': '244', 'zone_id': '1', 'occupancy':...       1   \n",
       "2   [{'spots': '46', 'zone_id': '1', 'occupancy': ...       1   \n",
       "3   [{'spots': '68', 'zone_id': '1', 'occupancy': ...       1   \n",
       "4   [{'spots': '117', 'zone_id': '1', 'occupancy':...       1   \n",
       "5   [{'spots': '151', 'zone_id': '1', 'occupancy':...       1   \n",
       "6   [{'spots': '373', 'zone_id': '1', 'occupancy':...       1   \n",
       "7   [{'spots': '1884', 'zone_id': '1', 'occupancy'...       1   \n",
       "8   [{'spots': '1429', 'zone_id': '1', 'occupancy'...       1   \n",
       "9   [{'spots': '682', 'zone_id': '1', 'occupancy':...       1   \n",
       "10  [{'spots': '68', 'zone_id': '1', 'occupancy': ...       1   \n",
       "11  [{'spots': '368', 'zone_id': 'CPS-KVE1', 'occu...       1   \n",
       "12  [{'spots': '118', 'zone_id': '1', 'occupancy':...       1   \n",
       "13  [{'spots': '230', 'zone_id': '1', 'occupancy':...       1   \n",
       "14  [{'spots': '1144', 'zone_id': '1', 'occupancy'...       1   \n",
       "15  [{'spots': '910', 'zone_id': '1', 'occupancy':...       1   \n",
       "16  [{'spots': '700', 'zone_id': '1', 'occupancy':...       1   \n",
       "17  [{'spots': '145', 'zone_id': '1', 'occupancy':...       1   \n",
       "18  [{'spots': '121', 'zone_id': '1', 'occupancy':...       1   \n",
       "19  [{'spots': '455', 'zone_id': '1', 'occupancy':...       1   \n",
       "20  [{'spots': '397', 'zone_id': '1', 'occupancy':...       1   \n",
       "21  [{'spots': '351', 'zone_id': '1', 'occupancy':...       1   \n",
       "22  [{'spots': '800', 'zone_id': 'CPS-BLV', 'occup...       1   \n",
       "23  [{'spots': '964', 'zone_id': '1', 'occupancy':...       1   \n",
       "24  [{'spots': '777', 'zone_id': '1', 'occupancy':...       1   \n",
       "25  [{'spots': '584', 'zone_id': '1', 'occupancy':...       1   \n",
       "26  [{'spots': '384', 'zone_id': '1', 'occupancy':...       1   \n",
       "27  [{'spots': '600', 'zone_id': 'CPS-SHW', 'occup...       1   \n",
       "28  [{'spots': '228', 'zone_id': '1', 'occupancy':...       1   \n",
       "29  [{'spots': '259', 'zone_id': '2', 'occupancy':...       3   \n",
       "30  [{'spots': '874', 'zone_id': '4', 'occupancy':...       4   \n",
       "31  [{'spots': '142', 'zone_id': '1', 'occupancy':...       1   \n",
       "32  [{'spots': '246', 'zone_id': '1', 'occupancy':...       1   \n",
       "33  [{'spots': '400', 'zone_id': 'CPS-CHE', 'occup...       1   \n",
       "34  [{'spots': '213', 'zone_id': '1', 'occupancy':...       1   \n",
       "35  [{'spots': '42', 'zone_id': '1', 'occupancy': ...       1   \n",
       "36  [{'spots': '1057', 'zone_id': '1', 'occupancy'...       1   \n",
       "37  [{'spots': '934', 'zone_id': '1', 'occupancy':...       1   \n",
       "\n",
       "                                            occupancy          MessageDate  \\\n",
       "0   {'loop': None, 'total': '981', 'monthlies': No...  2023-07-17T12:48:39   \n",
       "1   {'loop': None, 'total': '60', 'monthlies': Non...  2024-02-06T19:33:55   \n",
       "2   {'loop': '63981', 'total': '6', 'monthlies': N...  2024-02-06T19:37:27   \n",
       "3   {'loop': None, 'total': '37', 'monthlies': Non...  2024-02-06T19:36:22   \n",
       "4   {'loop': '53474', 'total': '37', 'monthlies': ...  2024-02-06T19:38:06   \n",
       "5   {'loop': '228460', 'total': '23', 'monthlies':...  2024-02-06T19:32:45   \n",
       "6   {'loop': None, 'total': '35', 'monthlies': Non...  2024-02-06T19:30:15   \n",
       "7   {'loop': '811983', 'total': '312', 'monthlies'...  2024-02-06T19:37:18   \n",
       "8   {'loop': '742989', 'total': '108', 'monthlies'...  2024-02-06T19:37:55   \n",
       "9   {'loop': None, 'total': '107', 'monthlies': No...  2024-02-06T19:38:51   \n",
       "10  {'loop': '147734', 'total': '33', 'monthlies':...  2024-02-06T19:38:50   \n",
       "11  {'loop': None, 'total': '1363', 'monthlies': N...  2023-07-17T12:48:39   \n",
       "12  {'loop': '178056', 'total': '33', 'monthlies':...  2024-02-06T19:35:58   \n",
       "13  {'loop': '74516', 'total': '19', 'monthlies': ...  2024-02-06T18:38:00   \n",
       "14  {'loop': '522646', 'total': '91', 'monthlies':...  2024-02-06T18:38:46   \n",
       "15  {'loop': None, 'total': '110', 'monthlies': No...  2024-02-06T19:36:32   \n",
       "16  {'loop': '478766', 'total': '49', 'monthlies':...  2024-02-06T19:38:59   \n",
       "17  {'loop': '104953', 'total': '25', 'monthlies':...  2024-02-06T19:34:43   \n",
       "18  {'loop': '90929', 'total': '14', 'monthlies': ...  2024-02-06T19:37:30   \n",
       "19  {'loop': '173680', 'total': '28', 'monthlies':...  2024-02-06T19:38:27   \n",
       "20  {'loop': '103032', 'total': '51', 'monthlies':...  2024-02-06T19:37:42   \n",
       "21  {'loop': '77329', 'total': '45', 'monthlies': ...  2024-02-06T19:38:14   \n",
       "22  {'loop': None, 'total': '314', 'monthlies': No...  2023-07-17T12:48:39   \n",
       "23  {'loop': '290767', 'total': '100', 'monthlies'...  2024-02-06T19:35:51   \n",
       "24  {'loop': '245560', 'total': '110', 'monthlies'...  2024-02-06T19:38:11   \n",
       "25  {'loop': '204073', 'total': '69', 'monthlies':...  2024-02-06T19:39:22   \n",
       "26  {'loop': '141861', 'total': '65', 'monthlies':...  2024-02-06T19:38:51   \n",
       "27  {'loop': None, 'total': '532', 'monthlies': No...  2023-07-17T12:48:39   \n",
       "28  {'loop': None, 'total': '53', 'monthlies': '0'...  2024-02-06T19:39:24   \n",
       "29  {'loop': None, 'total': '29', 'monthlies': '0'...  2024-02-06T19:38:56   \n",
       "30  {'loop': None, 'total': '152', 'monthlies': '0...  2024-02-06T19:39:24   \n",
       "31  {'loop': None, 'total': '26', 'monthlies': '0'...  2024-02-06T19:36:48   \n",
       "32  {'loop': None, 'total': '27', 'monthlies': '0'...  2024-02-06T19:39:38   \n",
       "33  {'loop': None, 'total': '400', 'monthlies': No...  2023-07-17T12:48:39   \n",
       "34  {'loop': None, 'total': '25', 'monthlies': Non...  2024-02-06T19:37:46   \n",
       "35  {'loop': None, 'total': '-2', 'monthlies': Non...  2024-02-06T19:39:45   \n",
       "36  {'loop': None, 'total': '188', 'monthlies': No...  2024-02-06T19:36:16   \n",
       "37  {'loop': '322681', 'total': '98', 'monthlies':...  2024-02-06T19:39:23   \n",
       "\n",
       "    facility_id                              facility_name tfnsw_facility_id  \n",
       "0             1                 Tallawong Station Car Park     2155384CCP001  \n",
       "1            10                        Warriewood Car Park     2101131TPR001  \n",
       "2            11                         Narrabeen Car Park     2101130TPR001  \n",
       "3            12                         Mona Vale Car Park     2103108TPR001  \n",
       "4            13                           Dee Why Car Park     2099207TPR001  \n",
       "5            14                         West Ryde Car Park      211420TPR001  \n",
       "6            15            Sutherland East Parade Car Park      223210TPR001  \n",
       "7            16                        Leppington Car Park      217933TPR001  \n",
       "8            17              Edmondson Park South Car Park      217426TPR001  \n",
       "9            18                          St Marys Car Park      276010TPR001  \n",
       "10           19      Campbelltown Farrow Rd North Car Park      256020TPR001  \n",
       "11            2                Kellyville Station Car Park     2155382CCP001  \n",
       "12           20  Campbelltown Hurley Street South Car Park       25602TPR002  \n",
       "13           21        Penrith Combewood At-Grade Car Park      275010TPR001  \n",
       "14           22     Penrith Combewood Multi-Level Car Park      275010TPR002  \n",
       "15           23                      Warwick Farm Car Park      217010TPR001  \n",
       "16           24                        Schofields Car Park      276220TPR001  \n",
       "17           25                 Hornsby Jersey St Car Park      207720TPR001  \n",
       "18           26                      Tallawong P1 Car Park     2155384TPR001  \n",
       "19           27                      Tallawong P2 Car Park     2155384TPR002  \n",
       "20           28                      Tallawong P3 Car Park     2155384TPR003  \n",
       "21           29                  Kellyville North Car Park     2155382TPR001  \n",
       "22            3               Bella Vista Station Car Park     2153478CCP001  \n",
       "23           30                  Kellyville South Car Park     2155382TPR002  \n",
       "24           31                       Bella Vista Car Park     2153478TPR001  \n",
       "25           32                  Hills Showground Car Park     2154392TPR001  \n",
       "26           33                       Cherrybrook Car Park     2126158TPR001  \n",
       "27            4          Hills Showground Station Car Park     2154392CCP001  \n",
       "28          486                          Ashfield Car Park      213110TPR001  \n",
       "29          487                           Kogarah Car Park      221710TPR001  \n",
       "30          488                       Seven Hills Car Park      214710TPR001  \n",
       "31          489                        Manly Vale Car Park     2093117TPR001  \n",
       "32          490                         Brookvale Car Park      210020TPR001  \n",
       "33            5               Cherrybrook Station Car Park     2126158CCP001  \n",
       "34            6             Gordon Henry St North Car Park      207210TPR001  \n",
       "35            7                             Kiama Car Park      253330TPR001  \n",
       "36            8                           Gosford Car Park      225040TPR001  \n",
       "37            9                           Revesby Car Park      221210TPR001  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Saving carpark details to file\n",
    "with open('./data/carpark_details.json', 'w') as f:\n",
    "  json.dump(carpark_details_array, f)\n",
    "\n",
    "# Reading as a dataframe\n",
    "df_carpark_details = pd.read_json('./data/carpark_details.json')\n",
    "df_carpark_details"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Deleting facility ids 486-490 as they will not be used. The source of the info indicates they contain inaccurate data for the columns that will be needed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tsn</th>\n",
       "      <th>time</th>\n",
       "      <th>spots</th>\n",
       "      <th>zones</th>\n",
       "      <th>ParkID</th>\n",
       "      <th>occupancy</th>\n",
       "      <th>MessageDate</th>\n",
       "      <th>facility_id</th>\n",
       "      <th>facility_name</th>\n",
       "      <th>tfnsw_facility_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2155384</td>\n",
       "      <td>742877319</td>\n",
       "      <td>1004</td>\n",
       "      <td>[{'spots': '152', 'zone_id': 'CPS-CUD1', 'occu...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '981', 'monthlies': No...</td>\n",
       "      <td>2023-07-17T12:48:39</td>\n",
       "      <td>1</td>\n",
       "      <td>Tallawong Station Car Park</td>\n",
       "      <td>2155384CCP001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2155382</td>\n",
       "      <td>742877319</td>\n",
       "      <td>1374</td>\n",
       "      <td>[{'spots': '368', 'zone_id': 'CPS-KVE1', 'occu...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '1363', 'monthlies': N...</td>\n",
       "      <td>2023-07-17T12:48:39</td>\n",
       "      <td>2</td>\n",
       "      <td>Kellyville Station Car Park</td>\n",
       "      <td>2155382CCP001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2153478</td>\n",
       "      <td>742877319</td>\n",
       "      <td>800</td>\n",
       "      <td>[{'spots': '800', 'zone_id': 'CPS-BLV', 'occup...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '314', 'monthlies': No...</td>\n",
       "      <td>2023-07-17T12:48:39</td>\n",
       "      <td>3</td>\n",
       "      <td>Bella Vista Station Car Park</td>\n",
       "      <td>2153478CCP001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>2154392</td>\n",
       "      <td>742877319</td>\n",
       "      <td>600</td>\n",
       "      <td>[{'spots': '600', 'zone_id': 'CPS-SHW', 'occup...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '532', 'monthlies': No...</td>\n",
       "      <td>2023-07-17T12:48:39</td>\n",
       "      <td>4</td>\n",
       "      <td>Hills Showground Station Car Park</td>\n",
       "      <td>2154392CCP001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>2126158</td>\n",
       "      <td>742877319</td>\n",
       "      <td>400</td>\n",
       "      <td>[{'spots': '400', 'zone_id': 'CPS-CHE', 'occup...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '400', 'monthlies': No...</td>\n",
       "      <td>2023-07-17T12:48:39</td>\n",
       "      <td>5</td>\n",
       "      <td>Cherrybrook Station Car Park</td>\n",
       "      <td>2126158CCP001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>207210</td>\n",
       "      <td>760523866</td>\n",
       "      <td>213</td>\n",
       "      <td>[{'spots': '213', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '25', 'monthlies': Non...</td>\n",
       "      <td>2024-02-06T19:37:46</td>\n",
       "      <td>6</td>\n",
       "      <td>Gordon Henry St North Car Park</td>\n",
       "      <td>207210TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>253330</td>\n",
       "      <td>760523985</td>\n",
       "      <td>42</td>\n",
       "      <td>[{'spots': '42', 'zone_id': '1', 'occupancy': ...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '-2', 'monthlies': Non...</td>\n",
       "      <td>2024-02-06T19:39:45</td>\n",
       "      <td>7</td>\n",
       "      <td>Kiama Car Park</td>\n",
       "      <td>253330TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>225040</td>\n",
       "      <td>760523776</td>\n",
       "      <td>1057</td>\n",
       "      <td>[{'spots': '1057', 'zone_id': '1', 'occupancy'...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '188', 'monthlies': No...</td>\n",
       "      <td>2024-02-06T19:36:16</td>\n",
       "      <td>8</td>\n",
       "      <td>Gosford Car Park</td>\n",
       "      <td>225040TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>221210</td>\n",
       "      <td>760523963</td>\n",
       "      <td>934</td>\n",
       "      <td>[{'spots': '934', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '322681', 'total': '98', 'monthlies':...</td>\n",
       "      <td>2024-02-06T19:39:23</td>\n",
       "      <td>9</td>\n",
       "      <td>Revesby Car Park</td>\n",
       "      <td>221210TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2101131</td>\n",
       "      <td>760523635</td>\n",
       "      <td>244</td>\n",
       "      <td>[{'spots': '244', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '60', 'monthlies': Non...</td>\n",
       "      <td>2024-02-06T19:33:55</td>\n",
       "      <td>10</td>\n",
       "      <td>Warriewood Car Park</td>\n",
       "      <td>2101131TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2101130</td>\n",
       "      <td>760523847</td>\n",
       "      <td>46</td>\n",
       "      <td>[{'spots': '46', 'zone_id': '1', 'occupancy': ...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '63981', 'total': '6', 'monthlies': N...</td>\n",
       "      <td>2024-02-06T19:37:27</td>\n",
       "      <td>11</td>\n",
       "      <td>Narrabeen Car Park</td>\n",
       "      <td>2101130TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2103108</td>\n",
       "      <td>760523782</td>\n",
       "      <td>68</td>\n",
       "      <td>[{'spots': '68', 'zone_id': '1', 'occupancy': ...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '37', 'monthlies': Non...</td>\n",
       "      <td>2024-02-06T19:36:22</td>\n",
       "      <td>12</td>\n",
       "      <td>Mona Vale Car Park</td>\n",
       "      <td>2103108TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2099207</td>\n",
       "      <td>760523886</td>\n",
       "      <td>117</td>\n",
       "      <td>[{'spots': '117', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '53474', 'total': '37', 'monthlies': ...</td>\n",
       "      <td>2024-02-06T19:38:06</td>\n",
       "      <td>13</td>\n",
       "      <td>Dee Why Car Park</td>\n",
       "      <td>2099207TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>211420</td>\n",
       "      <td>760523565</td>\n",
       "      <td>151</td>\n",
       "      <td>[{'spots': '151', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '228460', 'total': '23', 'monthlies':...</td>\n",
       "      <td>2024-02-06T19:32:45</td>\n",
       "      <td>14</td>\n",
       "      <td>West Ryde Car Park</td>\n",
       "      <td>211420TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>223210</td>\n",
       "      <td>760523415</td>\n",
       "      <td>373</td>\n",
       "      <td>[{'spots': '373', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '35', 'monthlies': Non...</td>\n",
       "      <td>2024-02-06T19:30:15</td>\n",
       "      <td>15</td>\n",
       "      <td>Sutherland East Parade Car Park</td>\n",
       "      <td>223210TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>217933</td>\n",
       "      <td>760523838</td>\n",
       "      <td>1884</td>\n",
       "      <td>[{'spots': '1884', 'zone_id': '1', 'occupancy'...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '811983', 'total': '312', 'monthlies'...</td>\n",
       "      <td>2024-02-06T19:37:18</td>\n",
       "      <td>16</td>\n",
       "      <td>Leppington Car Park</td>\n",
       "      <td>217933TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>217426</td>\n",
       "      <td>760523875</td>\n",
       "      <td>1429</td>\n",
       "      <td>[{'spots': '1429', 'zone_id': '1', 'occupancy'...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '742989', 'total': '108', 'monthlies'...</td>\n",
       "      <td>2024-02-06T19:37:55</td>\n",
       "      <td>17</td>\n",
       "      <td>Edmondson Park South Car Park</td>\n",
       "      <td>217426TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>276010</td>\n",
       "      <td>760523931</td>\n",
       "      <td>682</td>\n",
       "      <td>[{'spots': '682', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '107', 'monthlies': No...</td>\n",
       "      <td>2024-02-06T19:38:51</td>\n",
       "      <td>18</td>\n",
       "      <td>St Marys Car Park</td>\n",
       "      <td>276010TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>256020</td>\n",
       "      <td>760523930</td>\n",
       "      <td>68</td>\n",
       "      <td>[{'spots': '68', 'zone_id': '1', 'occupancy': ...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '147734', 'total': '33', 'monthlies':...</td>\n",
       "      <td>2024-02-06T19:38:50</td>\n",
       "      <td>19</td>\n",
       "      <td>Campbelltown Farrow Rd North Car Park</td>\n",
       "      <td>256020TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>256020</td>\n",
       "      <td>760523758</td>\n",
       "      <td>118</td>\n",
       "      <td>[{'spots': '118', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '178056', 'total': '33', 'monthlies':...</td>\n",
       "      <td>2024-02-06T19:35:58</td>\n",
       "      <td>20</td>\n",
       "      <td>Campbelltown Hurley Street South Car Park</td>\n",
       "      <td>25602TPR002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>275010</td>\n",
       "      <td>760523880</td>\n",
       "      <td>230</td>\n",
       "      <td>[{'spots': '230', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '74516', 'total': '19', 'monthlies': ...</td>\n",
       "      <td>2024-02-06T18:38:00</td>\n",
       "      <td>21</td>\n",
       "      <td>Penrith Combewood At-Grade Car Park</td>\n",
       "      <td>275010TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>275010</td>\n",
       "      <td>760523926</td>\n",
       "      <td>1144</td>\n",
       "      <td>[{'spots': '1144', 'zone_id': '1', 'occupancy'...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '522646', 'total': '91', 'monthlies':...</td>\n",
       "      <td>2024-02-06T18:38:46</td>\n",
       "      <td>22</td>\n",
       "      <td>Penrith Combewood Multi-Level Car Park</td>\n",
       "      <td>275010TPR002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>217010</td>\n",
       "      <td>760523792</td>\n",
       "      <td>910</td>\n",
       "      <td>[{'spots': '910', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '110', 'monthlies': No...</td>\n",
       "      <td>2024-02-06T19:36:32</td>\n",
       "      <td>23</td>\n",
       "      <td>Warwick Farm Car Park</td>\n",
       "      <td>217010TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>276220</td>\n",
       "      <td>760523939</td>\n",
       "      <td>700</td>\n",
       "      <td>[{'spots': '700', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '478766', 'total': '49', 'monthlies':...</td>\n",
       "      <td>2024-02-06T19:38:59</td>\n",
       "      <td>24</td>\n",
       "      <td>Schofields Car Park</td>\n",
       "      <td>276220TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>207720</td>\n",
       "      <td>760523683</td>\n",
       "      <td>145</td>\n",
       "      <td>[{'spots': '145', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '104953', 'total': '25', 'monthlies':...</td>\n",
       "      <td>2024-02-06T19:34:43</td>\n",
       "      <td>25</td>\n",
       "      <td>Hornsby Jersey St Car Park</td>\n",
       "      <td>207720TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2155384</td>\n",
       "      <td>760523850</td>\n",
       "      <td>121</td>\n",
       "      <td>[{'spots': '121', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '90929', 'total': '14', 'monthlies': ...</td>\n",
       "      <td>2024-02-06T19:37:30</td>\n",
       "      <td>26</td>\n",
       "      <td>Tallawong P1 Car Park</td>\n",
       "      <td>2155384TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2155384</td>\n",
       "      <td>760523907</td>\n",
       "      <td>455</td>\n",
       "      <td>[{'spots': '455', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '173680', 'total': '28', 'monthlies':...</td>\n",
       "      <td>2024-02-06T19:38:27</td>\n",
       "      <td>27</td>\n",
       "      <td>Tallawong P2 Car Park</td>\n",
       "      <td>2155384TPR002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2155384</td>\n",
       "      <td>760523862</td>\n",
       "      <td>397</td>\n",
       "      <td>[{'spots': '397', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '103032', 'total': '51', 'monthlies':...</td>\n",
       "      <td>2024-02-06T19:37:42</td>\n",
       "      <td>28</td>\n",
       "      <td>Tallawong P3 Car Park</td>\n",
       "      <td>2155384TPR003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2155382</td>\n",
       "      <td>760523894</td>\n",
       "      <td>351</td>\n",
       "      <td>[{'spots': '351', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '77329', 'total': '45', 'monthlies': ...</td>\n",
       "      <td>2024-02-06T19:38:14</td>\n",
       "      <td>29</td>\n",
       "      <td>Kellyville North Car Park</td>\n",
       "      <td>2155382TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2155382</td>\n",
       "      <td>760523751</td>\n",
       "      <td>964</td>\n",
       "      <td>[{'spots': '964', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '290767', 'total': '100', 'monthlies'...</td>\n",
       "      <td>2024-02-06T19:35:51</td>\n",
       "      <td>30</td>\n",
       "      <td>Kellyville South Car Park</td>\n",
       "      <td>2155382TPR002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2153478</td>\n",
       "      <td>760523891</td>\n",
       "      <td>777</td>\n",
       "      <td>[{'spots': '777', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '245560', 'total': '110', 'monthlies'...</td>\n",
       "      <td>2024-02-06T19:38:11</td>\n",
       "      <td>31</td>\n",
       "      <td>Bella Vista Car Park</td>\n",
       "      <td>2153478TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>2154392</td>\n",
       "      <td>760523962</td>\n",
       "      <td>584</td>\n",
       "      <td>[{'spots': '584', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '204073', 'total': '69', 'monthlies':...</td>\n",
       "      <td>2024-02-06T19:39:22</td>\n",
       "      <td>32</td>\n",
       "      <td>Hills Showground Car Park</td>\n",
       "      <td>2154392TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>2126158</td>\n",
       "      <td>760523931</td>\n",
       "      <td>384</td>\n",
       "      <td>[{'spots': '384', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '141861', 'total': '65', 'monthlies':...</td>\n",
       "      <td>2024-02-06T19:38:51</td>\n",
       "      <td>33</td>\n",
       "      <td>Cherrybrook Car Park</td>\n",
       "      <td>2126158TPR001</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        tsn       time  spots  \\\n",
       "0   2155384  742877319   1004   \n",
       "11  2155382  742877319   1374   \n",
       "22  2153478  742877319    800   \n",
       "27  2154392  742877319    600   \n",
       "28  2126158  742877319    400   \n",
       "29   207210  760523866    213   \n",
       "30   253330  760523985     42   \n",
       "31   225040  760523776   1057   \n",
       "32   221210  760523963    934   \n",
       "1   2101131  760523635    244   \n",
       "2   2101130  760523847     46   \n",
       "3   2103108  760523782     68   \n",
       "4   2099207  760523886    117   \n",
       "5    211420  760523565    151   \n",
       "6    223210  760523415    373   \n",
       "7    217933  760523838   1884   \n",
       "8    217426  760523875   1429   \n",
       "9    276010  760523931    682   \n",
       "10   256020  760523930     68   \n",
       "12   256020  760523758    118   \n",
       "13   275010  760523880    230   \n",
       "14   275010  760523926   1144   \n",
       "15   217010  760523792    910   \n",
       "16   276220  760523939    700   \n",
       "17   207720  760523683    145   \n",
       "18  2155384  760523850    121   \n",
       "19  2155384  760523907    455   \n",
       "20  2155384  760523862    397   \n",
       "21  2155382  760523894    351   \n",
       "23  2155382  760523751    964   \n",
       "24  2153478  760523891    777   \n",
       "25  2154392  760523962    584   \n",
       "26  2126158  760523931    384   \n",
       "\n",
       "                                                zones  ParkID  \\\n",
       "0   [{'spots': '152', 'zone_id': 'CPS-CUD1', 'occu...       1   \n",
       "11  [{'spots': '368', 'zone_id': 'CPS-KVE1', 'occu...       1   \n",
       "22  [{'spots': '800', 'zone_id': 'CPS-BLV', 'occup...       1   \n",
       "27  [{'spots': '600', 'zone_id': 'CPS-SHW', 'occup...       1   \n",
       "28  [{'spots': '400', 'zone_id': 'CPS-CHE', 'occup...       1   \n",
       "29  [{'spots': '213', 'zone_id': '1', 'occupancy':...       1   \n",
       "30  [{'spots': '42', 'zone_id': '1', 'occupancy': ...       1   \n",
       "31  [{'spots': '1057', 'zone_id': '1', 'occupancy'...       1   \n",
       "32  [{'spots': '934', 'zone_id': '1', 'occupancy':...       1   \n",
       "1   [{'spots': '244', 'zone_id': '1', 'occupancy':...       1   \n",
       "2   [{'spots': '46', 'zone_id': '1', 'occupancy': ...       1   \n",
       "3   [{'spots': '68', 'zone_id': '1', 'occupancy': ...       1   \n",
       "4   [{'spots': '117', 'zone_id': '1', 'occupancy':...       1   \n",
       "5   [{'spots': '151', 'zone_id': '1', 'occupancy':...       1   \n",
       "6   [{'spots': '373', 'zone_id': '1', 'occupancy':...       1   \n",
       "7   [{'spots': '1884', 'zone_id': '1', 'occupancy'...       1   \n",
       "8   [{'spots': '1429', 'zone_id': '1', 'occupancy'...       1   \n",
       "9   [{'spots': '682', 'zone_id': '1', 'occupancy':...       1   \n",
       "10  [{'spots': '68', 'zone_id': '1', 'occupancy': ...       1   \n",
       "12  [{'spots': '118', 'zone_id': '1', 'occupancy':...       1   \n",
       "13  [{'spots': '230', 'zone_id': '1', 'occupancy':...       1   \n",
       "14  [{'spots': '1144', 'zone_id': '1', 'occupancy'...       1   \n",
       "15  [{'spots': '910', 'zone_id': '1', 'occupancy':...       1   \n",
       "16  [{'spots': '700', 'zone_id': '1', 'occupancy':...       1   \n",
       "17  [{'spots': '145', 'zone_id': '1', 'occupancy':...       1   \n",
       "18  [{'spots': '121', 'zone_id': '1', 'occupancy':...       1   \n",
       "19  [{'spots': '455', 'zone_id': '1', 'occupancy':...       1   \n",
       "20  [{'spots': '397', 'zone_id': '1', 'occupancy':...       1   \n",
       "21  [{'spots': '351', 'zone_id': '1', 'occupancy':...       1   \n",
       "23  [{'spots': '964', 'zone_id': '1', 'occupancy':...       1   \n",
       "24  [{'spots': '777', 'zone_id': '1', 'occupancy':...       1   \n",
       "25  [{'spots': '584', 'zone_id': '1', 'occupancy':...       1   \n",
       "26  [{'spots': '384', 'zone_id': '1', 'occupancy':...       1   \n",
       "\n",
       "                                            occupancy          MessageDate  \\\n",
       "0   {'loop': None, 'total': '981', 'monthlies': No...  2023-07-17T12:48:39   \n",
       "11  {'loop': None, 'total': '1363', 'monthlies': N...  2023-07-17T12:48:39   \n",
       "22  {'loop': None, 'total': '314', 'monthlies': No...  2023-07-17T12:48:39   \n",
       "27  {'loop': None, 'total': '532', 'monthlies': No...  2023-07-17T12:48:39   \n",
       "28  {'loop': None, 'total': '400', 'monthlies': No...  2023-07-17T12:48:39   \n",
       "29  {'loop': None, 'total': '25', 'monthlies': Non...  2024-02-06T19:37:46   \n",
       "30  {'loop': None, 'total': '-2', 'monthlies': Non...  2024-02-06T19:39:45   \n",
       "31  {'loop': None, 'total': '188', 'monthlies': No...  2024-02-06T19:36:16   \n",
       "32  {'loop': '322681', 'total': '98', 'monthlies':...  2024-02-06T19:39:23   \n",
       "1   {'loop': None, 'total': '60', 'monthlies': Non...  2024-02-06T19:33:55   \n",
       "2   {'loop': '63981', 'total': '6', 'monthlies': N...  2024-02-06T19:37:27   \n",
       "3   {'loop': None, 'total': '37', 'monthlies': Non...  2024-02-06T19:36:22   \n",
       "4   {'loop': '53474', 'total': '37', 'monthlies': ...  2024-02-06T19:38:06   \n",
       "5   {'loop': '228460', 'total': '23', 'monthlies':...  2024-02-06T19:32:45   \n",
       "6   {'loop': None, 'total': '35', 'monthlies': Non...  2024-02-06T19:30:15   \n",
       "7   {'loop': '811983', 'total': '312', 'monthlies'...  2024-02-06T19:37:18   \n",
       "8   {'loop': '742989', 'total': '108', 'monthlies'...  2024-02-06T19:37:55   \n",
       "9   {'loop': None, 'total': '107', 'monthlies': No...  2024-02-06T19:38:51   \n",
       "10  {'loop': '147734', 'total': '33', 'monthlies':...  2024-02-06T19:38:50   \n",
       "12  {'loop': '178056', 'total': '33', 'monthlies':...  2024-02-06T19:35:58   \n",
       "13  {'loop': '74516', 'total': '19', 'monthlies': ...  2024-02-06T18:38:00   \n",
       "14  {'loop': '522646', 'total': '91', 'monthlies':...  2024-02-06T18:38:46   \n",
       "15  {'loop': None, 'total': '110', 'monthlies': No...  2024-02-06T19:36:32   \n",
       "16  {'loop': '478766', 'total': '49', 'monthlies':...  2024-02-06T19:38:59   \n",
       "17  {'loop': '104953', 'total': '25', 'monthlies':...  2024-02-06T19:34:43   \n",
       "18  {'loop': '90929', 'total': '14', 'monthlies': ...  2024-02-06T19:37:30   \n",
       "19  {'loop': '173680', 'total': '28', 'monthlies':...  2024-02-06T19:38:27   \n",
       "20  {'loop': '103032', 'total': '51', 'monthlies':...  2024-02-06T19:37:42   \n",
       "21  {'loop': '77329', 'total': '45', 'monthlies': ...  2024-02-06T19:38:14   \n",
       "23  {'loop': '290767', 'total': '100', 'monthlies'...  2024-02-06T19:35:51   \n",
       "24  {'loop': '245560', 'total': '110', 'monthlies'...  2024-02-06T19:38:11   \n",
       "25  {'loop': '204073', 'total': '69', 'monthlies':...  2024-02-06T19:39:22   \n",
       "26  {'loop': '141861', 'total': '65', 'monthlies':...  2024-02-06T19:38:51   \n",
       "\n",
       "    facility_id                              facility_name tfnsw_facility_id  \n",
       "0             1                 Tallawong Station Car Park     2155384CCP001  \n",
       "11            2                Kellyville Station Car Park     2155382CCP001  \n",
       "22            3               Bella Vista Station Car Park     2153478CCP001  \n",
       "27            4          Hills Showground Station Car Park     2154392CCP001  \n",
       "28            5               Cherrybrook Station Car Park     2126158CCP001  \n",
       "29            6             Gordon Henry St North Car Park      207210TPR001  \n",
       "30            7                             Kiama Car Park      253330TPR001  \n",
       "31            8                           Gosford Car Park      225040TPR001  \n",
       "32            9                           Revesby Car Park      221210TPR001  \n",
       "1            10                        Warriewood Car Park     2101131TPR001  \n",
       "2            11                         Narrabeen Car Park     2101130TPR001  \n",
       "3            12                         Mona Vale Car Park     2103108TPR001  \n",
       "4            13                           Dee Why Car Park     2099207TPR001  \n",
       "5            14                         West Ryde Car Park      211420TPR001  \n",
       "6            15            Sutherland East Parade Car Park      223210TPR001  \n",
       "7            16                        Leppington Car Park      217933TPR001  \n",
       "8            17              Edmondson Park South Car Park      217426TPR001  \n",
       "9            18                          St Marys Car Park      276010TPR001  \n",
       "10           19      Campbelltown Farrow Rd North Car Park      256020TPR001  \n",
       "12           20  Campbelltown Hurley Street South Car Park       25602TPR002  \n",
       "13           21        Penrith Combewood At-Grade Car Park      275010TPR001  \n",
       "14           22     Penrith Combewood Multi-Level Car Park      275010TPR002  \n",
       "15           23                      Warwick Farm Car Park      217010TPR001  \n",
       "16           24                        Schofields Car Park      276220TPR001  \n",
       "17           25                 Hornsby Jersey St Car Park      207720TPR001  \n",
       "18           26                      Tallawong P1 Car Park     2155384TPR001  \n",
       "19           27                      Tallawong P2 Car Park     2155384TPR002  \n",
       "20           28                      Tallawong P3 Car Park     2155384TPR003  \n",
       "21           29                  Kellyville North Car Park     2155382TPR001  \n",
       "23           30                  Kellyville South Car Park     2155382TPR002  \n",
       "24           31                       Bella Vista Car Park     2153478TPR001  \n",
       "25           32                  Hills Showground Car Park     2154392TPR001  \n",
       "26           33                       Cherrybrook Car Park     2126158TPR001  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Dropping rows 28,29,30,31,32\n",
    "df_carpark_details.drop(index=[28,29,30,31,32],inplace=True)\n",
    "\n",
    "# Resetting the index\n",
    "df_carpark_details.reset_index(drop=True,inplace=True)\n",
    "\n",
    "# Sorting by facility_id\n",
    "df_carpark_details.sort_values(by='facility_id',inplace=True)\n",
    "df_carpark_details"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Attempting to create a date_time function that gives the dates of all days in an array from 31st December 2023 to a target date that is separated by a time delta"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def date_getter(td):\n",
    "  # Array that stores the dates to be searched for\n",
    "  date_period_array = []\n",
    "  \n",
    "  # The last date to be searched for\n",
    "  cutoff_date = datetime(2023,12,31)\n",
    "  target_date = cutoff_date - td\n",
    "  \n",
    "  # Ensure that records of each day are obtained\n",
    "  delta = timedelta(days=1)\n",
    "  \n",
    "  while target_date <= cutoff_date:\n",
    "    date_period_array.append(target_date.strftime(\"%Y-%m-%d\"))\n",
    "    target_date += delta\n",
    "\n",
    "  return date_period_array"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "\n",
    "def carpark_history_period(facility, dates_array):\n",
    "    data_array = []\n",
    "    json_file_path = f\"./data/carpark_history/facility_{facility}.json\"\n",
    "    \n",
    "    # Request header\n",
    "    headers = {\n",
    "        \"Authorization\":f\"apikey {os.environ.get('apikey')}\"\n",
    "    }\n",
    "    \n",
    "    # Deleting file if it exists\n",
    "    if os.path.exists(json_file_path):\n",
    "        os.remove(json_file_path)\n",
    "    \n",
    "    # Make a request for each date\n",
    "    for date in dates_array:\n",
    "        url = f'https://api.transport.nsw.gov.au/v1/carpark/history?facility={facility}&eventdate={date}'\n",
    "    \n",
    "        response = requests.get(url, headers=headers).json()\n",
    "    \n",
    "        if data_array == []:\n",
    "            data_array = response\n",
    "        else:\n",
    "            data_array = data_array + response\n",
    "    \n",
    "    # Saving data to json file\n",
    "    with open(json_file_path, 'w') as f:\n",
    "        json.dump(data_array, f)\n",
    "\n",
    "    # Reading json file\n",
    "    with open(json_file_path) as f:\n",
    "        data = json.load(f)\n",
    "    \n",
    "    # Converting read data into a pandas dataframe\n",
    "    return pd.DataFrame(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# for key,row in df_carparks.iterrows():\n",
    "#   # Get the facility id\n",
    "#   facility = row['facility_id']\n",
    "  \n",
    "#   # Save file with carpark history for a month\n",
    "#   carpark_history_period(facility=facility, dates_array=date_getter(td=timedelta(days=30)))\n",
    "  \n",
    "#   # Feedback once done\n",
    "#   print(f\"Created file for facility {facility}\")\n",
    "\n",
    "# # df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Displaying facilities and their id's"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>facility_id</th>\n",
       "      <th>CarParkName</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Tallawong Station Car Park (historical only)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10</td>\n",
       "      <td>Warriewood Car Park</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>11</td>\n",
       "      <td>Narrabeen Car Park</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>12</td>\n",
       "      <td>Mona Vale Car Park</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>13</td>\n",
       "      <td>Dee Why Car Park</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>14</td>\n",
       "      <td>West Ryde Car Park</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>15</td>\n",
       "      <td>Sutherland East Parade Car Park</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>16</td>\n",
       "      <td>Leppington Car Park</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>17</td>\n",
       "      <td>Edmondson Park South Car Park</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>18</td>\n",
       "      <td>St Marys Car Park</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>19</td>\n",
       "      <td>Campbelltown Farrow Rd North Car Park</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2</td>\n",
       "      <td>Kellyville Station Car Park (historical only)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>20</td>\n",
       "      <td>Campbelltown Hurley Street South Car Park</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>21</td>\n",
       "      <td>Penrith Combewood At-Grade Car Park</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>22</td>\n",
       "      <td>Penrith Combewood Multi-Level Car Park</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>23</td>\n",
       "      <td>Warwick Farm Car Park</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>24</td>\n",
       "      <td>Schofields Car Park</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>25</td>\n",
       "      <td>Hornsby Jersey St Car Park</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>26</td>\n",
       "      <td>Tallawong P1 Car Park</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>27</td>\n",
       "      <td>Tallawong P2 Car Park</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>28</td>\n",
       "      <td>Tallawong P3 Car Park</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>29</td>\n",
       "      <td>Kellyville North Car Park</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>3</td>\n",
       "      <td>Bella Vista Station Car Park (historical only)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>30</td>\n",
       "      <td>Kellyville South Car Park</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>31</td>\n",
       "      <td>Bella Vista Car Park</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>32</td>\n",
       "      <td>Hills Showground Car Park</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>33</td>\n",
       "      <td>Cherrybrook Car Park</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>4</td>\n",
       "      <td>Hills Showground Station Car Park (historical ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>486</td>\n",
       "      <td>Ashfield Car Park</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>487</td>\n",
       "      <td>Kogarah Car Park</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>488</td>\n",
       "      <td>Seven Hills Car Park</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>489</td>\n",
       "      <td>Manly Vale Car Park</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>490</td>\n",
       "      <td>Brookvale Car Park</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>5</td>\n",
       "      <td>Cherrybrook Station Car Park (historical only)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>6</td>\n",
       "      <td>Gordon Henry St North Car Park</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>7</td>\n",
       "      <td>Kiama Car Park</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>8</td>\n",
       "      <td>Gosford Car Park</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>9</td>\n",
       "      <td>Revesby Car Park</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   facility_id                                        CarParkName\n",
       "0            1       Tallawong Station Car Park (historical only)\n",
       "1           10                                Warriewood Car Park\n",
       "2           11                                 Narrabeen Car Park\n",
       "3           12                                 Mona Vale Car Park\n",
       "4           13                                   Dee Why Car Park\n",
       "5           14                                 West Ryde Car Park\n",
       "6           15                    Sutherland East Parade Car Park\n",
       "7           16                                Leppington Car Park\n",
       "8           17                      Edmondson Park South Car Park\n",
       "9           18                                  St Marys Car Park\n",
       "10          19              Campbelltown Farrow Rd North Car Park\n",
       "11           2      Kellyville Station Car Park (historical only)\n",
       "12          20          Campbelltown Hurley Street South Car Park\n",
       "13          21                Penrith Combewood At-Grade Car Park\n",
       "14          22             Penrith Combewood Multi-Level Car Park\n",
       "15          23                              Warwick Farm Car Park\n",
       "16          24                                Schofields Car Park\n",
       "17          25                         Hornsby Jersey St Car Park\n",
       "18          26                              Tallawong P1 Car Park\n",
       "19          27                              Tallawong P2 Car Park\n",
       "20          28                              Tallawong P3 Car Park\n",
       "21          29                          Kellyville North Car Park\n",
       "22           3     Bella Vista Station Car Park (historical only)\n",
       "23          30                          Kellyville South Car Park\n",
       "24          31                               Bella Vista Car Park\n",
       "25          32                          Hills Showground Car Park\n",
       "26          33                               Cherrybrook Car Park\n",
       "27           4  Hills Showground Station Car Park (historical ...\n",
       "28         486                                  Ashfield Car Park\n",
       "29         487                                   Kogarah Car Park\n",
       "30         488                               Seven Hills Car Park\n",
       "31         489                                Manly Vale Car Park\n",
       "32         490                                 Brookvale Car Park\n",
       "33           5     Cherrybrook Station Car Park (historical only)\n",
       "34           6                     Gordon Henry St North Car Park\n",
       "35           7                                     Kiama Car Park\n",
       "36           8                                   Gosford Car Park\n",
       "37           9                                   Revesby Car Park"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_carparks"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Inspecting the `carpark_details.json` data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tsn</th>\n",
       "      <th>time</th>\n",
       "      <th>spots</th>\n",
       "      <th>zones</th>\n",
       "      <th>ParkID</th>\n",
       "      <th>occupancy</th>\n",
       "      <th>MessageDate</th>\n",
       "      <th>facility_id</th>\n",
       "      <th>facility_name</th>\n",
       "      <th>tfnsw_facility_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2155384</td>\n",
       "      <td>742877319</td>\n",
       "      <td>1004</td>\n",
       "      <td>[{'spots': '152', 'zone_id': 'CPS-CUD1', 'occu...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '981', 'monthlies': No...</td>\n",
       "      <td>2023-07-17T12:48:39</td>\n",
       "      <td>1</td>\n",
       "      <td>Tallawong Station Car Park</td>\n",
       "      <td>2155384CCP001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2101131</td>\n",
       "      <td>760523635</td>\n",
       "      <td>244</td>\n",
       "      <td>[{'spots': '244', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '60', 'monthlies': Non...</td>\n",
       "      <td>2024-02-06T19:33:55</td>\n",
       "      <td>10</td>\n",
       "      <td>Warriewood Car Park</td>\n",
       "      <td>2101131TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2101130</td>\n",
       "      <td>760523847</td>\n",
       "      <td>46</td>\n",
       "      <td>[{'spots': '46', 'zone_id': '1', 'occupancy': ...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '63981', 'total': '6', 'monthlies': N...</td>\n",
       "      <td>2024-02-06T19:37:27</td>\n",
       "      <td>11</td>\n",
       "      <td>Narrabeen Car Park</td>\n",
       "      <td>2101130TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2103108</td>\n",
       "      <td>760523782</td>\n",
       "      <td>68</td>\n",
       "      <td>[{'spots': '68', 'zone_id': '1', 'occupancy': ...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '37', 'monthlies': Non...</td>\n",
       "      <td>2024-02-06T19:36:22</td>\n",
       "      <td>12</td>\n",
       "      <td>Mona Vale Car Park</td>\n",
       "      <td>2103108TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2099207</td>\n",
       "      <td>760523886</td>\n",
       "      <td>117</td>\n",
       "      <td>[{'spots': '117', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '53474', 'total': '37', 'monthlies': ...</td>\n",
       "      <td>2024-02-06T19:38:06</td>\n",
       "      <td>13</td>\n",
       "      <td>Dee Why Car Park</td>\n",
       "      <td>2099207TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>211420</td>\n",
       "      <td>760523565</td>\n",
       "      <td>151</td>\n",
       "      <td>[{'spots': '151', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '228460', 'total': '23', 'monthlies':...</td>\n",
       "      <td>2024-02-06T19:32:45</td>\n",
       "      <td>14</td>\n",
       "      <td>West Ryde Car Park</td>\n",
       "      <td>211420TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>223210</td>\n",
       "      <td>760523415</td>\n",
       "      <td>373</td>\n",
       "      <td>[{'spots': '373', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '35', 'monthlies': Non...</td>\n",
       "      <td>2024-02-06T19:30:15</td>\n",
       "      <td>15</td>\n",
       "      <td>Sutherland East Parade Car Park</td>\n",
       "      <td>223210TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>217933</td>\n",
       "      <td>760523838</td>\n",
       "      <td>1884</td>\n",
       "      <td>[{'spots': '1884', 'zone_id': '1', 'occupancy'...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '811983', 'total': '312', 'monthlies'...</td>\n",
       "      <td>2024-02-06T19:37:18</td>\n",
       "      <td>16</td>\n",
       "      <td>Leppington Car Park</td>\n",
       "      <td>217933TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>217426</td>\n",
       "      <td>760523875</td>\n",
       "      <td>1429</td>\n",
       "      <td>[{'spots': '1429', 'zone_id': '1', 'occupancy'...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '742989', 'total': '108', 'monthlies'...</td>\n",
       "      <td>2024-02-06T19:37:55</td>\n",
       "      <td>17</td>\n",
       "      <td>Edmondson Park South Car Park</td>\n",
       "      <td>217426TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>276010</td>\n",
       "      <td>760523931</td>\n",
       "      <td>682</td>\n",
       "      <td>[{'spots': '682', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '107', 'monthlies': No...</td>\n",
       "      <td>2024-02-06T19:38:51</td>\n",
       "      <td>18</td>\n",
       "      <td>St Marys Car Park</td>\n",
       "      <td>276010TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>256020</td>\n",
       "      <td>760523930</td>\n",
       "      <td>68</td>\n",
       "      <td>[{'spots': '68', 'zone_id': '1', 'occupancy': ...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '147734', 'total': '33', 'monthlies':...</td>\n",
       "      <td>2024-02-06T19:38:50</td>\n",
       "      <td>19</td>\n",
       "      <td>Campbelltown Farrow Rd North Car Park</td>\n",
       "      <td>256020TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2155382</td>\n",
       "      <td>742877319</td>\n",
       "      <td>1374</td>\n",
       "      <td>[{'spots': '368', 'zone_id': 'CPS-KVE1', 'occu...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '1363', 'monthlies': N...</td>\n",
       "      <td>2023-07-17T12:48:39</td>\n",
       "      <td>2</td>\n",
       "      <td>Kellyville Station Car Park</td>\n",
       "      <td>2155382CCP001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>256020</td>\n",
       "      <td>760523758</td>\n",
       "      <td>118</td>\n",
       "      <td>[{'spots': '118', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '178056', 'total': '33', 'monthlies':...</td>\n",
       "      <td>2024-02-06T19:35:58</td>\n",
       "      <td>20</td>\n",
       "      <td>Campbelltown Hurley Street South Car Park</td>\n",
       "      <td>25602TPR002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>275010</td>\n",
       "      <td>760523880</td>\n",
       "      <td>230</td>\n",
       "      <td>[{'spots': '230', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '74516', 'total': '19', 'monthlies': ...</td>\n",
       "      <td>2024-02-06T18:38:00</td>\n",
       "      <td>21</td>\n",
       "      <td>Penrith Combewood At-Grade Car Park</td>\n",
       "      <td>275010TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>275010</td>\n",
       "      <td>760523926</td>\n",
       "      <td>1144</td>\n",
       "      <td>[{'spots': '1144', 'zone_id': '1', 'occupancy'...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '522646', 'total': '91', 'monthlies':...</td>\n",
       "      <td>2024-02-06T18:38:46</td>\n",
       "      <td>22</td>\n",
       "      <td>Penrith Combewood Multi-Level Car Park</td>\n",
       "      <td>275010TPR002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>217010</td>\n",
       "      <td>760523792</td>\n",
       "      <td>910</td>\n",
       "      <td>[{'spots': '910', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '110', 'monthlies': No...</td>\n",
       "      <td>2024-02-06T19:36:32</td>\n",
       "      <td>23</td>\n",
       "      <td>Warwick Farm Car Park</td>\n",
       "      <td>217010TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>276220</td>\n",
       "      <td>760523939</td>\n",
       "      <td>700</td>\n",
       "      <td>[{'spots': '700', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '478766', 'total': '49', 'monthlies':...</td>\n",
       "      <td>2024-02-06T19:38:59</td>\n",
       "      <td>24</td>\n",
       "      <td>Schofields Car Park</td>\n",
       "      <td>276220TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>207720</td>\n",
       "      <td>760523683</td>\n",
       "      <td>145</td>\n",
       "      <td>[{'spots': '145', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '104953', 'total': '25', 'monthlies':...</td>\n",
       "      <td>2024-02-06T19:34:43</td>\n",
       "      <td>25</td>\n",
       "      <td>Hornsby Jersey St Car Park</td>\n",
       "      <td>207720TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2155384</td>\n",
       "      <td>760523850</td>\n",
       "      <td>121</td>\n",
       "      <td>[{'spots': '121', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '90929', 'total': '14', 'monthlies': ...</td>\n",
       "      <td>2024-02-06T19:37:30</td>\n",
       "      <td>26</td>\n",
       "      <td>Tallawong P1 Car Park</td>\n",
       "      <td>2155384TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2155384</td>\n",
       "      <td>760523907</td>\n",
       "      <td>455</td>\n",
       "      <td>[{'spots': '455', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '173680', 'total': '28', 'monthlies':...</td>\n",
       "      <td>2024-02-06T19:38:27</td>\n",
       "      <td>27</td>\n",
       "      <td>Tallawong P2 Car Park</td>\n",
       "      <td>2155384TPR002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2155384</td>\n",
       "      <td>760523862</td>\n",
       "      <td>397</td>\n",
       "      <td>[{'spots': '397', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '103032', 'total': '51', 'monthlies':...</td>\n",
       "      <td>2024-02-06T19:37:42</td>\n",
       "      <td>28</td>\n",
       "      <td>Tallawong P3 Car Park</td>\n",
       "      <td>2155384TPR003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2155382</td>\n",
       "      <td>760523894</td>\n",
       "      <td>351</td>\n",
       "      <td>[{'spots': '351', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '77329', 'total': '45', 'monthlies': ...</td>\n",
       "      <td>2024-02-06T19:38:14</td>\n",
       "      <td>29</td>\n",
       "      <td>Kellyville North Car Park</td>\n",
       "      <td>2155382TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2153478</td>\n",
       "      <td>742877319</td>\n",
       "      <td>800</td>\n",
       "      <td>[{'spots': '800', 'zone_id': 'CPS-BLV', 'occup...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '314', 'monthlies': No...</td>\n",
       "      <td>2023-07-17T12:48:39</td>\n",
       "      <td>3</td>\n",
       "      <td>Bella Vista Station Car Park</td>\n",
       "      <td>2153478CCP001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2155382</td>\n",
       "      <td>760523751</td>\n",
       "      <td>964</td>\n",
       "      <td>[{'spots': '964', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '290767', 'total': '100', 'monthlies'...</td>\n",
       "      <td>2024-02-06T19:35:51</td>\n",
       "      <td>30</td>\n",
       "      <td>Kellyville South Car Park</td>\n",
       "      <td>2155382TPR002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2153478</td>\n",
       "      <td>760523891</td>\n",
       "      <td>777</td>\n",
       "      <td>[{'spots': '777', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '245560', 'total': '110', 'monthlies'...</td>\n",
       "      <td>2024-02-06T19:38:11</td>\n",
       "      <td>31</td>\n",
       "      <td>Bella Vista Car Park</td>\n",
       "      <td>2153478TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>2154392</td>\n",
       "      <td>760523962</td>\n",
       "      <td>584</td>\n",
       "      <td>[{'spots': '584', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '204073', 'total': '69', 'monthlies':...</td>\n",
       "      <td>2024-02-06T19:39:22</td>\n",
       "      <td>32</td>\n",
       "      <td>Hills Showground Car Park</td>\n",
       "      <td>2154392TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>2126158</td>\n",
       "      <td>760523931</td>\n",
       "      <td>384</td>\n",
       "      <td>[{'spots': '384', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '141861', 'total': '65', 'monthlies':...</td>\n",
       "      <td>2024-02-06T19:38:51</td>\n",
       "      <td>33</td>\n",
       "      <td>Cherrybrook Car Park</td>\n",
       "      <td>2126158TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>2154392</td>\n",
       "      <td>742877319</td>\n",
       "      <td>600</td>\n",
       "      <td>[{'spots': '600', 'zone_id': 'CPS-SHW', 'occup...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '532', 'monthlies': No...</td>\n",
       "      <td>2023-07-17T12:48:39</td>\n",
       "      <td>4</td>\n",
       "      <td>Hills Showground Station Car Park</td>\n",
       "      <td>2154392CCP001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>213110</td>\n",
       "      <td>760563564</td>\n",
       "      <td>228</td>\n",
       "      <td>[{'spots': '228', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '53', 'monthlies': '0'...</td>\n",
       "      <td>2024-02-06T19:39:24</td>\n",
       "      <td>486</td>\n",
       "      <td>Ashfield Car Park</td>\n",
       "      <td>213110TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>221710</td>\n",
       "      <td>760563536</td>\n",
       "      <td>259</td>\n",
       "      <td>[{'spots': '259', 'zone_id': '2', 'occupancy':...</td>\n",
       "      <td>3</td>\n",
       "      <td>{'loop': None, 'total': '29', 'monthlies': '0'...</td>\n",
       "      <td>2024-02-06T19:38:56</td>\n",
       "      <td>487</td>\n",
       "      <td>Kogarah Car Park</td>\n",
       "      <td>221710TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>214710</td>\n",
       "      <td>760563564</td>\n",
       "      <td>1613</td>\n",
       "      <td>[{'spots': '874', 'zone_id': '4', 'occupancy':...</td>\n",
       "      <td>4</td>\n",
       "      <td>{'loop': None, 'total': '152', 'monthlies': '0...</td>\n",
       "      <td>2024-02-06T19:39:24</td>\n",
       "      <td>488</td>\n",
       "      <td>Seven Hills Car Park</td>\n",
       "      <td>214710TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>2093117</td>\n",
       "      <td>760563408</td>\n",
       "      <td>142</td>\n",
       "      <td>[{'spots': '142', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '26', 'monthlies': '0'...</td>\n",
       "      <td>2024-02-06T19:36:48</td>\n",
       "      <td>489</td>\n",
       "      <td>Manly Vale Car Park</td>\n",
       "      <td>2093117TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>210020</td>\n",
       "      <td>760563578</td>\n",
       "      <td>246</td>\n",
       "      <td>[{'spots': '246', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '27', 'monthlies': '0'...</td>\n",
       "      <td>2024-02-06T19:39:38</td>\n",
       "      <td>490</td>\n",
       "      <td>Brookvale Car Park</td>\n",
       "      <td>210020TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>2126158</td>\n",
       "      <td>742877319</td>\n",
       "      <td>400</td>\n",
       "      <td>[{'spots': '400', 'zone_id': 'CPS-CHE', 'occup...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '400', 'monthlies': No...</td>\n",
       "      <td>2023-07-17T12:48:39</td>\n",
       "      <td>5</td>\n",
       "      <td>Cherrybrook Station Car Park</td>\n",
       "      <td>2126158CCP001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>207210</td>\n",
       "      <td>760523866</td>\n",
       "      <td>213</td>\n",
       "      <td>[{'spots': '213', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '25', 'monthlies': Non...</td>\n",
       "      <td>2024-02-06T19:37:46</td>\n",
       "      <td>6</td>\n",
       "      <td>Gordon Henry St North Car Park</td>\n",
       "      <td>207210TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>253330</td>\n",
       "      <td>760523985</td>\n",
       "      <td>42</td>\n",
       "      <td>[{'spots': '42', 'zone_id': '1', 'occupancy': ...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '-2', 'monthlies': Non...</td>\n",
       "      <td>2024-02-06T19:39:45</td>\n",
       "      <td>7</td>\n",
       "      <td>Kiama Car Park</td>\n",
       "      <td>253330TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>225040</td>\n",
       "      <td>760523776</td>\n",
       "      <td>1057</td>\n",
       "      <td>[{'spots': '1057', 'zone_id': '1', 'occupancy'...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '188', 'monthlies': No...</td>\n",
       "      <td>2024-02-06T19:36:16</td>\n",
       "      <td>8</td>\n",
       "      <td>Gosford Car Park</td>\n",
       "      <td>225040TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>221210</td>\n",
       "      <td>760523963</td>\n",
       "      <td>934</td>\n",
       "      <td>[{'spots': '934', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '322681', 'total': '98', 'monthlies':...</td>\n",
       "      <td>2024-02-06T19:39:23</td>\n",
       "      <td>9</td>\n",
       "      <td>Revesby Car Park</td>\n",
       "      <td>221210TPR001</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        tsn       time  spots  \\\n",
       "0   2155384  742877319   1004   \n",
       "1   2101131  760523635    244   \n",
       "2   2101130  760523847     46   \n",
       "3   2103108  760523782     68   \n",
       "4   2099207  760523886    117   \n",
       "5    211420  760523565    151   \n",
       "6    223210  760523415    373   \n",
       "7    217933  760523838   1884   \n",
       "8    217426  760523875   1429   \n",
       "9    276010  760523931    682   \n",
       "10   256020  760523930     68   \n",
       "11  2155382  742877319   1374   \n",
       "12   256020  760523758    118   \n",
       "13   275010  760523880    230   \n",
       "14   275010  760523926   1144   \n",
       "15   217010  760523792    910   \n",
       "16   276220  760523939    700   \n",
       "17   207720  760523683    145   \n",
       "18  2155384  760523850    121   \n",
       "19  2155384  760523907    455   \n",
       "20  2155384  760523862    397   \n",
       "21  2155382  760523894    351   \n",
       "22  2153478  742877319    800   \n",
       "23  2155382  760523751    964   \n",
       "24  2153478  760523891    777   \n",
       "25  2154392  760523962    584   \n",
       "26  2126158  760523931    384   \n",
       "27  2154392  742877319    600   \n",
       "28   213110  760563564    228   \n",
       "29   221710  760563536    259   \n",
       "30   214710  760563564   1613   \n",
       "31  2093117  760563408    142   \n",
       "32   210020  760563578    246   \n",
       "33  2126158  742877319    400   \n",
       "34   207210  760523866    213   \n",
       "35   253330  760523985     42   \n",
       "36   225040  760523776   1057   \n",
       "37   221210  760523963    934   \n",
       "\n",
       "                                                zones  ParkID  \\\n",
       "0   [{'spots': '152', 'zone_id': 'CPS-CUD1', 'occu...       1   \n",
       "1   [{'spots': '244', 'zone_id': '1', 'occupancy':...       1   \n",
       "2   [{'spots': '46', 'zone_id': '1', 'occupancy': ...       1   \n",
       "3   [{'spots': '68', 'zone_id': '1', 'occupancy': ...       1   \n",
       "4   [{'spots': '117', 'zone_id': '1', 'occupancy':...       1   \n",
       "5   [{'spots': '151', 'zone_id': '1', 'occupancy':...       1   \n",
       "6   [{'spots': '373', 'zone_id': '1', 'occupancy':...       1   \n",
       "7   [{'spots': '1884', 'zone_id': '1', 'occupancy'...       1   \n",
       "8   [{'spots': '1429', 'zone_id': '1', 'occupancy'...       1   \n",
       "9   [{'spots': '682', 'zone_id': '1', 'occupancy':...       1   \n",
       "10  [{'spots': '68', 'zone_id': '1', 'occupancy': ...       1   \n",
       "11  [{'spots': '368', 'zone_id': 'CPS-KVE1', 'occu...       1   \n",
       "12  [{'spots': '118', 'zone_id': '1', 'occupancy':...       1   \n",
       "13  [{'spots': '230', 'zone_id': '1', 'occupancy':...       1   \n",
       "14  [{'spots': '1144', 'zone_id': '1', 'occupancy'...       1   \n",
       "15  [{'spots': '910', 'zone_id': '1', 'occupancy':...       1   \n",
       "16  [{'spots': '700', 'zone_id': '1', 'occupancy':...       1   \n",
       "17  [{'spots': '145', 'zone_id': '1', 'occupancy':...       1   \n",
       "18  [{'spots': '121', 'zone_id': '1', 'occupancy':...       1   \n",
       "19  [{'spots': '455', 'zone_id': '1', 'occupancy':...       1   \n",
       "20  [{'spots': '397', 'zone_id': '1', 'occupancy':...       1   \n",
       "21  [{'spots': '351', 'zone_id': '1', 'occupancy':...       1   \n",
       "22  [{'spots': '800', 'zone_id': 'CPS-BLV', 'occup...       1   \n",
       "23  [{'spots': '964', 'zone_id': '1', 'occupancy':...       1   \n",
       "24  [{'spots': '777', 'zone_id': '1', 'occupancy':...       1   \n",
       "25  [{'spots': '584', 'zone_id': '1', 'occupancy':...       1   \n",
       "26  [{'spots': '384', 'zone_id': '1', 'occupancy':...       1   \n",
       "27  [{'spots': '600', 'zone_id': 'CPS-SHW', 'occup...       1   \n",
       "28  [{'spots': '228', 'zone_id': '1', 'occupancy':...       1   \n",
       "29  [{'spots': '259', 'zone_id': '2', 'occupancy':...       3   \n",
       "30  [{'spots': '874', 'zone_id': '4', 'occupancy':...       4   \n",
       "31  [{'spots': '142', 'zone_id': '1', 'occupancy':...       1   \n",
       "32  [{'spots': '246', 'zone_id': '1', 'occupancy':...       1   \n",
       "33  [{'spots': '400', 'zone_id': 'CPS-CHE', 'occup...       1   \n",
       "34  [{'spots': '213', 'zone_id': '1', 'occupancy':...       1   \n",
       "35  [{'spots': '42', 'zone_id': '1', 'occupancy': ...       1   \n",
       "36  [{'spots': '1057', 'zone_id': '1', 'occupancy'...       1   \n",
       "37  [{'spots': '934', 'zone_id': '1', 'occupancy':...       1   \n",
       "\n",
       "                                            occupancy          MessageDate  \\\n",
       "0   {'loop': None, 'total': '981', 'monthlies': No...  2023-07-17T12:48:39   \n",
       "1   {'loop': None, 'total': '60', 'monthlies': Non...  2024-02-06T19:33:55   \n",
       "2   {'loop': '63981', 'total': '6', 'monthlies': N...  2024-02-06T19:37:27   \n",
       "3   {'loop': None, 'total': '37', 'monthlies': Non...  2024-02-06T19:36:22   \n",
       "4   {'loop': '53474', 'total': '37', 'monthlies': ...  2024-02-06T19:38:06   \n",
       "5   {'loop': '228460', 'total': '23', 'monthlies':...  2024-02-06T19:32:45   \n",
       "6   {'loop': None, 'total': '35', 'monthlies': Non...  2024-02-06T19:30:15   \n",
       "7   {'loop': '811983', 'total': '312', 'monthlies'...  2024-02-06T19:37:18   \n",
       "8   {'loop': '742989', 'total': '108', 'monthlies'...  2024-02-06T19:37:55   \n",
       "9   {'loop': None, 'total': '107', 'monthlies': No...  2024-02-06T19:38:51   \n",
       "10  {'loop': '147734', 'total': '33', 'monthlies':...  2024-02-06T19:38:50   \n",
       "11  {'loop': None, 'total': '1363', 'monthlies': N...  2023-07-17T12:48:39   \n",
       "12  {'loop': '178056', 'total': '33', 'monthlies':...  2024-02-06T19:35:58   \n",
       "13  {'loop': '74516', 'total': '19', 'monthlies': ...  2024-02-06T18:38:00   \n",
       "14  {'loop': '522646', 'total': '91', 'monthlies':...  2024-02-06T18:38:46   \n",
       "15  {'loop': None, 'total': '110', 'monthlies': No...  2024-02-06T19:36:32   \n",
       "16  {'loop': '478766', 'total': '49', 'monthlies':...  2024-02-06T19:38:59   \n",
       "17  {'loop': '104953', 'total': '25', 'monthlies':...  2024-02-06T19:34:43   \n",
       "18  {'loop': '90929', 'total': '14', 'monthlies': ...  2024-02-06T19:37:30   \n",
       "19  {'loop': '173680', 'total': '28', 'monthlies':...  2024-02-06T19:38:27   \n",
       "20  {'loop': '103032', 'total': '51', 'monthlies':...  2024-02-06T19:37:42   \n",
       "21  {'loop': '77329', 'total': '45', 'monthlies': ...  2024-02-06T19:38:14   \n",
       "22  {'loop': None, 'total': '314', 'monthlies': No...  2023-07-17T12:48:39   \n",
       "23  {'loop': '290767', 'total': '100', 'monthlies'...  2024-02-06T19:35:51   \n",
       "24  {'loop': '245560', 'total': '110', 'monthlies'...  2024-02-06T19:38:11   \n",
       "25  {'loop': '204073', 'total': '69', 'monthlies':...  2024-02-06T19:39:22   \n",
       "26  {'loop': '141861', 'total': '65', 'monthlies':...  2024-02-06T19:38:51   \n",
       "27  {'loop': None, 'total': '532', 'monthlies': No...  2023-07-17T12:48:39   \n",
       "28  {'loop': None, 'total': '53', 'monthlies': '0'...  2024-02-06T19:39:24   \n",
       "29  {'loop': None, 'total': '29', 'monthlies': '0'...  2024-02-06T19:38:56   \n",
       "30  {'loop': None, 'total': '152', 'monthlies': '0...  2024-02-06T19:39:24   \n",
       "31  {'loop': None, 'total': '26', 'monthlies': '0'...  2024-02-06T19:36:48   \n",
       "32  {'loop': None, 'total': '27', 'monthlies': '0'...  2024-02-06T19:39:38   \n",
       "33  {'loop': None, 'total': '400', 'monthlies': No...  2023-07-17T12:48:39   \n",
       "34  {'loop': None, 'total': '25', 'monthlies': Non...  2024-02-06T19:37:46   \n",
       "35  {'loop': None, 'total': '-2', 'monthlies': Non...  2024-02-06T19:39:45   \n",
       "36  {'loop': None, 'total': '188', 'monthlies': No...  2024-02-06T19:36:16   \n",
       "37  {'loop': '322681', 'total': '98', 'monthlies':...  2024-02-06T19:39:23   \n",
       "\n",
       "    facility_id                              facility_name tfnsw_facility_id  \n",
       "0             1                 Tallawong Station Car Park     2155384CCP001  \n",
       "1            10                        Warriewood Car Park     2101131TPR001  \n",
       "2            11                         Narrabeen Car Park     2101130TPR001  \n",
       "3            12                         Mona Vale Car Park     2103108TPR001  \n",
       "4            13                           Dee Why Car Park     2099207TPR001  \n",
       "5            14                         West Ryde Car Park      211420TPR001  \n",
       "6            15            Sutherland East Parade Car Park      223210TPR001  \n",
       "7            16                        Leppington Car Park      217933TPR001  \n",
       "8            17              Edmondson Park South Car Park      217426TPR001  \n",
       "9            18                          St Marys Car Park      276010TPR001  \n",
       "10           19      Campbelltown Farrow Rd North Car Park      256020TPR001  \n",
       "11            2                Kellyville Station Car Park     2155382CCP001  \n",
       "12           20  Campbelltown Hurley Street South Car Park       25602TPR002  \n",
       "13           21        Penrith Combewood At-Grade Car Park      275010TPR001  \n",
       "14           22     Penrith Combewood Multi-Level Car Park      275010TPR002  \n",
       "15           23                      Warwick Farm Car Park      217010TPR001  \n",
       "16           24                        Schofields Car Park      276220TPR001  \n",
       "17           25                 Hornsby Jersey St Car Park      207720TPR001  \n",
       "18           26                      Tallawong P1 Car Park     2155384TPR001  \n",
       "19           27                      Tallawong P2 Car Park     2155384TPR002  \n",
       "20           28                      Tallawong P3 Car Park     2155384TPR003  \n",
       "21           29                  Kellyville North Car Park     2155382TPR001  \n",
       "22            3               Bella Vista Station Car Park     2153478CCP001  \n",
       "23           30                  Kellyville South Car Park     2155382TPR002  \n",
       "24           31                       Bella Vista Car Park     2153478TPR001  \n",
       "25           32                  Hills Showground Car Park     2154392TPR001  \n",
       "26           33                       Cherrybrook Car Park     2126158TPR001  \n",
       "27            4          Hills Showground Station Car Park     2154392CCP001  \n",
       "28          486                          Ashfield Car Park      213110TPR001  \n",
       "29          487                           Kogarah Car Park      221710TPR001  \n",
       "30          488                       Seven Hills Car Park      214710TPR001  \n",
       "31          489                        Manly Vale Car Park     2093117TPR001  \n",
       "32          490                         Brookvale Car Park      210020TPR001  \n",
       "33            5               Cherrybrook Station Car Park     2126158CCP001  \n",
       "34            6             Gordon Henry St North Car Park      207210TPR001  \n",
       "35            7                             Kiama Car Park      253330TPR001  \n",
       "36            8                           Gosford Car Park      225040TPR001  \n",
       "37            9                           Revesby Car Park      221210TPR001  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "park_details = pd.read_json(\"data/carpark_details.json\")\n",
    "park_details.head(38)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 38 entries, 0 to 37\n",
      "Data columns (total 10 columns):\n",
      " #   Column             Non-Null Count  Dtype \n",
      "---  ------             --------------  ----- \n",
      " 0   tsn                38 non-null     int64 \n",
      " 1   time               38 non-null     int64 \n",
      " 2   spots              38 non-null     int64 \n",
      " 3   zones              38 non-null     object\n",
      " 4   ParkID             38 non-null     int64 \n",
      " 5   occupancy          38 non-null     object\n",
      " 6   MessageDate        38 non-null     object\n",
      " 7   facility_id        38 non-null     int64 \n",
      " 8   facility_name      38 non-null     object\n",
      " 9   tfnsw_facility_id  38 non-null     object\n",
      "dtypes: int64(5), object(5)\n",
      "memory usage: 3.1+ KB\n"
     ]
    }
   ],
   "source": [
    "park_details.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "inspecting the `carparks.json` dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Tallawong Station Car Park (historical only)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Warriewood Car Park</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Narrabeen Car Park</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Mona Vale Car Park</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Dee Why Car Park</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                               0\n",
       "1   Tallawong Station Car Park (historical only)\n",
       "10                           Warriewood Car Park\n",
       "11                            Narrabeen Car Park\n",
       "12                            Mona Vale Car Park\n",
       "13                              Dee Why Car Park"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "carparks = pd.read_json(\"data/carparks.json\", orient= \"index\")\n",
    "carparks.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 38 entries, 1 to 9\n",
      "Data columns (total 1 columns):\n",
      " #   Column  Non-Null Count  Dtype \n",
      "---  ------  --------------  ----- \n",
      " 0   0       38 non-null     object\n",
      "dtypes: object(1)\n",
      "memory usage: 608.0+ bytes\n"
     ]
    }
   ],
   "source": [
    "carparks.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "inspecting the `NSW response.json` file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tsn</th>\n",
       "      <th>time</th>\n",
       "      <th>spots</th>\n",
       "      <th>zones</th>\n",
       "      <th>ParkID</th>\n",
       "      <th>occupancy</th>\n",
       "      <th>MessageDate</th>\n",
       "      <th>facility_id</th>\n",
       "      <th>facility_name</th>\n",
       "      <th>tfnsw_facility_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>211420</td>\n",
       "      <td>700405713</td>\n",
       "      <td>151</td>\n",
       "      <td>[{'spots': '151', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '28302', 'total': '2', 'monthlies': N...</td>\n",
       "      <td>2022-03-13T00:08:33</td>\n",
       "      <td>14</td>\n",
       "      <td>West Ryde Car Park</td>\n",
       "      <td>211420TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>211420</td>\n",
       "      <td>700406314</td>\n",
       "      <td>151</td>\n",
       "      <td>[{'spots': '151', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '28302', 'total': '2', 'monthlies': N...</td>\n",
       "      <td>2022-03-13T00:18:34</td>\n",
       "      <td>14</td>\n",
       "      <td>West Ryde Car Park</td>\n",
       "      <td>211420TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>211420</td>\n",
       "      <td>700406916</td>\n",
       "      <td>151</td>\n",
       "      <td>[{'spots': '151', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '28302', 'total': '2', 'monthlies': N...</td>\n",
       "      <td>2022-03-13T00:28:36</td>\n",
       "      <td>14</td>\n",
       "      <td>West Ryde Car Park</td>\n",
       "      <td>211420TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>211420</td>\n",
       "      <td>700407517</td>\n",
       "      <td>151</td>\n",
       "      <td>[{'spots': '151', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '28302', 'total': '2', 'monthlies': N...</td>\n",
       "      <td>2022-03-13T00:38:37</td>\n",
       "      <td>14</td>\n",
       "      <td>West Ryde Car Park</td>\n",
       "      <td>211420TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>211420</td>\n",
       "      <td>700408119</td>\n",
       "      <td>151</td>\n",
       "      <td>[{'spots': '151', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '28302', 'total': '2', 'monthlies': N...</td>\n",
       "      <td>2022-03-13T00:48:39</td>\n",
       "      <td>14</td>\n",
       "      <td>West Ryde Car Park</td>\n",
       "      <td>211420TPR001</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      tsn       time  spots  \\\n",
       "0  211420  700405713    151   \n",
       "1  211420  700406314    151   \n",
       "2  211420  700406916    151   \n",
       "3  211420  700407517    151   \n",
       "4  211420  700408119    151   \n",
       "\n",
       "                                               zones  ParkID  \\\n",
       "0  [{'spots': '151', 'zone_id': '1', 'occupancy':...       1   \n",
       "1  [{'spots': '151', 'zone_id': '1', 'occupancy':...       1   \n",
       "2  [{'spots': '151', 'zone_id': '1', 'occupancy':...       1   \n",
       "3  [{'spots': '151', 'zone_id': '1', 'occupancy':...       1   \n",
       "4  [{'spots': '151', 'zone_id': '1', 'occupancy':...       1   \n",
       "\n",
       "                                           occupancy          MessageDate  \\\n",
       "0  {'loop': '28302', 'total': '2', 'monthlies': N...  2022-03-13T00:08:33   \n",
       "1  {'loop': '28302', 'total': '2', 'monthlies': N...  2022-03-13T00:18:34   \n",
       "2  {'loop': '28302', 'total': '2', 'monthlies': N...  2022-03-13T00:28:36   \n",
       "3  {'loop': '28302', 'total': '2', 'monthlies': N...  2022-03-13T00:38:37   \n",
       "4  {'loop': '28302', 'total': '2', 'monthlies': N...  2022-03-13T00:48:39   \n",
       "\n",
       "   facility_id       facility_name tfnsw_facility_id  \n",
       "0           14  West Ryde Car Park      211420TPR001  \n",
       "1           14  West Ryde Car Park      211420TPR001  \n",
       "2           14  West Ryde Car Park      211420TPR001  \n",
       "3           14  West Ryde Car Park      211420TPR001  \n",
       "4           14  West Ryde Car Park      211420TPR001  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nsw_response = pd.read_json(\"data/NSW response - 2022-03-13.json\")\n",
    "nsw_response.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 191 entries, 0 to 190\n",
      "Data columns (total 10 columns):\n",
      " #   Column             Non-Null Count  Dtype \n",
      "---  ------             --------------  ----- \n",
      " 0   tsn                191 non-null    int64 \n",
      " 1   time               191 non-null    int64 \n",
      " 2   spots              191 non-null    int64 \n",
      " 3   zones              191 non-null    object\n",
      " 4   ParkID             191 non-null    int64 \n",
      " 5   occupancy          191 non-null    object\n",
      " 6   MessageDate        191 non-null    object\n",
      " 7   facility_id        191 non-null    int64 \n",
      " 8   facility_name      191 non-null    object\n",
      " 9   tfnsw_facility_id  191 non-null    object\n",
      "dtypes: int64(5), object(5)\n",
      "memory usage: 15.1+ KB\n"
     ]
    }
   ],
   "source": [
    "nsw_response.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tsn</th>\n",
       "      <th>time</th>\n",
       "      <th>spots</th>\n",
       "      <th>zones</th>\n",
       "      <th>ParkID</th>\n",
       "      <th>occupancy</th>\n",
       "      <th>MessageDate</th>\n",
       "      <th>facility_id</th>\n",
       "      <th>facility_name</th>\n",
       "      <th>tfnsw_facility_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>223210</td>\n",
       "      <td>754664452</td>\n",
       "      <td>373</td>\n",
       "      <td>[{'spots': '373', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '16', 'monthlies': Non...</td>\n",
       "      <td>2023-12-01T00:00:52</td>\n",
       "      <td>15</td>\n",
       "      <td>Sutherland East Parade Car Park</td>\n",
       "      <td>223210TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>223210</td>\n",
       "      <td>754665189</td>\n",
       "      <td>373</td>\n",
       "      <td>[{'spots': '373', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '15', 'monthlies': Non...</td>\n",
       "      <td>2023-12-01T00:13:09</td>\n",
       "      <td>15</td>\n",
       "      <td>Sutherland East Parade Car Park</td>\n",
       "      <td>223210TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>223210</td>\n",
       "      <td>754665355</td>\n",
       "      <td>373</td>\n",
       "      <td>[{'spots': '373', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '14', 'monthlies': Non...</td>\n",
       "      <td>2023-12-01T00:15:55</td>\n",
       "      <td>15</td>\n",
       "      <td>Sutherland East Parade Car Park</td>\n",
       "      <td>223210TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>223210</td>\n",
       "      <td>754665706</td>\n",
       "      <td>373</td>\n",
       "      <td>[{'spots': '373', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '13', 'monthlies': Non...</td>\n",
       "      <td>2023-12-01T00:21:46</td>\n",
       "      <td>15</td>\n",
       "      <td>Sutherland East Parade Car Park</td>\n",
       "      <td>223210TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>223210</td>\n",
       "      <td>754665740</td>\n",
       "      <td>373</td>\n",
       "      <td>[{'spots': '373', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '12', 'monthlies': Non...</td>\n",
       "      <td>2023-12-01T00:22:20</td>\n",
       "      <td>15</td>\n",
       "      <td>Sutherland East Parade Car Park</td>\n",
       "      <td>223210TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18470</th>\n",
       "      <td>223210</td>\n",
       "      <td>757341099</td>\n",
       "      <td>373</td>\n",
       "      <td>[{'spots': '373', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '98', 'monthlies': Non...</td>\n",
       "      <td>2023-12-31T23:31:39</td>\n",
       "      <td>15</td>\n",
       "      <td>Sutherland East Parade Car Park</td>\n",
       "      <td>223210TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18471</th>\n",
       "      <td>223210</td>\n",
       "      <td>757341147</td>\n",
       "      <td>373</td>\n",
       "      <td>[{'spots': '373', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '97', 'monthlies': Non...</td>\n",
       "      <td>2023-12-31T23:32:27</td>\n",
       "      <td>15</td>\n",
       "      <td>Sutherland East Parade Car Park</td>\n",
       "      <td>223210TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18472</th>\n",
       "      <td>223210</td>\n",
       "      <td>757341211</td>\n",
       "      <td>373</td>\n",
       "      <td>[{'spots': '373', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '96', 'monthlies': Non...</td>\n",
       "      <td>2023-12-31T23:33:31</td>\n",
       "      <td>15</td>\n",
       "      <td>Sutherland East Parade Car Park</td>\n",
       "      <td>223210TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18473</th>\n",
       "      <td>223210</td>\n",
       "      <td>757341343</td>\n",
       "      <td>373</td>\n",
       "      <td>[{'spots': '373', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '95', 'monthlies': Non...</td>\n",
       "      <td>2023-12-31T23:35:43</td>\n",
       "      <td>15</td>\n",
       "      <td>Sutherland East Parade Car Park</td>\n",
       "      <td>223210TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18474</th>\n",
       "      <td>223210</td>\n",
       "      <td>757342603</td>\n",
       "      <td>373</td>\n",
       "      <td>[{'spots': '373', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '94', 'monthlies': Non...</td>\n",
       "      <td>2023-12-31T23:56:43</td>\n",
       "      <td>15</td>\n",
       "      <td>Sutherland East Parade Car Park</td>\n",
       "      <td>223210TPR001</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>18475 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          tsn       time  spots  \\\n",
       "0      223210  754664452    373   \n",
       "1      223210  754665189    373   \n",
       "2      223210  754665355    373   \n",
       "3      223210  754665706    373   \n",
       "4      223210  754665740    373   \n",
       "...       ...        ...    ...   \n",
       "18470  223210  757341099    373   \n",
       "18471  223210  757341147    373   \n",
       "18472  223210  757341211    373   \n",
       "18473  223210  757341343    373   \n",
       "18474  223210  757342603    373   \n",
       "\n",
       "                                                   zones  ParkID  \\\n",
       "0      [{'spots': '373', 'zone_id': '1', 'occupancy':...       1   \n",
       "1      [{'spots': '373', 'zone_id': '1', 'occupancy':...       1   \n",
       "2      [{'spots': '373', 'zone_id': '1', 'occupancy':...       1   \n",
       "3      [{'spots': '373', 'zone_id': '1', 'occupancy':...       1   \n",
       "4      [{'spots': '373', 'zone_id': '1', 'occupancy':...       1   \n",
       "...                                                  ...     ...   \n",
       "18470  [{'spots': '373', 'zone_id': '1', 'occupancy':...       1   \n",
       "18471  [{'spots': '373', 'zone_id': '1', 'occupancy':...       1   \n",
       "18472  [{'spots': '373', 'zone_id': '1', 'occupancy':...       1   \n",
       "18473  [{'spots': '373', 'zone_id': '1', 'occupancy':...       1   \n",
       "18474  [{'spots': '373', 'zone_id': '1', 'occupancy':...       1   \n",
       "\n",
       "                                               occupancy          MessageDate  \\\n",
       "0      {'loop': None, 'total': '16', 'monthlies': Non...  2023-12-01T00:00:52   \n",
       "1      {'loop': None, 'total': '15', 'monthlies': Non...  2023-12-01T00:13:09   \n",
       "2      {'loop': None, 'total': '14', 'monthlies': Non...  2023-12-01T00:15:55   \n",
       "3      {'loop': None, 'total': '13', 'monthlies': Non...  2023-12-01T00:21:46   \n",
       "4      {'loop': None, 'total': '12', 'monthlies': Non...  2023-12-01T00:22:20   \n",
       "...                                                  ...                  ...   \n",
       "18470  {'loop': None, 'total': '98', 'monthlies': Non...  2023-12-31T23:31:39   \n",
       "18471  {'loop': None, 'total': '97', 'monthlies': Non...  2023-12-31T23:32:27   \n",
       "18472  {'loop': None, 'total': '96', 'monthlies': Non...  2023-12-31T23:33:31   \n",
       "18473  {'loop': None, 'total': '95', 'monthlies': Non...  2023-12-31T23:35:43   \n",
       "18474  {'loop': None, 'total': '94', 'monthlies': Non...  2023-12-31T23:56:43   \n",
       "\n",
       "       facility_id                    facility_name tfnsw_facility_id  \n",
       "0               15  Sutherland East Parade Car Park      223210TPR001  \n",
       "1               15  Sutherland East Parade Car Park      223210TPR001  \n",
       "2               15  Sutherland East Parade Car Park      223210TPR001  \n",
       "3               15  Sutherland East Parade Car Park      223210TPR001  \n",
       "4               15  Sutherland East Parade Car Park      223210TPR001  \n",
       "...            ...                              ...               ...  \n",
       "18470           15  Sutherland East Parade Car Park      223210TPR001  \n",
       "18471           15  Sutherland East Parade Car Park      223210TPR001  \n",
       "18472           15  Sutherland East Parade Car Park      223210TPR001  \n",
       "18473           15  Sutherland East Parade Car Park      223210TPR001  \n",
       "18474           15  Sutherland East Parade Car Park      223210TPR001  \n",
       "\n",
       "[18475 rows x 10 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "_park = pd.read_json(\"data/carpark_history/facility_15.json\")\n",
    "_park"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tsn</th>\n",
       "      <th>time</th>\n",
       "      <th>spots</th>\n",
       "      <th>ParkID</th>\n",
       "      <th>facility_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>18475.0</td>\n",
       "      <td>1.847500e+04</td>\n",
       "      <td>18475.0</td>\n",
       "      <td>18475.0</td>\n",
       "      <td>18475.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>223210.0</td>\n",
       "      <td>7.558284e+08</td>\n",
       "      <td>373.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.0</td>\n",
       "      <td>7.040404e+05</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>223210.0</td>\n",
       "      <td>7.546645e+08</td>\n",
       "      <td>373.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>223210.0</td>\n",
       "      <td>7.552248e+08</td>\n",
       "      <td>373.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>223210.0</td>\n",
       "      <td>7.557671e+08</td>\n",
       "      <td>373.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>223210.0</td>\n",
       "      <td>7.563410e+08</td>\n",
       "      <td>373.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>223210.0</td>\n",
       "      <td>7.573426e+08</td>\n",
       "      <td>373.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            tsn          time    spots   ParkID  facility_id\n",
       "count   18475.0  1.847500e+04  18475.0  18475.0      18475.0\n",
       "mean   223210.0  7.558284e+08    373.0      1.0         15.0\n",
       "std         0.0  7.040404e+05      0.0      0.0          0.0\n",
       "min    223210.0  7.546645e+08    373.0      1.0         15.0\n",
       "25%    223210.0  7.552248e+08    373.0      1.0         15.0\n",
       "50%    223210.0  7.557671e+08    373.0      1.0         15.0\n",
       "75%    223210.0  7.563410e+08    373.0      1.0         15.0\n",
       "max    223210.0  7.573426e+08    373.0      1.0         15.0"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "_park.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tsn</th>\n",
       "      <th>time</th>\n",
       "      <th>spots</th>\n",
       "      <th>zones</th>\n",
       "      <th>ParkID</th>\n",
       "      <th>MessageDate</th>\n",
       "      <th>facility_id</th>\n",
       "      <th>facility_name</th>\n",
       "      <th>tfnsw_facility_id</th>\n",
       "      <th>occupancy.loop</th>\n",
       "      <th>occupancy.total</th>\n",
       "      <th>occupancy.monthlies</th>\n",
       "      <th>occupancy.open_gate</th>\n",
       "      <th>occupancy.transients</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>253330</td>\n",
       "      <td>754680376</td>\n",
       "      <td>42</td>\n",
       "      <td>[{'spots': '42', 'zone_id': '1', 'occupancy': ...</td>\n",
       "      <td>1</td>\n",
       "      <td>2023-12-01T04:26:16</td>\n",
       "      <td>7</td>\n",
       "      <td>Kiama Car Park</td>\n",
       "      <td>253330TPR001</td>\n",
       "      <td>None</td>\n",
       "      <td>5</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>253330</td>\n",
       "      <td>754683734</td>\n",
       "      <td>42</td>\n",
       "      <td>[{'spots': '42', 'zone_id': '1', 'occupancy': ...</td>\n",
       "      <td>1</td>\n",
       "      <td>2023-12-01T05:22:14</td>\n",
       "      <td>7</td>\n",
       "      <td>Kiama Car Park</td>\n",
       "      <td>253330TPR001</td>\n",
       "      <td>None</td>\n",
       "      <td>7</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>253330</td>\n",
       "      <td>754687723</td>\n",
       "      <td>42</td>\n",
       "      <td>[{'spots': '42', 'zone_id': '1', 'occupancy': ...</td>\n",
       "      <td>1</td>\n",
       "      <td>2023-12-01T06:28:43</td>\n",
       "      <td>7</td>\n",
       "      <td>Kiama Car Park</td>\n",
       "      <td>253330TPR001</td>\n",
       "      <td>None</td>\n",
       "      <td>8</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>253330</td>\n",
       "      <td>754688235</td>\n",
       "      <td>42</td>\n",
       "      <td>[{'spots': '42', 'zone_id': '1', 'occupancy': ...</td>\n",
       "      <td>1</td>\n",
       "      <td>2023-12-01T06:37:15</td>\n",
       "      <td>7</td>\n",
       "      <td>Kiama Car Park</td>\n",
       "      <td>253330TPR001</td>\n",
       "      <td>None</td>\n",
       "      <td>9</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>253330</td>\n",
       "      <td>754693058</td>\n",
       "      <td>42</td>\n",
       "      <td>[{'spots': '42', 'zone_id': '1', 'occupancy': ...</td>\n",
       "      <td>1</td>\n",
       "      <td>2023-12-01T07:57:38</td>\n",
       "      <td>7</td>\n",
       "      <td>Kiama Car Park</td>\n",
       "      <td>253330TPR001</td>\n",
       "      <td>None</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>701</th>\n",
       "      <td>253330</td>\n",
       "      <td>757335433</td>\n",
       "      <td>42</td>\n",
       "      <td>[{'spots': '42', 'zone_id': '1', 'occupancy': ...</td>\n",
       "      <td>1</td>\n",
       "      <td>2023-12-31T21:57:13</td>\n",
       "      <td>7</td>\n",
       "      <td>Kiama Car Park</td>\n",
       "      <td>253330TPR001</td>\n",
       "      <td>None</td>\n",
       "      <td>17</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>702</th>\n",
       "      <td>253330</td>\n",
       "      <td>757335453</td>\n",
       "      <td>42</td>\n",
       "      <td>[{'spots': '42', 'zone_id': '1', 'occupancy': ...</td>\n",
       "      <td>1</td>\n",
       "      <td>2023-12-31T21:57:33</td>\n",
       "      <td>7</td>\n",
       "      <td>Kiama Car Park</td>\n",
       "      <td>253330TPR001</td>\n",
       "      <td>None</td>\n",
       "      <td>16</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>703</th>\n",
       "      <td>253330</td>\n",
       "      <td>757336142</td>\n",
       "      <td>42</td>\n",
       "      <td>[{'spots': '42', 'zone_id': '1', 'occupancy': ...</td>\n",
       "      <td>1</td>\n",
       "      <td>2023-12-31T22:09:02</td>\n",
       "      <td>7</td>\n",
       "      <td>Kiama Car Park</td>\n",
       "      <td>253330TPR001</td>\n",
       "      <td>None</td>\n",
       "      <td>14</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>704</th>\n",
       "      <td>253330</td>\n",
       "      <td>757336173</td>\n",
       "      <td>42</td>\n",
       "      <td>[{'spots': '42', 'zone_id': '1', 'occupancy': ...</td>\n",
       "      <td>1</td>\n",
       "      <td>2023-12-31T22:09:33</td>\n",
       "      <td>7</td>\n",
       "      <td>Kiama Car Park</td>\n",
       "      <td>253330TPR001</td>\n",
       "      <td>None</td>\n",
       "      <td>13</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>705</th>\n",
       "      <td>253330</td>\n",
       "      <td>757337708</td>\n",
       "      <td>42</td>\n",
       "      <td>[{'spots': '42', 'zone_id': '1', 'occupancy': ...</td>\n",
       "      <td>1</td>\n",
       "      <td>2023-12-31T22:35:08</td>\n",
       "      <td>7</td>\n",
       "      <td>Kiama Car Park</td>\n",
       "      <td>253330TPR001</td>\n",
       "      <td>None</td>\n",
       "      <td>11</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>706 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        tsn       time spots  \\\n",
       "0    253330  754680376    42   \n",
       "1    253330  754683734    42   \n",
       "2    253330  754687723    42   \n",
       "3    253330  754688235    42   \n",
       "4    253330  754693058    42   \n",
       "..      ...        ...   ...   \n",
       "701  253330  757335433    42   \n",
       "702  253330  757335453    42   \n",
       "703  253330  757336142    42   \n",
       "704  253330  757336173    42   \n",
       "705  253330  757337708    42   \n",
       "\n",
       "                                                 zones ParkID  \\\n",
       "0    [{'spots': '42', 'zone_id': '1', 'occupancy': ...      1   \n",
       "1    [{'spots': '42', 'zone_id': '1', 'occupancy': ...      1   \n",
       "2    [{'spots': '42', 'zone_id': '1', 'occupancy': ...      1   \n",
       "3    [{'spots': '42', 'zone_id': '1', 'occupancy': ...      1   \n",
       "4    [{'spots': '42', 'zone_id': '1', 'occupancy': ...      1   \n",
       "..                                                 ...    ...   \n",
       "701  [{'spots': '42', 'zone_id': '1', 'occupancy': ...      1   \n",
       "702  [{'spots': '42', 'zone_id': '1', 'occupancy': ...      1   \n",
       "703  [{'spots': '42', 'zone_id': '1', 'occupancy': ...      1   \n",
       "704  [{'spots': '42', 'zone_id': '1', 'occupancy': ...      1   \n",
       "705  [{'spots': '42', 'zone_id': '1', 'occupancy': ...      1   \n",
       "\n",
       "             MessageDate facility_id   facility_name tfnsw_facility_id  \\\n",
       "0    2023-12-01T04:26:16           7  Kiama Car Park      253330TPR001   \n",
       "1    2023-12-01T05:22:14           7  Kiama Car Park      253330TPR001   \n",
       "2    2023-12-01T06:28:43           7  Kiama Car Park      253330TPR001   \n",
       "3    2023-12-01T06:37:15           7  Kiama Car Park      253330TPR001   \n",
       "4    2023-12-01T07:57:38           7  Kiama Car Park      253330TPR001   \n",
       "..                   ...         ...             ...               ...   \n",
       "701  2023-12-31T21:57:13           7  Kiama Car Park      253330TPR001   \n",
       "702  2023-12-31T21:57:33           7  Kiama Car Park      253330TPR001   \n",
       "703  2023-12-31T22:09:02           7  Kiama Car Park      253330TPR001   \n",
       "704  2023-12-31T22:09:33           7  Kiama Car Park      253330TPR001   \n",
       "705  2023-12-31T22:35:08           7  Kiama Car Park      253330TPR001   \n",
       "\n",
       "    occupancy.loop occupancy.total occupancy.monthlies occupancy.open_gate  \\\n",
       "0             None               5                None                None   \n",
       "1             None               7                None                None   \n",
       "2             None               8                None                None   \n",
       "3             None               9                None                None   \n",
       "4             None              10                None                None   \n",
       "..             ...             ...                 ...                 ...   \n",
       "701           None              17                None                None   \n",
       "702           None              16                None                None   \n",
       "703           None              14                None                None   \n",
       "704           None              13                None                None   \n",
       "705           None              11                None                None   \n",
       "\n",
       "    occupancy.transients  \n",
       "0                   None  \n",
       "1                   None  \n",
       "2                   None  \n",
       "3                   None  \n",
       "4                   None  \n",
       "..                   ...  \n",
       "701                 None  \n",
       "702                 None  \n",
       "703                 None  \n",
       "704                 None  \n",
       "705                 None  \n",
       "\n",
       "[706 rows x 14 columns]"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# import pandas as pd\n",
    "# import glob\n",
    "\n",
    "# def load_json_files(file_path):\n",
    "#     \"\"\"Load all json files in a directory into a list\"\"\"\n",
    "#     json_files = glob.glob(file_path)\n",
    "#     json_data = []\n",
    "#     for file in json_files:\n",
    "#         with open(file, 'r') as f:\n",
    "#             data = pd.json_normalize(json.load(f))\n",
    "#             json_data.append(data)\n",
    "#     return json_data\n",
    "\n",
    "# def concatenate_dataframes(json_data):\n",
    "#     \"\"\"Concatenate a list of dataframes into one\"\"\"\n",
    "#     concatenated_data = pd.concat(json_data, ignore_index=True)\n",
    "#     return concatenated_data\n",
    "\n",
    "# # Load json files\n",
    "# json_data = load_json_files('data/carpark_history/facility_7.json')\n",
    "\n",
    "# # Concatenate dataframes\n",
    "# concatenated_data = concatenate_dataframes(json_data)\n",
    "\n",
    "# # Print the concatenated dataframe\n",
    "# concatenated_data\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "def read_json_files_into_dataframe(folder_path):\n",
    "    # Check if the folder exists\n",
    "    if not os.path.exists(folder_path):\n",
    "        print(f\"The specified folder '{folder_path}' does not exist.\")\n",
    "        return None\n",
    "\n",
    "    # Initialize an empty DataFrame\n",
    "    combined_df = pd.DataFrame()\n",
    "\n",
    "    # Loop through each file in the folder\n",
    "    for filename in os.listdir(folder_path):\n",
    "        if filename.endswith(\".json\"):\n",
    "            file_path = os.path.join(folder_path, filename)\n",
    "\n",
    "            # Read the JSON file into a DataFrame\n",
    "            try:\n",
    "                df = pd.read_json(file_path)\n",
    "            except Exception as e:\n",
    "                print(f\"Error reading file '{filename}': {e}\")\n",
    "                continue\n",
    "\n",
    "            # Concatenate the DataFrame to the combined DataFrame\n",
    "            combined_df = pd.concat([combined_df, df], ignore_index=True)\n",
    "\n",
    "    return combined_df\n",
    "\n",
    "carparks_df = read_json_files_into_dataframe('data/carpark_history')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tsn</th>\n",
       "      <th>time</th>\n",
       "      <th>spots</th>\n",
       "      <th>zones</th>\n",
       "      <th>ParkID</th>\n",
       "      <th>occupancy</th>\n",
       "      <th>MessageDate</th>\n",
       "      <th>facility_id</th>\n",
       "      <th>facility_name</th>\n",
       "      <th>tfnsw_facility_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2101131</td>\n",
       "      <td>754667606</td>\n",
       "      <td>244</td>\n",
       "      <td>[{'spots': '244', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '20', 'monthlies': Non...</td>\n",
       "      <td>2023-12-01T00:53:26</td>\n",
       "      <td>10</td>\n",
       "      <td>Warriewood Car Park</td>\n",
       "      <td>2101131TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2101131</td>\n",
       "      <td>754667759</td>\n",
       "      <td>244</td>\n",
       "      <td>[{'spots': '244', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '19', 'monthlies': Non...</td>\n",
       "      <td>2023-12-01T00:55:59</td>\n",
       "      <td>10</td>\n",
       "      <td>Warriewood Car Park</td>\n",
       "      <td>2101131TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2101131</td>\n",
       "      <td>754669534</td>\n",
       "      <td>244</td>\n",
       "      <td>[{'spots': '244', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '18', 'monthlies': Non...</td>\n",
       "      <td>2023-12-01T01:25:34</td>\n",
       "      <td>10</td>\n",
       "      <td>Warriewood Car Park</td>\n",
       "      <td>2101131TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2101131</td>\n",
       "      <td>754669597</td>\n",
       "      <td>244</td>\n",
       "      <td>[{'spots': '244', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '17', 'monthlies': Non...</td>\n",
       "      <td>2023-12-01T01:26:37</td>\n",
       "      <td>10</td>\n",
       "      <td>Warriewood Car Park</td>\n",
       "      <td>2101131TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2101131</td>\n",
       "      <td>754671198</td>\n",
       "      <td>244</td>\n",
       "      <td>[{'spots': '244', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': None, 'total': '16', 'monthlies': Non...</td>\n",
       "      <td>2023-12-01T01:53:18</td>\n",
       "      <td>10</td>\n",
       "      <td>Warriewood Car Park</td>\n",
       "      <td>2101131TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78492</th>\n",
       "      <td>221210</td>\n",
       "      <td>757340347</td>\n",
       "      <td>934</td>\n",
       "      <td>[{'spots': '934', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '298422', 'total': '52', 'monthlies':...</td>\n",
       "      <td>2023-12-31T23:19:07</td>\n",
       "      <td>9</td>\n",
       "      <td>Revesby Car Park</td>\n",
       "      <td>221210TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78493</th>\n",
       "      <td>221210</td>\n",
       "      <td>757340513</td>\n",
       "      <td>934</td>\n",
       "      <td>[{'spots': '934', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '298423', 'total': '51', 'monthlies':...</td>\n",
       "      <td>2023-12-31T23:21:53</td>\n",
       "      <td>9</td>\n",
       "      <td>Revesby Car Park</td>\n",
       "      <td>221210TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78494</th>\n",
       "      <td>221210</td>\n",
       "      <td>757341113</td>\n",
       "      <td>934</td>\n",
       "      <td>[{'spots': '934', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '298423', 'total': '51', 'monthlies':...</td>\n",
       "      <td>2023-12-31T23:31:53</td>\n",
       "      <td>9</td>\n",
       "      <td>Revesby Car Park</td>\n",
       "      <td>221210TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78495</th>\n",
       "      <td>221210</td>\n",
       "      <td>757341714</td>\n",
       "      <td>934</td>\n",
       "      <td>[{'spots': '934', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '298423', 'total': '51', 'monthlies':...</td>\n",
       "      <td>2023-12-31T23:41:54</td>\n",
       "      <td>9</td>\n",
       "      <td>Revesby Car Park</td>\n",
       "      <td>221210TPR001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78496</th>\n",
       "      <td>221210</td>\n",
       "      <td>757342316</td>\n",
       "      <td>934</td>\n",
       "      <td>[{'spots': '934', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>{'loop': '298423', 'total': '51', 'monthlies':...</td>\n",
       "      <td>2023-12-31T23:51:56</td>\n",
       "      <td>9</td>\n",
       "      <td>Revesby Car Park</td>\n",
       "      <td>221210TPR001</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>78497 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           tsn       time  spots  \\\n",
       "0      2101131  754667606    244   \n",
       "1      2101131  754667759    244   \n",
       "2      2101131  754669534    244   \n",
       "3      2101131  754669597    244   \n",
       "4      2101131  754671198    244   \n",
       "...        ...        ...    ...   \n",
       "78492   221210  757340347    934   \n",
       "78493   221210  757340513    934   \n",
       "78494   221210  757341113    934   \n",
       "78495   221210  757341714    934   \n",
       "78496   221210  757342316    934   \n",
       "\n",
       "                                                   zones  ParkID  \\\n",
       "0      [{'spots': '244', 'zone_id': '1', 'occupancy':...       1   \n",
       "1      [{'spots': '244', 'zone_id': '1', 'occupancy':...       1   \n",
       "2      [{'spots': '244', 'zone_id': '1', 'occupancy':...       1   \n",
       "3      [{'spots': '244', 'zone_id': '1', 'occupancy':...       1   \n",
       "4      [{'spots': '244', 'zone_id': '1', 'occupancy':...       1   \n",
       "...                                                  ...     ...   \n",
       "78492  [{'spots': '934', 'zone_id': '1', 'occupancy':...       1   \n",
       "78493  [{'spots': '934', 'zone_id': '1', 'occupancy':...       1   \n",
       "78494  [{'spots': '934', 'zone_id': '1', 'occupancy':...       1   \n",
       "78495  [{'spots': '934', 'zone_id': '1', 'occupancy':...       1   \n",
       "78496  [{'spots': '934', 'zone_id': '1', 'occupancy':...       1   \n",
       "\n",
       "                                               occupancy          MessageDate  \\\n",
       "0      {'loop': None, 'total': '20', 'monthlies': Non...  2023-12-01T00:53:26   \n",
       "1      {'loop': None, 'total': '19', 'monthlies': Non...  2023-12-01T00:55:59   \n",
       "2      {'loop': None, 'total': '18', 'monthlies': Non...  2023-12-01T01:25:34   \n",
       "3      {'loop': None, 'total': '17', 'monthlies': Non...  2023-12-01T01:26:37   \n",
       "4      {'loop': None, 'total': '16', 'monthlies': Non...  2023-12-01T01:53:18   \n",
       "...                                                  ...                  ...   \n",
       "78492  {'loop': '298422', 'total': '52', 'monthlies':...  2023-12-31T23:19:07   \n",
       "78493  {'loop': '298423', 'total': '51', 'monthlies':...  2023-12-31T23:21:53   \n",
       "78494  {'loop': '298423', 'total': '51', 'monthlies':...  2023-12-31T23:31:53   \n",
       "78495  {'loop': '298423', 'total': '51', 'monthlies':...  2023-12-31T23:41:54   \n",
       "78496  {'loop': '298423', 'total': '51', 'monthlies':...  2023-12-31T23:51:56   \n",
       "\n",
       "       facility_id        facility_name tfnsw_facility_id  \n",
       "0               10  Warriewood Car Park     2101131TPR001  \n",
       "1               10  Warriewood Car Park     2101131TPR001  \n",
       "2               10  Warriewood Car Park     2101131TPR001  \n",
       "3               10  Warriewood Car Park     2101131TPR001  \n",
       "4               10  Warriewood Car Park     2101131TPR001  \n",
       "...            ...                  ...               ...  \n",
       "78492            9     Revesby Car Park      221210TPR001  \n",
       "78493            9     Revesby Car Park      221210TPR001  \n",
       "78494            9     Revesby Car Park      221210TPR001  \n",
       "78495            9     Revesby Car Park      221210TPR001  \n",
       "78496            9     Revesby Car Park      221210TPR001  \n",
       "\n",
       "[78497 rows x 10 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "carparks_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>time</th>\n",
       "      <th>spots</th>\n",
       "      <th>zones</th>\n",
       "      <th>ParkID</th>\n",
       "      <th>facility_name</th>\n",
       "      <th>date</th>\n",
       "      <th>day_of_week</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>00:53:26</td>\n",
       "      <td>244</td>\n",
       "      <td>[{'spots': '244', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>Warriewood Car Park</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>Friday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>00:55:59</td>\n",
       "      <td>244</td>\n",
       "      <td>[{'spots': '244', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>Warriewood Car Park</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>Friday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>01:25:34</td>\n",
       "      <td>244</td>\n",
       "      <td>[{'spots': '244', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>Warriewood Car Park</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>Friday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>01:26:37</td>\n",
       "      <td>244</td>\n",
       "      <td>[{'spots': '244', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>Warriewood Car Park</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>Friday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>01:53:18</td>\n",
       "      <td>244</td>\n",
       "      <td>[{'spots': '244', 'zone_id': '1', 'occupancy':...</td>\n",
       "      <td>1</td>\n",
       "      <td>Warriewood Car Park</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>Friday</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       time  spots                                              zones  ParkID  \\\n",
       "0  00:53:26    244  [{'spots': '244', 'zone_id': '1', 'occupancy':...       1   \n",
       "1  00:55:59    244  [{'spots': '244', 'zone_id': '1', 'occupancy':...       1   \n",
       "2  01:25:34    244  [{'spots': '244', 'zone_id': '1', 'occupancy':...       1   \n",
       "3  01:26:37    244  [{'spots': '244', 'zone_id': '1', 'occupancy':...       1   \n",
       "4  01:53:18    244  [{'spots': '244', 'zone_id': '1', 'occupancy':...       1   \n",
       "\n",
       "         facility_name        date day_of_week  \n",
       "0  Warriewood Car Park  2023-12-01      Friday  \n",
       "1  Warriewood Car Park  2023-12-01      Friday  \n",
       "2  Warriewood Car Park  2023-12-01      Friday  \n",
       "3  Warriewood Car Park  2023-12-01      Friday  \n",
       "4  Warriewood Car Park  2023-12-01      Friday  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def extract_date_time(message_date):\n",
    "  date = message_date.split('T')[0]\n",
    "  time = message_date.split('T')[1]\n",
    "  return date,time\n",
    "\n",
    "carparks_df_copy = carparks_df.copy()\n",
    "\n",
    "# Separate the date and time in to 2 separate columns\n",
    "carparks_df_copy[['date','time']] = carparks_df['MessageDate'].apply(extract_date_time).apply(pd.Series)\n",
    "\n",
    "# Indicate the day of the week according to the date\n",
    "carparks_df_copy['day_of_week'] = pd.to_datetime(carparks_df_copy['date']).apply(lambda x: x.strftime('%A'))\n",
    "\n",
    "# Drop unnecessary columns\n",
    "carparks_df_copy.drop(['tsn', 'occupancy','tfnsw_facility_id', 'MessageDate', 'facility_id'], axis=1, inplace=True)\n",
    "carparks_df_copy.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Converting the zones column to its own dataframe\n",
    "df_zones = pd.DataFrame(columns=['spots', 'zone_id', 'zone_name', 'parent_zone_id', 'occupancy'])\n",
    "rename_format = {\n",
    "    0: 'spots',\n",
    "    1: 'zone_id',\n",
    "    2: 'zone_name',\n",
    "    3: 'parent_zone_id',\n",
    "    4: 'occupancy loops',\n",
    "    5: 'occupancy total',\n",
    "    6: 'occupancy monthlies',\n",
    "    7: 'occupancy open_gate',\n",
    "    8: 'occupancy transients'\n",
    "}\n",
    "\n",
    "# Accumulate DataFrames in a list\n",
    "zones_list = []\n",
    "\n",
    "for key, value in carparks_df['zones'].items():\n",
    "    # Check if the 'zones' value is a list\n",
    "    if isinstance(value, list):\n",
    "        # Normalize values in each record in zones column\n",
    "        val = pd.json_normalize(value)\n",
    "        \n",
    "        # Convert it to a DataFrame\n",
    "        temp_holder = pd.DataFrame.from_dict(val.values)\n",
    "        \n",
    "        # Rename columns\n",
    "        temp_holder.rename(mapper=rename_format, axis=1, inplace=True)\n",
    "        \n",
    "        # Append to the list instead of concatenating in each iteration\n",
    "        zones_list.append(temp_holder)\n",
    "\n",
    "# Concatenate all DataFrames outside the loop\n",
    "df_zones = pd.concat(zones_list, ignore_index=True)\n",
    "\n",
    "df_zones.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>spots</th>\n",
       "      <th>zone_id</th>\n",
       "      <th>zone_name</th>\n",
       "      <th>parent_zone_id</th>\n",
       "      <th>occupancy</th>\n",
       "      <th>occupancy loops</th>\n",
       "      <th>occupancy total</th>\n",
       "      <th>occupancy monthlies</th>\n",
       "      <th>occupancy open_gate</th>\n",
       "      <th>occupancy transients</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>244</td>\n",
       "      <td>1</td>\n",
       "      <td>Warriewood Car Park</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>20</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>244</td>\n",
       "      <td>1</td>\n",
       "      <td>Warriewood Car Park</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>19</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>244</td>\n",
       "      <td>1</td>\n",
       "      <td>Warriewood Car Park</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>18</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>244</td>\n",
       "      <td>1</td>\n",
       "      <td>Warriewood Car Park</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>17</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>244</td>\n",
       "      <td>1</td>\n",
       "      <td>Warriewood Car Park</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>16</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  spots zone_id            zone_name parent_zone_id occupancy occupancy loops  \\\n",
       "0   244       1  Warriewood Car Park              0       NaN            None   \n",
       "1   244       1  Warriewood Car Park              0       NaN            None   \n",
       "2   244       1  Warriewood Car Park              0       NaN            None   \n",
       "3   244       1  Warriewood Car Park              0       NaN            None   \n",
       "4   244       1  Warriewood Car Park              0       NaN            None   \n",
       "\n",
       "  occupancy total occupancy monthlies occupancy open_gate occupancy transients  \n",
       "0              20                None                None                 None  \n",
       "1              19                None                None                 None  \n",
       "2              18                None                None                 None  \n",
       "3              17                None                None                 None  \n",
       "4              16                None                None                 None  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# # Converting the zones column to its own dataframe\n",
    "\n",
    "# df_zones = pd.DataFrame(columns=['spots','zone_id','zone_name','parent_zone_id','occupancy'])\n",
    "# rename_format = {\n",
    "#     0:'spots',\n",
    "#     1:'zone_id',\n",
    "#     2:'zone_name',\n",
    "#     3:'parent_zone_id',\n",
    "#     4:'occupancy loops',\n",
    "#     5:'occupancy total',\n",
    "#     6:'occupancy monthlies',\n",
    "#     7:'occupancy open_gate',\n",
    "#     8:'occupancy transients'}\n",
    "\n",
    "\n",
    "\n",
    "# for key,value in carparks_df['zones'].items():    \n",
    "#     # Normalize values in each record in zones column\n",
    "#     val = pd.json_normalize(value)\n",
    "    \n",
    "#     # Convert it to a dataframe\n",
    "#     temp_holder = pd.DataFrame.from_dict(val.values)\n",
    "#     # Renaming columns\n",
    "#     temp_holder.rename(mapper=rename_format, axis=1, inplace=True)\n",
    "#     # merge it with main dataframe\n",
    "#     df_zones = pd.concat([df_zones, temp_holder], ignore_index=True)\n",
    "\n",
    "# df_zones.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>time</th>\n",
       "      <th>total_parking_spots</th>\n",
       "      <th>ParkID</th>\n",
       "      <th>facility_name</th>\n",
       "      <th>date</th>\n",
       "      <th>day_of_week</th>\n",
       "      <th>zone_id</th>\n",
       "      <th>occupancy total</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>00:53:26</td>\n",
       "      <td>244</td>\n",
       "      <td>1</td>\n",
       "      <td>Warriewood Car Park</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>Friday</td>\n",
       "      <td>1</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
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       "      <td>244</td>\n",
       "      <td>1</td>\n",
       "      <td>Warriewood Car Park</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>Friday</td>\n",
       "      <td>1</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>01:25:34</td>\n",
       "      <td>244</td>\n",
       "      <td>1</td>\n",
       "      <td>Warriewood Car Park</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>Friday</td>\n",
       "      <td>1</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>01:26:37</td>\n",
       "      <td>244</td>\n",
       "      <td>1</td>\n",
       "      <td>Warriewood Car Park</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>Friday</td>\n",
       "      <td>1</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>01:53:18</td>\n",
       "      <td>244</td>\n",
       "      <td>1</td>\n",
       "      <td>Warriewood Car Park</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>Friday</td>\n",
       "      <td>1</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       time  total_parking_spots  ParkID        facility_name        date  \\\n",
       "0  00:53:26                  244       1  Warriewood Car Park  2023-12-01   \n",
       "1  00:55:59                  244       1  Warriewood Car Park  2023-12-01   \n",
       "2  01:25:34                  244       1  Warriewood Car Park  2023-12-01   \n",
       "3  01:26:37                  244       1  Warriewood Car Park  2023-12-01   \n",
       "4  01:53:18                  244       1  Warriewood Car Park  2023-12-01   \n",
       "\n",
       "  day_of_week zone_id  occupancy total  \n",
       "0      Friday       1               20  \n",
       "1      Friday       1               19  \n",
       "2      Friday       1               18  \n",
       "3      Friday       1               17  \n",
       "4      Friday       1               16  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Keeping the necessary columns from the zones data frame\n",
    "df_zones = df_zones[['zone_id', 'occupancy total']]\n",
    "# Merge the zones dataframe to the main one \n",
    "carparks_df_copy = pd.concat([carparks_df_copy,df_zones],axis=1)\n",
    "carparks_df_copy.drop('zones', axis = 1, inplace=True)\n",
    "\n",
    "# Renaming the spots column to something more intuitive\n",
    "carparks_df_copy.rename(columns={'spots': 'total_parking_spots'}, inplace=True)\n",
    "\n",
    "# Converting the columns to their respective data types\n",
    "carparks_df_copy['occupancy total'] = carparks_df_copy['occupancy total'].astype(np.int64)\n",
    "carparks_df_copy['total_parking_spots'] = carparks_df_copy['total_parking_spots'].astype(np.int64)\n",
    "\n",
    "carparks_df_copy.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>facility_name</th>\n",
       "      <th>ParkID</th>\n",
       "      <th>zone_id</th>\n",
       "      <th>total_parking_spots</th>\n",
       "      <th>occupancy total</th>\n",
       "      <th>day_of_week</th>\n",
       "      <th>date</th>\n",
       "      <th>time</th>\n",
       "      <th>parking_availability</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Warriewood Car Park</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>244</td>\n",
       "      <td>20</td>\n",
       "      <td>Friday</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>00:53:26</td>\n",
       "      <td>224</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Warriewood Car Park</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>244</td>\n",
       "      <td>19</td>\n",
       "      <td>Friday</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>00:55:59</td>\n",
       "      <td>225</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Warriewood Car Park</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>244</td>\n",
       "      <td>18</td>\n",
       "      <td>Friday</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>01:25:34</td>\n",
       "      <td>226</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Warriewood Car Park</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>244</td>\n",
       "      <td>17</td>\n",
       "      <td>Friday</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>01:26:37</td>\n",
       "      <td>227</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Warriewood Car Park</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>244</td>\n",
       "      <td>16</td>\n",
       "      <td>Friday</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>01:53:18</td>\n",
       "      <td>228</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78492</th>\n",
       "      <td>Revesby Car Park</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>934</td>\n",
       "      <td>52</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>2023-12-31</td>\n",
       "      <td>23:19:07</td>\n",
       "      <td>882</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78493</th>\n",
       "      <td>Revesby Car Park</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>934</td>\n",
       "      <td>51</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>2023-12-31</td>\n",
       "      <td>23:21:53</td>\n",
       "      <td>883</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78494</th>\n",
       "      <td>Revesby Car Park</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>934</td>\n",
       "      <td>51</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>2023-12-31</td>\n",
       "      <td>23:31:53</td>\n",
       "      <td>883</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78495</th>\n",
       "      <td>Revesby Car Park</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>934</td>\n",
       "      <td>51</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>2023-12-31</td>\n",
       "      <td>23:41:54</td>\n",
       "      <td>883</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78496</th>\n",
       "      <td>Revesby Car Park</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>934</td>\n",
       "      <td>51</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>2023-12-31</td>\n",
       "      <td>23:51:56</td>\n",
       "      <td>883</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>78497 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             facility_name  ParkID zone_id  total_parking_spots  \\\n",
       "0      Warriewood Car Park       1       1                  244   \n",
       "1      Warriewood Car Park       1       1                  244   \n",
       "2      Warriewood Car Park       1       1                  244   \n",
       "3      Warriewood Car Park       1       1                  244   \n",
       "4      Warriewood Car Park       1       1                  244   \n",
       "...                    ...     ...     ...                  ...   \n",
       "78492     Revesby Car Park       1       1                  934   \n",
       "78493     Revesby Car Park       1       1                  934   \n",
       "78494     Revesby Car Park       1       1                  934   \n",
       "78495     Revesby Car Park       1       1                  934   \n",
       "78496     Revesby Car Park       1       1                  934   \n",
       "\n",
       "       occupancy total day_of_week        date      time  parking_availability  \n",
       "0                   20      Friday  2023-12-01  00:53:26                   224  \n",
       "1                   19      Friday  2023-12-01  00:55:59                   225  \n",
       "2                   18      Friday  2023-12-01  01:25:34                   226  \n",
       "3                   17      Friday  2023-12-01  01:26:37                   227  \n",
       "4                   16      Friday  2023-12-01  01:53:18                   228  \n",
       "...                ...         ...         ...       ...                   ...  \n",
       "78492               52      Sunday  2023-12-31  23:19:07                   882  \n",
       "78493               51      Sunday  2023-12-31  23:21:53                   883  \n",
       "78494               51      Sunday  2023-12-31  23:31:53                   883  \n",
       "78495               51      Sunday  2023-12-31  23:41:54                   883  \n",
       "78496               51      Sunday  2023-12-31  23:51:56                   883  \n",
       "\n",
       "[78497 rows x 9 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create a new column `parking_availability` which calculates how many parking spots are available at a given time\n",
    "carparks_df_copy['parking_availability'] = carparks_df_copy['total_parking_spots'] - carparks_df_copy['occupancy total']\n",
    "carparks_df_copy = carparks_df_copy[['facility_name','ParkID','zone_id','total_parking_spots','occupancy total','day_of_week', 'date', 'time', 'parking_availability']]\n",
    "carparks_df_copy"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## DATA UNDERSTANDING"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " ################### Details about the data ################### \n",
      " \n",
      "The dataset is a DataFrame with 78497 rows and 9 columns\n",
      "\n",
      "Columns of the dataset: ['facility_name', 'ParkID', 'zone_id', 'total_parking_spots', 'occupancy total', 'day_of_week', 'date', 'time', 'parking_availability']\n",
      "\n",
      "First 5 records of the dataset \n"
     ]
    },
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>facility_name</th>\n",
       "      <th>ParkID</th>\n",
       "      <th>zone_id</th>\n",
       "      <th>total_parking_spots</th>\n",
       "      <th>occupancy total</th>\n",
       "      <th>day_of_week</th>\n",
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       "      <th>parking_availability</th>\n",
       "    </tr>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Warriewood Car Park</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>244</td>\n",
       "      <td>20</td>\n",
       "      <td>Friday</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>00:53:26</td>\n",
       "      <td>224</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Warriewood Car Park</td>\n",
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       "      <td>1</td>\n",
       "      <td>244</td>\n",
       "      <td>19</td>\n",
       "      <td>Friday</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>00:55:59</td>\n",
       "      <td>225</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Warriewood Car Park</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>244</td>\n",
       "      <td>18</td>\n",
       "      <td>Friday</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>01:25:34</td>\n",
       "      <td>226</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Warriewood Car Park</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>244</td>\n",
       "      <td>17</td>\n",
       "      <td>Friday</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>01:26:37</td>\n",
       "      <td>227</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Warriewood Car Park</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>244</td>\n",
       "      <td>16</td>\n",
       "      <td>Friday</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>01:53:18</td>\n",
       "      <td>228</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         facility_name  ParkID zone_id  total_parking_spots  occupancy total  \\\n",
       "0  Warriewood Car Park       1       1                  244               20   \n",
       "1  Warriewood Car Park       1       1                  244               19   \n",
       "2  Warriewood Car Park       1       1                  244               18   \n",
       "3  Warriewood Car Park       1       1                  244               17   \n",
       "4  Warriewood Car Park       1       1                  244               16   \n",
       "\n",
       "  day_of_week        date      time  parking_availability  \n",
       "0      Friday  2023-12-01  00:53:26                   224  \n",
       "1      Friday  2023-12-01  00:55:59                   225  \n",
       "2      Friday  2023-12-01  01:25:34                   226  \n",
       "3      Friday  2023-12-01  01:26:37                   227  \n",
       "4      Friday  2023-12-01  01:53:18                   228  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Data information\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 78497 entries, 0 to 78496\n",
      "Data columns (total 9 columns):\n",
      " #   Column                Non-Null Count  Dtype \n",
      "---  ------                --------------  ----- \n",
      " 0   facility_name         78497 non-null  object\n",
      " 1   ParkID                78497 non-null  int64 \n",
      " 2   zone_id               78497 non-null  object\n",
      " 3   total_parking_spots   78497 non-null  int64 \n",
      " 4   occupancy total       78497 non-null  int64 \n",
      " 5   day_of_week           78497 non-null  object\n",
      " 6   date                  78497 non-null  object\n",
      " 7   time                  78497 non-null  object\n",
      " 8   parking_availability  78497 non-null  int64 \n",
      "dtypes: int64(4), object(5)\n",
      "memory usage: 5.4+ MB\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "None"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Null Values \n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "facility_name           0\n",
       "ParkID                  0\n",
       "zone_id                 0\n",
       "total_parking_spots     0\n",
       "occupancy total         0\n",
       "day_of_week             0\n",
       "date                    0\n",
       "time                    0\n",
       "parking_availability    0\n",
       "dtype: int64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Duplicate Values \n",
      "3 duplicate values\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ParkID</th>\n",
       "      <th>total_parking_spots</th>\n",
       "      <th>occupancy total</th>\n",
       "      <th>parking_availability</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>78497.0</td>\n",
       "      <td>78497.000000</td>\n",
       "      <td>78497.000000</td>\n",
       "      <td>78497.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1.0</td>\n",
       "      <td>704.322267</td>\n",
       "      <td>285.833318</td>\n",
       "      <td>418.488949</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.0</td>\n",
       "      <td>419.758321</td>\n",
       "      <td>257.457731</td>\n",
       "      <td>312.282565</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.0</td>\n",
       "      <td>42.000000</td>\n",
       "      <td>-7.000000</td>\n",
       "      <td>-49.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.0</td>\n",
       "      <td>213.000000</td>\n",
       "      <td>67.000000</td>\n",
       "      <td>103.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1.0</td>\n",
       "      <td>934.000000</td>\n",
       "      <td>208.000000</td>\n",
       "      <td>433.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1057.000000</td>\n",
       "      <td>441.000000</td>\n",
       "      <td>706.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1057.000000</td>\n",
       "      <td>1106.000000</td>\n",
       "      <td>983.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        ParkID  total_parking_spots  occupancy total  parking_availability\n",
       "count  78497.0         78497.000000     78497.000000          78497.000000\n",
       "mean       1.0           704.322267       285.833318            418.488949\n",
       "std        0.0           419.758321       257.457731            312.282565\n",
       "min        1.0            42.000000        -7.000000            -49.000000\n",
       "25%        1.0           213.000000        67.000000            103.000000\n",
       "50%        1.0           934.000000       208.000000            433.000000\n",
       "75%        1.0          1057.000000       441.000000            706.000000\n",
       "max        1.0          1057.000000      1106.000000            983.000000"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Data Details\n",
      "Number of unique Parking Facilities: 7\n",
      "Number of unique days: 31\n"
     ]
    }
   ],
   "source": [
    "class DataUnderstanding:\n",
    "    def __init__(self, df):\n",
    "        self.df = df\n",
    "\n",
    "    def examine_data(self):\n",
    "        print(\" ################### Details about the data ################### \\n \")\n",
    "        print(f\"The dataset is a DataFrame with {self.df.shape[0]} rows and {self.df.shape[1]} columns\\n\")\n",
    "        print(\"Columns of the dataset:\", self.df.columns.to_list())\n",
    "        print(\"\\nFirst 5 records of the dataset \")\n",
    "        display(self.df.head())\n",
    "        # Display information about the dataset\n",
    "        print(\"\\nData information\")\n",
    "        display(self.df.info())\n",
    "        print(\"\\nNull Values \")\n",
    "        display(self.df.isnull().sum())\n",
    "        print(\"\\nDuplicate Values \")\n",
    "        print(self.df.duplicated().sum(), 'duplicate values')\n",
    "        display(self.df.describe())\n",
    "        print('\\nData Details')\n",
    "        print(f'Number of unique Parking Facilities:', carparks_df_copy.facility_name.nunique())\n",
    "        print(f'Number of unique days:', carparks_df_copy.date.nunique())\n",
    "\n",
    "# Instantiate the DataUnderstanding class\n",
    "data_understanding = DataUnderstanding(carparks_df_copy)\n",
    "\n",
    "# Replace \"movie_rating_df\" with your actual dataframe\n",
    "data_understanding.examine_data()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>facility_name</th>\n",
       "      <th>total_parking_spots</th>\n",
       "      <th>occupancy total</th>\n",
       "      <th>day_of_week</th>\n",
       "      <th>date</th>\n",
       "      <th>time</th>\n",
       "      <th>parking_availability</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Warriewood Car Park</td>\n",
       "      <td>244</td>\n",
       "      <td>20</td>\n",
       "      <td>Friday</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>00:53:26</td>\n",
       "      <td>224</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Warriewood Car Park</td>\n",
       "      <td>244</td>\n",
       "      <td>19</td>\n",
       "      <td>Friday</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>00:55:59</td>\n",
       "      <td>225</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Warriewood Car Park</td>\n",
       "      <td>244</td>\n",
       "      <td>18</td>\n",
       "      <td>Friday</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>01:25:34</td>\n",
       "      <td>226</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Warriewood Car Park</td>\n",
       "      <td>244</td>\n",
       "      <td>17</td>\n",
       "      <td>Friday</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>01:26:37</td>\n",
       "      <td>227</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Warriewood Car Park</td>\n",
       "      <td>244</td>\n",
       "      <td>16</td>\n",
       "      <td>Friday</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>01:53:18</td>\n",
       "      <td>228</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78492</th>\n",
       "      <td>Revesby Car Park</td>\n",
       "      <td>934</td>\n",
       "      <td>52</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>2023-12-31</td>\n",
       "      <td>23:19:07</td>\n",
       "      <td>882</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78493</th>\n",
       "      <td>Revesby Car Park</td>\n",
       "      <td>934</td>\n",
       "      <td>51</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>2023-12-31</td>\n",
       "      <td>23:21:53</td>\n",
       "      <td>883</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78494</th>\n",
       "      <td>Revesby Car Park</td>\n",
       "      <td>934</td>\n",
       "      <td>51</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>2023-12-31</td>\n",
       "      <td>23:31:53</td>\n",
       "      <td>883</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78495</th>\n",
       "      <td>Revesby Car Park</td>\n",
       "      <td>934</td>\n",
       "      <td>51</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>2023-12-31</td>\n",
       "      <td>23:41:54</td>\n",
       "      <td>883</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78496</th>\n",
       "      <td>Revesby Car Park</td>\n",
       "      <td>934</td>\n",
       "      <td>51</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>2023-12-31</td>\n",
       "      <td>23:51:56</td>\n",
       "      <td>883</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>78494 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             facility_name  total_parking_spots  occupancy total day_of_week  \\\n",
       "0      Warriewood Car Park                  244               20      Friday   \n",
       "1      Warriewood Car Park                  244               19      Friday   \n",
       "2      Warriewood Car Park                  244               18      Friday   \n",
       "3      Warriewood Car Park                  244               17      Friday   \n",
       "4      Warriewood Car Park                  244               16      Friday   \n",
       "...                    ...                  ...              ...         ...   \n",
       "78492     Revesby Car Park                  934               52      Sunday   \n",
       "78493     Revesby Car Park                  934               51      Sunday   \n",
       "78494     Revesby Car Park                  934               51      Sunday   \n",
       "78495     Revesby Car Park                  934               51      Sunday   \n",
       "78496     Revesby Car Park                  934               51      Sunday   \n",
       "\n",
       "             date      time  parking_availability  \n",
       "0      2023-12-01  00:53:26                   224  \n",
       "1      2023-12-01  00:55:59                   225  \n",
       "2      2023-12-01  01:25:34                   226  \n",
       "3      2023-12-01  01:26:37                   227  \n",
       "4      2023-12-01  01:53:18                   228  \n",
       "...           ...       ...                   ...  \n",
       "78492  2023-12-31  23:19:07                   882  \n",
       "78493  2023-12-31  23:21:53                   883  \n",
       "78494  2023-12-31  23:31:53                   883  \n",
       "78495  2023-12-31  23:41:54                   883  \n",
       "78496  2023-12-31  23:51:56                   883  \n",
       "\n",
       "[78494 rows x 7 columns]"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Drop the duplicate entries\n",
    "no_duplicate_df = carparks_df_copy.drop_duplicates()\n",
    "processed_df = no_duplicate_df.drop(columns=['ParkID', 'zone_id'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [],
   "source": [
    "no_duplicate_df.to_csv('no_duplicate_df.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [],
   "source": [
    "processed_df.to_csv('processed_df.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## EXPLORATORY DATA ANALYSIS\n",
    "### Univariate Data Analysis\n",
    "\n",
    "The distribution of the numerical columns is visualized below using distribution plots (histogram with KDE) and boxplots."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1800x500 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1800x500 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1800x500 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Function to create varioous distribution plots for numeriacal columns\n",
    "def create_distribution_plots(dataframe):\n",
    "    # Check if the input is a DataFrame\n",
    "    if not isinstance(dataframe, pd.DataFrame):\n",
    "        raise ValueError(\"Input is not a DataFrame.\")\n",
    "\n",
    "    # Loop through each column in the DataFrame\n",
    "    for column in dataframe.columns:\n",
    "        # Check if the column is numerical\n",
    "        if pd.api.types.is_numeric_dtype(dataframe[column]):\n",
    "            # Create a figure with subplots\n",
    "            fig, axes = plt.subplots(nrows=1, ncols=3, figsize=(18, 5))\n",
    "\n",
    "            # Histogram with KDE\n",
    "            sns.histplot(dataframe[column], kde=True, ax=axes[0])\n",
    "            axes[0].set_title(f'Distribution Plot for {column}')\n",
    "            axes[0].set_xlabel(column)\n",
    "            axes[0].set_ylabel('Frequency')\n",
    "\n",
    "            # Boxplot\n",
    "            sns.boxplot(x=dataframe[column], ax=axes[1])\n",
    "            axes[1].set_title(f'Boxplot for {column}')\n",
    "            axes[1].set_xlabel(column)\n",
    "            axes[1].set_ylabel('')\n",
    "\n",
    "            # Violin plot\n",
    "            sns.violinplot(x=dataframe[column], ax=axes[2])\n",
    "            axes[2].set_title(f'Violin Plot for {column}')\n",
    "            axes[2].set_xlabel(column)\n",
    "            axes[2].set_ylabel('')\n",
    "\n",
    "            plt.tight_layout()\n",
    "            plt.show()\n",
    "\n",
    "\n",
    "create_distribution_plots(processed_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 700x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Bar plot\n",
    "plt.figure(figsize=(7, 4))\n",
    "sns.barplot(x='day_of_week', y='parking_availability', data=processed_df, palette='viridis')\n",
    "plt.title('Parking Availability by Day of the Week')\n",
    "plt.xlabel('Day of the Week')\n",
    "plt.ylabel('Parking Availability')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 700x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Convert 'time' to datetime format\n",
    "processed_df['time'] = pd.to_datetime(processed_df['time'], format='%H:%M:%S')\n",
    "\n",
    "# Define time categories\n",
    "def categorize_time(hour):\n",
    "    if 6 <= hour < 12:\n",
    "        return 'Morning'\n",
    "    elif 12 <= hour < 18:\n",
    "        return 'Afternoon'\n",
    "    elif 18 <= hour < 24:\n",
    "        return 'Evening'\n",
    "    else:\n",
    "        return 'Night'\n",
    "\n",
    "# Create a new column 'time_category'\n",
    "processed_df['time_category'] = processed_df['time'].dt.hour.apply(categorize_time)\n",
    "\n",
    "# Bar plot grouped by time category\n",
    "plt.figure(figsize=(7, 4))\n",
    "sns.barplot(x='time_category', y='parking_availability', data=processed_df, palette='viridis')\n",
    "plt.title('Parking Availability by Time Category')\n",
    "plt.xlabel('Time Category')\n",
    "plt.ylabel('Parking Availability')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Bar plot\n",
    "plt.figure(figsize=(10, 4))\n",
    "sns.barplot(x='facility_name', y='parking_availability', data=processed_df, palette='viridis')\n",
    "plt.title('Parking Availability by Parking Facility')\n",
    "plt.xlabel('Facility Name')\n",
    "plt.xticks(rotation=45)\n",
    "plt.ylabel('Parking Facility')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create a pivot table for heatmap\n",
    "heatmap_data = processed_df.pivot_table(values='parking_availability', index='day_of_week', columns='time_category', aggfunc='mean')\n",
    "\n",
    "# Define the order of days of the week\n",
    "days_order = ['Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday', 'Sunday']\n",
    "\n",
    "# Define the order of time categories\n",
    "time_order = ['Morning', 'Afternoon', 'Evening', 'Night']\n",
    "\n",
    "# Create a heatmap\n",
    "plt.figure(figsize=(12, 8))\n",
    "sns.heatmap(heatmap_data.loc[days_order, time_order], annot=True, cmap='viridis', fmt='.1f', linewidths=.5)\n",
    "plt.title('Overall Parking Availability Trends')\n",
    "plt.xlabel('Time Category')\n",
    "plt.ylabel('Day of the Week')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create a side-by-side boxplot or violin plot\n",
    "plt.figure(figsize=(12, 6))\n",
    "\n",
    "# Side-by-side boxplot\n",
    "plt.subplot(1, 2, 1)\n",
    "sns.boxplot(x='time_category', y='parking_availability', data=processed_df, palette='Set2')\n",
    "plt.title('Parking Availability Distribution Across Time Intervals')\n",
    "\n",
    "# Side-by-side violin plot\n",
    "plt.subplot(1, 2, 2)\n",
    "sns.violinplot(x='time_category', y='occupancy total', data=processed_df, palette='Set2')\n",
    "plt.title('Occupancy Rate Distribution Across Time Intervals')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Scatter plot\n",
    "plt.figure(figsize=(8, 6))\n",
    "sns.barplot(x='total_parking_spots', y='occupancy total', data=processed_df, hue='facility_name', palette='Set2')\n",
    "plt.title('Relationship Between Facility Capacity and Parking Demand')\n",
    "plt.xlabel('Facility Capacity')\n",
    "plt.ylabel('Parking Demand')\n",
    "plt.legend(title='Facility')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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wYEFFRERoy5Yt2rVrly5evKg5c+bIz89P0u0u4N955x01bdpUS5Ys0W+//aaIiAiVLl062c5Kklv2BPPnz5eXl5c6derkUPf2iZdbut0BwZ3zP3fuXJJ1JiVdjylZs2aNDh8+rObNm+vSpUvWPtOiRQtdvXpVX375paTb2+Hll1/W4sWLreeNZs6cqdy5c6tu3brW9MaOHauuXbuqUqVKWrhwoX799VdFRETomWeeua9OXlq1aqUJEyaoU6dOWr58uX7//XdFREQoZ86cyU4vMDAw2bKE/Su9NGnSRAUKFLBuT5w5c6auXLmSqoRhwYIFiomJUYsWLaz1Hx0drRYtWuj48eNauXKlJFnPI6W2I5TE++S5c+fk6uqapPMKm81mt44KFiyoVatWKVeuXOrevbsKFiyoggUL6uOPP7bGefnllzV9+nQdPXpUzz33nHLlyqVKlSpZsd5Lzpw5Vb58ebtPjhw5Un2+cHRdpKd//vlHFy9elLu7e5JzUlRUlHU+Ss16BfBw4RkyAA6bPn26jDH65ptv9M033yQZPmvWLA0fPlwuLi5q2bKlevfurZkzZ+r999/X7Nmz1bRpU7sWrhw5cty1c4HEz+8kl2zMnz9fbm5uWrp0qd2v+t9++61dvYTk459//lGePHms8ps3bya5mM6RI4dKlSql999/P9m4goKCki2/k6enp8qXL5/i8Dlz5qhNmzYaMWKEXfnZs2eTfRbpbonW3Llz9c477yg8PFwrVqxQmTJl7hlfavn7++uff/5JUh4VFZWq8RM6QBg7dqzGjh2b7PAuXbpIuv2M34cffqj58+frhRde0Pfff69evXrJxcXFqj9nzhxVr15dEydOtJvO5cuXU71MCaKjo7V06VINGTJEAwYMsMpjY2OtZ9USS265o6KiVKhQIYfn74hMmTKpe/fueuuttzRmzBh9/vnnqlmzZpJnDZOTsA169epl1znHncPr1q1rJVInTpxIVUyJ90l/f3/dvHlTZ86csUvKjDGKiopShQoVrLJq1aqpWrVqio+P15YtW/Tpp5+qV69eCggIsFrf27dvr/bt2+vKlSv65ZdfNGTIEDVs2FD79u1T/vz5UxVjYqk9X9y5LoKDg+9rXmklR44c8vf317Jly5Id7uPjY/2dmvUK4OFBCxkAhyR0VV6wYEH9/PPPST59+vTRqVOn9NNPP0mSsmXLpqZNm+qLL77Q0qVLFRUVleTWs4YNG+rgwYPy9/dP8mt2+fLl79l7mXT7otDV1dXuov3atWuaPXu2Xb2ETioWLFhgV/7NN98kefi/YcOG2rVrlwoWLJhsXKlJyFITt4eHh13ZDz/8cF/v58qePbtWrVqlYsWKqUaNGvr111//dXwJwsPDtWbNGrtWwVu3bunrr7++57gXLlzQ4sWL9cQTTyS7z7Ru3VoRERHatWuXJKlYsWKqVKmSZsyYoXnz5ik2NtbqACZBcuttx44d9/WeNZvNJmNMkulNnTpV8fHxyY4zd+5cu/83bdqko0ePpsmLfBPiSKmlr1OnTlYHJ3v37k3Vy50jIyO1efNmPffcc8lug5o1a+q7777TuXPnVLhwYRUsWFDTp09XbGysw/HXrFlTkpJ0+LJw4UJduXLFGn4nFxcXVapUyWr527ZtW5I63t7eqlevngYNGqS4uDjt3r3b4dgSpPZ8UadOHbm4uCRJ/NPKvbb1nRo2bKhz584pPj4+2fNRckl5atYrAOejhQyAQ3766SedPHlSH3zwQbIXnyVKlNCECRM0bdo0NWzYUNLt2xYXLFig1157TXnz5lWtWrXsxunVq5cWLlyop556Sm+88YZKlSqlW7du6dixY1qxYoX69OmjSpUq3TWuBg0aaOzYsWrVqpVeeeUVnTt3Th999FGSi+zHH39cLVu21JgxY+Ti4qKnn35au3fv1pgxY+Tn52fXs9+wYcO0cuVKVa1aVa+//rqKFCmi69ev68iRI/rxxx81adKkf30rU8OGDTVz5kwVLVpUpUqV0tatW/Xhhx/e93R9fHy0bNkyNWvWTLVr19b333+vGjVq/KsYJWnQoEFasmSJatasqUGDBsnLy0uTJk2yXktw53pLLOHlw6+//nqy+4y/v7/mzp2radOmady4cZJu7zNdunTRyZMnVbVq1SQXmw0bNtR7772nIUOGKDw8XHv37tWwYcMUEhLi8CsJfH199dRTT+nDDz9Ujhw5VKBAAa1bt07Tpk1LscfELVu2qFOnTmrevLmOHz+uQYMGKU+ePOrWrZtD805OyZIlJUkff/yx1WNpkSJFrBaQrFmzqk2bNpo4caLy58+vRo0a3XOaCa1j/fv3V8WKFZMMv3z5slavXq05c+aoZ8+e+uyzz9SoUSNVrlxZb7zxhvLly6djx45p+fLlSZLRxGrXrq26devqzTff1KVLl/TEE09YvSyWLVvWehXGpEmTtGbNGjVo0ED58uXT9evXrVbyhHNE586d5eXlpSeeeEK5c+dWVFSURo4cKT8/P7uWNkel9nxRoEABvfXWW3rvvfd07do1tWzZUn5+ftqzZ4/Onj2rd999975jkO69re/04osvau7cuapfv7569uypihUrys3NTSdOnNDPP/+sJk2a6Nlnn03VegXwkHFmjyIA/nuaNm1q3N3dzenTp1Os8+KLLxpXV1cTFRVljLndg1lwcLCRZAYNGpTsODExMebtt982RYoUMe7u7sbPz8+ULFnSvPHGG9Z0jLndc1r37t2Tncb06dNNkSJFjIeHh3nsscfMyJEjzbRp05L0Ynb9+nXTu3dvkytXLuPp6WkqV65sNm/ebPz8/Ox6NjTGmDNnzpjXX3/dhISEGDc3N5M9e3YTFhZmBg0aZGJiYu66rhJ6WbybCxcumI4dO5pcuXKZzJkzmyeffNKsX78+SQ9rCb3hff3110mmcWcviwliY2PNc889Zzw9Pc0PP/xgjEm5l8UGDRokG/ud8zfGmPXr15tKlSoZDw8PExgYaPr162c++OADI8lcvHgxxWUsU6aMyZUrl4mNjU2xTuXKlU2OHDmsOtHR0cbLyyvFXvFiY2NN3759TZ48eYynp6cpV66c+fbbb5Pt7U6p6GXxxIkT5rnnnjPZsmUzPj4+5plnnjG7du1K0lNewrpesWKFefnll03WrFmNl5eXqV+/vtm/f7/dfO+35z1jjBk4cKAJCgoymTJlSrZHyLVr1xpJZtSoUcmuzzvFxcWZXLlyJemd8U43b940efPmNSVLlrTKNm/ebOrVq2f8/PyMh4eHKViwoN3xkbA/3dnzZoJr166ZN9980+TPn9+4ubmZ3Llzm65du5oLFy7YTf/ZZ581+fPnNx4eHsbf39+Eh4eb77//3qoza9YsU6NGDRMQEGDc3d1NUFCQadGihdmxY8c9l/tu5wpjUn++MOZ2r7IVKlQwnp6eJkuWLKZs2bJ22yw9tnVyx+CNGzfMRx99ZEqXLm3FUrRoUdOlSxdr/0vNegXwcLEZk8wbEAHgEbNp0yY98cQTmjt3rlq1auXscP4z6tSpoyNHjmjfvn3ODuWR0qdPH02cOFHHjx9PtlMWAMB/B7csAnjkrFy5Ups3b1ZYWJi8vLz0559/atSoUQoNDVWzZs2cHd5Dq3fv3ipbtqyCg4N1/vx5zZ07VytXrrRuh0P6+/XXX7Vv3z59/vnn6tKlC8kYAGQAJGQAHjm+vr5asWKFxo8fr8uXLytHjhyqV6+eRo4cmep3dz2K4uPjNXjwYEVFRclms6l48eKaPXu2XnrpJWeH9sioUqWKMmfOrIYNG2r48OHODgcAkAa4ZREAAAAAnIRu7wEAAADASUjIAAAAAMBJSMgAAAAAwEno1EPSrVu3dPLkSfn4+Mhmszk7HAAAAABOYozR5cuXFRQUpEyZ0r/9ioRM0smTJxUcHOzsMAAAAAA8JI4fP668efOm+3xIyCT5+PhIur3SfX19nRwNAAAAAGe5dOmSgoODrRwhvZGQSdZtir6+viRkAAAAAB7Yo0x06gEAAAAATkJCBgAAAABOQkIGAAAAAE5CQgYAAAAATkJCBgAAAABOQkIGAAAAAE5CQgYAAAAATkJCBgAAAABOQkIGAAAAAE5CQgYAAAAATkJCBgAAAABOQkIGAAAAAE5CQgYAAAAATkJCBgAAAABOQkIGAAAAAE5CQgYAAAAATkJCBgAAAABOQkIGAAAAAE5CQgYAAAAATuLq7AAAAACQdk7+Xt/ZIWRoQRV/dHYIyGBoIQMAAAAAJyEhAwAAAAAnISEDAAAAACchIQMAAAAAJyEhAwAAAAAnISEDAAAAACdxakJWoEAB2Wy2JJ/u3btLkowxGjp0qIKCguTl5aXq1atr9+7ddtOIjY1Vjx49lCNHDnl7e6tx48Y6ceKEMxYHAAAAABzi1IQsIiJCp06dsj4rV66UJDVv3lySNHr0aI0dO1YTJkxQRESEAgMDVbt2bV2+fNmaRq9evbR48WLNnz9fGzZsUExMjBo2bKj4+HinLBMAAAAApJbNGGOcHUSCXr16aenSpdq/f78kKSgoSL169dKbb74p6XZrWEBAgD744AN16dJF0dHRypkzp2bPnq0XXnhBknTy5EkFBwfrxx9/VN26dVM130uXLsnPz0/R0dHy9fVNn4UDAAB4AHgxdPrixdAZ34PODR6aZ8ji4uI0Z84cdejQQTabTYcPH1ZUVJTq1Klj1fHw8FB4eLg2bdokSdq6datu3LhhVycoKEglSpSw6iQnNjZWly5dsvsAAAAAwIP20CRk3377rS5evKh27dpJkqKioiRJAQEBdvUCAgKsYVFRUXJ3d1e2bNlSrJOckSNHys/Pz/oEBwen4ZIAAAAAQOo8NAnZtGnTVK9ePQUFBdmV22w2u/+NMUnKErtXnYEDByo6Otr6HD9+/P4DBwAAAID79FAkZEePHtWqVavUqVMnqywwMFCSkrR0nT592mo1CwwMVFxcnC5cuJBineR4eHjI19fX7gMAAAAAD9pDkZDNmDFDuXLlUoMGDayykJAQBQYGWj0vSrefM1u3bp2qVq0qSQoLC5Obm5tdnVOnTmnXrl1WHQAAAAB4WLk6O4Bbt25pxowZatu2rVxd/y8cm82mXr16acSIEQoNDVVoaKhGjBihzJkzq1WrVpIkPz8/dezYUX369JG/v7+yZ8+uvn37qmTJkqpVq5azFgkAAAAAUsXpCdmqVat07NgxdejQIcmw/v3769q1a+rWrZsuXLigSpUqacWKFfLx8bHqjBs3Tq6urmrRooWuXbummjVraubMmXJxcXmQiwEAAAAADnuo3kPmLLyHDAAAZBS8hyx98R6yjO+RfQ8ZAAAAADxqSMgAAAAAwElIyAAAAADASUjIAAAAAMBJSMgAAAAAwElIyAAAAADASUjIAAAAAMBJSMgAAAAAwElIyAAAAADASUjIAAAAAMBJSMgAAAAAwElIyAAAAADASUjIAAAAAMBJSMgAAAAAwElIyAAAAADASUjIAAAAAMBJSMgAAAAAwElIyAAAAADASUjIAAAAAMBJSMgAAAAAwElIyAAAAADASUjIAAAAAMBJSMgAAAAAwElIyAAAAADASUjIAAAAAMBJSMgAAAAAwElIyAAAAADASUjIAAAAAMBJSMgAAAAAwElIyAAAAADASUjIAAAAAMBJSMgAAAAAwElIyAAAAADASUjIAAAAAMBJSMgAAAAAwElIyAAAAADASUjIAAAAAMBJSMgAAAAAwElIyAAAAADASUjIAAAAAMBJSMgAAAAAwElIyAAAAADASUjIAAAAAMBJSMgAAAAAwElIyAAAAADASUjIAAAAAMBJSMgAAAAAwElIyAAAAADASUjIAAAAAMBJSMgAAAAAwEmcnpD9/fffeumll+Tv76/MmTOrTJky2rp1qzXcGKOhQ4cqKChIXl5eql69unbv3m03jdjYWPXo0UM5cuSQt7e3GjdurBMnTjzoRQEAAAAAhzg1Ibtw4YKeeOIJubm56aefftKePXs0ZswYZc2a1aozevRojR07VhMmTFBERIQCAwNVu3ZtXb582arTq1cvLV68WPPnz9eGDRsUExOjhg0bKj4+3glLBQAAAACpYzPGGGfNfMCAAdq4caPWr1+f7HBjjIKCgtSrVy+9+eabkm63hgUEBOiDDz5Qly5dFB0drZw5c2r27Nl64YUXJEknT55UcHCwfvzxR9WtW/eecVy6dEl+fn6Kjo6Wr69v2i0gAADAA3by9/rODiFDC6r4o7NDQDp70LmBU1vIvv/+e5UvX17NmzdXrly5VLZsWU2ZMsUafvjwYUVFRalOnTpWmYeHh8LDw7Vp0yZJ0tatW3Xjxg27OkFBQSpRooRVJ7HY2FhdunTJ7gMAAAAAD5pTE7JDhw5p4sSJCg0N1fLly/Xqq6/q9ddf1xdffCFJioqKkiQFBATYjRcQEGANi4qKkru7u7Jly5ZincRGjhwpPz8/6xMcHJzWiwYAAAAA9+TUhOzWrVsqV66cRowYobJly6pLly7q3LmzJk6caFfPZrPZ/W+MSVKW2N3qDBw4UNHR0dbn+PHj/25BAAAAAOA+ODUhy507t4oXL25XVqxYMR07dkySFBgYKElJWrpOnz5ttZoFBgYqLi5OFy5cSLFOYh4eHvL19bX7AAAAAMCD5tSE7IknntDevXvtyvbt26f8+fNLkkJCQhQYGKiVK1daw+Pi4rRu3TpVrVpVkhQWFiY3Nze7OqdOndKuXbusOgAAAADwMHJ15szfeOMNVa1aVSNGjFCLFi30+++/a/LkyZo8ebKk27cq9urVSyNGjFBoaKhCQ0M1YsQIZc6cWa1atZIk+fn5qWPHjurTp4/8/f2VPXt29e3bVyVLllStWrWcuXgAAAAAcFdOTcgqVKigxYsXa+DAgRo2bJhCQkI0fvx4tW7d2qrTv39/Xbt2Td26ddOFCxdUqVIlrVixQj4+PladcePGydXVVS1atNC1a9dUs2ZNzZw5Uy4uLs5YLAAAAABIFae+h+xhwXvIAABARsF7yNIX7yHL+B6p95ABAAAAwKOMhAwAAAAAnISEDAAAAACchIQMAAAAAJyEhAwAAAAAnISEDAAAAACchIQMAAAAAJyEhAwAAAAAnISEDAAAAACchIQMAAAAAJyEhAwAAAAAnISEDAAAAACchIQMAAAAAJyEhAwAAAAAnISEDAAAAACchIQMAAAAAJyEhAwAAAAAnISEDAAAAACchIQMAAAAAJyEhAwAAAAAnISEDAAAAACchIQMAAAAAJzE1dkBAA/S6Yn9nR1Chpar62hnhwAAAPCfQgsZAAAAADgJCRkAAAAAOAkJGQAAAAA4CQkZAAAAADgJCRkAAAAAOAkJGQAAAAA4CQkZAAAAADgJCRkAAAAAOAkJGQAAAAA4CQkZAAAAADgJCRkAAAAAOInDCdnatWvTIQwAAAAAePQ4nJA988wzKliwoIYPH67jx4+nR0wAAAAA8EhwOCE7efKkevbsqUWLFikkJER169bVV199pbi4uPSIDwAAAAAyLIcTsuzZs+v111/Xtm3btGXLFhUpUkTdu3dX7ty59frrr+vPP/9MjzgBAAAAIMP5V516lClTRgMGDFD37t115coVTZ8+XWFhYapWrZp2796dVjECAAAAQIZ0XwnZjRs39M0336h+/frKnz+/li9frgkTJuiff/7R4cOHFRwcrObNm6d1rAAAAACQobg6OkKPHj305ZdfSpJeeukljR49WiVKlLCGe3t7a9SoUSpQoECaBQkAAAAAGZHDCdmePXv06aef6rnnnpO7u3uydYKCgvTzzz//6+AAAAAAICNz+JbFIUOGqHnz5kmSsZs3b+qXX36RJLm6uio8PDxtIgQAAACADMrhhKxGjRo6f/58kvLo6GjVqFEjTYICAAAAgEeBwwmZMUY2my1J+blz5+Tt7Z0mQQEAAADAoyDVz5A1a9ZMkmSz2dSuXTt5eHhYw+Lj47Vjxw5VrVo17SMEAAAAgAwq1QmZn5+fpNstZD4+PvLy8rKGubu7q3LlyurcuXPaRwgAAAAAGVSqE7IZM2ZIkgoUKKC+fftyeyIAAAAA/EsOd3s/ZMiQ9IgDAAAAAB45qUrIypUrp9WrVytbtmwqW7Zssp16JNi2bVuaBQcAAAAAGVmqErImTZpYnXg0bdo0zWY+dOhQvfvuu3ZlAQEBioqKknT7ebV3331XkydP1oULF1SpUiV99tlnevzxx636sbGx6tu3r7788ktdu3ZNNWvW1Oeff668efOmWZwAAAAAkB5SlZDdeZtiWt+y+Pjjj2vVqlXW/y4uLtbfo0eP1tixYzVz5kwVLlxYw4cPV+3atbV37175+PhIknr16qUlS5Zo/vz58vf3V58+fdSwYUNt3brVbloAAAAA8LBx+BmyNA/A1VWBgYFJyo0xGj9+vAYNGmR1uT9r1iwFBARo3rx56tKli6KjozVt2jTNnj1btWrVkiTNmTNHwcHBWrVqlerWrftAlwUAAAAAHJGqF0Nny5ZN2bNnT9XHUfv371dQUJBCQkL04osv6tChQ5Kkw4cPKyoqSnXq1LHqenh4KDw8XJs2bZIkbd26VTdu3LCrExQUpBIlSlh1khMbG6tLly7ZfQAAAADgQUtVC9n48ePTZeaVKlXSF198ocKFC+uff/7R8OHDVbVqVe3evdt6jiwgIMBunICAAB09elSSFBUVJXd3d2XLli1JnYTxkzNy5Mgkz64BAAAAwIOWqoSsbdu26TLzevXqWX+XLFlSVapUUcGCBTVr1ixVrlxZkpL06GiMuWsvj6mpM3DgQPXu3dv6/9KlSwoODr6fRQAAAACA+5aqWxbvvKUv8a1+aXnrn7e3t0qWLKn9+/dbz5Ulbuk6ffq01WoWGBiouLg4XbhwIcU6yfHw8JCvr6/dBwAAAAAetFQ/Q3b69GlJUtasWZUtW7Ykn4TyfyM2NlaRkZHKnTu3QkJCFBgYqJUrV1rD4+LitG7dOlWtWlWSFBYWJjc3N7s6p06d0q5du6w6AAAAAPCwStUti2vWrLE67Pj555/TbOZ9+/ZVo0aNlC9fPp0+fVrDhw/XpUuX1LZtW9lsNvXq1UsjRoxQaGioQkNDNWLECGXOnFmtWrWSJPn5+aljx47q06eP/P39lT17dvXt21clS5a0el0EAAAAgIdVqhKy8PDwZP/+t06cOKGWLVvq7NmzypkzpypXrqxff/1V+fPnlyT1799f165dU7du3awXQ69YscJ6B5kkjRs3Tq6urmrRooX1YuiZM2fyDjIAAAAADz2bMcY4OtKFCxc0bdo0RUZGymazqVixYmrfvv19dXv/MLh06ZL8/PwUHR3N82QZ3OmJ/Z0dQoaWq+toZ4cAAI+8k7/Xd3YIGVpQxR+dHQLS2YPODVL1DNmd1q1bpwIFCuiTTz7RhQsXdP78eX3yyScKCQnRunXr0iNGAAAAAMiQUnXL4p26d++uF154QRMnTrRuC4yPj1e3bt3UvXt37dq1K82DBAAAAICMyOEWsoMHD6pPnz52z2i5uLiod+/eOnjwYJoGBwAAAAAZmcMJWbly5RQZGZmkPDIyUmXKlEmLmAAAAADgkZCqWxZ37Nhh/f3666+rZ8+eOnDggCpXrixJ+vXXX/XZZ59p1KhR6RMlAAAAAGRAqUrIypQpI5vNpjs7ZOzfP2lvda1atdILL7yQdtEBAAAAQAaWqoTs8OHD6R0HAAAAADxyUpWQJbyoGQAAAACQdhzu9j7Bnj17dOzYMcXFxdmVN27c+F8HBQAAAACPAocTskOHDunZZ5/Vzp077Z4rs9lskm6/kwwAAAAAcG8Od3vfs2dPhYSE6J9//lHmzJm1e/du/fLLLypfvrzWrl2bDiECAAAAQMbkcAvZ5s2btWbNGuXMmVOZMmVSpkyZ9OSTT2rkyJF6/fXX9ccff6RHnAAAAACQ4TjcQhYfH68sWbJIknLkyKGTJ09Kut3xx969e9M2OgAAAADIwBxuIStRooR27Nihxx57TJUqVdLo0aPl7u6uyZMn67HHHkuPGAEAAAAgQ3I4IXv77bd15coVSdLw4cPVsGFDVatWTf7+/lqwYEGaBwgAAAAAGZXDCVndunWtvx977DHt2bNH58+fV7Zs2ayeFgEAAAAA93bf7yG7U/bs2dNiMgAAAADwSElVQtasWbNUT3DRokX3HQwAAAAAPEpSlZD5+fmldxwAAAAA8MhJVUI2Y8aM9I4DAAAAAB45Dr+HDAAAAACQNlLVQlauXDmtXr1a2bJlU9myZe/am+K2bdvSLDgAAAAAyMhSlZA1adJEHh4ekqSmTZumZzwAAAAA8MhIVUI2ZMiQZP8GAAAAANw/niEDAAAAACdx+MXQ8fHxGjdunL766isdO3ZMcXFxdsPPnz+fZsEBAAAAQEbmcAvZu+++q7Fjx6pFixaKjo5W79691axZM2XKlElDhw5NhxABAAAAIGNyOCGbO3eupkyZor59+8rV1VUtW7bU1KlTNXjwYP3666/pESMAAAAAZEgOJ2RRUVEqWbKkJClLliyKjo6WJDVs2FA//PBD2kYHAAAAABmYwwlZ3rx5derUKUlSoUKFtGLFCklSRESE1TU+AAAAAODeHE7Inn32Wa1evVqS1LNnT73zzjsKDQ1VmzZt1KFDhzQPEAAAAAAyKod7WRw1apT19/PPP6/g4GBt3LhRhQoVUuPGjdM0OAAAAADIyBxOyK5evarMmTNb/1eqVEmVKlVK06AAAAAA4FHg8C2LuXLl0ksvvaTly5fr1q1b6RETAAAAADwSHE7IvvjiC8XGxurZZ59VUFCQevbsqYiIiPSIDQAAAAAyNIcTsmbNmunrr7/WP//8o5EjRyoyMlJVq1ZV4cKFNWzYsPSIEQAAAAAyJIcTsgQ+Pj5q3769VqxYoT///FPe3t5699130zI2AAAAAMjQ7jshu379ur766is1bdpU5cqV07lz59S3b9+0jA0AAAAAMjSHe1lcsWKF5s6dq2+//VYuLi56/vnntXz5coWHh6dHfAAAAACQYTmckDVt2lQNGjTQrFmz1KBBA7m5uVnDbt68KVdXhycJAAAAAI8kh7OnqKgo+fr62pXt2bNHU6dO1dy5c/XPP/+kWXAAAAAAkJE5/AxZQjIWExOjqVOnqkqVKipVqpR+//13DRgwIM0DBAAAAICMyuEWsg0bNmjq1KlauHChQkJCtGfPHq1bt05PPPFEesQHAAAAABlWqlvIRo8eraJFi+rFF19Uzpw5tWHDBu3YsUM2m03ZsmVLzxgBAAAAIENKdQvZW2+9pTfffFPDhg2Ti4tLesYEAAAAAI+EVLeQDRs2TF9//bVCQkL05ptvateuXekZFwAAAABkeKlOyN566y3t27dPs2fPVlRUlCpXrqzSpUvLGKMLFy6kZ4wAAAAAkCE53MtieHi4Zs2apVOnTqlr164KCwtTeHi4qlatqrFjx6ZHjAAAAACQITmckCXw8fHRq6++qt9++01//PGHKlasqFGjRqVlbAAAAACQod13QnankiVLavz48fr777/TYnIAAAAA8EhIk4QsgZubW1pODgAAAAAytDRNyP6NkSNHymazqVevXlaZMUZDhw5VUFCQvLy8VL16de3evdtuvNjYWPXo0UM5cuSQt7e3GjdurBMnTjzg6AEAAADAcQ9FQhYREaHJkyerVKlSduWjR4/W2LFjNWHCBEVERCgwMFC1a9fW5cuXrTq9evXS4sWLNX/+fG3YsEExMTFq2LCh4uPjH/RiAAAAAIBDnJ6QxcTEqHXr1poyZYqyZctmlRtjNH78eA0aNEjNmjVTiRIlNGvWLF29elXz5s2TJEVHR2vatGkaM2aMatWqpbJly2rOnDnauXOnVq1a5axFAgAAAIBUcTghu3TpUrKfy5cvKy4uzuEAunfvrgYNGqhWrVp25YcPH1ZUVJTq1KljlXl4eCg8PFybNm2SJG3dulU3btywqxMUFKQSJUpYdZITGxubJH4AAAAAeNBcHR0ha9asstlsKQ7Pmzev2rVrpyFDhihTprvne/Pnz9e2bdsUERGRZFhUVJQkKSAgwK48ICBAR48eteq4u7vbtawl1EkYPzkjR47Uu+++e9fYAAAAACC9OZyQzZw5U4MGDVK7du1UsWJFGWMUERGhWbNm6e2339aZM2f00UcfycPDQ2+99VaK0zl+/Lh69uypFStWyNPTM8V6iZM/Y8xdE8LU1Bk4cKB69+5t/X/p0iUFBwffdZoAAAAAkNYcTshmzZqlMWPGqEWLFlZZ48aNVbJkSf3vf//T6tWrlS9fPr3//vt3Tci2bt2q06dPKywszCqLj4/XL7/8ogkTJmjv3r2SbreC5c6d26pz+vRpq9UsMDBQcXFxunDhgl0r2enTp1W1atUU5+3h4SEPDw9HFx0AAAAA0pTDz5Bt3rxZZcuWTVJetmxZbd68WZL05JNP6tixY3edTs2aNbVz505t377d+pQvX16tW7fW9u3b9dhjjykwMFArV660xomLi9O6deusZCssLExubm52dU6dOqVdu3bdNSEDAAAAgIeBwy1kefPm1bRp0zRq1Ci78mnTplm3/Z07dy7Jc12J+fj4qESJEnZl3t7e8vf3t8p79eqlESNGKDQ0VKGhoRoxYoQyZ86sVq1aSZL8/PzUsWNH9enTR/7+/sqePbv69u2rkiVLJukkBAAAAAAeNg4nZB999JGaN2+un376SRUqVJDNZlNERIT++usvffPNN5Juv1fshRde+NfB9e/fX9euXVO3bt104cIFVapUSStWrJCPj49VZ9y4cXJ1dVWLFi107do11axZUzNnzpSLi8u/nj8AAAAApCebMcY4OtKRI0c0adIk7du3T8YYFS1aVF26dFGBAgXSIcT0d+nSJfn5+Sk6Olq+vr7ODgfp6PTE/s4OIUPL1XW0s0MAgEfeyd/rOzuEDC2o4o/ODgHp7EHnBg63kElSgQIFktyyCAAAAABwzH0lZBcvXtTvv/+u06dP69atW3bD2rRpkyaBAQAAAEBG53BCtmTJErVu3VpXrlyRj4+P3fu+bDYbCRkAAAAApJLD3d736dNHHTp00OXLl3Xx4kVduHDB+pw/fz49YgQAAACADMnhhOzvv//W66+/rsyZM6dHPAAAAADwyHA4Iatbt662bNmSHrEAAAAAwCPF4WfIGjRooH79+mnPnj0qWbKk3Nzc7IY3btw4zYIDAAAAgIzM4YSsc+fOkqRhw4YlGWaz2RQfH//vowIAAACAR4DDCVnibu4BAAAAAPfH4WfIAAAAAABpI1UtZJ988oleeeUVeXp66pNPPrlr3ddffz1NAgMAAACAjC5VCdm4cePUunVreXp6aty4cSnWs9lsJGQAAAAAkEqpSsgOHz6c7N8AAAAAgPvn8DNkO3bsSHHYt99++29iAQAAAIBHyn29GPrQoUNJyhcuXKjWrVunSVAAAAAA8ChwOCHr2rWratasqVOnTlllCxYsUJs2bTRz5sy0jA0AAAAAMjSH30M2ePBgnTt3TrVq1dL69eu1bNkyderUSbNnz9Zzzz2XHjECAAAAQIbkcEImSR9//LFefvllVa5cWX///be+/PJLNWnSJK1jAwAAAIAMLVUJ2ffff5+krGnTplq3bp1atmwpm81m1WncuHHaRggAAAAAGVSqErKmTZumOGz69OmaPn26pNvvIYuPj0+TwAAAAAAgo0tVQnbr1q30jgMAAAAAHjkO9bJ448YN1ahRQ/v27UuveAAAAADgkeFQQubm5qZdu3bJZrOlVzwAAAAA8Mhw+D1kbdq00bRp09IjFgAAAAB4pDjc7X1cXJymTp2qlStXqnz58vL29rYbPnbs2DQLDgAAAAAyMocTsl27dqlcuXKSlORZMm5lBAAAAIDUczgh+/nnn9MjDgAAAAB45Dj8DBkAAAAAIG043EImSREREfr666917NgxxcXF2Q1btGhRmgQGAAAAABmdwy1k8+fP1xNPPKE9e/Zo8eLFunHjhvbs2aM1a9bIz88vPWIEAAAAgAzJ4YRsxIgRGjdunJYuXSp3d3d9/PHHioyMVIsWLZQvX770iBEAAAAAMiSHE7KDBw+qQYMGkiQPDw9duXJFNptNb7zxhiZPnpzmAQIAAABARuVwQpY9e3ZdvnxZkpQnTx7t2rVLknTx4kVdvXo1baMDAAAAgAzM4U49qlWrppUrV6pkyZJq0aKFevbsqTVr1mjlypWqWbNmesQIAAAAABmSwwnZhAkTdP36dUnSwIED5ebmpg0bNqhZs2Z655130jxAAAAAAMioHErIjh49qhUrVujGjRsKDw/X448/rv79+6t///7pFR8AAAAAZFipTsh++eUX1a9f33pOzNXVVbNmzVLLli3TLTgAAAAAyMhS3anHO++8oxo1aujEiRM6d+6cOnToQMsYAAAAAPwLqU7Idu7cqZEjRyooKEjZsmXTmDFjdPLkSV24cCE94wMAAACADCvVCdnFixeVK1cu639vb29lzpxZFy9eTI+4AAAAACDDc6hTjz179igqKsr63xijyMhI671kklSqVKm0iw4AAAAAMjCHErKaNWvKGGNX1rBhQ9lsNhljZLPZFB8fn6YBAgAAAEBGleqE7PDhw+kZBwAAAAA8clKdkOXPnz894wAAAACAR06qO/UAAAAAAKQtEjIAAAAAcBISMgAAAABwEhIyAAAAAHCS+0rIbt68qVWrVul///uf9Q6ykydPKiYmJk2DAwAAAICMzKH3kEnS0aNH9cwzz+jYsWOKjY1V7dq15ePjo9GjR+v69euaNGlSesQJAAAAABmOwy1kPXv2VPny5XXhwgV5eXlZ5c8++6xWr17t0LQmTpyoUqVKydfXV76+vqpSpYp++ukna7gxRkOHDlVQUJC8vLxUvXp17d69224asbGx6tGjh3LkyCFvb281btxYJ06ccHSxAAAAAOCBczgh27Bhg95++225u7vblefPn19///23Q9PKmzevRo0apS1btmjLli16+umn1aRJEyvpGj16tMaOHasJEyYoIiJCgYGBql27tnWbpCT16tVLixcv1vz587VhwwbFxMSoYcOGio+Pd3TRAAAAAOCBcjghu3XrVrLJzokTJ+Tj4+PQtBo1aqT69eurcOHCKly4sN5//31lyZJFv/76q4wxGj9+vAYNGqRmzZqpRIkSmjVrlq5evap58+ZJkqKjozVt2jSNGTNGtWrVUtmyZTVnzhzt3LlTq1atcnTRAAAAAOCBcjghq127tsaPH2/9b7PZFBMToyFDhqh+/fr3HUh8fLzmz5+vK1euqEqVKjp8+LCioqJUp04dq46Hh4fCw8O1adMmSdLWrVt148YNuzpBQUEqUaKEVSc5sbGxunTpkt0HAAAAAB40hxOycePGad26dSpevLiuX7+uVq1aqUCBAvr777/1wQcfOBzAzp07lSVLFnl4eOjVV1/V4sWLVbx4cUVFRUmSAgIC7OoHBARYw6KiouTu7q5s2bKlWCc5I0eOlJ+fn/UJDg52OG4AAAAA+Lcc7mUxKChI27dv15dffqlt27bp1q1b6tixo1q3bm3XyUdqFSlSRNu3b9fFixe1cOFCtW3bVuvWrbOG22w2u/rGmCRlid2rzsCBA9W7d2/r/0uXLpGUAQAAAHjgHE7IJMnLy0sdOnRQhw4d/nUA7u7uKlSokCSpfPnyioiI0Mcff6w333xT0u1WsNy5c1v1T58+bbWaBQYGKi4uThcuXLBrJTt9+rSqVq2a4jw9PDzk4eHxr2MHAAAAgH/D4YTs+++/T7bcZrPJ09NThQoVUkhIyH0HZIxRbGysQkJCFBgYqJUrV6ps2bKSpLi4OK1bt866NTIsLExubm5auXKlWrRoIUk6deqUdu3apdGjR993DAAAAADwIDickDVt2lQ2m03GGLvyhDKbzaYnn3xS3377bZJnuxJ76623VK9ePQUHB+vy5cuaP3++1q5dq2XLlslms6lXr14aMWKEQkNDFRoaqhEjRihz5sxq1aqVJMnPz08dO3ZUnz595O/vr+zZs6tv374qWbKkatWq5eiiAQAAAMAD5XCnHitXrlSFChW0cuVKRUdHKzo6WitXrlTFihW1dOlS/fLLLzp37pz69u17z2n9888/evnll1WkSBHVrFlTv/32m5YtW6batWtLkvr3769evXqpW7duKl++vP7++2+tWLHCrnv9cePGqWnTpmrRooWeeOIJZc6cWUuWLJGLi4ujiwYAAAAAD5TNJG7quocSJUpo8uTJSZ7R2rhxo1555RXt3r1bq1atUocOHXTs2LE0DTa9XLp0SX5+foqOjpavr6+zw0E6Oj2xv7NDyNBydeVWYQBwtpO/3/9riHBvQRV/dHYISGcPOjdwuIXs4MGDyQbm6+urQ4cOSZJCQ0N19uzZfx8dAAAAAGRgDidkYWFh6tevn86cOWOVnTlzRv3791eFChUkSfv371fevHnTLkoAAAAAyIAc7tRj2rRpatKkifLmzavg4GDZbDYdO3ZMjz32mL777jtJUkxMjN555500DxYAAAAAMhKHE7IiRYooMjJSy5cv1759+2SMUdGiRVW7dm1lynS7wa1p06ZpHScAAAAAZDj39WJom82mZ555Rs8880xaxwMAAAAAj4z7SsiuXLmidevW6dixY4qLi7Mb9vrrr6dJYAAAAACQ0TmckP3xxx+qX7++rl69qitXrih79uw6e/asMmfOrFy5cpGQAQAAAEAqOdzL4htvvKFGjRrp/Pnz8vLy0q+//qqjR48qLCxMH330UXrECAAAAAAZksMJ2fbt29WnTx+5uLjIxcVFsbGxCg4O1ujRo/XWW2+lR4wAAAAAkCE5nJC5ubnJZrNJkgICAnTs2DFJkp+fn/U3AAAAAODeHH6GrGzZstqyZYsKFy6sGjVqaPDgwTp79qxmz56tkiVLpkeMAAAAAJAhOdxCNmLECOXOnVuS9N5778nf319du3bV6dOnNXny5DQPEAAAAAAyKodayIwxypkzpx5//HFJUs6cOfXjjz+mS2AAAAAAkNE51EJmjFFoaKhOnDiRXvEAAAAAwCPDoYQsU6ZMCg0N1blz59IrHgAAAAB4ZDj8DNno0aPVr18/7dq1Kz3iAQAAAIBHhsO9LL700ku6evWqSpcuLXd3d3l5edkNP3/+fJoFBwAAAAAZmcMJ2fjx49MhDAAAAAB49DickLVt2zY94gAAAACAR47Dz5BJ0sGDB/X222+rZcuWOn36tCRp2bJl2r17d5oGBwAAAAAZmcMJ2bp161SyZEn99ttvWrRokWJiYiRJO3bs0JAhQ9I8QAAAAADIqBxOyAYMGKDhw4dr5cqVcnd3t8pr1KihzZs3p2lwAAAAAJCROZyQ7dy5U88++2yS8pw5c/J+MgAAAABwgMMJWdasWXXq1Kkk5X/88Yfy5MmTJkEBAAAAwKPA4YSsVatWevPNNxUVFSWbzaZbt25p48aN6tu3r9q0aZMeMQIAAABAhuRwQvb+++8rX758ypMnj2JiYlS8eHE99dRTqlq1qt5+++30iBEAAAAAMiSH30Pm5uamuXPnatiwYfrjjz9069YtlS1bVqGhoekRHwAAAABkWA4nZOvWrVN4eLgKFiyoggULpkdMAAAAAPBIcPiWxdq1aytfvnwaMGCAdu3alR4xAQAAAMAjweGE7OTJk+rfv7/Wr1+vUqVKqVSpUho9erROnDiRHvEBAAAAQIblcEKWI0cOvfbaa9q4caMOHjyoF154QV988YUKFCigp59+Oj1iBAAAAIAMyeGE7E4hISEaMGCARo0apZIlS2rdunVpFRcAAAAAZHj3nZBt3LhR3bp1U+7cudWqVSs9/vjjWrp0aVrGBgAAAAAZmsO9LL711lv68ssvdfLkSdWqVUvjx49X06ZNlTlz5vSIDwAAAAAyLIcTsrVr16pv37564YUXlCNHDrth27dvV5kyZdIqNgAAAADI0BxOyDZt2mT3f3R0tObOnaupU6fqzz//VHx8fJoFBwAAAAAZ2X0/Q7ZmzRq99NJLyp07tz799FPVr19fW7ZsScvYAAAAACBDc6iF7MSJE5o5c6amT5+uK1euqEWLFrpx44YWLlyo4sWLp1eMAAAAAJAhpbqFrH79+ipevLj27NmjTz/9VCdPntSnn36anrEBAAAAQIaW6hayFStW6PXXX1fXrl0VGhqanjEBAAAAwCMh1S1k69ev1+XLl1W+fHlVqlRJEyZM0JkzZ9IzNgAAAADI0FKdkFWpUkVTpkzRqVOn1KVLF82fP1958uTRrVu3tHLlSl2+fDk94wQAAACADMfhXhYzZ86sDh06aMOGDdq5c6f69OmjUaNGKVeuXGrcuHF6xAgAAAAAGdJ9d3svSUWKFNHo0aN14sQJffnll2kVEwAAAAA8Ev5VQpbAxcVFTZs21ffff58WkwMAAACAR0KaJGQAAAAAAMeRkAEAAACAk5CQAQAAAICTkJABAAAAgJOQkAEAAACAkzg1IRs5cqQqVKggHx8f5cqVS02bNtXevXvt6hhjNHToUAUFBcnLy0vVq1fX7t277erExsaqR48eypEjh7y9vdW4cWOdOHHiQS4KAAAAADjMqQnZunXr1L17d/36669auXKlbt68qTp16ujKlStWndGjR2vs2LGaMGGCIiIiFBgYqNq1a+vy5ctWnV69emnx4sWaP3++NmzYoJiYGDVs2FDx8fHOWCwAAAAASBVXZ8582bJldv/PmDFDuXLl0tatW/XUU0/JGKPx48dr0KBBatasmSRp1qxZCggI0Lx589SlSxdFR0dr2rRpmj17tmrVqiVJmjNnjoKDg7Vq1SrVrVv3gS8XAAAAAKTGQ/UMWXR0tCQpe/bskqTDhw8rKipKderUsep4eHgoPDxcmzZtkiRt3bpVN27csKsTFBSkEiVKWHUSi42N1aVLl+w+AAAAAPCgPTQJmTFGvXv31pNPPqkSJUpIkqKioiRJAQEBdnUDAgKsYVFRUXJ3d1e2bNlSrJPYyJEj5efnZ32Cg4PTenEAAAAA4J4emoTstdde044dO/Tll18mGWaz2ez+N8YkKUvsbnUGDhyo6Oho63P8+PH7DxwAAAAA7tNDkZD16NFD33//vX7++WflzZvXKg8MDJSkJC1dp0+ftlrNAgMDFRcXpwsXLqRYJzEPDw/5+vrafQAAAADgQXNqQmaM0WuvvaZFixZpzZo1CgkJsRseEhKiwMBArVy50iqLi4vTunXrVLVqVUlSWFiY3Nzc7OqcOnVKu3btsuoAAAAAwMPIqb0sdu/eXfPmzdN3330nHx8fqyXMz89PXl5estls6tWrl0aMGKHQ0FCFhoZqxIgRypw5s1q1amXV7dixo/r06SN/f39lz55dffv2VcmSJa1eFwEAAADgYeTUhGzixImSpOrVq9uVz5gxQ+3atZMk9e/fX9euXVO3bt104cIFVapUSStWrJCPj49Vf9y4cXJ1dVWLFi107do11axZUzNnzpSLi8uDWhQAAAAAcJjNGGOcHYSzXbp0SX5+foqOjuZ5sgzu9MT+zg4hQ8vVdbSzQwCAR97J3+s7O4QMLajij84OAensQecGD0WnHgAAAADwKCIhAwAAAAAnISEDAAAAACchIQMAAAAAJyEhAwAAAAAnISEDAAAAACchIQMAAAAAJyEhAwAAAAAnISEDAAAAACchIQMAAAAAJyEhAwAAAAAnISEDAAAAACchIQMAAAAAJyEhAwAAAAAnISEDAAAAACchIQMAAAAAJyEhAwAAAAAnISEDAAAAACchIQMAAAAAJyEhAwAAAAAnISEDAAAAACchIQMAAAAAJyEhAwAAAAAnISEDAAAAACchIQMAAAAAJyEhAwAAAAAnISEDAAAAACchIQMAAAAAJyEhAwAAAAAnISEDAAAAACchIQMAAAAAJ3F1dgAAAADAo+7A+hnODiHDK1StvbNDSBYtZAAAAADgJCRkAAAAAOAkJGQAAAAA4CQkZAAAAADgJCRkAAAAAOAkJGQAAAAA4CQkZAAAAADgJCRkAAAAAOAkJGQAAAAA4CQkZAAAAADgJCRkAAAAAOAkJGQAAAAA4CQkZAAAAADgJCRkAAAAAOAkJGQAAAAA4CQkZAAAAADgJCRkAAAAAOAkJGQAAAAA4CQkZAAAAADgJE5NyH755Rc1atRIQUFBstls+vbbb+2GG2M0dOhQBQUFycvLS9WrV9fu3bvt6sTGxqpHjx7KkSOHvL291bhxY504ceIBLgUAAAAA3B9XZ878ypUrKl26tNq3b6/nnnsuyfDRo0dr7NixmjlzpgoXLqzhw4erdu3a2rt3r3x8fCRJvXr10pIlSzR//nz5+/urT58+atiwobZu3SoXF5d0ibvPT1+ky3Txf8bUa+PsEAAAAIB059SErF69eqpXr16yw4wxGj9+vAYNGqRmzZpJkmbNmqWAgADNmzdPXbp0UXR0tKZNm6bZs2erVq1akqQ5c+YoODhYq1atUt26dZOddmxsrGJjY63/L126lMZLBgAAAAD39tA+Q3b48GFFRUWpTp06VpmHh4fCw8O1adMmSdLWrVt148YNuzpBQUEqUaKEVSc5I0eOlJ+fn/UJDg5OvwUBAAAAgBQ8tAlZVFSUJCkgIMCuPCAgwBoWFRUld3d3ZcuWLcU6yRk4cKCio6Otz/Hjx9M4egAAAAC4N6fespgaNpvN7n9jTJKyxO5Vx8PDQx4eHmkSHwAAAADcr4e2hSwwMFCSkrR0nT592mo1CwwMVFxcnC5cuJBiHQAAAAB4WD20CVlISIgCAwO1cuVKqywuLk7r1q1T1apVJUlhYWFyc3Ozq3Pq1Cnt2rXLqgMAAAAADyun3rIYExOjAwcOWP8fPnxY27dvV/bs2ZUvXz716tVLI0aMUGhoqEJDQzVixAhlzpxZrVq1kiT5+fmpY8eO6tOnj/z9/ZU9e3b17dtXJUuWtHpdBAAAAICHlVMTsi1btqhGjRrW/71795YktW3bVjNnzlT//v117do1devWTRcuXFClSpW0YsUK6x1kkjRu3Di5urqqRYsWunbtmmrWrKmZM2em2zvIAAAAACCtODUhq169uowxKQ632WwaOnSohg4dmmIdT09Pffrpp/r000/TIUIAAAAASD8P7TNkAAAAAJDRkZABAAAAgJOQkAEAAACAk5CQAQAAAICTkJABAAAAgJOQkAEAAACAk5CQAQAAAICTkJABAAAAgJOQkAEAAACAk5CQAQAAAICTkJABAAAAgJOQkAEAAACAk5CQAQAAAICTkJABAAAAgJOQkAEAAACAk5CQAQAAAICTkJABAAAAgJOQkAEAAACAk5CQAQAAAICTkJABAAAAgJOQkAEAAACAk5CQAQAAAICTkJABAAAAgJOQkAEAAACAk5CQAQAAAICTkJABAAAAgJOQkAEAAACAk5CQAQAAAICTkJABAAAAgJOQkAEAAACAk5CQAQAAAICTkJABAAAAgJOQkAEAAACAk5CQAQAAAICTkJABAAAAgJO4OjsAAADw8Jn92yvODiFDe7nSZGeHAOAhQUIG4KH3+ZwNzg4hw+v20pPODgEAgEcSCRkAIN0cmLjO2SFkeIW6hjs7BADAv8AzZAAAAADgJCRkAAAAAOAkJGQAAAAA4CQkZAAAAADgJCRkAAAAAOAkJGQAAAAA4CQkZAAAAADgJCRkAAAAAOAkJGQAAAAA4CQkZAAAAADgJCRkAAAAAOAkJGQAAAAA4CQZJiH7/PPPFRISIk9PT4WFhWn9+vXODgkAAAAA7ipDJGQLFixQr169NGjQIP3xxx+qVq2a6tWrp2PHjjk7NAAAAABIUYZIyMaOHauOHTuqU6dOKlasmMaPH6/g4GBNnDjR2aEBAAAAQIpcnR3AvxUXF6etW7dqwIABduV16tTRpk2bkh0nNjZWsbGx1v/R0dGSpEuXLqVqnrFXr91ntEit1G4LR12+FnvvSrhvnum03a5du5Iu08X/Sb9jjm2X3tJr2127Epcu08Vt6bXdJOlyzI10mzbS8Xx5hevL9JbabZdQzxiTnuFYbOZBzSmdnDx5Unny5NHGjRtVtWpVq3zEiBGaNWuW9u7dm2ScoUOH6t13332QYQIAAAD4Dzl+/Ljy5s2b7vP5z7eQJbDZbHb/G2OSlCUYOHCgevfubf1/69YtnT9/Xv7+/imO81916dIlBQcH6/jx4/L19XV2OHAA2+6/i23338R2++9i2/13se3+uzLytjPG6PLlywoKCnog8/vPJ2Q5cuSQi4uLoqKi7MpPnz6tgICAZMfx8PCQh4eHXVnWrFnTK8SHgq+vb4Y7WB4VbLv/LrbdfxPb7b+Lbfffxbb778qo287Pz++Bzes/36mHu7u7wsLCtHLlSrvylStX2t3CCAAAAAAPm/98C5kk9e7dWy+//LLKly+vKlWqaPLkyTp27JheffVVZ4cGAAAAACnKEAnZCy+8oHPnzmnYsGE6deqUSpQooR9//FH58+d3dmhO5+HhoSFDhiS5RRMPP7bdfxfb7r+J7fbfxbb772Lb/Xex7dLOf76XRQAAAAD4r/rPP0MGAAAAAP9VJGQAAAAA4CQkZAAAAADgJP+JhMxms+nbb791dhhIJ9WrV1evXr2cHUaKvv32WxUqVEguLi5pHufMmTOVKVMmjR8/Pk2n+zCaOXPmv3rfX7t27dS0adM0iwfJK1CgQIbfH4cOHaoyZco4O4yHRnp9xz4K+5KzHTlyRDabTdu3b3/g8167dq1sNpsuXrz4wOf9X5FWx9Z/8Tr4Udo/0mJZHU7IoqKi1LNnTxUqVEienp4KCAjQk08+qUmTJunq1av3HYiz3e1i8WE+EOLj4zVy5EgVLVpUXl5eyp49uypXrqwZM2ZYdVKb8FSvXl02m03z58+3Kx8/frwKFCjwr2NN64Nz//79qlChgtzd3WWz2eTi4qKsWbOqS5cuunLlSprMQ5K6dOmi559/Xrdu3dLHH38sm80mHx8flS9fXosWLUqz+dzNzz//rPr168vf31+ZM2dW8eLF1adPH/39999pPq+hQ4fKZrNZ6zQ4OFidOnXSmTNn0nxeCZJLtr755ht5enpq9OjRkqSPP/5YM2fOTLcY/q1Lly5p0KBBKlq0qDw9PRUYGKhatWpp0aJFSo++kxK2UVrtj+3atZPNZtO5c+eSDOvWrZtsNpvatWv3LyL+98aMGSM/P79kv2uuX7+urFmzauzYsQ8snqioKPXo0UOPPfaYPDw8FBwcrEaNGmn16tVpPq+EC++ET7Zs2fTUU0/pmWeekc1m06hRo+zqf/vtt7LZbGkeR0Zy4MABtW/fXnnz5pWHh4dCQkLUsmVLbdmyJc3nlfD9l/DJmTOn6tWrpz///DPZ+gnHo81mk6urq/Lly6euXbvqwoULaR7bw+hhOLbWrVunSZMmycfHRzdv3rTqx8TEyM3NTdWqVbObzvr162Wz2bRv3740j/HUqVOqV69emk/3YfDHH3+oefPmCggIkKenpwoXLqzOnTuny3qcOXOm3bbOnTu3WrRoocOHD6f5vBzlUEJ26NAhlS1bVitWrNCIESP0xx9/aNWqVXrjjTe0ZMkSrVq16r4DuXHjxn2PmxHExcXd13hDhw7V+PHj9d5772nPnj36+eef1blz5/s+aXt6eurtt99O8+2R1tPbvn27ihcvru3bt6tz5876/vvv9e233+rFF1/UnDlz9N13393XdI0xSU68p0+fVt26dSVJM2bM0KlTpxQREaHSpUurefPm2rx58z2nm9z2Te02/9///qdatWopMDBQCxcu1J49ezRp0iRFR0drzJgxqVyy1MWU4PHHH9epU6d07NgxTZw4UUuWLFGbNm3ue16Obv+pU6eqdevWmjBhgvr37y9J8vPz+1ctbOnp4sWLqlq1qr744gsNHDhQ27Zt0y+//KIXXnhB/fv3V3R09H1NN/H+mNj97o/JuXXrloKDg3XlyhW7feP69ev68ssvlS9fvvuablpq06aNrl27poULFyYZtnDhQl29elUvv/zyA4nlyJEjCgsL05o1azR69Gjt3LlTy5YtU40aNdS9e/f7nm58fLxu3bqV4vBVq1bp1KlTWrdunXx9fbVq1Sp5eHjogw8+cPi8f69zUHLD77VP/lds2bJFYWFh2rdvn/73v/9pz549Wrx4sYoWLao+ffrc93Tvda7bu3evTp06pR9++EEXLlzQM888k+L54ZlnntGpU6d05MgRTZ06VUuWLFG3bt2s4fd73fCwe1iOrfr16ys0NFQxMTF2Sfr69esVGBioiIgIux+H1q5dq6CgIBUuXNjhbZPScZUwncDAwAzZtfzSpUtVuXJlxcbGau7cuYqMjNTs2bPl5+end955576ne7f17+vrq1OnTunkyZOaN2+etm/frsaNGys+Pv6+5pVm17fGAXXr1jV58+Y1MTExyQ6/deuW9ffRo0dN48aNjbe3t/Hx8THNmzc3UVFR1vAhQ4aY0qVLm2nTppmQkBBjs9nMrVu3zL59+0y1atWMh4eHKVasmFmxYoWRZBYvXmyNu2PHDlOjRg3j6elpsmfPbjp37mwuX75sDW/btq1p0qSJ+fDDD01gYKDJnj276datm4mLi0tx2WbMmGH8/PySHZZ4/idOnDAtWrQwWbNmNdmzZzeNGzc2hw8fdmj++fPnN++9955p27at8fX1NW3atDE1atQw3bt3t5v32bNnjbu7u1m9enWysZUuXdoMHTo0xeVq27atkWT3uTPWO4WHh5v27dubHDlymM8++8wqHzdunMmfP79d3c8//9w89thjxs3NzRQuXNh88cUXSdbZxIkTTePGjU3mzJlNmzZtksTRtm1ba749evQw/fr1M9myZTMBAQFmyJAhKS6TMcYEBwcbm81m9u/fn2TY5cuXrXU9e/ZsU7JkSePi4mJsNptxdXU1jRs3tvbFn3/+2UgypUqVMpkyZTKSTGhoqImIiLCG3fl57733jDHGfPPNN6ZYsWJGkvH19TWjR482HTp0MAUKFDCenp7G1dXV1K9f3277tm3b1pQtW9b4+fkZScbLy8t89NFHxmazmXHjxlnxT58+3fj6+poVK1aY48ePG3d3d9OrV69k18OFCxeMMbf3kxdffNHkyZPHeHl5mRIlSph58+Yl2b7du3c3b7zxhvH39zdPPfVUstNMODbvNHz4cJMpUyZz9epV89NPP5knnnjC+Pn5mezZs5sGDRqYAwcOWHUPHz5sJJkFCxaY8PBw4+HhYaZPn57kGDt79qypUKGCadSokXnppZdMkyZNjDHGfPDBB8bDw8N88803djEkHFcJHInjySefNJ6enqZ8+fJm79695vfffzdhYWHG29vb1K1b15w+fdoa7/fffze1atUy/v7+xtfX1zz11FNm69atya6rBF27djXe3t7m77//TjLs8uXL5saNG8aY2/tjWFiYyZIliwkICDAtW7Y0//zzj1U3YZ9btmyZCQsLM25ubmbNmjXJzjPxeSkuLs5kzpzZDBgwwNy8edNufyxcuLAZP358sutzxIgRJnfu3Mbb29s0adLEuLm5mZdeesmq98orr5hMmTKZKlWqWMesMcZcv37d9OjRw+TMmdN4eHiYJ554wvz+++9JlmXVqlUmLCzMeHl5mSpVqpi//vrLqnPgwAHTuHFjkytXLuPt7W3Kly9vVq5cedd13axZM1O9evUk5U8//bR57rnnjDHG9O/f34SGhhovLy8TEhJi3n77bbvzb3L7+PTp003RokWNh4eHKVKkiN05MDn16tUzefLkSfb7MOG4NMaYMWPGmBIlSpjMmTObvHnzmq5du9p9XyUcF0uWLDHFihUzLi4u5tChQ0mmmbA///HHH1bZiRMnjCRTsmRJExoaaooWLWqdA/Lly2fu/Io/e/asyZkzp/H29jaurq7GxcXFFC1a1Bjzf/tSwjmiSpUqxmazmXLlyqW4T6Zm2+XPn98MGzbMtGzZ0nh7e5vcuXObTz75xK7OxYsXTefOnU3OnDmNj4+PqVGjhtm+fbtdne+//96UK1fOeHh4mJCQEDN06FDrmEqIf8qUKaZp06bGy8vLFCpUyHz33Xcpbrtbt26Zxx9/3ISFhZn4+Pi7br/U7kuJr2USS1iPd057w4YN1rpNvD79/f1N1apV7abh4+NjvLy87L5XRo8ebSQZd3d3U6RIETNhwgTTqVMnExoaasqWLWvefPNNu2mcPn3auLq6WueV2NhY069fPxMUFGQyZ85sKlasaH7++Wer/pEjR0zDhg1N1qxZTebMmU3x4sXNDz/8YLdMS5cuNaVKlTIeHh6mYsWKZseOHcYYY2JiYoyPj4/5+uuv7WL4/vvvTebMmc2lS5eS3T4P07E1adIkExgYaEqVKmUdWzly5DC1a9c2xYsXt/b58PBwkydPHlO0aFHj7+9vihQpYsLCwowkkzVrVutc/+6775pcuXKZKVOmJHtcpfQ97ch16I4dO4zNZjNnzpwxxhhz/vx5Y7PZzPPPP2+NP2LECFO5cmXr/7Vr15oKFSoYd3d3ExgYaN588027Y+xe53tjjPnhhx9MaGio8fT0NNWrVzczZsxIss/f6cqVKyZHjhymadOmyQ5PGO9+vs8SX7MmSO5af86cOUaS+euvv1L1/Z/4+nbw4MFJju+rV6+a+vXrm0qVKplz584lG0tiqU7Izp49a2w2mxk5cuQ96966dcuULVvWPPnkk2bLli3m119/NeXKlTPh4eFWnSFDhlgXQ9u2bTN//vmnuXnzpilRooSpXr26+eOPP8y6detM2bJl7XbEK1eumKCgINOsWTOzc+dOs3r1ahMSEmJ3oZBwsnr11VdNZGSkWbJkicmcObOZPHlyijGnNiG7cuWKCQ0NNR06dDA7duwwe/bsMa1atTJFihQxsbGxqZ5//vz5ja+vr/nwww/N/v37zf79+83cuXNNtmzZzPXr1616H3/8sSlQoECyJ3hjbifJTz31lN0F5Z0uXrxoqlSpYjp37mxOnTplTp06ZW7evJls3fDwcNOzZ08zduxYExAQYJ0MEydkixYtMm5ubuazzz4ze/fuNWPGjDEuLi52F46STK5cucy0adPMwYMHzZEjR8zChQuNJLN3715z6tQpc/HiRWu+vr6+ZujQoWbfvn1m1qxZxmazmRUrViQb5+nTp40kU7FixWSH32nq1KmmYMGCpnz58mbGjBnm8ccfN76+vta+mHAQZc2a1UydOtWsWrXKTJs2zWzfvt3ExsaavXv3GklW7F999ZXZsmWLyZQpkxk2bJi1D3t5eZnGjRub33//3Rw6dMjkyJHDSDIvvfSStX3r169vJJmyZcuapUuXmgEDBpisWbPaJWQffvihyZ49u9m8ebMxxpixY8caSebkyZN3Xc4TJ06YDz/80Pzxxx/m4MGD5pNPPjEuLi7m119/tdu+WbJkMf369TN//fWXiYyMTHZayV2sjhkzxkgyly5dMt98841ZuHCh2bdvn/njjz9Mo0aNTMmSJa0Lm4QvtwIFCpiFCxeaQ4cOmb///tvuGDt+/LgpVqyYefnll82NGzesk+mbb75psmTJkuxFeeKELLVxFC1a1Cxbtszs2bPHVK5c2ZQrV85Ur17dbNiwwWzbts0UKlTIvPrqq9Z0V69ebWbPnm327Nlj9uzZYzp27GgCAgJSvHiIj4832bJlM6+88spdt5ExxkybNs38+OOP5uDBg2bz5s2mcuXKpl69etbwO38gWLFihTlw4IA5e/ZsstNK/AVtjDG+vr6mT58+Ji4uzgwePNjaH+fMmWMyZ85sFixYYLc+s2TJYl5++WWza9cu07hxY9OkSROTLVs2Exoaaoy5vT+6urqanj17miZNmtidZ19//XUTFBRkfvzxR7N7927Ttm1bky1bNuvLJ2FZKlWqZNauXWt2795tqlWrZneRuX37djNp0iSzY8cOs2/fPjNo0CDj6elpjh49muI6/OGHH4zNZrO7sDp8+LCx2Wzmxx9/NMYY895775mNGzeaw4cPm++//94EBASYDz74wKqfeB+fPHmyyZ07t7W/Lly40GTPnt3MnDkz2RjOnTtnbDabGTFiRIpxJhg3bpxZs2aNOXTokFm9erUpUqSI6dq1qzV8xowZxs3NzVStWtVs3LjR/PXXX8leiCZ30Xj+/HkrIZsyZYpxdXU1y5YtMwcPHjSdOnUykqxzwIkTJ8xjjz1mvLy8TOfOnc2gQYOsc8SdCZmbm5vx8fExy5YtM5GRkSnuk6nZdvnz5zc+Pj5m5MiRZu/evdZ5KeHcfuvWLfPEE0+YRo0amYiICLNv3z7Tp08f4+/vb+1Hy5YtM76+vmbmzJnm4MGDZsWKFaZAgQJ2P0RKMnnz5jXz5s0z+/fvN6+//rrJkiVLihdC27ZtM5KS/GiVnNTsS4mvZVKbkG3dutVIMkuWLEmyPhN+JExYnwcPHjRubm7GZrNZ1w3Dhw83uXLlspKiBQsWGHd3d5MvXz7zzz//mE8//dTky5fPLp5PP/3U5MmTxzpPtmrVylStWtX88ssv5sCBA+bDDz80Hh4eZt++fcYYYxo0aGBq165tduzYYQ4ePGiWLFli1q1bZ7dMCT+e79ixwzRs2NAUKFDASlo7d+5s6tevb7cunn32WdOmTZtk1/fDdmx9+umnpmnTpqZw4cLW92u+fPlMpkyZTLNmzcxbb71ljDGmWrVqRpKpW7eu+euvv8zw4cPNjz/+aCSZUaNGmcqVK5v8+fObfPnymX379qV4XKX0Pe3IdeitW7dMjhw5rB81v/32W5MjRw6TK1cua/nq1KljJesnTpwwmTNnNt26dTORkZFm8eLFJkeOHHY/jN/rfH/s2DHj4eFhevbsaf766y8zZ84cExAQcNeEbNGiRUaS2bRp01238/18n+3cuTPZaSV3rZ9wfZeQU9zr+z+569s7j++LFy+aJ5980tSqVSvFBqzkpDohSzhpL1q0yK7c39/feHt7G29vb9O/f39jjDErVqwwLi4u5tixY1a93bt3G0lWRj1kyBDj5uZml0gsX77cuLi4mOPHj1tlP/30k92OOHnyZJMtWza7hfzhhx9MpkyZrFaPtm3bmvz589slHs2bNzcvvPBCisuXkMknLMudnzvnP23aNFOkSBG7E1xsbKzx8vIyy5cvT/X88+fPn+RXgevXr5vs2bPb7WRlypS5awvY7t27TbFixUymTJlMyZIlTZcuXayLkgQJida9JNS7fv269cumMUkTsqpVq5rOnTvbjdu8eXO7k66kJK06yX0hJcz3ySeftCurUKFCkl/2EiSc5Nq1a2dXnpp98ffff7dau37//Xcrptdffz3ZeV24cMFIsuotXrzYtGrVytSsWdO89957RpL58ccfTb9+/Uzx4sWt8fLnz29CQkKsX+yNMSYkJMS4u7tbibsxxrzwwgtWQjZgwACTO3du69dFY263vPj6+iYb273Ur1/f9OnTx/o/PDzclClT5p7jJb5YjYyMNIUKFUoxAU5IkBNOgAlfbol/wUo4Ee7du9fky5fP9OjRwzqO2rZta9zd3Y2kFFuDEydkqY1j6tSpVp0vv/wyyTxGjhxpihQpkuJ0b968aXx8fMySJUuSHf7PP/8YSWbs2LEpTiMlCftjwq+6CfvZt99+e89x7zwvXb9+3W5/TE63bt3s9se2bduagIAAux+SmjRpYvLmzWtcXV3Nq6++av0aeubMGbuELCYmxri5uZm5c+da04uLizNBQUFm9OjRdsuyatUqq84PP/xgJJlr166luFzFixc3n376aYrDb968afLkyWMGDx5slQ0ePNjkyZMnxR+bRo8ebcLCwqz/E+/jwcHBSS7O33vvPVOlSpVkp/fbb78l+32YGl999ZXx9/e3/k/47kncKpRY4ovGmJgY06VLF2Oz2UyNGjWMMcZUrlzZdOjQwRhjzOLFi42ku54DEs4RkszXX39tcuXKZTw8POy+gx3ZJxNvu/z585tnnnnGrs4LL7xg/QixevVq4+vra/cjpDHGFCxY0Pzvf/8zxty+0E18cT579myTO3du639J5u2337b+j4mJMTabzfz000/JxrlgwQIjyWzbtu2ey5RYcvtS4muZ5CT+/jt79qxp3Lix8fHxsWslT5Bwd4u7u7vx9PS0vrdKlChh1QkODjYff/yxkWTWr19vatWqZfLly2edqxNaw3755RdrnCpVqph+/foZY263UNtstiQt+zVr1jQDBw40xhhTsmTJFK9BEpZp/vz5Vtm5c+eMl5eXdR3z22+/GRcXF2seZ86cMW5ubmbt2rXJTvNhOrZcXFzMjh07zOTJk423t7e5ceOGuXTpknF1dTU1a9Y0DRo0sH5gKl26tJFkDh48aDfthGPrmWeesVphjEn5uErpe9rR69BmzZqZ1157zRhjTK9evUyfPn1Mjhw5zO7du82NGzdMlixZrOPjrbfeSjK9zz77zGTJksXEx8en6nw/cOBAU6xYMbtpvPnmm3dNyD744AMjyZw/fz7Z4Xdzr++zlCROyI4fP24qV65s8ubNm+y4yX3/3+369q+//jKlS5c2zZo1u2csibnKQYkfEv79999169YttW7dWrGxsZKkyMhIBQcHKzg42KpXvHhxZc2aVZGRkapQoYIkKX/+/MqZM6dVJzIyUvny5VPevHmtsipVqtjNLzIyUqVLl5a3t7dV9sQTT+jWrVvau3evAgICJN1+BsbFxcWqkzt3bu3cufOuy+bj46Nt27YlKQ8NDbX+3rp1qw4cOCAfHx+7OtevX9fBgwet/1Mz//Lly9v97+HhoZdeeknTp09XixYttH37dv3555937VCkePHi2rVrl7Zu3aoNGzbol19+UaNGjdSuXTtNnTr1rsubEg8PDw0bNkyvvfaaunbtmmR4ZGSkXnnlFbuyJ554Qh9//PFdl+9uSpUqZfd/7ty5dfr06buOkymT/SOQye2LK1eulIeHh5588kmdP3/eun/c19fX2t8k6fPPP9fu3btVq1YtNW/eXAULFkx2ni1btlRcXJyMMdq2bZs++ugj1atXT3FxcRo7dqzCwsJ07NgxnTt3TjabTTly5LDGjY6OVt68eeXu7m6VValSRV999ZXGjBmjK1euaMuWLXrssces4caYVD2YHx8fr1GjRmnBggX6+++/FRsbq9jYWLvjREr9Ntm5c6eyZMmi+Ph4xcbGqnr16po8ebIk6eDBg3rnnXf066+/6uzZs9Y6PXbsmEqUKHHXeV27dk1PPvmkWrZsmWR/KVWqlM6ePavBgwerQoUKSY6xxFIbx537VsL5oWTJknZld+5rp0+f1uDBg7VmzRr9888/io+P19WrV3Xs2LFk4zD/v8OO1GynP/74Q0OHDtX27dvt9sdjx46pePHiVr3UbqeWLVvKxcVF165dk5+fn7U/StKkSZM0depUHT16VNeuXVNcXFySngVLlixptz9KkouLi9zc3DRz5ky98sor+vvvv+32Y+n2ur9x44aeeOIJq8zNzU0VK1ZUZGSkXd0713/u3Lkl3V7H+fLl05UrV/Tuu+9q6dKlOnnypG7evKlr166luK4T4mvbtq1mzpypIUOGyGazadasWWrXrp11zv3mm280fvx4HThwQDExMbp586Z8fX2Tnd6ZM2d0/PhxdezYUZ07d7bKb968KT8/v2THcWSb//zzzxoxYoT27NmjS5cu6ebNm7p+/bquXLliHZ/u7u5JzoEpqVq1qjJlyqSrV68qd+7ceuKJJ+Tr66v4+Hg9/vjjmjZtmhYuXKjr169LkrUu4+PjdfToUUVHR8vf3z/JOeKNN97QpUuX1Lx5c7vv4ASJ98nUbrvE3+FVqlSxel7cunWrYmJi5O/vb1fn2rVr1vfp1q1bFRERoffff98aHh8fr+vXr+vq1avKnDmzJPv9zNvbWz4+Pil+hziy/VKzLyW+lrmbhHV75coVhYaG6uuvv1auXLmSrM+EjqnatGmjHj16aOrUqZoyZYqaN28u6f/22zfffFOS9NRTT8lms8nNzc3a9jlz5lTt2rU1d+5cVatWTYcPH9bmzZs1ceJESdK2bdtkjFHhwoXtYoyNjbW2yeuvv66uXbtqxYoVqlWrlp577rkk++qd2zh79uwqUqSIdR6oWLGiHn/8cX3xxRcaMGCAZs+erXz58umpp55Kdv08TMfWzJkzrXPklStXVKRIEZ0+fVrx8fFat26d6tWrp4iICF25ckUXL15UlixZrO/vhHO9JLVo0cKaR+LnlJI719/r/J+a69A7v7PXrVun9957T4cPH9a6desUHR2ta9euWefvyMhIValSxW6dP/HEE4qJidGJEyd08eLFe57vIyMjVblyZbtpJD72E0vY1qlxv99nyYmOjlaWLFlkjNHVq1dVrlw5LVq0SO7u7qn+/k9pG9WqVUsVKlTQV199ZZcDpEaqO/UoVKiQbDab/vrrL7vyxx57TIUKFZKXl5dVltJFZOLyxBeLyW2cxNO52wXqneVubm5Jht3tYU7p9gV+oUKFknzudOvWLYWFhWn79u12n3379qlVq1YOzT/x8ktSp06dtHLlSp04cULTp09XzZo1lT9//nvGXaFCBb3xxhtavHixZs6cqWnTpv2rXmNeeuklFShQQMOHD092eGq2S3LLlxJHtlfCgbBr1y678sT74pUrV/T555/LZrNpzpw5ioiI0OLFiyXd3o53xrt582Y1aNBAa9asUfHixa16iY0bN05FihRRv379dP78eevh7w0bNig+Pl7t27fXihUrFBQUpEqVKtk9WGqMSfFkUa1aNcXHx+urr76yKy9cuLCio6N16tSpZMdLMGbMGI0bN079+/fXmjVrtH37dtWtWzfJg62p3SZFihTR9u3btWfPHl27dk1r1qyxjoVGjRrp3LlzmjJlin777Tf99ttvkpI+RJvcvDw8PFSrVi398MMPOnHihN2wPHnyaN26dTp16pSeeeYZXb58+a4xpjaOO/ethG2euOzOfa1du3baunWrxo8fr02bNmn79u3y9/dP8SHhnDlzKlu2bEkSkcSuXLmiOnXqKEuWLEn2x/vdTuPGjdP27dt16tQpu/3xq6++0htvvKEOHTpoxYoV2r59u9q3b5/q+VSoUEGxsbGaPXu2OnTokGR4ShdNyZ0Hklv/Ceu7X79+Wrhwod5//32tX79e27dvV8mSJe/5QHyHDh10/PhxrVmzRqtXr9axY8fUvn17SdKvv/6qF198UfXq1dPSpUv1xx9/aNCgQSlOMyGWKVOm2J3Td+3apV9//TXZcUJDQ2Wz2e65zY8ePar69eurRIkSWrhwobZu3arPPvtMkv2D4F5eXqnuEXHBggX6888/debMGf3999/Wj0djxozRt99+q9KlS6ts2bIaN26cpP/bt8aMGaMTJ06oYsWKyZ4jateurdjY2BR7U028r9zvtpPs94PcuXMn+T7du3ev+vXrZ9V599137Ybv3LlT+/fvl6enpzVNR75DEhKQe22/1O5LjnzXrV+/Xn/++aeio6O1b98+q8OoxOuzUaNG8vX1lbe3t0qVKqVPPvlExhht2LDBWi+SNHLkSEm3L/rd3d01ZcoUu/22devW+uabb3Tjxg3NmzdPjz/+uEqXLm1Nw8XFRVu3brVbv5GRkdYPZp06ddKhQ4f08ssva+fOnSpfvrw+/fTTey7nnftzp06drJ6fZ8yYofbt26e4vz9Mx9ZLL70kSfruu++UKVMmhYWFqVmzZmrZsqXq1q2rTJkyKSQkRBs3btTFixetRog7z/WS1LRpU7m63m7/SM2+c6/9KTXXodWrV9fu3bt14MAB7dq1S9WqVVN4eLjWrVuntWvXKiwszErokjtv33mOT8353pHkKkHCcZg4r0js336fJebj42OdR2JiYrR161aroSi13/8pzatBgwZav3699uzZk6pY7pTqhMzf31+1a9fWhAkT7tmlePHixXXs2DEdP37cKtuzZ4+io6NVrFixe4538uRJqyxxj2EJPevdGcPGjRuVKVOmJL/ypIdy5cpp//79ypUrV5LELaVfUx1RsmRJlS9fXlOmTNG8efOSvRi6l4Rf2hPWkbu7u8O9x2TKlEkjR47UxIkTdeTIEbthxYoVs74UEmzatOmu2zYhDinpL0SOypkzp/LmzauIiAgdOHAgyfCEnpT++usvXblyRdevX1eBAgVUtGhR6xfTmJgYu3gLFSqkN954QytWrFCzZs3sXhtwp8DAQJUtW1Z//PGHXfnq1avl7e2t1157TWXLlpWrq6vOnj1rVydr1qw6f/68XVnCF2fFihW1bNkyjRgxQh9++KE1/Pnnn5e7u7vV9XtiCa8QWL9+vZo0aaKXXnpJpUuX1mOPPab9+/cnO05quLu7q1ChQgoJCbHr2encuXOKjIzU22+/rZo1a6pYsWIO9eyWKVMmzZ49W2FhYXr66aftjnVJypcvn9atW6fTp0+rTp06unTpUrLT+bdx3M369ev1+uuvq379+nr88cfl4eGRZFsmXqYXXnhBc+fOTbI80u3j8ObNm/rrr7909uxZjRo1StWqVbPbH+9XYGCgChUqpFy5ciVZhqpVq6pbt24qW7asChUqZNeCfy9NmjSRv7+/Ll68mOydBYUKFZK7u7vdeeDGjRvasmXLPc8DieNs166dnn32WZUsWVKBgYFJzjfJKViwoMLDwzVjxgxNnz5d1atXtxKTjRs3Kn/+/Bo0aJDKly+v0NBQHT16NMVpBQQEKE+ePDp06FCSc3pISEiy42TPnl1169bVZ599luz3YcJxuWXLFt28eVNjxoxR5cqVVbhw4WT3EUcEBwerYMGCSVqVEs4Bs2fP1i+//KJDhw4lGZ4jRw4VLVo02XNE48aNVbx4ca1atSrJq0+Sk9ptlzip/fXXX1W0aFFJt79Po6Ki5OrqmmTdJ7TKlitXTnv37k32x9LEd0mkVpkyZVS8eHGNGTMm2aQtYfs5ui+lRkhIiAoWLJiklS3x+vTy8kryeoesWbNq7dq1OnnypLXfJvxyP2DAAI0ePVpdu3a1+zW/adOmun79upYtW6Z58+ZZSYYklS1bVvHx8Tp9+nSSdRsYGGjVCw4O1quvvqpFixapT58+mjJlil1cd27jCxcuaN++fdY2lm7/wHvs2DF98skn2r17t9q2bZvi+nlYj62QkBBdvHhRe/bsUaNGjaxjJzw8XMuXL9fly5ethOzOc710u5UzoXfMZcuW/asYpdRdh5YoUUL+/v4aPny4SpcuLV9fX7uELDw83Jpe8eLFtWnTJrukatOmTfLx8VGePHlSdb4vXrx4ssf63dSpU0c5cuRI1fXNv/k+Syyh8eWxxx5Lklg5+v2f2KhRo9S2bVvVrFnT4aTMobPZ559/rps3b6p8+fJasGCBIiMjtXfvXs2ZM0d//fWX1TxXq1YtlSpVSq1bt9a2bdv0+++/q02bNgoPD79rU2ytWrVUpEgRtWnTRn/++afWr1+vQYMG2dVp3bq1PD091bZtW+3atUs///yzevTooZdfftm6HSk9tW7dWjly5FCTJk20fv16qwm4Z8+eSX7xv1+dOnXSqFGjFB8fr2efffaudZ9//nmNGzdOv/32m44ePaq1a9eqe/fuKly4sHVCLFCggH777TcdOXLE7taue2nQoIEqVaqk//3vf3bl/fr108yZMzVp0iTt379fY8eO1aJFi9S3b9+7Ti9//vyy2WxaunSpzpw5o5iYmFTFkZyEX6yKFSum7t27a8mSJVq+fLk6d+6szZs369atW8qXL5/c3Nzk7++v5557TuPGjdNbb70lSQoLC1P58uWtWxs3bNigo0ePauPGjYqIiLjrRWWfPn20evVqvffee9q3b59mzZqlXbt2KT4+XsuXL9e+fft08eLFJE3cxYoV0+nTpzV69Gjt27dPEyZMsDs5V6lSRT/99JOGDRtm/bodHByscePG6eOPP1bHjh21bt06K84uXbrovffek3T7AnnlypXatGmTIiMj1aVLF0VFRd33+k1JtmzZ5O/vr8mTJ+vAgQNas2aNevfu7dA0XFxcNHfuXJUuXVpPP/10kjjz5s2rtWvX6ty5c6pTp06yXUKnRRwpKVSokGbPnq3IyEj99ttvat26td0dAMkZMWKEgoODValSJX3xxRfas2eP9u/fr+nTp6tMmTKKiYlRvnz55O7urk8//VSHDh3S999/b22/tFaoUCFt2bLF2h/feecdRUREpHr8TJky6eDBg1q2bJmGDx9u7Y8JvL291bVrV/Xr10/Lli3Tnj171LlzZ129elUdO3Z0KM5FixZZt2e3atUq1eenjh07atGiRVq8eLHdPAsVKqRjx45p/vz5OnjwoD755JMUW7wTDB06VCNHjtTHH3+sffv2aefOnZoxY8Zd32n2+eefKz4+XhUrVtTChQu1f/9+RUZG6pNPPrFu1SlYsKBu3rxpbfPZs2dr0qRJqVo+RyWcAy5fvqyGDRsm2WaFChXShQsXdPLkyRTPETly5FDdunXVvn17ffPNN/ecX2q23caNG61z3meffaavv/5aPXv2lHT7O79KlSpq2rSpli9friNHjmjTpk16++23rW7GBw8erC+++EJDhw7V7t27FRkZqQULFujtt9++73Vls9k0Y8YM7du3T0899ZR+/PFHHTp0SDt27ND777+vJk2aWMvo6L50vxKvz19++SVJnYR3v44YMULS7f024fbDo0ePqnr16mrUqJHq1KljXTx7e3urSZMmeueddxQZGWl3J0/hwoXVunVrtWnTRosWLdLhw4cVERGhDz74QD/++KMkqVevXlq+fLkOHz6sbdu2ac2aNUm+H4cNG6bVq1dr165dateunXLkyGH3Xsls2bKpWbNm6tevn+rUqZPsLbF3ehiPrfPnz+uXX37R9u3btWTJEuvYCQ8P15QpU3Tr1i1rue4810u3H6f46aefJElDhgy557F1L6m5DrXZbHrqqac0Z84cVa9eXdLt23rj4uK0evVqq0y6/Z7J48ePq0ePHvrrr7/03XffaciQIerdu7cyZcqUqvP9q6++qoMHD6p3797au3ev5s2bd8/3hnp7e2vq1Kn64Ycf1LhxY61atUpHjhzRli1b1L9/f7366qvW+v8332eOuJ/v/8Q++ugjtW7dWk8//fQ9W//sOPTEmTHm5MmT5rXXXjMhISHGzc3NZMmSxVSsWNF8+OGH5sqVK1a91HZ7n9jevXvNk08+adzd3U3hwoXNsmXLkvQmltpu7+/Us2dPu14eE3Ok2/tTp06ZNm3amBw5chgPDw/z2GOPmc6dO5vo6OhUzz9//vx2XZ3f6fLly1aPN/cyefJkU6NGDZMzZ06rd6V27dqZI0eOWHX27t1rKleubLy8vIx0927vE3f+sWnTJiPpvrq9T9wDnDHGDBs2zAQGBhqbzWbX7X3i+Sbu0S05f/31lylXrpxxdXU1kozNZjO+vr6mbdu2Vqcv8+bNM3nz5jWZMmUymTJlstZBQkcDCa9VyJMnj3F3dzdBQUHmtddeszodSK5TD2Nu9/BXvHhx4+bmZvLly2dGjhxp2rVrZ/z8/EzWrFmNj4+PqVmzpt0+3rZtW1OmTBmTN29e4+XlZRo1apRst/fr1q0z3t7e5uOPP7bKVq5caerWrWuyZctmPD09TdGiRU3fvn2t3hfPnTtnmjRpYrJkyWJy5cpl3n77bdOmTRu7/TC1nbukdGzeGUuxYsWMh4eHKVWqlFm7dq3dukmuxypjkh5jN27cMM2aNTPFihUzL7zwQpJj5uTJk6ZIkSKmQoUK5sKFC0mOq/uJI7mOZRLHtW3bNlO+fHnj4eFhQkNDzddff33X4zXBxYsXzYABA0xoaKhxd3c3AQEBplatWmbx4sXWg87z5s0zBQoUMB4eHqZKlSrm+++/t4sxpY5vkpPSMWbM7U4+7twfu3btagYMGJBkf7xzfSb8n3hZE/bHkiVL2h2T165dMz169LDOgyl1e3/nsvzxxx9256DDhw+bGjVqGC8vLxMcHGwmTJiQ6v306tWrxs/Pz/j5+ZmrV6/aDevXr5/x9/c3WbJkMS+88IIZN26c3TZObh+fO3euKVOmjHF3dzfZsmUzTz311D07Fjh58qTp3r27yZ8/v3F3dzd58uQxjRs3tus2fOzYsSZ37tzGy8vL1K1b13zxxRd26+Vu3z13Sum4Sthud54D/P39jYuLi5FkbeNz584Zf39/4+bmluQckbAvJaz7BQsWGE9PT7Nw4cIU98nUbLv8+fObd99917Ro0cJkzpzZBAQEJOns59KlS6ZHjx4mKCjIuLm5meDgYNO6dWu7TsGWLVtmqlatary8vIyvr6+pWLGiXa/FyR0Lfn5+ZsaMGXddp3v37jVt2rQxQUFBxt3d3eTPn9+0bNnSrrOP+9mXknOvYzvx+qxUqZLx9/dPsj5feukl4+7ubq2f8ePHG0nGzc3N2m/btWtnfHx8zMaNG40x/9eZTnKvOknowa5AgQLGzc3NBAYGmmeffdbqXOq1114zBQsWNB4eHiZnzpzm5Zdftnp+TVimJUuWmMcff9y4u7ubChUqJNuJxurVq410u6fi1HgYjq0E586dM7Vr1zaSjIuLi92xc/z4cSPJeHp62m2rhHO9JFOkSBHrXP/BBx8YT09P8+6776bYyVly5z9Hr0ONud2jpv5/D5wJmjRpYlxcXOzqGXPvbu/vdb43xpglS5aYQoUKGQ8PD1OtWjUzffr0VH2fRUREmGbNmlmdSBUqVMi88sor1muN7uf7LCX32idS8/2f3PkmueO7R48eJnfu3Gbv3r33jMsYY2z/f+J4iBw/flwFChRQRESEypUr5+xwAAAA7tvcuXPVs2dPnTx5MlUdLwCPGod7WUT6uXHjhk6dOqUBAwaocuXKJGP4f+3cX0jTXRzH8c9vWKErIsUpRZApu1FDISIRTJGhC8Q7L2VpIu4qCINdK4wEoxb+u3HEGgSRqFRE9AeiKLYGU7zoYlhX/glDBumFbvjcPO15Vk9B/unn9rxfcC7Oztnve36XH875HQAAMtb6+ro+fvwor9er7u5uwhjwE9v7IhZ74tsHxJFIZM/OQgMAAPwJAwMDqqqqUlFRkTwej9nLAfYtjiwCAAAAgEnYIQMAAAAAkxDIAAAAAMAkBDIAAAAAMAmBDAAAAABMQiADAAAAAJMQyAAA+Ft9fb2uXLmS6p86dUo3b95M9Q3D0OTk5B9fFwAgexHIAAAZx+VyyTCMH1osFtvRcycmJtTX1/fT8cXFRTmdTknSp0+fZBiGotHojmoCAP7fcsxeAAAA29Hc3Cy/35/2W2Fh4Y6emZ+f/8vx4uLiHT0fAIDvsUMGAMhIhw4dUnFxcVq7deuWKisrZbVadfLkSbndbn39+jXtf2/evNGFCxeUl5enY8eOqampSaurq5J+PLL4vX8fWSwpKZEkVVdXyzAM1dfX69WrVzpw4ICWlpbS/nf16lXV1dXt3ssDALIGgQwAkDUsFot8Pp/m5uZ0584dvXjxQteuXUuNR6NRNTY2qry8XG/fvtXr16/V0tKiZDL527VCoZAk6dmzZ1pcXNTExITq6up0+vRpBQKB1LxEIqG7d+/q0qVLO39BAEDW4cgiACAjPXz4UIcPH071nU6n7t+/n+qXlJSor69PPT09Gh4eliQNDAzo7Nmzqb4klZeXb6v+t+ORBQUFaUcZOzs75ff71dvbK0l69OiR1tfX1dbWtq06AIDsxg4ZACAjNTQ0KBqNpprP59PLly/lcDh04sQJHTlyRO3t7fry5YvW1tYk/bNDtpdcLpdisZjevXsnSRofH1dbW5usVuue1gUAZCYCGQAgI1mtVpWVlaXaxsaGLl68qIqKCj148ECRSERDQ0OSpM3NTUlSbm7unq/LZrOppaVFfr9fnz9/1uPHj9XR0bHndQEAmYlABgDICu/fv1cikdDg4KDOnz8vu92uhYWFtDlnzpzR8+fPd6XewYMHJek/vz+7fPmy7t27p7GxMZWWlqq2tnZXagIAsg+BDACQFUpLS5VIJHT79m3Nz88rEAhodHQ0bY7H41E4HJbb7dbs7Kw+fPigkZERrays/HY9m82m3NxcPXnyRMvLy4rH46mxpqYmHT16VP39/VzmAQD4JQIZACArVFVV6caNG7p+/boqKioUDAbl9XrT5tjtdj19+lQzMzM6d+6campqNDU1pZyc37/jKicnRz6fT2NjYzp+/LhaW1tTYxaLRS6XS8lkUu3t7Tt+NwBA9jK2tra2zF4EAADZpqurS8vLy5qenjZ7KQCAfYxr7wEA2EXxeFzhcFjBYFBTU1NmLwcAsM8RyAAA2EWtra0KhULq7u6Ww+EwezkAgH2OI4sAAAAAYBIu9QAAAAAAkxDIAAAAAMAkBDIAAAAAMAmBDAAAAABMQiADAAAAAJMQyAAAAADAJAQyAAAAADAJgQwAAAAATPIXPriB7cSXR/QAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Facilities with consistently high parking availability: ['Gordon Henry St North Car Park', 'Gosford Car Park', 'Revesby Car Park', 'Warriewood Car Park']\n",
      "Facilities with consistently low parking availability: ['Kiama Car Park', 'Mona Vale Car Park', 'Narrabeen Car Park']\n"
     ]
    }
   ],
   "source": [
    "# Calculate average parking availability for each facility\n",
    "avg_availability = processed_df.groupby('facility_name')['parking_availability'].mean().reset_index()\n",
    "\n",
    "# Plot a bar chart to visualize the distribution of average parking availability\n",
    "plt.figure(figsize=(10, 6))\n",
    "sns.barplot(x='facility_name', y='parking_availability', data=avg_availability, palette='Set2')\n",
    "plt.title('Average Parking Availability Across Facilities')\n",
    "plt.xlabel('Facility')\n",
    "plt.ylabel('Average Parking Availability')\n",
    "plt.show()\n",
    "\n",
    "# Identify facilities with consistently high or low parking availability\n",
    "threshold = 70  # Adjust the threshold based on your criteria\n",
    "high_availability_facilities = avg_availability[avg_availability['parking_availability'] >= threshold]['facility_name']\n",
    "low_availability_facilities = avg_availability[avg_availability['parking_availability'] < threshold]['facility_name']\n",
    "\n",
    "print(f'Facilities with consistently high parking availability: {list(high_availability_facilities)}')\n",
    "print(f'Facilities with consistently low parking availability: {list(low_availability_facilities)}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Calculate z-scores for parking availability\n",
    "processed_df['z_score'] = (processed_df['parking_availability'] - processed_df['parking_availability'].mean()) / processed_df['parking_availability'].std()\n",
    "\n",
    "# Set a threshold for anomaly detection (e.g., z-score greater than 3)\n",
    "anomaly_threshold = 3\n",
    "anomalies = processed_df[processed_df['z_score'] > anomaly_threshold]\n",
    "\n",
    "# Visualize anomalies in a scatter plot\n",
    "plt.figure(figsize=(10, 6))\n",
    "sns.scatterplot(x='date', y='parking_availability', data=processed_df, label='Normal', color='blue')\n",
    "sns.scatterplot(x='date', y='parking_availability', data=anomalies, label='Anomalies', color='red', s=100)\n",
    "plt.title('Anomalous Patterns in Parking Availability')\n",
    "plt.xlabel('Date')\n",
    "plt.xticks(rotation=90)\n",
    "plt.ylabel('Parking Availability')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>facility_name</th>\n",
       "      <th>total_parking_spots</th>\n",
       "      <th>occupancy total</th>\n",
       "      <th>day_of_week</th>\n",
       "      <th>date</th>\n",
       "      <th>time</th>\n",
       "      <th>parking_availability</th>\n",
       "      <th>time_category</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Warriewood Car Park</td>\n",
       "      <td>244</td>\n",
       "      <td>20</td>\n",
       "      <td>Friday</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>1900-01-01 00:53:26</td>\n",
       "      <td>224</td>\n",
       "      <td>Night</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Warriewood Car Park</td>\n",
       "      <td>244</td>\n",
       "      <td>19</td>\n",
       "      <td>Friday</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>1900-01-01 00:55:59</td>\n",
       "      <td>225</td>\n",
       "      <td>Night</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Warriewood Car Park</td>\n",
       "      <td>244</td>\n",
       "      <td>18</td>\n",
       "      <td>Friday</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>1900-01-01 01:25:34</td>\n",
       "      <td>226</td>\n",
       "      <td>Night</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Warriewood Car Park</td>\n",
       "      <td>244</td>\n",
       "      <td>17</td>\n",
       "      <td>Friday</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>1900-01-01 01:26:37</td>\n",
       "      <td>227</td>\n",
       "      <td>Night</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Warriewood Car Park</td>\n",
       "      <td>244</td>\n",
       "      <td>16</td>\n",
       "      <td>Friday</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>1900-01-01 01:53:18</td>\n",
       "      <td>228</td>\n",
       "      <td>Night</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78492</th>\n",
       "      <td>Revesby Car Park</td>\n",
       "      <td>934</td>\n",
       "      <td>52</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>2023-12-31</td>\n",
       "      <td>1900-01-01 23:19:07</td>\n",
       "      <td>882</td>\n",
       "      <td>Evening</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78493</th>\n",
       "      <td>Revesby Car Park</td>\n",
       "      <td>934</td>\n",
       "      <td>51</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>2023-12-31</td>\n",
       "      <td>1900-01-01 23:21:53</td>\n",
       "      <td>883</td>\n",
       "      <td>Evening</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78494</th>\n",
       "      <td>Revesby Car Park</td>\n",
       "      <td>934</td>\n",
       "      <td>51</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>2023-12-31</td>\n",
       "      <td>1900-01-01 23:31:53</td>\n",
       "      <td>883</td>\n",
       "      <td>Evening</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78495</th>\n",
       "      <td>Revesby Car Park</td>\n",
       "      <td>934</td>\n",
       "      <td>51</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>2023-12-31</td>\n",
       "      <td>1900-01-01 23:41:54</td>\n",
       "      <td>883</td>\n",
       "      <td>Evening</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78496</th>\n",
       "      <td>Revesby Car Park</td>\n",
       "      <td>934</td>\n",
       "      <td>51</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>2023-12-31</td>\n",
       "      <td>1900-01-01 23:51:56</td>\n",
       "      <td>883</td>\n",
       "      <td>Evening</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>78494 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             facility_name  total_parking_spots  occupancy total day_of_week  \\\n",
       "0      Warriewood Car Park                  244               20      Friday   \n",
       "1      Warriewood Car Park                  244               19      Friday   \n",
       "2      Warriewood Car Park                  244               18      Friday   \n",
       "3      Warriewood Car Park                  244               17      Friday   \n",
       "4      Warriewood Car Park                  244               16      Friday   \n",
       "...                    ...                  ...              ...         ...   \n",
       "78492     Revesby Car Park                  934               52      Sunday   \n",
       "78493     Revesby Car Park                  934               51      Sunday   \n",
       "78494     Revesby Car Park                  934               51      Sunday   \n",
       "78495     Revesby Car Park                  934               51      Sunday   \n",
       "78496     Revesby Car Park                  934               51      Sunday   \n",
       "\n",
       "             date                time  parking_availability time_category  \n",
       "0      2023-12-01 1900-01-01 00:53:26                   224         Night  \n",
       "1      2023-12-01 1900-01-01 00:55:59                   225         Night  \n",
       "2      2023-12-01 1900-01-01 01:25:34                   226         Night  \n",
       "3      2023-12-01 1900-01-01 01:26:37                   227         Night  \n",
       "4      2023-12-01 1900-01-01 01:53:18                   228         Night  \n",
       "...           ...                 ...                   ...           ...  \n",
       "78492  2023-12-31 1900-01-01 23:19:07                   882       Evening  \n",
       "78493  2023-12-31 1900-01-01 23:21:53                   883       Evening  \n",
       "78494  2023-12-31 1900-01-01 23:31:53                   883       Evening  \n",
       "78495  2023-12-31 1900-01-01 23:41:54                   883       Evening  \n",
       "78496  2023-12-31 1900-01-01 23:51:56                   883       Evening  \n",
       "\n",
       "[78494 rows x 8 columns]"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "processed_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th></th>\n",
       "      <th>facility_name</th>\n",
       "      <th>ParkID</th>\n",
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       "  </thead>\n",
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       "      <th>880</th>\n",
       "      <td>Warriewood Car Park</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>244</td>\n",
       "      <td>244</td>\n",
       "      <td>Tuesday</td>\n",
       "      <td>2023-12-05</td>\n",
       "      <td>08:11:24</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>918</th>\n",
       "      <td>Warriewood Car Park</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>244</td>\n",
       "      <td>244</td>\n",
       "      <td>Tuesday</td>\n",
       "      <td>2023-12-05</td>\n",
       "      <td>08:55:38</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>962</th>\n",
       "      <td>Warriewood Car Park</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>244</td>\n",
       "      <td>244</td>\n",
       "      <td>Tuesday</td>\n",
       "      <td>2023-12-05</td>\n",
       "      <td>15:10:08</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6808</th>\n",
       "      <td>Narrabeen Car Park</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>46</td>\n",
       "      <td>46</td>\n",
       "      <td>Monday</td>\n",
       "      <td>2023-12-04</td>\n",
       "      <td>09:02:50</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6811</th>\n",
       "      <td>Narrabeen Car Park</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>46</td>\n",
       "      <td>46</td>\n",
       "      <td>Monday</td>\n",
       "      <td>2023-12-04</td>\n",
       "      <td>09:20:03</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
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       "    <tr>\n",
       "      <th>28217</th>\n",
       "      <td>Kiama Car Park</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>42</td>\n",
       "      <td>42</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>2023-12-31</td>\n",
       "      <td>20:00:02</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28219</th>\n",
       "      <td>Kiama Car Park</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>42</td>\n",
       "      <td>42</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>2023-12-31</td>\n",
       "      <td>20:45:57</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28221</th>\n",
       "      <td>Kiama Car Park</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>42</td>\n",
       "      <td>42</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>2023-12-31</td>\n",
       "      <td>21:16:04</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34284</th>\n",
       "      <td>Gosford Car Park</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1057</td>\n",
       "      <td>1057</td>\n",
       "      <td>Tuesday</td>\n",
       "      <td>2023-12-05</td>\n",
       "      <td>10:03:58</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60460</th>\n",
       "      <td>Gosford Car Park</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1057</td>\n",
       "      <td>1057</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>2023-12-31</td>\n",
       "      <td>19:31:28</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>819 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             facility_name  ParkID zone_id  total_parking_spots  \\\n",
       "880    Warriewood Car Park       1       1                  244   \n",
       "918    Warriewood Car Park       1       1                  244   \n",
       "962    Warriewood Car Park       1       1                  244   \n",
       "6808    Narrabeen Car Park       1       1                   46   \n",
       "6811    Narrabeen Car Park       1       1                   46   \n",
       "...                    ...     ...     ...                  ...   \n",
       "28217       Kiama Car Park       1       1                   42   \n",
       "28219       Kiama Car Park       1       1                   42   \n",
       "28221       Kiama Car Park       1       1                   42   \n",
       "34284     Gosford Car Park       1       1                 1057   \n",
       "60460     Gosford Car Park       1       1                 1057   \n",
       "\n",
       "       occupancy total day_of_week        date      time  parking_availability  \n",
       "880                244     Tuesday  2023-12-05  08:11:24                     0  \n",
       "918                244     Tuesday  2023-12-05  08:55:38                     0  \n",
       "962                244     Tuesday  2023-12-05  15:10:08                     0  \n",
       "6808                46      Monday  2023-12-04  09:02:50                     0  \n",
       "6811                46      Monday  2023-12-04  09:20:03                     0  \n",
       "...                ...         ...         ...       ...                   ...  \n",
       "28217               42      Sunday  2023-12-31  20:00:02                     0  \n",
       "28219               42      Sunday  2023-12-31  20:45:57                     0  \n",
       "28221               42      Sunday  2023-12-31  21:16:04                     0  \n",
       "34284             1057     Tuesday  2023-12-05  10:03:58                     0  \n",
       "60460             1057      Sunday  2023-12-31  19:31:28                     0  \n",
       "\n",
       "[819 rows x 9 columns]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "carparks_df_copy.loc[carparks_df_copy.parking_availability == 0]"
   ]
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