WeatherPy.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import the requests library.\n",
    "import requests\n",
    "import numpy as np\n",
    "\n",
    "# Import the API key.\n",
    "from config import weather_api_key\n",
    "\n",
    "# Import the time library and the datetime module from the datetime library \n",
    "import time\n",
    "from datetime import datetime\n",
    "from citipy import citipy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "25.12903645 -67.59741259\n",
      "25.92017388 11.09532135\n",
      "26.62509167 74.84233102\n",
      "-59.98969384 -76.89176677\n",
      "37.30571269 -61.13376282\n",
      "castro cl\n",
      "clyde river ca\n",
      "nizhneyansk ru\n",
      "vaini to\n",
      "luderitz na\n",
      "dicabisagan ph\n",
      "bluff nz\n",
      "kutum sd\n",
      "rikitea pf\n",
      "ulladulla au\n",
      "provideniya ru\n",
      "zlatoust ru\n",
      "ribeira grande pt\n",
      "whitianga nz\n",
      "umm lajj sa\n",
      "hilo us\n",
      "hasaki jp\n",
      "ushuaia ar\n",
      "peto mx\n",
      "albany au\n",
      "atuona pf\n",
      "batagay-alyta ru\n",
      "baisha cn\n",
      "torbay ca\n",
      "inhambane mz\n",
      "lang son vn\n",
      "barrow us\n",
      "jiuquan cn\n",
      "arraial do cabo br\n",
      "kavieng pg\n",
      "cape town za\n",
      "busselton au\n",
      "clyde river ca\n",
      "mataura pf\n",
      "mareeba au\n",
      "rikitea pf\n",
      "nhulunbuy au\n",
      "pontes e lacerda br\n",
      "puerto madryn ar\n",
      "port alfred za\n",
      "roma au\n",
      "pisco pe\n",
      "rikitea pf\n",
      "atuona pf\n",
      "quchan ir\n",
      "churapcha ru\n",
      "vaini to\n",
      "hermanus za\n",
      "ushuaia ar\n",
      "tirumullaivasal in\n",
      "faya td\n",
      "luwuk id\n",
      "kapaa us\n",
      "mys shmidta ru\n",
      "rikitea pf\n",
      "zhigansk ru\n",
      "tuatapere nz\n",
      "atuona pf\n",
      "the valley ai\n",
      "linxia cn\n",
      "mouzakion gr\n",
      "arraial do cabo br\n",
      "port alfred za\n",
      "taolanaro mg\n",
      "poum nc\n",
      "kearney us\n",
      "huilong cn\n",
      "georgetown sh\n",
      "geraldton au\n",
      "rikitea pf\n",
      "pevek ru\n",
      "tigzirt dz\n",
      "barentsburg sj\n",
      "kruisfontein za\n",
      "bambous virieux mu\n",
      "la brea pe\n",
      "timmins ca\n",
      "mouzouras gr\n",
      "baykit ru\n",
      "ushuaia ar\n",
      "laguna br\n",
      "puerto ayora ec\n",
      "tyup kg\n",
      "cabildo cl\n",
      "hermanus za\n",
      "el alto pe\n",
      "illoqqortoormiut gl\n",
      "nikolskoye ru\n",
      "yellowknife ca\n",
      "aykhal ru\n",
      "vaini to\n",
      "winchester us\n",
      "qaanaaq gl\n",
      "fairbanks us\n",
      "mataura pf\n",
      "dikson ru\n",
      "kodinsk ru\n",
      "hilo us\n",
      "attawapiskat ca\n",
      "chokurdakh ru\n",
      "cidreira br\n",
      "hilo us\n",
      "mys shmidta ru\n",
      "amapa br\n",
      "upernavik gl\n",
      "amderma ru\n",
      "yellowknife ca\n",
      "illoqqortoormiut gl\n",
      "namibe ao\n",
      "punta arenas cl\n",
      "taolanaro mg\n",
      "ushuaia ar\n",
      "cloquet us\n",
      "atuona pf\n",
      "rikitea pf\n",
      "illoqqortoormiut gl\n",
      "traverse city us\n",
      "katsuura jp\n",
      "mount isa au\n",
      "upernavik gl\n",
      "broome au\n",
      "new norfolk au\n",
      "rikitea pf\n",
      "karaul ru\n",
      "vaini to\n",
      "hermanus za\n",
      "carnarvon au\n",
      "barra dos coqueiros br\n",
      "new norfolk au\n",
      "ushuaia ar\n",
      "zhigansk ru\n",
      "mataura pf\n",
      "mataura pf\n",
      "hermanus za\n",
      "cape town za\n",
      "coquimbo cl\n",
      "busselton au\n",
      "ushuaia ar\n",
      "bluff nz\n",
      "lompoc us\n",
      "busselton au\n",
      "hasaki jp\n",
      "lebu cl\n",
      "ilulissat gl\n",
      "new norfolk au\n",
      "pevek ru\n",
      "hamilton bm\n",
      "keti bandar pk\n",
      "half moon bay us\n",
      "nizhneyansk ru\n",
      "amot no\n",
      "olafsvik is\n",
      "nikolskoye ru\n",
      "ribeira grande pt\n",
      "maroon town jm\n",
      "vaini to\n",
      "alice springs au\n",
      "bintulu my\n",
      "mataura pf\n",
      "yulara au\n",
      "airai pw\n",
      "canutama br\n",
      "saskylakh ru\n",
      "hasaki jp\n",
      "taolanaro mg\n",
      "valparaiso cl\n",
      "pevek ru\n",
      "saint george bm\n",
      "hamilton bm\n",
      "upernavik gl\n",
      "stefan cel mare ro\n",
      "vaini to\n",
      "new norfolk au\n",
      "tarudant ma\n",
      "muros es\n",
      "tsihombe mg\n",
      "salalah om\n",
      "tual id\n",
      "marsa matruh eg\n",
      "korla cn\n",
      "leningradskiy ru\n",
      "ilulissat gl\n",
      "necochea ar\n",
      "lodja cd\n",
      "kruisfontein za\n",
      "zabol ir\n",
      "tuktoyaktuk ca\n",
      "jamestown sh\n",
      "port elizabeth za\n",
      "soe id\n",
      "tateyama jp\n",
      "arraial do cabo br\n",
      "ketchikan us\n",
      "dikson ru\n",
      "avanigadda in\n",
      "chokurdakh ru\n",
      "igarka ru\n",
      "taolanaro mg\n",
      "torbay ca\n",
      "rikitea pf\n",
      "mataura pf\n",
      "fairlie nz\n",
      "doctor pedro p. pena py\n",
      "ushuaia ar\n",
      "atuona pf\n",
      "comodoro rivadavia ar\n",
      "ust-nera ru\n",
      "kudat my\n",
      "kamaishi jp\n",
      "nouadhibou mr\n",
      "port hardy ca\n",
      "stepnogorsk kz\n",
      "tuatapere nz\n",
      "busselton au\n",
      "hoa binh vn\n",
      "vaini to\n",
      "ballina au\n",
      "port augusta au\n",
      "mandalgovi mn\n",
      "norman wells ca\n",
      "maniitsoq gl\n",
      "albany au\n",
      "cape town za\n",
      "albany au\n",
      "arraial do cabo br\n",
      "rikitea pf\n",
      "punta arenas cl\n",
      "upernavik gl\n",
      "klaksvik fo\n",
      "vaini to\n",
      "albany au\n",
      "jamestown sh\n",
      "samusu ws\n",
      "butaritari ki\n",
      "atuona pf\n",
      "lucea jm\n",
      "nikolskoye ru\n",
      "busselton au\n",
      "san patricio mx\n",
      "castro cl\n",
      "kapaa us\n",
      "dikson ru\n",
      "faanui pf\n",
      "college us\n",
      "sedro-woolley us\n",
      "rikitea pf\n",
      "norman wells ca\n",
      "pimentel pe\n",
      "new norfolk au\n",
      "hobart au\n",
      "tumannyy ru\n",
      "hambantota lk\n",
      "mys shmidta ru\n",
      "severo-kurilsk ru\n",
      "luganville vu\n",
      "mataura pf\n",
      "qaanaaq gl\n",
      "ushuaia ar\n",
      "mataura pf\n",
      "yellowknife ca\n",
      "havre-saint-pierre ca\n",
      "georgetown sh\n",
      "rikitea pf\n",
      "thompson ca\n",
      "sao miguel br\n",
      "alyangula au\n",
      "punta arenas cl\n",
      "hofn is\n",
      "ulaangom mn\n",
      "stoyba ru\n",
      "albany au\n",
      "beaverlodge ca\n",
      "bredasdorp za\n",
      "taolanaro mg\n",
      "millau fr\n",
      "roald no\n",
      "yellowknife ca\n",
      "haines junction ca\n",
      "taolanaro mg\n",
      "illoqqortoormiut gl\n",
      "puerto baquerizo moreno ec\n",
      "sinjar iq\n",
      "taolanaro mg\n",
      "rikitea pf\n",
      "mataura pf\n",
      "shimoda jp\n",
      "mataura pf\n",
      "busselton au\n",
      "ushuaia ar\n",
      "sant julia de loria ad\n",
      "manyana bw\n",
      "abnub eg\n",
      "nisia floresta br\n",
      "kapaa us\n",
      "sentyabrskiy ru\n",
      "port alfred za\n",
      "arraial do cabo br\n",
      "miraflores co\n",
      "cabo san lucas mx\n",
      "verkhnetulomskiy ru\n",
      "severobaykalsk ru\n",
      "zhigansk ru\n",
      "lautaro cl\n",
      "mazzarino it\n",
      "punta arenas cl\n",
      "hobart au\n",
      "bluff nz\n",
      "barrow us\n",
      "acarau br\n",
      "metro id\n",
      "bengkulu id\n",
      "bethel us\n",
      "umzimvubu za\n",
      "hasaki jp\n",
      "hobart au\n",
      "hof no\n",
      "faya td\n",
      "illoqqortoormiut gl\n",
      "pacific grove us\n",
      "zyryanka ru\n",
      "atasu kz\n",
      "severo-kurilsk ru\n",
      "puyo ec\n",
      "carnarvon au\n",
      "butaritari ki\n",
      "victoria sc\n",
      "albany au\n",
      "seoul kr\n",
      "rikitea pf\n",
      "kapaa us\n",
      "taolanaro mg\n",
      "kodiak us\n",
      "sao filipe cv\n",
      "te anau nz\n",
      "rikitea pf\n",
      "hilo us\n",
      "abonnema ng\n",
      "camacha pt\n",
      "kaitangata nz\n",
      "la ronge ca\n",
      "colgong in\n",
      "barrow us\n",
      "mecca sa\n",
      "saint-pierre pm\n",
      "kapaa us\n",
      "arcachon fr\n",
      "richards bay za\n",
      "esperance au\n",
      "taolanaro mg\n",
      "ushuaia ar\n",
      "rikitea pf\n",
      "ponta do sol cv\n",
      "nauta pe\n",
      "jamestown sh\n",
      "fare pf\n",
      "rikitea pf\n",
      "thompson ca\n",
      "cape town za\n",
      "clyde river ca\n",
      "cabo san lucas mx\n",
      "kaitangata nz\n",
      "chuy uy\n",
      "nanortalik gl\n",
      "albany au\n",
      "mataura pf\n",
      "caravelas br\n",
      "stromness gb\n",
      "new norfolk au\n",
      "bathsheba bb\n",
      "praia da vitoria pt\n",
      "gazanjyk tm\n",
      "mataura pf\n",
      "nikolskoye ru\n",
      "bolonchen mx\n",
      "algiers dz\n",
      "saint-philippe re\n",
      "gwembe zm\n",
      "dikson ru\n",
      "yulara au\n",
      "belushya guba ru\n",
      "mys shmidta ru\n",
      "new norfolk au\n",
      "rikitea pf\n",
      "nemuro jp\n",
      "castro cl\n",
      "kavieng pg\n",
      "jamestown sh\n",
      "pevek ru\n",
      "yellowknife ca\n",
      "bredasdorp za\n",
      "barentsburg sj\n",
      "myitkyina mm\n",
      "butaritari ki\n",
      "cabo san lucas mx\n",
      "bethel us\n",
      "zhoucheng cn\n",
      "poya nc\n",
      "progreso mx\n",
      "saint george bm\n",
      "tsihombe mg\n",
      "saint george bm\n",
      "rikitea pf\n",
      "dudinka ru\n",
      "balakhta ru\n",
      "ushuaia ar\n",
      "sitka us\n",
      "sobolevo ru\n",
      "lompoc us\n",
      "port alfred za\n",
      "salento co\n",
      "sucha beskidzka pl\n",
      "narsaq gl\n",
      "castro cl\n",
      "hilo us\n",
      "booue ga\n",
      "armidale au\n",
      "tiksi ru\n",
      "arraial do cabo br\n",
      "tuktoyaktuk ca\n",
      "vaini to\n",
      "bethel us\n",
      "pevek ru\n",
      "jamestown sh\n",
      "aitape pg\n",
      "were ilu et\n",
      "kapaa us\n",
      "toliary mg\n",
      "tema gh\n",
      "vaini to\n",
      "atuona pf\n",
      "savannah bight hn\n",
      "necochea ar\n",
      "rikitea pf\n",
      "ilebo cd\n",
      "rikitea pf\n",
      "illoqqortoormiut gl\n",
      "umm lajj sa\n",
      "rikitea pf\n",
      "cape town za\n",
      "kununurra au\n",
      "karpogory ru\n",
      "doha kw\n",
      "cape town za\n",
      "san policarpo ph\n",
      "clyde river ca\n",
      "kangaatsiaq gl\n",
      "geraldton au\n",
      "rikitea pf\n",
      "los llanos de aridane es\n",
      "rikitea pf\n",
      "itoman jp\n",
      "punta arenas cl\n",
      "aklavik ca\n",
      "lebu cl\n",
      "bredasdorp za\n",
      "reconquista ar\n",
      "poum nc\n",
      "hobart au\n",
      "simao cn\n",
      "mataura pf\n",
      "ahipara nz\n",
      "port alfred za\n",
      "lashio mm\n",
      "laguna br\n",
      "abu zabad sd\n",
      "tulum mx\n",
      "mataura pf\n",
      "basco ph\n",
      "puerto ayora ec\n",
      "hobart au\n",
      "saint-leu re\n",
      "awjilah ly\n",
      "torbay ca\n",
      "ushuaia ar\n",
      "vaini to\n",
      "rikitea pf\n",
      "padang id\n",
      "tuktoyaktuk ca\n",
      "yellowknife ca\n",
      "busselton au\n",
      "albany au\n",
      "sigli id\n",
      "bluff nz\n",
      "rikitea pf\n",
      "hermanus za\n",
      "hilo us\n",
      "ponta do sol cv\n",
      "san jose gt\n",
      "marinette us\n",
      "najran sa\n",
      "klaksvik fo\n",
      "busselton au\n",
      "pilar ph\n",
      "illoqqortoormiut gl\n",
      "saryozek kz\n",
      "jamestown sh\n",
      "northam au\n",
      "chester ca\n",
      "ojinaga mx\n",
      "lavrentiya ru\n",
      "giresun tr\n",
      "jamestown sh\n",
      "ushuaia ar\n",
      "ushuaia ar\n",
      "faya td\n",
      "touros br\n",
      "saint-joseph re\n",
      "cape town za\n",
      "rikitea pf\n",
      "hermanus za\n",
      "bluff nz\n",
      "nikolskoye ru\n",
      "umm durman sd\n",
      "wattegama lk\n",
      "puerto narino co\n",
      "bredasdorp za\n",
      "bengkulu id\n",
      "port hawkesbury ca\n",
      "sao filipe cv\n",
      "hermanus za\n",
      "ferrol es\n",
      "punta arenas cl\n",
      "samarai pg\n",
      "acarau br\n",
      "geraldton au\n",
      "mataura pf\n",
      "bethel us\n",
      "mataura pf\n",
      "mataura pf\n",
      "arraial do cabo br\n",
      "barrow us\n",
      "usinsk ru\n",
      "albany au\n",
      "tasiilaq gl\n",
      "uthal pk\n",
      "aanekoski fi\n",
      "mehamn no\n",
      "santa rosalia mx\n",
      "yellowknife ca\n",
      "ushuaia ar\n",
      "yellowknife ca\n",
      "new norfolk au\n",
      "dikson ru\n",
      "taolanaro mg\n",
      "port elizabeth za\n",
      "barrow us\n",
      "vaini to\n",
      "illoqqortoormiut gl\n",
      "rikitea pf\n",
      "punta arenas cl\n",
      "grand river south east mu\n",
      "hamilton bm\n",
      "quang ngai vn\n",
      "hermanus za\n",
      "taolanaro mg\n",
      "port alfred za\n",
      "eskilstuna se\n",
      "fortuna us\n",
      "hilo us\n",
      "matara lk\n",
      "ambon id\n",
      "yabelo et\n",
      "teluk intan my\n",
      "beira mz\n",
      "port elizabeth za\n",
      "bethel us\n",
      "arraial do cabo br\n",
      "hofn is\n",
      "khatanga ru\n",
      "ushuaia ar\n",
      "vaini to\n",
      "bengkulu id\n",
      "sao joao da barra br\n",
      "disna by\n",
      "toamasina mg\n",
      "bethanien na\n",
      "albany au\n",
      "vaini to\n",
      "sampang id\n",
      "gogrial sd\n",
      "bethel us\n",
      "pindiga ng\n",
      "qaanaaq gl\n",
      "kalocsa hu\n",
      "albany au\n",
      "ribeira grande pt\n",
      "kayerkan ru\n",
      "rikitea pf\n",
      "taolanaro mg\n",
      "ilulissat gl\n",
      "rayachoti in\n",
      "mahebourg mu\n",
      "koster za\n",
      "saskylakh ru\n",
      "samusu ws\n",
      "hermanus za\n",
      "saint george bm\n",
      "pingliang cn\n",
      "hobart au\n",
      "san luis potosi mx\n",
      "bengkulu id\n",
      "nabire id\n",
      "mahebourg mu\n",
      "paka my\n",
      "ponta do sol cv\n",
      "butaritari ki\n",
      "illoqqortoormiut gl\n",
      "vaini to\n",
      "itoman jp\n",
      "talcahuano cl\n",
      "norman wells ca\n",
      "srandakan id\n",
      "chuy uy\n",
      "leningradskiy ru\n",
      "semnan ir\n",
      "bredasdorp za\n",
      "hambantota lk\n",
      "birao cf\n",
      "dikson ru\n",
      "sarai ru\n",
      "castro cl\n",
      "qaanaaq gl\n",
      "grand centre ca\n",
      "tekax mx\n",
      "vaini to\n",
      "yellowknife ca\n",
      "vaini to\n",
      "tiksi ru\n",
      "punta arenas cl\n",
      "klaksvik fo\n",
      "cape town za\n",
      "klaipeda lt\n",
      "qaanaaq gl\n",
      "albany au\n",
      "hermanus za\n",
      "mackay au\n",
      "tuktoyaktuk ca\n",
      "puerto ayora ec\n",
      "lompoc us\n",
      "asfi ma\n",
      "port elizabeth za\n",
      "cape town za\n",
      "amapa br\n",
      "balaguer es\n",
      "dikson ru\n",
      "matehuala mx\n",
      "port alfred za\n",
      "bathsheba bb\n",
      "taolanaro mg\n",
      "castro cl\n",
      "verkhoyansk ru\n",
      "ushuaia ar\n",
      "kaitangata nz\n",
      "hilo us\n",
      "leningradskiy ru\n",
      "touros br\n",
      "rikitea pf\n",
      "toftir fo\n",
      "ketchikan us\n",
      "guastalla it\n",
      "along in\n",
      "bafoulabe ml\n",
      "hailey us\n",
      "port macquarie au\n",
      "taolanaro mg\n",
      "ushuaia ar\n",
      "dawlatabad af\n",
      "punta arenas cl\n",
      "punta arenas cl\n",
      "mar del plata ar\n",
      "barrow us\n",
      "barentsburg sj\n",
      "hasaki jp\n",
      "port alfred za\n",
      "punta arenas cl\n",
      "mayo ca\n",
      "rikitea pf\n",
      "severomuysk ru\n",
      "bredasdorp za\n",
      "kaitangata nz\n",
      "atuona pf\n",
      "bluff nz\n",
      "coquimbo cl\n",
      "jeremie ht\n",
      "naze jp\n",
      "san patricio mx\n",
      "petropavlovsk-kamchatskiy ru\n",
      "kapaa us\n",
      "ushuaia ar\n",
      "port elizabeth za\n",
      "kavieng pg\n",
      "rikitea pf\n",
      "port elizabeth za\n",
      "punta arenas cl\n",
      "jalu ly\n",
      "albany au\n",
      "ushuaia ar\n",
      "tuktoyaktuk ca\n",
      "hilo us\n",
      "mataura pf\n",
      "aswan eg\n",
      "waitati nz\n",
      "dolbeau ca\n",
      "yumen cn\n",
      "hobart au\n",
      "pangnirtung ca\n",
      "provideniya ru\n",
      "grand river south east mu\n",
      "punta arenas cl\n",
      "saint-philippe re\n",
      "qaanaaq gl\n",
      "illoqqortoormiut gl\n",
      "broome au\n",
      "cidreira br\n",
      "atuona pf\n",
      "bengkulu id\n",
      "sattahip th\n",
      "bhadrachalam in\n",
      "mataura pf\n",
      "punta arenas cl\n",
      "rikitea pf\n",
      "hutchinson us\n",
      "punta arenas cl\n",
      "mar del plata ar\n",
      "albany au\n",
      "taolanaro mg\n",
      "taolanaro mg\n",
      "sabancuy mx\n",
      "henties bay na\n",
      "avarua ck\n",
      "mataura pf\n",
      "ilulissat gl\n",
      "albany au\n",
      "sobolevo ru\n",
      "lata sb\n",
      "burnie au\n",
      "marienburg sr\n",
      "albany au\n",
      "avarua ck\n",
      "guerrero negro mx\n",
      "bougouni ml\n",
      "ushuaia ar\n",
      "provideniya ru\n",
      "ushuaia ar\n",
      "adeje es\n",
      "tigil ru\n",
      "busselton au\n",
      "vaini to\n",
      "taolanaro mg\n",
      "albany au\n",
      "kapaa us\n",
      "tarko-sale ru\n",
      "tuatapere nz\n",
      "boyolangu id\n",
      "santa isabel mx\n",
      "xinpu cn\n",
      "ushuaia ar\n",
      "hermanus za\n",
      "vianopolis br\n",
      "barentsburg sj\n",
      "albany au\n",
      "punta arenas cl\n",
      "sept-iles ca\n",
      "cherskiy ru\n",
      "bethel us\n",
      "mataura pf\n",
      "neftcala az\n",
      "ponta do sol pt\n",
      "palabuhanratu id\n",
      "luleburgaz tr\n",
      "albany au\n",
      "yellowknife ca\n",
      "cidreira br\n",
      "hilo us\n",
      "kapaa us\n",
      "westport ie\n",
      "cape town za\n",
      "barentsburg sj\n",
      "kinshasa cd\n",
      "vaini to\n",
      "ilulissat gl\n",
      "santa isabel do rio negro br\n",
      "bredasdorp za\n",
      "cape town za\n",
      "mataura pf\n",
      "atuona pf\n",
      "meulaboh id\n",
      "thompson ca\n",
      "saskylakh ru\n",
      "borogontsy ru\n",
      "taolanaro mg\n",
      "sungaipenuh id\n",
      "yellowknife ca\n",
      "mataura pf\n",
      "petropavlovsk-kamchatskiy ru\n",
      "yellowknife ca\n",
      "spisske podhradie sk\n",
      "mataura pf\n",
      "timra se\n",
      "punta arenas cl\n",
      "san quintin mx\n",
      "nacala mz\n",
      "lasa cn\n",
      "tasiilaq gl\n",
      "mataura pf\n",
      "ushuaia ar\n",
      "isangel vu\n",
      "cidreira br\n",
      "sao luiz gonzaga br\n",
      "iracoubo gf\n",
      "cape town za\n",
      "geraldton au\n",
      "pevek ru\n",
      "wahran dz\n",
      "vila velha br\n",
      "kapaa us\n",
      "bluff nz\n",
      "ushuaia ar\n",
      "hobart au\n",
      "kongoussi bf\n",
      "dikson ru\n",
      "avarua ck\n",
      "naze jp\n",
      "punta arenas cl\n",
      "aguas vermelhas br\n",
      "kaitangata nz\n",
      "sinnamary gf\n",
      "amderma ru\n",
      "rikitea pf\n",
      "sandpoint us\n",
      "matara lk\n",
      "cape town za\n",
      "belushya guba ru\n",
      "bethel us\n",
      "carnarvon au\n",
      "torbay ca\n",
      "airai pw\n",
      "mataura pf\n",
      "vaitupu wf\n",
      "mataura pf\n",
      "norman wells ca\n",
      "anori br\n",
      "mana gf\n",
      "new norfolk au\n",
      "ushuaia ar\n",
      "cape town za\n",
      "severo-kurilsk ru\n",
      "umzimvubu za\n",
      "puerto ayora ec\n",
      "lufilufi ws\n",
      "lompoc us\n",
      "sargur in\n",
      "puerto ayora ec\n",
      "iqaluit ca\n",
      "jamestown sh\n",
      "vaini to\n",
      "yatou cn\n",
      "rockland us\n",
      "kruisfontein za\n",
      "kinsale ie\n",
      "clyde river ca\n",
      "petropavlovsk-kamchatskiy ru\n",
      "turbat pk\n",
      "vaini to\n",
      "pangnirtung ca\n",
      "narsaq gl\n",
      "mandurah au\n",
      "mataura pf\n",
      "souillac mu\n",
      "new norfolk au\n",
      "carnarvon au\n",
      "kapaa us\n",
      "rikitea pf\n",
      "ilulissat gl\n",
      "cape town za\n",
      "palmer us\n",
      "thompson ca\n",
      "nanortalik gl\n",
      "benalla au\n",
      "chuy uy\n",
      "nome us\n",
      "garissa ke\n",
      "kailua us\n",
      "rikitea pf\n",
      "kapaa us\n",
      "mogadishu so\n",
      "port elizabeth za\n",
      "rikitea pf\n",
      "ushuaia ar\n",
      "chhabra in\n",
      "caxito ao\n",
      "nanortalik gl\n",
      "bluff nz\n",
      "bambous virieux mu\n",
      "mataura pf\n",
      "hermanus za\n",
      "san lorenzo bo\n",
      "rikitea pf\n",
      "vestmannaeyjar is\n",
      "chokurdakh ru\n",
      "cherskiy ru\n",
      "punta arenas cl\n",
      "tasiilaq gl\n",
      "illoqqortoormiut gl\n",
      "eucaliptus bo\n",
      "rikitea pf\n",
      "vaini to\n",
      "qaanaaq gl\n",
      "hilo us\n",
      "upernavik gl\n",
      "padang id\n",
      "illoqqortoormiut gl\n",
      "jamestown sh\n",
      "albany au\n",
      "busselton au\n",
      "labuhan id\n",
      "chumikan ru\n",
      "chuy uy\n",
      "san patricio mx\n",
      "albany au\n",
      "ushuaia ar\n",
      "minas cu\n",
      "bluff nz\n",
      "tanout ne\n",
      "ushuaia ar\n",
      "bengkulu id\n",
      "gushikawa jp\n",
      "norman wells ca\n",
      "barrow us\n",
      "punta arenas cl\n",
      "kamina cd\n",
      "butaritari ki\n",
      "vostok ru\n",
      "lavrentiya ru\n",
      "bluff nz\n",
      "ushuaia ar\n",
      "campbell river ca\n",
      "souillac mu\n",
      "kudahuvadhoo mv\n",
      "serafimovich ru\n",
      "busselton au\n",
      "chokurdakh ru\n",
      "port moresby pg\n",
      "nathdwara in\n",
      "sakaiminato jp\n",
      "kireyevsk ru\n",
      "new norfolk au\n",
      "bluff nz\n",
      "saint george bm\n",
      "severo-kurilsk ru\n",
      "minsk by\n",
      "new norfolk au\n",
      "ushuaia ar\n",
      "inhambane mz\n",
      "rikitea pf\n",
      "mys shmidta ru\n",
      "talnakh ru\n",
      "xuddur so\n",
      "cabo san lucas mx\n",
      "whitefish us\n",
      "jamestown sh\n",
      "rawlins us\n",
      "punta arenas cl\n",
      "puerto ayora ec\n",
      "alotau pg\n",
      "novyy urengoy ru\n",
      "yerbogachen ru\n",
      "port elizabeth za\n",
      "attawapiskat ca\n",
      "jishui cn\n",
      "sentyabrskiy ru\n",
      "barrow us\n",
      "yunjinghong cn\n",
      "pangnirtung ca\n",
      "mahebourg mu\n",
      "codrington ag\n",
      "port-cartier ca\n",
      "manavalakurichi in\n",
      "puerto ayora ec\n",
      "chuy uy\n",
      "kuche cn\n",
      "teopisca mx\n",
      "thompson ca\n",
      "bac lieu vn\n",
      "bluff nz\n",
      "busselton au\n",
      "rikitea pf\n",
      "port elizabeth za\n",
      "mys shmidta ru\n",
      "puerto ayora ec\n",
      "najran sa\n",
      "asau tv\n",
      "ensley us\n",
      "saint-pierre pm\n",
      "port lincoln au\n",
      "bengkulu id\n",
      "lufilufi ws\n",
      "kapaa us\n",
      "karratha au\n",
      "bambous virieux mu\n",
      "chuy uy\n",
      "barrow us\n",
      "saint-philippe re\n",
      "constitucion mx\n",
      "mataura pf\n",
      "busselton au\n",
      "nizhneyansk ru\n",
      "puerto ayora ec\n",
      "kupang id\n",
      "hobart au\n",
      "atuona pf\n",
      "amderma ru\n",
      "mataura pf\n",
      "punta arenas cl\n",
      "ushuaia ar\n",
      "yerofey pavlovich ru\n",
      "yulara au\n",
      "taolanaro mg\n",
      "gornopravdinsk ru\n",
      "castro cl\n",
      "port elizabeth za\n",
      "punta arenas cl\n",
      "dikson ru\n",
      "lyngseidet no\n",
      "cape town za\n",
      "edd er\n",
      "los llanos de aridane es\n",
      "dikson ru\n",
      "rikitea pf\n",
      "karratha au\n",
      "tanout ne\n",
      "rikitea pf\n",
      "lorengau pg\n",
      "egvekinot ru\n",
      "attawapiskat ca\n",
      "hilo us\n",
      "tuktoyaktuk ca\n",
      "buzuluk ru\n",
      "bluff nz\n",
      "illoqqortoormiut gl\n",
      "ushuaia ar\n",
      "butaritari ki\n",
      "ribeira grande pt\n",
      "rikitea pf\n",
      "kyzyl ru\n",
      "la paz mx\n",
      "nemuro jp\n",
      "georgetown sh\n",
      "guerrero negro mx\n",
      "torbay ca\n",
      "mataura pf\n",
      "belushya guba ru\n",
      "butaritari ki\n",
      "sao francisco br\n",
      "hammerfest no\n",
      "taoudenni ml\n",
      "provideniya ru\n",
      "adrar dz\n",
      "busselton au\n",
      "airai pw\n",
      "bluff nz\n",
      "cape town za\n",
      "port alfred za\n",
      "maracaibo ve\n",
      "taolanaro mg\n",
      "kutum sd\n",
      "cape town za\n",
      "carutapera br\n",
      "vanavara ru\n",
      "new norfolk au\n",
      "kropotkin ru\n",
      "avarua ck\n",
      "cabo san lucas mx\n",
      "severo-kurilsk ru\n",
      "bambous virieux mu\n",
      "saint george bm\n",
      "victoria sc\n",
      "labutta mm\n",
      "jamestown sh\n",
      "surin th\n",
      "bluff nz\n",
      "ambilobe mg\n",
      "mount gambier au\n",
      "tambopata pe\n",
      "taolanaro mg\n",
      "illoqqortoormiut gl\n",
      "hasaki jp\n",
      "marmande fr\n",
      "tchollire cm\n",
      "busselton au\n",
      "ternate id\n",
      "kapaa us\n",
      "vaitupu wf\n",
      "bethel us\n",
      "bluff nz\n",
      "tsienyane bw\n",
      "weihe cn\n",
      "mataura pf\n",
      "busselton au\n",
      "victoria sc\n",
      "attawapiskat ca\n",
      "severo-kurilsk ru\n",
      "kodiak us\n",
      "faanui pf\n",
      "rikitea pf\n",
      "albany au\n",
      "puerto ayora ec\n",
      "sotouboua tg\n",
      "narsaq gl\n",
      "hermanus za\n",
      "new norfolk au\n",
      "belushya guba ru\n",
      "bredasdorp za\n",
      "qaanaaq gl\n",
      "sao filipe cv\n",
      "barentsburg sj\n",
      "torbay ca\n",
      "teguise es\n",
      "samfya zm\n",
      "xichang cn\n",
      "cepelare bg\n",
      "palabuhanratu id\n",
      "pleasanton us\n",
      "butaritari ki\n",
      "new norfolk au\n",
      "arraial do cabo br\n",
      "chokurdakh ru\n",
      "ilulissat gl\n",
      "kamenskoye ru\n",
      "hilo us\n",
      "busselton au\n",
      "samusu ws\n",
      "kahului us\n",
      "bluff nz\n",
      "tsihombe mg\n",
      "aklavik ca\n",
      "asheville us\n",
      "rio grande br\n",
      "port-gentil ga\n",
      "castro cl\n",
      "clyde river ca\n",
      "zhigansk ru\n",
      "ostrovnoy ru\n",
      "bluff nz\n",
      "bengkulu id\n",
      "castro cl\n",
      "vila velha br\n",
      "lagoa pt\n",
      "liberal us\n",
      "qaanaaq gl\n",
      "tiksi ru\n",
      "warkworth nz\n",
      "alofi nu\n",
      "ushuaia ar\n",
      "ribeira grande pt\n",
      "jamestown sh\n",
      "rikitea pf\n",
      "antofagasta cl\n",
      "albany au\n",
      "pevek ru\n",
      "aklavik ca\n",
      "srednekolymsk ru\n",
      "mount gambier au\n",
      "wulanhaote cn\n",
      "madras in\n",
      "haapiti pf\n",
      "atikokan ca\n",
      "kovur in\n",
      "tuktoyaktuk ca\n",
      "san quintin mx\n",
      "pau dos ferros br\n",
      "busselton au\n",
      "dalvik is\n",
      "jamestown sh\n",
      "hermanus za\n",
      "punta arenas cl\n",
      "chokurdakh ru\n",
      "rovaniemi fi\n",
      "qaanaaq gl\n",
      "ca mau vn\n",
      "taolanaro mg\n",
      "provideniya ru\n",
      "sibu my\n",
      "maldonado uy\n",
      "courtenay ca\n",
      "los aquijes pe\n",
      "mataura pf\n",
      "portland au\n",
      "cidreira br\n",
      "jamestown sh\n",
      "atuona pf\n",
      "mercedes ar\n",
      "ahipara nz\n",
      "punta arenas cl\n",
      "vysokogornyy ru\n",
      "castro cl\n",
      "santa rosa ar\n",
      "muros es\n",
      "albany au\n",
      "kloulklubed pw\n",
      "tagab af\n",
      "quatre cocos mu\n",
      "ahipara nz\n",
      "pisco pe\n",
      "sentyabrskiy ru\n",
      "westport nz\n",
      "hedensted dk\n",
      "ushuaia ar\n",
      "vaitupu wf\n",
      "rikitea pf\n",
      "new norfolk au\n",
      "quang ngai vn\n",
      "te anau nz\n",
      "hilo us\n",
      "bex ch\n",
      "ushuaia ar\n",
      "mataura pf\n",
      "saint george bm\n",
      "kodiak us\n",
      "oussouye sn\n",
      "cape town za\n",
      "pangkalanbuun id\n",
      "ribeira grande pt\n",
      "buala sb\n",
      "valparaiso cl\n",
      "husavik is\n",
      "busselton au\n",
      "rikitea pf\n",
      "khatanga ru\n",
      "sargatskoye ru\n",
      "codrington ag\n",
      "cape town za\n",
      "plover us\n",
      "georgetown sh\n",
      "hilo us\n",
      "cherskiy ru\n",
      "loum cm\n",
      "aklavik ca\n",
      "saint-pierre pm\n",
      "kieta pg\n",
      "kapaa us\n",
      "norman wells ca\n",
      "yumen cn\n",
      "constitucion cl\n",
      "yellowknife ca\n",
      "kapaa us\n",
      "kodiak us\n",
      "batagay-alyta ru\n",
      "atuona pf\n",
      "taolanaro mg\n",
      "qaanaaq gl\n",
      "praya id\n",
      "pontianak id\n",
      "coihaique cl\n",
      "tuktoyaktuk ca\n",
      "katsuura jp\n",
      "vrangel ru\n",
      "lavrentiya ru\n",
      "vaini to\n",
      "sentyabrskiy ru\n",
      "arraial do cabo br\n",
      "kashi cn\n",
      "rikitea pf\n",
      "vestmannaeyjar is\n",
      "albany au\n",
      "presidencia roque saenz pena ar\n",
      "cabedelo br\n",
      "hobart au\n",
      "olinda br\n",
      "husavik is\n",
      "sentyabrskiy ru\n",
      "rozkishne ua\n",
      "qiongshan cn\n",
      "floro no\n",
      "naryan-mar ru\n",
      "castro cl\n",
      "cherskiy ru\n",
      "kapaa us\n",
      "barentsburg sj\n",
      "chuy uy\n",
      "albany au\n",
      "grindavik is\n",
      "longyearbyen sj\n",
      "mentok id\n",
      "avarua ck\n",
      "mataura pf\n",
      "sao filipe cv\n",
      "maningrida au\n",
      "codrington ag\n",
      "ushuaia ar\n",
      "porto novo cv\n",
      "bolgatanga gh\n",
      "hobart au\n",
      "tasiilaq gl\n",
      "samusu ws\n",
      "boende cd\n",
      "poole gb\n",
      "waghai in\n",
      "khatanga ru\n",
      "zhangye cn\n",
      "ushuaia ar\n",
      "atuona pf\n",
      "guerrero negro mx\n",
      "salinopolis br\n",
      "kapaa us\n",
      "bluff nz\n",
      "khatanga ru\n",
      "dicabisagan ph\n",
      "cidreira br\n",
      "bredasdorp za\n",
      "albany au\n",
      "sentyabrskiy ru\n",
      "cape town za\n",
      "puerto escondido mx\n",
      "tutoia br\n",
      "inirida co\n",
      "karratha au\n",
      "kruisfontein za\n",
      "khani ru\n",
      "nosy varika mg\n",
      "coquimbo cl\n",
      "richards bay za\n",
      "tuktoyaktuk ca\n",
      "taolanaro mg\n",
      "rikitea pf\n",
      "rocha uy\n",
      "lefka cy\n",
      "verkh-usugli ru\n",
      "nome us\n",
      "port elizabeth za\n",
      "saint-philippe re\n",
      "barrow us\n",
      "arraial do cabo br\n",
      "luau ao\n",
      "torbay ca\n",
      "betanzos bo\n",
      "butaritari ki\n",
      "chokurdakh ru\n",
      "victoria sc\n",
      "bredasdorp za\n",
      "tsihombe mg\n",
      "ayan ru\n",
      "bredasdorp za\n",
      "geraldton au\n",
      "road town vg\n",
      "bluff nz\n",
      "illoqqortoormiut gl\n",
      "progreso mx\n",
      "esperance au\n",
      "lebu cl\n",
      "vandoeuvre-les-nancy fr\n",
      "san cristobal ec\n",
      "yellowknife ca\n",
      "rikitea pf\n",
      "vaitupu wf\n",
      "dunedin nz\n",
      "longyearbyen sj\n",
      "lompoc us\n",
      "tuatapere nz\n",
      "vaini to\n",
      "brunswick us\n",
      "bereda so\n",
      "hermanus za\n",
      "padang id\n",
      "umea se\n",
      "provideniya ru\n",
      "cape town za\n",
      "barrow us\n",
      "constitucion mx\n",
      "punta arenas cl\n",
      "fort nelson ca\n",
      "rikitea pf\n",
      "emba kz\n",
      "mataura pf\n",
      "puerto ayora ec\n",
      "pevek ru\n",
      "barrow us\n",
      "narsaq gl\n",
      "khani ru\n",
      "bengkulu id\n",
      "touros br\n",
      "hobart au\n",
      "kapaa us\n",
      "klaksvik fo\n",
      "nizhniye sergi ru\n",
      "kahului us\n",
      "lorengau pg\n",
      "bredasdorp za\n",
      "popondetta pg\n",
      "helena us\n",
      "ushuaia ar\n",
      "isangel vu\n",
      "mahebourg mu\n",
      "nantucket us\n",
      "chokurdakh ru\n",
      "belaya gora ru\n",
      "illoqqortoormiut gl\n",
      "totskoye ru\n",
      "ancud cl\n",
      "ushuaia ar\n",
      "valle de allende mx\n",
      "chuy uy\n",
      "hambantota lk\n",
      "airai pw\n",
      "shenjiamen cn\n",
      "cape town za\n",
      "cidreira br\n",
      "kinablangan ph\n",
      "cape town za\n",
      "iqaluit ca\n",
      "punta arenas cl\n",
      "kaduna ng\n",
      "saint-augustin ca\n",
      "illoqqortoormiut gl\n",
      "kismayo so\n",
      "vardo no\n",
      "srednekolymsk ru\n",
      "kavieng pg\n",
      "sao joao da barra br\n",
      "ondjiva ao\n",
      "keuruu fi\n",
      "leningradskiy ru\n",
      "kilcormac ie\n",
      "bluff nz\n",
      "rio gallegos ar\n",
      "bluff nz\n",
      "shumskiy ru\n",
      "hami cn\n",
      "kiama au\n",
      "spokane us\n",
      "pisco pe\n",
      "el tigre ve\n",
      "ponta do sol cv\n",
      "dikson ru\n",
      "busselton au\n",
      "vrangel ru\n",
      "umzimvubu za\n",
      "barrow us\n",
      "mecca sa\n",
      "chuy uy\n",
      "dagua co\n",
      "puerto ayora ec\n",
      "ponta delgada pt\n",
      "saldanha za\n",
      "bubaque gw\n",
      "grand river south east mu\n",
      "byron bay au\n",
      "vazante br\n",
      "taolanaro mg\n",
      "yellowknife ca\n",
      "san blas mx\n",
      "ushuaia ar\n",
      "kapaa us\n",
      "sitka us\n",
      "bluff nz\n",
      "severo-kurilsk ru\n",
      "mugur-aksy ru\n",
      "illoqqortoormiut gl\n",
      "beringovskiy ru\n",
      "parabel ru\n",
      "benghazi ly\n",
      "jutai br\n",
      "severo-kurilsk ru\n",
      "isangel vu\n",
      "rikitea pf\n",
      "ushuaia ar\n",
      "kalmunai lk\n",
      "cape town za\n",
      "meulaboh id\n",
      "korla cn\n",
      "mataura pf\n",
      "yellowknife ca\n",
      "ardistan ir\n",
      "cape town za\n",
      "barentsburg sj\n",
      "bredasdorp za\n",
      "georgetown sh\n",
      "ancud cl\n",
      "bredasdorp za\n",
      "santa cruz de la palma es\n",
      "mataura pf\n",
      "amderma ru\n",
      "thompson ca\n",
      "airai pw\n",
      "torbat-e jam ir\n",
      "constitucion mx\n",
      "hobart au\n",
      "sulangan ph\n",
      "nizhneyansk ru\n",
      "lagoa pt\n",
      "qaanaaq gl\n",
      "dzilam gonzalez mx\n",
      "sawakin sd\n",
      "illoqqortoormiut gl\n",
      "rikitea pf\n",
      "iqaluit ca\n",
      "albany au\n",
      "nanortalik gl\n",
      "saskylakh ru\n",
      "sitka us\n",
      "busselton au\n",
      "yellowknife ca\n",
      "airai pw\n",
      "la ronge ca\n",
      "portland au\n",
      "ankpa ng\n",
      "hunza pk\n",
      "cherskiy ru\n",
      "bengkulu id\n",
      "marystown ca\n",
      "mataura pf\n",
      "cape town za\n",
      "kapaa us\n",
      "coquimbo cl\n",
      "saint-philippe re\n",
      "cherskiy ru\n",
      "tabuk sa\n",
      "thompson ca\n",
      "illoqqortoormiut gl\n",
      "nizhneyansk ru\n",
      "cape town za\n",
      "homer us\n",
      "aswan eg\n",
      "ulaangom mn\n",
      "cehal ro\n",
      "atuona pf\n",
      "deputatskiy ru\n",
      "cantaura ve\n",
      "jamestown sh\n",
      "punta arenas cl\n",
      "wenling cn\n",
      "rikitea pf\n",
      "busselton au\n",
      "chara ru\n",
      "lavrentiya ru\n",
      "mataura pf\n",
      "miramar mx\n",
      "arraial do cabo br\n",
      "port augusta au\n",
      "hobart au\n",
      "georgetown sh\n",
      "rimbey ca\n",
      "chililabombwe zm\n",
      "yoro hn\n",
      "attawapiskat ca\n",
      "faya td\n",
      "san quintin mx\n",
      "saskylakh ru\n",
      "victoria sc\n",
      "narsaq gl\n",
      "tiksi ru\n",
      "bima id\n",
      "castro cl\n",
      "avera pf\n",
      "waddan ly\n",
      "dwarka in\n",
      "kununurra au\n",
      "ushuaia ar\n",
      "itaueira br\n",
      "chernyshevskiy ru\n",
      "tautira pf\n",
      "bathsheba bb\n",
      "hilo us\n",
      "ushuaia ar\n",
      "tilichiki ru\n",
      "zhezkazgan kz\n",
      "tuatapere nz\n",
      "tazovskiy ru\n",
      "hithadhoo mv\n",
      "mataura pf\n",
      "punta arenas cl\n",
      "puerto ayora ec\n",
      "svay rieng kh\n",
      "bluff nz\n",
      "mar del plata ar\n",
      "puerto ayora ec\n",
      "busselton au\n",
      "kavaratti in\n",
      "illoqqortoormiut gl\n",
      "kapaa us\n",
      "alofi nu\n",
      "qaanaaq gl\n",
      "mar del plata ar\n",
      "nouakchott mr\n",
      "vila vu\n",
      "ushuaia ar\n",
      "port alfred za\n",
      "vaini to\n",
      "talnakh ru\n",
      "chokurdakh ru\n",
      "hermanus za\n",
      "atuona pf\n",
      "hilo us\n",
      "palabuhanratu id\n",
      "punta arenas cl\n",
      "arraial do cabo br\n",
      "albany au\n",
      "mataura pf\n",
      "taolanaro mg\n",
      "albany au\n",
      "samarai pg\n",
      "ushuaia ar\n",
      "tuktoyaktuk ca\n",
      "yellowknife ca\n",
      "busselton au\n",
      "bluff nz\n",
      "khuzhir ru\n",
      "qaqortoq gl\n",
      "kapaa us\n",
      "mataura pf\n",
      "ushuaia ar\n",
      "cayambe ec\n",
      "abu dhabi ae\n",
      "seredka ru\n",
      "hilo us\n",
      "barrow us\n",
      "jamestown sh\n",
      "ushuaia ar\n",
      "inuvik ca\n",
      "provideniya ru\n",
      "norfolk us\n",
      "ushuaia ar\n",
      "alice springs au\n",
      "cherskiy ru\n",
      "rikitea pf\n",
      "mataura pf\n",
      "kawambwa zm\n",
      "butaritari ki\n",
      "marmaron gr\n",
      "mataura pf\n",
      "bredasdorp za\n",
      "attawapiskat ca\n",
      "mataura pf\n",
      "calvinia za\n",
      "vila do maio cv\n",
      "punta arenas cl\n",
      "alyangula au\n",
      "vaitupu wf\n",
      "port alfred za\n",
      "jamestown sh\n",
      "padang id\n",
      "skoghall se\n",
      "pevek ru\n",
      "boguchany ru\n",
      "braco do norte br\n",
      "krasnyy chikoy ru\n",
      "busselton au\n",
      "luwuk id\n",
      "illoqqortoormiut gl\n",
      "vaini to\n",
      "acapulco mx\n",
      "biak id\n",
      "pochutla mx\n",
      "yellowknife ca\n",
      "mount gambier au\n",
      "rikitea pf\n",
      "mataura pf\n",
      "luderitz na\n",
      "mar del plata ar\n",
      "rikitea pf\n",
      "monatele cm\n",
      "aklavik ca\n",
      "saint george bm\n",
      "rikitea pf\n",
      "hermanus za\n",
      "busselton au\n",
      "albany au\n",
      "crestview us\n",
      "qasigiannguit gl\n",
      "barentsburg sj\n",
      "chokurdakh ru\n",
      "lincoln nz\n",
      "bitlis tr\n",
      "chuy uy\n",
      "bafq ir\n",
      "hithadhoo mv\n",
      "valley city us\n",
      "darhan mn\n",
      "neuquen ar\n",
      "erenhot cn\n",
      "rikitea pf\n",
      "hithadhoo mv\n",
      "tuktoyaktuk ca\n",
      "moose factory ca\n",
      "nanortalik gl\n",
      "rudnya ru\n",
      "leningradskiy ru\n",
      "lasa cn\n",
      "srednekolymsk ru\n",
      "san cristobal ec\n",
      "chicama pe\n",
      "upernavik gl\n",
      "icod de los vinos es\n",
      "new norfolk au\n",
      "margate za\n",
      "pangai to\n",
      "cockburn town bs\n",
      "cidreira br\n",
      "arraial do cabo br\n",
      "martil ma\n",
      "dunedin nz\n",
      "new norfolk au\n",
      "torbay ca\n",
      "hilo us\n",
      "zhigansk ru\n",
      "abu zabad sd\n",
      "krasnoselkup ru\n",
      "ponta do sol cv\n",
      "tuktoyaktuk ca\n",
      "kodiak us\n",
      "ushuaia ar\n",
      "esperance au\n",
      "busselton au\n",
      "ellensburg us\n",
      "bengkulu id\n",
      "olinda br\n",
      "severo-yeniseyskiy ru\n",
      "lebu cl\n",
      "asosa et\n",
      "watertown us\n",
      "souillac mu\n",
      "ushuaia ar\n",
      "barrow us\n",
      "talnakh ru\n",
      "kodino ru\n",
      "constitucion mx\n",
      "east london za\n",
      "padang id\n",
      "saldanha za\n",
      "busselton au\n",
      "mys shmidta ru\n",
      "tias es\n",
      "rikitea pf\n",
      "mataura pf\n",
      "castro cl\n",
      "karasjok no\n",
      "kapaa us\n",
      "rio grande br\n",
      "busselton au\n",
      "illoqqortoormiut gl\n",
      "port alfred za\n",
      "busselton au\n",
      "dikson ru\n",
      "brae gb\n",
      "illoqqortoormiut gl\n",
      "busselton au\n",
      "yellowknife ca\n",
      "kapaa us\n",
      "taolanaro mg\n",
      "atuona pf\n",
      "busselton au\n",
      "kerema pg\n",
      "ixtapa mx\n",
      "rikitea pf\n",
      "cape town za\n",
      "faanui pf\n",
      "hobart au\n",
      "ushuaia ar\n",
      "pevek ru\n",
      "coihaique cl\n",
      "bredasdorp za\n",
      "yellowknife ca\n",
      "toliary mg\n",
      "rikitea pf\n",
      "cape town za\n",
      "linxia cn\n",
      "constitucion mx\n",
      "bluff nz\n",
      "atuona pf\n",
      "itarema br\n",
      "kaina ee\n",
      "kapaa us\n",
      "constitucion mx\n",
      "chokurdakh ru\n",
      "mitu co\n",
      "barrow us\n",
      "olesnica pl\n",
      "nikolskoye ru\n",
      "rabo de peixe pt\n",
      "sitka us\n",
      "puerto leguizamo co\n",
      "thompson ca\n",
      "vaini to\n",
      "port alfred za\n",
      "albany au\n",
      "bluff nz\n",
      "pemangkat id\n",
      "kapaa us\n",
      "jalu ly\n",
      "conceicao do araguaia br\n",
      "paciran id\n",
      "alice springs au\n",
      "grand river south east mu\n",
      "shimoda jp\n",
      "shingu jp\n",
      "cape town za\n",
      "tonekabon ir\n",
      "jamestown sh\n",
      "aksarka ru\n",
      "nome us\n",
      "sibolga id\n",
      "punta arenas cl\n",
      "hilo us\n",
      "sao joao da barra br\n",
      "cape town za\n",
      "qaanaaq gl\n",
      "punta arenas cl\n",
      "bontang id\n",
      "bereda so\n",
      "lerwick gb\n",
      "lorengau pg\n",
      "ushuaia ar\n",
      "busselton au\n",
      "mar del plata ar\n",
      "bago mm\n",
      "new norfolk au\n",
      "ponta do sol cv\n",
      "gamba ga\n",
      "hermanus za\n",
      "rikitea pf\n",
      "souillac mu\n",
      "chodziez pl\n",
      "otane nz\n",
      "rikitea pf\n",
      "barbar sd\n",
      "fortuna us\n",
      "saleaula ws\n",
      "ushuaia ar\n",
      "busselton au\n",
      "atuona pf\n",
      "kihei us\n",
      "barrow us\n",
      "fukue jp\n",
      "jacareacanga br\n",
      "east london za\n",
      "ushuaia ar\n",
      "saint-junien fr\n",
      "albany au\n",
      "kalemie cd\n",
      "ulaangom mn\n",
      "yeppoon au\n",
      "isangel vu\n",
      "norman wells ca\n",
      "bluff nz\n",
      "auki sb\n",
      "ambon id\n",
      "busselton au\n",
      "porto santo pt\n",
      "natchitoches us\n",
      "north battleford ca\n",
      "talaya ru\n",
      "krasnovishersk ru\n",
      "taolanaro mg\n",
      "barentsburg sj\n",
      "mitsamiouli km\n",
      "isangel vu\n",
      "umzimvubu za\n",
      "shelburne ca\n",
      "bredasdorp za\n",
      "busselton au\n",
      "rikitea pf\n",
      "bluff nz\n",
      "pangnirtung ca\n",
      "yellowknife ca\n",
      "apam gh\n",
      "mataura pf\n",
      "bodden town ky\n",
      "lompoc us\n",
      "kapaa us\n",
      "taolanaro mg\n",
      "mount gambier au\n",
      "albany au\n",
      "salalah om\n",
      "lorengau pg\n",
      "sao jose da coroa grande br\n",
      "andenes no\n",
      "puerto del rosario es\n",
      "grand centre ca\n",
      "takoradi gh\n",
      "kapaa us\n",
      "bengkulu id\n",
      "bilma ne\n",
      "atuona pf\n",
      "iwanai jp\n",
      "portland au\n",
      "lebu cl\n",
      "cape town za\n",
      "mar del plata ar\n",
      "punta arenas cl\n",
      "salina cruz mx\n",
      "gamba ga\n",
      "jamestown sh\n",
      "port blair in\n",
      "new norfolk au\n",
      "willmar us\n",
      "huilong cn\n",
      "roma au\n",
      "aklavik ca\n",
      "kapaa us\n",
      "guerrero negro mx\n",
      "dikson ru\n",
      "isangel vu\n",
      "airai pw\n",
      "hilo us\n",
      "busselton au\n",
      "saint-augustin ca\n",
      "east london za\n",
      "hilo us\n",
      "bengkulu id\n",
      "nelson bay au\n",
      "ushuaia ar\n",
      "sanmenxia cn\n",
      "mandalgovi mn\n",
      "kavaratti in\n",
      "hilo us\n",
      "sao filipe cv\n",
      "nokaneng bw\n",
      "neiafu to\n",
      "georgetown sh\n",
      "punta arenas cl\n",
      "punta arenas cl\n",
      "jutai br\n",
      "kruisfontein za\n",
      "vilhena br\n",
      "upernavik gl\n",
      "port alfred za\n",
      "tezu in\n",
      "lebu cl\n",
      "marystown ca\n",
      "bredasdorp za\n",
      "ust-maya ru\n",
      "tuktoyaktuk ca\n",
      "castro cl\n",
      "cabo san lucas mx\n",
      "hithadhoo mv\n",
      "port alfred za\n",
      "san borja bo\n",
      "ushuaia ar\n",
      "new norfolk au\n",
      "albany au\n",
      "la ronge ca\n",
      "tsihombe mg\n",
      "sao jose da coroa grande br\n",
      "qui nhon vn\n",
      "bethel us\n",
      "murray bridge au\n",
      "lebu cl\n",
      "chara ru\n",
      "ushuaia ar\n",
      "busselton au\n",
      "busselton au\n",
      "qaanaaq gl\n",
      "matara lk\n",
      "bela pk\n",
      "kapaa us\n",
      "barentsburg sj\n",
      "saint george bm\n",
      "isangel vu\n",
      "fuxin cn\n",
      "llanes es\n",
      "tuktoyaktuk ca\n",
      "murgab tm\n",
      "iqaluit ca\n",
      "alaverdi am\n",
      "ushuaia ar\n",
      "new norfolk au\n",
      "nishihara jp\n",
      "nisia floresta br\n",
      "pala td\n",
      "punta arenas cl\n",
      "albany au\n",
      "iqaluit ca\n",
      "taolanaro mg\n",
      "taolanaro mg\n",
      "vaini to\n",
      "bluff nz\n",
      "cherskiy ru\n",
      "thunder bay ca\n",
      "ushuaia ar\n",
      "qaanaaq gl\n",
      "samalaeulu ws\n",
      "jamestown sh\n",
      "new norfolk au\n",
      "kapaa us\n",
      "bluff nz\n",
      "mataura pf\n",
      "carnarvon au\n",
      "taolanaro mg\n",
      "rikitea pf\n",
      "albany au\n",
      "constitucion mx\n",
      "puerto ayora ec\n",
      "geraldton au\n",
      "amderma ru\n",
      "port hardy ca\n",
      "illoqqortoormiut gl\n",
      "jensen beach us\n",
      "hasaki jp\n",
      "illoqqortoormiut gl\n",
      "ancud cl\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "759"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = [25.12903645, 25.92017388, 26.62509167, -59.98969384, 37.30571269]\n",
    "y = [-67.59741259, 11.09532135, 74.84233102, -76.89176677, -61.13376282]\n",
    "coordinates = zip(x, y)\n",
    "\n",
    "# Create a set of random latitude and longitude combinations.\n",
    "lats = np.random.uniform(low=-90.000, high=90.000, size=2000)\n",
    "lngs = np.random.uniform(low=-180.000, high=180.000, size=2000)\n",
    "lat_lngs = zip(lats, lngs)\n",
    "lat_lngs\n",
    "# Use the tuple() function to display the latitude and longitude combinations.\n",
    "for coordinate in coordinates:\n",
    "    print(coordinate[0], coordinate[1])\n",
    "\n",
    "# Add the latitudes and longitudes to a list.\n",
    "coordinates = list(lat_lngs)\n",
    "len(coordinates)\n",
    "# Use the tuple() function to display the latitude and longitude combinations.\n",
    "for coordinate in coordinates:\n",
    "    print(citipy.nearest_city(coordinate[0], coordinate[1]).city_name,\n",
    "          citipy.nearest_city(coordinate[0], coordinate[1]).country_code)\n",
    "\n",
    "# Create a list for holding the cities.\n",
    "cities = []\n",
    "# Identify the nearest city for each latitude and longitude combination.\n",
    "for coordinate in coordinates:\n",
    "    city = citipy.nearest_city(coordinate[0], coordinate[1]).city_name\n",
    "\n",
    "    # If the city is unique, then we will add it to the cities list.\n",
    "    if city not in cities:\n",
    "        cities.append(city)\n",
    "# Print the city count to confirm sufficient count.\n",
    "len(cities)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "http://api.openweathermap.org/data/2.5/weather?units=Imperial&APPID=08e0b0a15de955e25ec80b5dfc322e8d\n"
     ]
    }
   ],
   "source": [
    "# Starting URL for Weather Map API Call.\n",
    "url = \"http://api.openweathermap.org/data/2.5/weather?units=Imperial&APPID=\" + weather_api_key\n",
    "print(url)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "http://api.openweathermap.org/data/2.5/weather?units=Imperial&APPID=08e0b0a15de955e25ec80b5dfc322e8d&q=Boston\n"
     ]
    }
   ],
   "source": [
    "# Create an endpoint URL for a city.\n",
    "city_url = url + \"&q=\" + \"Boston\"\n",
    "print(city_url)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Response [200]>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Make a 'Get' request for the city weather.\n",
    "city_weather = requests.get(city_url)\n",
    "city_weather"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Response [404]>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create an endpoint URL for a city.\n",
    "city_url = url + \"&q=\" + \"B0ston\"\n",
    "city_weather = requests.get(city_url)\n",
    "city_weather"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Response [200]>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get the JSON text of the 'Get' request.\n",
    "# Create an endpoint URL for a city.\n",
    "city_url = url + \"&q=\" + \"Boston\"\n",
    "city_weather = requests.get(city_url)\n",
    "city_weather"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'{\"coord\":{\"lon\":-71.0598,\"lat\":42.3584},\"weather\":[{\"id\":804,\"main\":\"Clouds\",\"description\":\"overcast clouds\",\"icon\":\"04d\"}],\"base\":\"stations\",\"main\":{\"temp\":41.61,\"feels_like\":35.64,\"temp_min\":38.88,\"temp_max\":44.35,\"pressure\":1031,\"humidity\":37},\"visibility\":10000,\"wind\":{\"speed\":10,\"deg\":298,\"gust\":15.99},\"clouds\":{\"all\":100},\"dt\":1646510041,\"sys\":{\"type\":2,\"id\":2013408,\"country\":\"US\",\"sunrise\":1646478799,\"sunset\":1646519906},\"timezone\":-18000,\"id\":4930956,\"name\":\"Boston\",\"cod\":200}'"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get the text of the 'Get' request.\n",
    "city_weather.text"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'coord': {'lon': -71.0598, 'lat': 42.3584},\n",
       " 'weather': [{'id': 804,\n",
       "   'main': 'Clouds',\n",
       "   'description': 'overcast clouds',\n",
       "   'icon': '04d'}],\n",
       " 'base': 'stations',\n",
       " 'main': {'temp': 41.61,\n",
       "  'feels_like': 35.64,\n",
       "  'temp_min': 38.88,\n",
       "  'temp_max': 44.35,\n",
       "  'pressure': 1031,\n",
       "  'humidity': 37},\n",
       " 'visibility': 10000,\n",
       " 'wind': {'speed': 10, 'deg': 298, 'gust': 15.99},\n",
       " 'clouds': {'all': 100},\n",
       " 'dt': 1646510041,\n",
       " 'sys': {'type': 2,\n",
       "  'id': 2013408,\n",
       "  'country': 'US',\n",
       "  'sunrise': 1646478799,\n",
       "  'sunset': 1646519906},\n",
       " 'timezone': -18000,\n",
       " 'id': 4930956,\n",
       " 'name': 'Boston',\n",
       " 'cod': 200}"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get the text of the 'Get' request.\n",
    "city_weather.json()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "City Weather found.\n"
     ]
    }
   ],
   "source": [
    "# Create an endpoint URL for a city.\n",
    "city_url = url + \"&q=\" + \"Boston\"\n",
    "city_weather = requests.get(city_url)\n",
    "if city_weather.status_code == 200:\n",
    "    print(f\"City Weather found.\")\n",
    "else:\n",
    "    print(f\"City weather not found.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'coord': {'lon': -71.0598, 'lat': 42.3584},\n",
       " 'weather': [{'id': 804,\n",
       "   'main': 'Clouds',\n",
       "   'description': 'overcast clouds',\n",
       "   'icon': '04d'}],\n",
       " 'base': 'stations',\n",
       " 'main': {'temp': 41.61,\n",
       "  'feels_like': 35.64,\n",
       "  'temp_min': 38.88,\n",
       "  'temp_max': 44.35,\n",
       "  'pressure': 1031,\n",
       "  'humidity': 37},\n",
       " 'visibility': 10000,\n",
       " 'wind': {'speed': 10, 'deg': 298, 'gust': 15.99},\n",
       " 'clouds': {'all': 100},\n",
       " 'dt': 1646510041,\n",
       " 'sys': {'type': 2,\n",
       "  'id': 2013408,\n",
       "  'country': 'US',\n",
       "  'sunrise': 1646478799,\n",
       "  'sunset': 1646519906},\n",
       " 'timezone': -18000,\n",
       " 'id': 4930956,\n",
       " 'name': 'Boston',\n",
       " 'cod': 200}"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create an endpoint URL for a city.\n",
    "city_url = url + \"&q=\" + \"Boston\"\n",
    "city_weather = requests.get(city_url)\n",
    "city_weather.json()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get the JSON data.\n",
    "boston_data = city_weather.json()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "42.3584 -71.0598 44.35 37 100 10\n"
     ]
    }
   ],
   "source": [
    "lat = boston_data[\"coord\"][\"lat\"]\n",
    "lng = boston_data[\"coord\"][\"lon\"]\n",
    "max_temp = boston_data[\"main\"][\"temp_max\"]\n",
    "humidity = boston_data[\"main\"][\"humidity\"]\n",
    "clouds = boston_data[\"clouds\"][\"all\"]\n",
    "wind = boston_data[\"wind\"][\"speed\"]\n",
    "print(lat, lng, max_temp, str(humidity), clouds, wind)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "datetime.datetime(2022, 3, 5, 19, 54, 1)"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Import the datetime module from the datetime library.\n",
    "from datetime import datetime\n",
    "# Get the date from the JSON file.\n",
    "date = boston_data[\"dt\"]\n",
    "# Convert the UTC date to a date format with year, month, day, hours, minutes, and seconds.\n",
    "datetime.utcfromtimestamp(date)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Beginning Data Retrieval     \n",
      "-----------------------------\n",
      "Processing Record 1 of Set 1 | castro\n",
      "City not found. Skipping...\n",
      "Processing Record 2 of Set 1 | clyde river\n",
      "City not found. Skipping...\n",
      "Processing Record 3 of Set 1 | nizhneyansk\n",
      "City not found. Skipping...\n",
      "Processing Record 4 of Set 1 | vaini\n",
      "City not found. Skipping...\n",
      "Processing Record 5 of Set 1 | luderitz\n",
      "City not found. Skipping...\n",
      "Processing Record 6 of Set 1 | dicabisagan\n",
      "City not found. Skipping...\n",
      "Processing Record 7 of Set 1 | bluff\n",
      "City not found. Skipping...\n",
      "Processing Record 8 of Set 1 | kutum\n",
      "City not found. Skipping...\n",
      "Processing Record 9 of Set 1 | rikitea\n",
      "City not found. Skipping...\n",
      "Processing Record 10 of Set 1 | ulladulla\n",
      "City not found. Skipping...\n",
      "Processing Record 11 of Set 1 | provideniya\n",
      "City not found. Skipping...\n",
      "Processing Record 12 of Set 1 | zlatoust\n",
      "City not found. Skipping...\n",
      "Processing Record 13 of Set 1 | ribeira grande\n",
      "City not found. Skipping...\n",
      "Processing Record 14 of Set 1 | whitianga\n",
      "City not found. Skipping...\n",
      "Processing Record 15 of Set 1 | umm lajj\n",
      "City not found. Skipping...\n",
      "Processing Record 16 of Set 1 | hilo\n",
      "City not found. Skipping...\n",
      "Processing Record 17 of Set 1 | hasaki\n",
      "City not found. Skipping...\n",
      "Processing Record 18 of Set 1 | ushuaia\n",
      "City not found. Skipping...\n",
      "Processing Record 19 of Set 1 | peto\n",
      "City not found. Skipping...\n",
      "Processing Record 20 of Set 1 | albany\n",
      "City not found. Skipping...\n",
      "Processing Record 21 of Set 1 | atuona\n",
      "City not found. Skipping...\n",
      "Processing Record 22 of Set 1 | batagay-alyta\n",
      "City not found. Skipping...\n",
      "Processing Record 23 of Set 1 | baisha\n",
      "City not found. Skipping...\n",
      "Processing Record 24 of Set 1 | torbay\n",
      "City not found. Skipping...\n",
      "Processing Record 25 of Set 1 | inhambane\n",
      "City not found. Skipping...\n",
      "Processing Record 26 of Set 1 | lang son\n",
      "City not found. Skipping...\n",
      "Processing Record 27 of Set 1 | barrow\n",
      "City not found. Skipping...\n",
      "Processing Record 28 of Set 1 | jiuquan\n",
      "City not found. Skipping...\n",
      "Processing Record 29 of Set 1 | arraial do cabo\n",
      "City not found. Skipping...\n",
      "Processing Record 30 of Set 1 | kavieng\n",
      "City not found. Skipping...\n",
      "Processing Record 31 of Set 1 | cape town\n",
      "City not found. Skipping...\n",
      "Processing Record 32 of Set 1 | busselton\n",
      "City not found. Skipping...\n",
      "Processing Record 33 of Set 1 | mataura\n",
      "City not found. Skipping...\n",
      "Processing Record 34 of Set 1 | mareeba\n",
      "City not found. Skipping...\n",
      "Processing Record 35 of Set 1 | nhulunbuy\n",
      "City not found. Skipping...\n",
      "Processing Record 36 of Set 1 | pontes e lacerda\n"
     ]
    }
   ],
   "source": [
    "# Create an empty list to hold the weather data.\n",
    "city_data = []\n",
    "# Print the beginning of the logging.\n",
    "print(\"Beginning Data Retrieval     \")\n",
    "print(\"-----------------------------\")\n",
    "# Create counters.\n",
    "record_count = 1\n",
    "set_count = 1\n",
    "\n",
    "# Loop through all the cities in the list.\n",
    "for i, city in enumerate(cities):\n",
    "\n",
    "    # Group cities in sets of 50 for logging purposes.\n",
    "    if (i % 50 == 0 and i >= 50):\n",
    "        set_count += 1\n",
    "        record_count = 1\n",
    "        time.sleep(60)\n",
    "\n",
    "    # Create endpoint URL with each city.\n",
    "    city_url = url + \"&q=\" + city.replace(\" \",\"+\")\n",
    "\n",
    "    # Log the URL, record, and set numbers and the city.\n",
    "    print(f\"Processing Record {record_count} of Set {set_count} | {city}\")\n",
    "    # Add 1 to the record count.\n",
    "    record_count += 1 \n",
    "\n",
    "    # Run an API request for each of the cities.\n",
    "    try:\n",
    "        # Parse the JSON and retrieve data.\n",
    "        city_weather = requests.get(city_url).json()\n",
    "        # Parse out the needed data.\n",
    "        city_lat = city_weather[\"coord\"][\"lat\"]\n",
    "        city_lng = city_weather[\"coord\"][\"lon\"]\n",
    "        city_max_temp = city_weather[\"main\"][\"temp_max\"]\n",
    "        city_humidity = city_weather[\"main\"][\"humidity\"]\n",
    "        city_clouds = city_weather[\"clouds\"][\"all\"]\n",
    "        city_wind = city_weather[\"wind\"][\"speed\"]\n",
    "        city_country = city_weather[\"weather\"][\"description\"]\n",
    "        # Convert the date to ISO standard.\n",
    "        city_date = datetime.utcfromtimestamp(city_weather[\"dt\"]).strftime('%Y-%m-%d %H:%M:%S')\n",
    "        # Append the city information into city_data list.\n",
    "        city_data.append({\"City\": city.title(),\n",
    "                          \"Lat\": city_lat,\n",
    "                          \"Lng\": city_lng,\n",
    "                          \"Max Temp\": city_max_temp,\n",
    "                          \"Humidity\": city_humidity,\n",
    "                          \"Cloudiness\": city_clouds,\n",
    "                          \"Wind Speed\": city_wind,\n",
    "                          \"Country\": city_country,\n",
    "                          \"Date\": city_date})\n",
    "\n",
    "# If an error is experienced, skip the city.\n",
    "    except:\n",
    "        print(\"City not found. Skipping...\")\n",
    "        pass\n",
    "\n",
    "# Indicate that Data Loading is complete.\n",
    "print(\"-----------------------------\")\n",
    "print(\"Data Retrieval Complete      \")\n",
    "print(\"-----------------------------\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create the output file (CSV).\n",
    "output_data_file = \"weather_data/cities.csv\"\n",
    "# Export the City_Data into a CSV.\n",
    "city_data_df.to_csv(output_data_file, index_label=\"City_ID\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "file_to_load = \"weather_data/cities.csv\"\n",
    "file_to_read= pd.read_csv(file_to_load)\n",
    "city_data_df= pd.DataFrame(file_to_read)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['City_ID', 'City', 'Country', 'Date', 'Lat', 'Lng', 'Max Temp',\n",
       "       'Humidity', 'Cloudiness', 'Wind Speed'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "city_data_df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "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>City</th>\n",
       "      <th>Country</th>\n",
       "      <th>Date</th>\n",
       "      <th>Lat</th>\n",
       "      <th>Lng</th>\n",
       "      <th>Max Temp</th>\n",
       "      <th>Humidity</th>\n",
       "      <th>Cloudiness</th>\n",
       "      <th>Wind Speed</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>San Policarpo</td>\n",
       "      <td>PH</td>\n",
       "      <td>2022-03-03 17:26:46</td>\n",
       "      <td>12.1791</td>\n",
       "      <td>125.5072</td>\n",
       "      <td>78.67</td>\n",
       "      <td>85</td>\n",
       "      <td>25</td>\n",
       "      <td>12.21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Paracambi</td>\n",
       "      <td>BR</td>\n",
       "      <td>2022-03-03 17:26:46</td>\n",
       "      <td>-22.6086</td>\n",
       "      <td>-43.7128</td>\n",
       "      <td>96.33</td>\n",
       "      <td>38</td>\n",
       "      <td>1</td>\n",
       "      <td>4.94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Berlevag</td>\n",
       "      <td>NO</td>\n",
       "      <td>2022-03-03 17:26:46</td>\n",
       "      <td>70.8578</td>\n",
       "      <td>29.0864</td>\n",
       "      <td>30.15</td>\n",
       "      <td>69</td>\n",
       "      <td>40</td>\n",
       "      <td>23.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Narsaq</td>\n",
       "      <td>GL</td>\n",
       "      <td>2022-03-03 17:26:47</td>\n",
       "      <td>60.9167</td>\n",
       "      <td>-46.0500</td>\n",
       "      <td>19.62</td>\n",
       "      <td>76</td>\n",
       "      <td>9</td>\n",
       "      <td>6.76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Fortuna</td>\n",
       "      <td>US</td>\n",
       "      <td>2022-03-03 17:26:47</td>\n",
       "      <td>40.5982</td>\n",
       "      <td>-124.1573</td>\n",
       "      <td>51.42</td>\n",
       "      <td>95</td>\n",
       "      <td>75</td>\n",
       "      <td>11.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Atuona</td>\n",
       "      <td>PF</td>\n",
       "      <td>2022-03-03 17:26:48</td>\n",
       "      <td>-9.8000</td>\n",
       "      <td>-139.0333</td>\n",
       "      <td>78.44</td>\n",
       "      <td>74</td>\n",
       "      <td>5</td>\n",
       "      <td>24.49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Punta Arenas</td>\n",
       "      <td>CL</td>\n",
       "      <td>2022-03-03 17:26:48</td>\n",
       "      <td>-53.1500</td>\n",
       "      <td>-70.9167</td>\n",
       "      <td>57.31</td>\n",
       "      <td>51</td>\n",
       "      <td>20</td>\n",
       "      <td>14.97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Rikitea</td>\n",
       "      <td>PF</td>\n",
       "      <td>2022-03-03 17:26:48</td>\n",
       "      <td>-23.1203</td>\n",
       "      <td>-134.9692</td>\n",
       "      <td>80.02</td>\n",
       "      <td>72</td>\n",
       "      <td>0</td>\n",
       "      <td>21.32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Chokurdakh</td>\n",
       "      <td>RU</td>\n",
       "      <td>2022-03-03 17:26:49</td>\n",
       "      <td>70.6333</td>\n",
       "      <td>147.9167</td>\n",
       "      <td>-13.90</td>\n",
       "      <td>99</td>\n",
       "      <td>96</td>\n",
       "      <td>4.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Aksarka</td>\n",
       "      <td>RU</td>\n",
       "      <td>2022-03-03 17:26:49</td>\n",
       "      <td>66.5606</td>\n",
       "      <td>67.7975</td>\n",
       "      <td>-3.95</td>\n",
       "      <td>94</td>\n",
       "      <td>99</td>\n",
       "      <td>17.94</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            City Country                 Date      Lat       Lng  Max Temp  \\\n",
       "0  San Policarpo      PH  2022-03-03 17:26:46  12.1791  125.5072     78.67   \n",
       "1      Paracambi      BR  2022-03-03 17:26:46 -22.6086  -43.7128     96.33   \n",
       "2       Berlevag      NO  2022-03-03 17:26:46  70.8578   29.0864     30.15   \n",
       "3         Narsaq      GL  2022-03-03 17:26:47  60.9167  -46.0500     19.62   \n",
       "4        Fortuna      US  2022-03-03 17:26:47  40.5982 -124.1573     51.42   \n",
       "5         Atuona      PF  2022-03-03 17:26:48  -9.8000 -139.0333     78.44   \n",
       "6   Punta Arenas      CL  2022-03-03 17:26:48 -53.1500  -70.9167     57.31   \n",
       "7        Rikitea      PF  2022-03-03 17:26:48 -23.1203 -134.9692     80.02   \n",
       "8     Chokurdakh      RU  2022-03-03 17:26:49  70.6333  147.9167    -13.90   \n",
       "9        Aksarka      RU  2022-03-03 17:26:49  66.5606   67.7975     -3.95   \n",
       "\n",
       "   Humidity  Cloudiness  Wind Speed  \n",
       "0        85          25       12.21  \n",
       "1        38           1        4.94  \n",
       "2        69          40       23.02  \n",
       "3        76           9        6.76  \n",
       "4        95          75       11.50  \n",
       "5        74           5       24.49  \n",
       "6        51          20       14.97  \n",
       "7        72           0       21.32  \n",
       "8        99          96        4.14  \n",
       "9        94          99       17.94  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_order= ['City','Country','Date','Lat', 'Lng', 'Max Temp', 'Humidity', 'Cloudiness','Wind Speed' ]\n",
    "city_data_df=city_data_df[new_order]\n",
    "city_data_df.head(10)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "file_to_load = \"weather_data/cities.csv\"\n",
    "file_to_read= pd.read_csv(file_to_load)\n",
    "city_data_df= pd.DataFrame(file_to_read)\n",
    "# Extract relevant fields from the DataFrame for plotting.\n",
    "# Extract relevant fields from the DataFrame for plotting.\n",
    "lats = city_data_df[\"Lat\"]\n",
    "max_temps = city_data_df[\"Max Temp\"]\n",
    "humidity = city_data_df[\"Humidity\"]\n",
    "cloudiness = city_data_df[\"Cloudiness\"]\n",
    "wind_speed = city_data_df[\"Wind Speed\"]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Import time module\n",
    "import time\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline \n",
    "\n",
    "# Build the scatter plot for latitude vs. max temperature.\n",
    "plt.scatter(lats,\n",
    "            max_temps,\n",
    "            edgecolor=\"black\", linewidths=1, marker=\"o\",\n",
    "            alpha=0.8, label=\"Cities\")\n",
    "\n",
    "# Incorporate the other graph properties.\n",
    "plt.title(f\"City Latitude vs. Max Temperature \"+ time.strftime(\"%x\"))\n",
    "plt.ylabel(\"Max Temperature (F)\")\n",
    "plt.xlabel(\"Latitude\")\n",
    "plt.grid(True)\n",
    "\n",
    "# Save the figure.\n",
    "plt.savefig(\"weather_data/Fig1.png\")\n",
    "\n",
    "# Show plot.\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Build the scatter plots for latitude vs. humidity.\n",
    "plt.scatter(lats,\n",
    "            humidity,\n",
    "            edgecolor=\"black\", linewidths=1, marker=\"o\",\n",
    "            alpha=0.8, label=\"Cities\")\n",
    "\n",
    "# Incorporate the other graph properties.\n",
    "plt.title(f\"City Latitude vs. Humidity \"+ time.strftime(\"%x\"))\n",
    "plt.ylabel(\"Humidity (%)\")\n",
    "plt.xlabel(\"Latitude\")\n",
    "plt.grid(True)\n",
    "# Save the figure.\n",
    "plt.savefig(\"weather_data/Fig2.png\")\n",
    "# Show plot.\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Build the scatter plots for latitude vs. cloudiness.\n",
    "plt.scatter(lats,\n",
    "            cloudiness,\n",
    "            edgecolor=\"black\", linewidths=1, marker=\"o\",\n",
    "            alpha=0.8, label=\"Cities\")\n",
    "\n",
    "# Incorporate the other graph properties.\n",
    "plt.title(f\"City Latitude vs. Cloudiness (%) \"+ time.strftime(\"%x\"))\n",
    "plt.ylabel(\"Cloudiness (%)\")\n",
    "plt.xlabel(\"Latitude\")\n",
    "plt.grid(True)\n",
    "# Save the figure.\n",
    "plt.savefig(\"weather_data/Fig3.png\")\n",
    "# Show plot.\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Build the scatter plots for latitude vs. wind speed.\n",
    "plt.scatter(lats ,\n",
    "            wind_speed,\n",
    "            edgecolor=\"black\", linewidths=1, marker=\"o\",\n",
    "            alpha=0.8, label=\"Cities\")\n",
    "\n",
    "# Incorporate the other graph properties.\n",
    "plt.title(f\"City Latitude vs. Wind Speed \"+ time.strftime(\"%x\"))\n",
    "plt.ylabel(\"Wind Speed (mph)\")\n",
    "plt.xlabel(\"Latitude\")\n",
    "plt.grid(True)\n",
    "# Save the figure.\n",
    "plt.savefig(\"weather_data/Fig4.png\")\n",
    "# Show plot.\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import linregress\n",
    "from scipy.stats import linregress\n",
    "\n",
    "# Create a function to create perform linear regression on the weather data\n",
    "# and plot a regression line and the equation with the data.\n",
    "def plot_linear_regression(x_values, y_values, title, y_label, text_coordinates):\n",
    "\n",
    "    # Run regression on hemisphere weather data.\n",
    "    (slope, intercept, r_value, p_value, std_err) = linregress(x_values, y_values)\n",
    "\n",
    "    # Calculate the regression line \"y values\" from the slope and intercept.\n",
    "    regress_values = x_values * slope + intercept\n",
    "    # Get the equation of the line.\n",
    "    line_eq = \"y = \" + str(round(slope,2)) + \"x + \" + str(round(intercept,2))\n",
    "    # Create a scatter plot and plot the regression line.\n",
    "    plt.scatter(x_values,y_values)\n",
    "    plt.plot(x_values,regress_values,\"r\")\n",
    "    # Annotate the text for the line equation.\n",
    "    plt.annotate(line_eq,text_coordinates, fontsize=15, color=\"black\")\n",
    "    plt.title(title)\n",
    "    plt.xlabel('Latitude')\n",
    "    plt.ylabel(y_label)\n",
    "    plt.show()\n",
    "    print (\"r value :\" + str(round(r_value,2)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>City_ID</th>\n",
       "      <th>City</th>\n",
       "      <th>Country</th>\n",
       "      <th>Date</th>\n",
       "      <th>Lat</th>\n",
       "      <th>Lng</th>\n",
       "      <th>Max Temp</th>\n",
       "      <th>Humidity</th>\n",
       "      <th>Cloudiness</th>\n",
       "      <th>Wind Speed</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>San Policarpo</td>\n",
       "      <td>PH</td>\n",
       "      <td>2022-03-03 17:26:46</td>\n",
       "      <td>12.1791</td>\n",
       "      <td>125.5072</td>\n",
       "      <td>78.67</td>\n",
       "      <td>85</td>\n",
       "      <td>25</td>\n",
       "      <td>12.21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>Berlevag</td>\n",
       "      <td>NO</td>\n",
       "      <td>2022-03-03 17:26:46</td>\n",
       "      <td>70.8578</td>\n",
       "      <td>29.0864</td>\n",
       "      <td>30.15</td>\n",
       "      <td>69</td>\n",
       "      <td>40</td>\n",
       "      <td>23.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>Narsaq</td>\n",
       "      <td>GL</td>\n",
       "      <td>2022-03-03 17:26:47</td>\n",
       "      <td>60.9167</td>\n",
       "      <td>-46.0500</td>\n",
       "      <td>19.62</td>\n",
       "      <td>76</td>\n",
       "      <td>9</td>\n",
       "      <td>6.76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>Fortuna</td>\n",
       "      <td>US</td>\n",
       "      <td>2022-03-03 17:26:47</td>\n",
       "      <td>40.5982</td>\n",
       "      <td>-124.1573</td>\n",
       "      <td>51.42</td>\n",
       "      <td>95</td>\n",
       "      <td>75</td>\n",
       "      <td>11.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>8</td>\n",
       "      <td>Chokurdakh</td>\n",
       "      <td>RU</td>\n",
       "      <td>2022-03-03 17:26:49</td>\n",
       "      <td>70.6333</td>\n",
       "      <td>147.9167</td>\n",
       "      <td>-13.90</td>\n",
       "      <td>99</td>\n",
       "      <td>96</td>\n",
       "      <td>4.14</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   City_ID           City Country                 Date      Lat       Lng  \\\n",
       "0        0  San Policarpo      PH  2022-03-03 17:26:46  12.1791  125.5072   \n",
       "2        2       Berlevag      NO  2022-03-03 17:26:46  70.8578   29.0864   \n",
       "3        3         Narsaq      GL  2022-03-03 17:26:47  60.9167  -46.0500   \n",
       "4        4        Fortuna      US  2022-03-03 17:26:47  40.5982 -124.1573   \n",
       "8        8     Chokurdakh      RU  2022-03-03 17:26:49  70.6333  147.9167   \n",
       "\n",
       "   Max Temp  Humidity  Cloudiness  Wind Speed  \n",
       "0     78.67        85          25       12.21  \n",
       "2     30.15        69          40       23.02  \n",
       "3     19.62        76           9        6.76  \n",
       "4     51.42        95          75       11.50  \n",
       "8    -13.90        99          96        4.14  "
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "city_data_df.loc[(city_data_df[\"Lat\"] >= 0)].head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create Northern and Southern Hemisphere DataFrames.\n",
    "northern_hemi_df = city_data_df.loc[(city_data_df[\"Lat\"] >= 0)]\n",
    "southern_hemi_df = city_data_df.loc[(city_data_df[\"Lat\"] < 0)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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/z+Ht12JZLo4zxux0ucaEUCe1P+HS0TmO127GmKur27Ex5ltjzBCsAe0eYKrt6ArjLGsdtKR0uCSyU97mxpjTnKeO2j9caju8fwtjTOeAlxEu8QxEHHV7ULlktYk+yINpwOnA98YY5z+9s+T4tVjT9BysNSXEsc81WKaPtVj272SwDct8FT5HJsHWTKgOa4BTo77DJibOstwOcsUx2lLxWwry3Ud/d+PstsOM5WC9EP+y70HuX3V+j5V+fyRYet0YsxHLD9DV0dyVitLlboSoqJ57GlaGf5gvXfr62Rjzm0dfWVj+HbD8SauMMevDG+3f/3tY5rMXog8WkUuxneLGmB+jt1cHVRD+eJaOrm7HInKhiLQxVunlIrvZWaH0/0SkqVhrE1wCTAnQbVwlkU3sUtux+BdwiYh0s8P47gY+NcasCni8U5ZtWD6NKiF/xCg5LiK/w/L3XIhlPrlFRLrFK4ML32DNzk4Xa/2IO6ioCpsqHgPusgcFxCqffVY1+tsTuN7+7Q7E8vG8neB33xzr6bhIrLpY0SGV0SXH47p/CciUlNLrNpPtvlqKSCcs/9FzAHao6bFilYvPFpGRWDO6T+1jT8eKOHL29ScROUREWtrXHe5rTxEZLCK72f+f/bBMVu+79WXf5/eBR4wxj0ULLVZI9N3AScaY7xO8dk9UQfhgYpeOrg6nAF+KyFbgQWCwqbzi1gdY0UFzgPuMMbMDyJtISWS/UtuxzjcH+D+sp/91WE9BCYfYGWMWGmNWuLR7lhy3TWsvYi2DucQY8y3WYjYvOGPPE5RnE9YylU9hzYq2YUXGpJIHsaLBZovIFiwn7JHV6O9TLHPdr8BdwHmOJ9l4v/uxWAEJm7CemKdHbR+HNcgWicjNCd6/eGRKZun10Vi+gx+w/vcmGGPesbc1Bh7B8vcUYs0YTjfGrBVrPYuDsRzkANjH3QvMtfv7we4frAedq7Huw0bgPiyf0Rv29nB4a5jLsJTuaHHkzkTdgz2wFuAKb6+iSBJFazGlGSKShzW4h4z7CmuKEggRGQZcZow5trZlqa+ItfbGecaYIGtwxOprL6zgi3YmTQZmnUEoiqIkThFWrkgy2B24MV2UA+ia1IqiKAkTxPQbR1/fYPlt0gY1MSmKoiiuqIlJURRFcaVemJhat25t8vLyalsMRVGUOsWiRYt+NcZ45vbUCwWRl5fHwoULa1sMRVGUOoWI/OC3XU1MiqIoiiuqIBRFURRXVEEoiqIorqRcQYi13N4vIvKFo62VWMvofWv/benYdquIfCciy+06JYqiKEotUBMziOew6g45GQXMMcYchFVraBSAiByCVcuns33MP+0KkIqiKEoNk/IoJmPMh3Z9ISdnYS3oAfA8MA8Yabe/YtczXyki32EtBPNJquVMB/ILCpkwazlri4ppl5PNiH4dGdA9t7bFUhSlgVJbYa572aV9McassxciAWuhmQWO/X6026ogIldgrdtM+/btUyhqaohWBn06tWHaokKKS6yK34VFxdw6fSmAKglFUWqFdHNSi0ubay0QY8wTxpiexpiebdqkeg2X5JJfUMit05dSWFSMwVIGLy1YHVEOYYpLypgwa3ntCKkoSoOnthTEzyLSFsD++4vd/iOVV1LbhwRWiEp3JsxaXkUZeFXEWltU7LFFURQltdSWgngTGGq/Hwq84WgfLCKNRWQ/rIVOPkuZFOvWgQh07gxbqiw/mzLiGfTb5WRX+pxfUEiv8e+z36iZ9Br/PvkFia5EqSiK4k9NhLm+jOVk7igiP4rIn4DxwEki8i3WAt3jAYwxX2ItOP8V8A5wjWMB+OTTzF4C+quvoEULOPZY2LHD/5gkED3oeyFAn04V5jM309St05eqklAUJSWkXEEYY4YYY9oaY0LGmH2MMU8bY34zxvQ1xhxk/93g2P8uY8wBxpiOxph/p1S4Fi2gvBxuvtn6PH8+ZGfDWWdBaeoWcxvRryPZodjRuwaYtqgwogDcTFPqp1AUJVWkm5O65hGBCROgrAwuvdRqe/NNCIXgkkssBZJkBnTPZdw5XcgNMJNwKgAv05T6KRRFSQWqIMJkZMDTT0NJCQwYYLU99xxkZlozjCQvrDSgey7zR53ApEHdYs4mwgrAyzQV1GSlKIoSD6ogosnKgtdfh+JiOO44q+3++y0FcvfdST/dgO65nNsjl0xxi/C1CCsAN9NUdiiTEf06Jl0uRVEUVRBeNGkCH34ImzfDIYdYbbffbpmkHn00aafJLyhk2qJCyjxmKE4F4DRNCZCbk824c7poIp2iKCmhXqxJ3bNnT5PyBYN++w0OPRR++qmi7V//giFDqtVtr/HvU+jhQ8iNo9xGssp0aLkPRWk4iMgiY0xPz+2qIOJk7VrYbz/YtauibeZMOO20hLrbb9RM1yQ5AVaOPz1QH+HwV2eEUyhD2K1JFkXbSwIP9G79ZIcydZaiKPWUWApCTUzx0q4d7NwJ331X0Xb66Zbp6aOP4u8uCY5nt/DXknLDxu0lceVLaBitoihO6sWa1LXCAQdYkU1Ll8Jhh1ltxx9v/V20CA4/3PfwsCmnsKgYoXKpjViO52gzkJeJykl4oPebCWgYraIoTnQGUV26dLEUxccfV7T16GHNKJa7P3k7M6LBUg7hGKZYjme3bGrv+KfKxBrovWYtBrSsh6I0QFRBJIujj7YUxezZFW2dOlmKYvXqSrt6FevLzclm/qgTfJ/yvY4NoiRima38Mry1rIeiNDxUQSSbk06yFMXUqRVtHTqwObs5Pa57iQNufdvTJBTElON1bFjBCJCTHSKUWVllBMmXiJXhrf4IRWlYqIJIFeeeC8bw+V/vA6DFjq0sevhC3n/sTzTfuc31kJymId8u8wsKPWcK4dnHyvGns3j0yUw4r2tC+RLhDG+v86g/QlEaDuqkTjGXZnShaOQMLvtsOnfMfYYORT+xdNIglux9EIP+OI4doSaRfTduLyFv1EzP/Iexb33pGRIbPTsY0D23WqGpXs7vmijrobkYipIe6AwiheQXFFJUXALAU0ecQ97IGfzj6EEAdP3pW5Y9cB6Tp/wfWWWVK8e62fvzCwrZuL3E9TyG5C9LWltlPbSkuaKkD5ooFydua0nPXbbe9WnXM0vaGP7+7qNcVPB2pOmNg//A8P43Up5RMSiHzUa+fQEtm4Zo2igr5hN3vE/mtfEk73WdznuhKEpy0EzqJOKWaRyNM/PYK0s6TEZ5GQ++dR9nLKtIsHv+8NMZfeJVIFIpmzpWX9EyHN5+dxZ8v5EyY8gU4aj9W/L56k01miWdiIJJRma5oijBUAWRRPye4p2En3b99s/JDrFtVyklZYZQWQnPvDaW435YHNn+4DFDePWMywLNIKpDpgjlxkQG8IU/bOClT1dHqps3DWVw9zmHxa1EEi3boTMIRak5VEEkkXie4nNt89O0RYWeg2R0NnXjkh289tJIuvy8oqKjiRPhhhsCzV6qS3RGt5MLj2rPnQO6RD47Zwc5TUMYA5uKK+o+ha8rmlgDfSzFog5sRUkeqiB8iHewOfj//k1xSfAV5jKA7EaZbNtlDXY52SHGnNkZoMp5nW2/a1zGK49eTcv1ayN9LRo7kTVnDPQceFONABMHdYsM0n7KKpQhlJS7/66CmIq8vhctJqgoyUUVhAfxDjb5BYXcMGVxteTMDmVybo9c31mFU7ZmRb/y/hNX0mLX9opOXn+dXsta1IqSCGI6C+M1G6mOqUjNT4qSXLSaqwfxVi5NRgZxcUkZL3+6JuZ5w7L92qwlhw1/lV5XPVOx89lnM//Wvpy5YoHrOQQ4aM9mrtt6HdAqkjznt4KdF+EkuSDKyeuxo0+nNnGfN/r8QdvBUra9xr/PfqNmaj0pRYmTBpso5zWoFBYV02v8+5XMTfkFhUl7YvdaOc4pT7RshbvvSd7IGRzw6xrmPH01AA9NvZOHgCsH3MZ7nXpRZkylBLs78pfy8qdrIlFMQ47ct4oPIV6fRjhJLlPE8zpiMXfZ+oSOC5/fK3nPzSwFVLrGcE4FUOm7VZ+GorhTqwpCRIYDl2E9cC4FLgGaAlOAPGAVcL4xZmOyz+1XJts5kACV3qcKZ4ayl2wrWu9L3sgZ9F6xkOemjgHg8Xx7nez334c+fQBr0Ju7bD3lUUrDSfiz09HslYgHEMqUyKCbqHKA6pXqGNGvo6tZsE+nNq6KoEkow3O25ubTcFMgitKQqTUTk4jkAtcDPY0xhwKZwGBgFDDHGHMQMMf+nHRG9OvoWwG1uKSMm15dwpg3v0xp5FCYbTtLI+aPEf06Esrwlm7eAT3JGzmDm0+7oaLxhBNAhLn/eidwJvKA7rmM6NeRdjnZFPkoB4BmjbIig2p1qE6pDq81uecuW++qCLwUXlhJ6QJJiuJPbfsgsoBsEcnCmjmsBc4Cnre3Pw8MSMWJB3TPjRmyWmZMpFSGG9mh5N2+ouKSSgN5aYCn9KldTiRv5Ay+uOGOSFufC07l6ztPJW9DxUDuNehFl7XwY5N9H4IOns0aZVZRwMko1REuJrhy/OmR0ujxzkrCSkoXSFIUf2rNxGSMKRSR+4DVQDEw2xgzW0T2Msass/dZJyJ7uh0vIlcAVwC0b98+IRlyA67G5kamCE1CmXGFvcaiuKSM26b/j+KS8sD5FgADd+vFuM9/ZMDLD8KECQDMe/JKAI748/P80nyPyKDntLlnxOFLiDWoOgllCrtKK1+DAOf2qF4BQT/Z3L7HnOwQO0vLq5ikwkqqNgsSKkpdoDZNTC2xZgv7Ae2AZiJyYdDjjTFPGGN6GmN6tmmTWGSM3wI5sSgzJqZZJhG2x6kcwDFDuPdeeo2bw7TOfSLbPvvnUFbd05+OjUurzBiCKgdntdjds/1LkufmZNOsUVaVPAhD9RzUfngVFhxzZmdXk1RYSdVWQUJFqSvUppP6RGClMWY9gIhMB44BfhaRtvbsoS3wS6oEcDpq451JhBfVqY18BDfCT/Yj+nXk1m23cFP/m3jxlds59oclALzztwHwNxh141RwlBiPhQAXHNU+4n/YtqvUdb9QpjDhvK6RGlR+MiabaId7dDSS16wl1nGK0tCpTQWxGjhKRJpimZj6AguBbcBQYLz9941UCuFcNyFo6KfzKTPV5S+CEjaLOAe9iwbfRbvdm/DvJ6+mxcpvAVj2wHkAHHhzPqWZVb/+UIawW5MsiraXVBkwJ8xaTklZ1VlHhhBRDmFZatJ0U51Q1equm6Eo9Zna9EF8KiJTgc+BUqAAeALYDXhVRP6EpUQG1pRM4YHCL2PaLWw06AwkQ8CjAgUCNHWU5YiHaLNIlUHv1m+grIxtzVrQbKeVlf3dfQNY3zSHI66dTEZGZqWCfV4DptcMwJjKT+le4ajVMd3kFxQy9q0vI5FJzrIl0aGqw6csZuEPGyrlfSiKEj8NttSGH4mUdPAr5CdYT8/bd5W6hl5minD/+V2B4DOS6CqsQZ6C8wsK+euri/jf+LMqtRd1OpScr/4HMbKr47kvsRL14iG/oJARU5dUmb2EMoRmjbNcI82ctaNi9R10fQ9FqW/EKrXRYDOp/UjkCdjLrOIcPL1s8+XGVJmR+EUZCXD/+V3jHrgiCxntPodNP//GF5POByBn2ReQkcFHBx/DxWfexu7ZIUSoYmYKel/yCwqZtqgwInuZMUxbVEjPDq0SKht+06tLXO9DSbl3GLKBSEKcX9/Rs48XF6yObNfEOaWhowrChUScl0EGzyC2ead5yEuhxFpi1M8mX8n8NNHAr7+CHQV23Ncfs/Lr/rzU7RRu73ct4D5I+t0XrwHdmcEclPAAnmjmdiynuFuiXDRucmt5DqWhoArCg3idl0EGz3hnJn6zEi/iLh/RujW9xs3BrP6Bjx+9FIALFr/DBYvf4cFjhjDxuAsoLilj7FtfVrq2iYO6sfCHDdz06hJumLI4smrdZys3Bqo3FYQgA3jLpiGKtpe4mvdiOcWDyuPcT8tzKA0JVRABCfLUGEupxDszScTU5Vc+ws/5bFpYBQEP/HU17z39ZwD+8vHL/OXjl/nriVcyuccZEf9JYVExN05ZjDNFsMwY5q/Y4CkXVAzYsRYbCssZawAPZQijz+hsrYK3YHUlJRHEKe5Xj8tNbkjs/ipKXUWd1AGozYVq4jVnJLKms5vzudva5eS/cFOltuvPGMGbh/wh3ksAKu4X+Dvinfc11pKtY87s7FqV1cuHEk1+QSEjXlviubhRmJZNQ4w+wzpXnofZT9fMVuoiuh5EEqjNom5utYf88DKr+Jlb3DKKF7frSN7IGVw8cGyk7aG3JrDqnv4c//2iOK7AIlxmI5bZyHlfvTKdJw3qxuLRJ1e6F+H7NHFQN3aWlrPRNjv5FSsE8K3YaLNxu1Un6478pZ67Z4joWhNKvUMVRAz81oJIx6JuiZSPiK6SmpMdomXTEAKsOPxYuo2ZxXVnjIjsP/m10ay6pz/dC5cFlmvaokLyCwoD3bPComL2GzWTCbOWc26P3CqlMgDPRYDiUeZeiX9uhBd78tq7zBh/RaQodRD1QfgQNi15kY5F3RItH+HnP8kvKOTW0nLyDvkDFy96i7+99zgAr794MwAn/umffNfav2BieJAOavcPP/1PW1Touhyrl5PYb42PaOJV8LGiqdQXodQ3dAbhg585JJ2LusVrlgrSX3iG8UKPM+g1bg7Lrhge2f7e039m1T39yd3kXzZrbVFx3AUSvZZj9drHaylVt3YvBR9PH9Gk46xSURJFFYQPfv/sNeGgTieilU6nxx8AY8g/on9kn/mPXcqqe/rTcvsm1z7a5WRXMWe1bBoiJzvk6wpwliqPZe7zesp3a/cyxw05ct/A7dGk46xSURJFTUw++OUh1GflEFfk1GOPsd+UxTwx7e+c9N2nABT84wIAOt/wKtsaNwUqlwz3Mmd5RS2F15wOYu7zWuPDLXfEzxzXs0Mr3/bComIE4g6tVZS6hIa5+pCK8NZ0z8JN5JojoZ/G8MbkG+n607eVtne86XUGHntAzFpMfuf2K4jolK8mQ5LT/btUlFjECnNVBRGDZA4CtZlPEZREChVGHyOmnAX/HMZeWx2Jc82awaZNkOlvovEq8udXDHFSVFG+IN+ZDu6KosX6qk08JTdiDTp1IQs3kXWaozO+jWTQ+4aXGH9GJ846cj9rp23bICsLOnaEr792rRzrV+QvHnNfrO8sViSU2/cIurCQ0vBQBZEkgtToSWTwrWkSWezHy5Z/Vvdca7GI7dutGQTA8uWQkQF9+8J77wEVitXtvGEFmsw1JmJFQkV/jyNeWwJCJGdC6y8pDQVVEEki1qAzYdZyTxNJOkW+9OnUplLJa2e7H75P7U2bWopi40Zo1cpqmzMHRFhz2jncevjlvtnVa4uK48rviDWT81PUbt+jWykOr5mfzj6U+oQqiCThNeiEnzbrSj7F3GXr42qPi5YtLUWxdi3kWgPkvm9P5+u3p/P4Eecwrs+lrocZLD/HiH4dPf0gYYLM5PxmSfHM5qL3dTv3iKlLwFQoGZ19KHUJzYNIEn5JV17KIVw6Ip0Gihoxg7VrZymKb76JNF352XRW3dOfKz6d5npIzJpKNkFKbfiVI4lnNhe9r+vso8xUmYHUVB0vRakuqiCShNeg45W4JZCULOdkk0ixv4Q56CB6jZvD6UMnRZpum/csq+7pz3lL36uye5CBNYiCi07Wcypqt+8xlCGEMis71d1mftWZfShKOqIKIkl4DTpei/ukk9/BSSLF/qp7vu/3tSrHDhl8d6T9vrcnseqe/pz47aeV9o81sO6eHXJtd65F0Wv8+wyfshiw1q12Kmq373HCwK5MOK+rq0JxO0cQ0vX7VxQnmgeRYupC7kM0qcgR8OszOoqp3zcf8/jrd1c6/vw/juezfQ/1zcfILyhkxNQlVSq0hjKECQO7AlXXokjmdxF0fYl0//6VhkNaJ8qJSA7wFHAoli/yUmA5MAXIA1YB5xtjNvr1k84KAjQpK6iSjF6M5/wls7n3nYcqtc19eRZ9Bp/seh6vJL+WTUMU/PVk3wWIcpOQBOmX7Z0pQrkxDfL7V9KXdFcQzwMfGWOeEpFGQFPgNmCDMWa8iIwCWhpjRvr1k+4KoqETNDv74P/7N8Ul5VX2u3rBa4z84PnKjd99BwccUKkp1mp6ftnYkPiTvZsCdCM641tRapu0XVFORFoAxwNPAxhjdhljioCzgPBo8DwwoDbkU5JH0MioceccVuUHmQF0nHiXFfU0vKLEOAceCCL8e/bnkcWDMjzKcYft/bHs/kGji8J+jPCCRWPe/DKmcgB0QSGlzlGbTur9gfXAsyJSICJPiUgzYC9jzDoA+++ebgeLyBUislBEFq5fn4QYfSVlBI2MGtA9lwcGdavkDH7A+dT9gFVinMGDI8ec2q8H82/tS/MdW10jxrJDmfTp1CYyi4m1okMsJ3h4tlBYVBxZ1KiouCRGrxZhBRStYFRpKOlKrZmYRKQnsADoZYz5VEQeBDYD1xljchz7bTTGtPTrS01M6U0yHfVOf84r/xrFkWu+qLS9443TKG3UJGLvz9sjm49XbKhkWoou0+3Eywkey8cQD9mhzDoVtKDUX9K5WN+PwI/GmHAc41RgFPCziLQ1xqwTkbaA/zJlStqT6DKo0URHKQ3643gwhrlPXsF+G9cBsPyBc62dS0rIX/ozw6csrqIMDNa62ztLywPVdgrqYwhKuhdsVJQwtaYgjDE/icgaEelojFkO9AW+sl9DgfH23zdqS0aleiQ7emvsW19WCWFFhD5XPElGeRlfTRxIk9JdVnsoxDEtWsNVz4BUtaRuKi5h4qBugeTzW3o2WWjinJKO1HYtpuuAl+wIpu+BS7D8Iq+KyJ+A1cDAWpRPSZAgNZHiZeN2b1t/eUYmnW6aTuPSXSy//xwA9tz8KyvvPZOCth05++L7K+2/e3YosPKqicFbE+eUdKRWFYQxZjHgZv/qW8OiKEmmtta+2JnViLyRM2i+cztLJ50PQPd1y1l1T3/+/btjuPrs2wDYtqs04lyOpby8ivsli1Rkqjf03BslOWipDSUlpKLoX45HGQ03Wuy1B/mf/0iv4S9H2k795mNW3dOfu+c8XsVU5RfiOqJfx5jRT35khzIJefynZQhJd1C7RVppiK2SCKoglJSQiqJ/Y87sTCij8lCdAZ6F9AZ0z2XERcfRa9wcjr3q6cj2Py58i1X39Oe6+S9XOs5LeQ3onuubYBdNBlb2djhU99weubjk/wHQokko6U/2QSraKkoQatsHodRTkrkCXBivaCi3NmfxvfAyor06zGG3b79m1jPXAnDTf17ipv+8xO0n/5mXup/mq7xy4zAzZWYKo8/oHJGh1/j3Pffd5JFDUR0TUV1YuVCpG2ixPiVl1LQd3Ot8bmGqh//4NdNfGlHp+M/ueYwjbrnSs2+3kFk/cnOyPVfoc+4TnXdR3byRoKVNFCWtazElC1UQit+g6pfg1nvFf3lu6tjKjbNnw0knRfoNK50moQzXWlHVISc7xJgzO1ca+Ks7wN+Rv5SXFqyupMw0GU9xI21rMSlKMvGzu/uZVuYd8HvyRs5geP+bKhpPPhlEmPfizErO3uKSckIZQrNGmZ79xUtRcUkVB3J1TET5BYVMW1RYJXP83B4+a4YrigeqIJS0JZ6aRX6DahDH+Oud+9Br3ByYNCnS1vui/nx956kc8NuaSFtJuWGHPYuoTmSTk2gHcnUc/G6K0gAzlqyrloxKw0QVhJKWxBuq6Teouq2S58baomL4y1+sgoC33RZpn/PU1ay6pz9tN1tFIcNFAZNpnHWalKqzqp+XoiwqLtEwVyVuVEEoaUm8oZp+g6pzGVE/KimZu+6i17g5TOlyUqTpk0cvYdU9/ckp3hzn1QQjPID7rZntdoxzluW15CqQ9DBXrUpb/1EFoaQl8drhYw2qA7rnMn/UCawafzoXHtW+inko+gk9v6CQ7btKGXnaX8gbOYO5+/eIbFv80B9ZdU9/mu6qKktOdqiSDBce1b7SZz+cA3hY3omDugEwfMriKoOw2yxr265Sz/6TGeaqyXgNA41iUtKSVIdqxloj2616qxjD289ex8HrV1VqP+jm1ynJDAWKFPJb9jS88p1TRr9wV7++3MjJDtGscVZSwo41lLZ+kJRy3yJyOHAsltl1vjHm8yTJpyiupCLRzkk4gc4Nr+qtTRtncc6Vj7JjVwkL/3Ehe9impm/vO5vNTXbj/f98FXPAHdGvo2c+RbQfJVY9q3hnBPHUn4omWqF6KSZNxqtfxDQxichfsZb+3ANojbUC3B2pFkxp2MRjh082XoPctl1lnNsjl3Ytm9Hz+n/xh7+/E9nWYsdWBvRsD126WE5uDwZ0z+UCHxOX064faxCOt2xJPPWnnLiZk7wiuLQqbf0iyAxiCNDdGLMDQETGA58Dd6ZSMCU9+ec//8nMmTNZsGABGzZsYO7cufTu3TvmcaNHj2b69On88MMPGGPo2LEjI0aMYNCgQZF9Vq1axX777Vfl2EGDBvHKK68k8zJ88XtCfmvxWs4PLeTxfz3Op7/8wuHduzNu9Gj6DRhg7fDFF5CRwcKjj+a23Xbjk8/+y45dZWTtuT8HnXY5f7t8AHcO6ELPDq2qmLhKSnbxp2FDKV77DWXbNiKhJjTa+yByjr+IxnsfGJFh29L3EOlfRbZWJ/+ZFt1Piyu6KsgTv1fobPTKfKmoSqvULkEUxCqgCbDD/twYWJEqgZT0ZvLkyYgI/fr14+WXX459gM3mzZsZNmwYhxxyCJmZmUydOpXBgweTmZnJeeedV2nf++67j169ekU+t27dOmnyB2FEv47cMGWx67bVc//FmE9e4c6//41u3brx4osvcsbAgcz/7DN+2ZrN6Sd0YQ1w4iefcDhw3X7deKrHWWz+dBpfPH0LN2fuBpeeCMC2naWRJ/Kxb31J2a6dlBlocdRAslq2xezczuaFb/Dzy7fR9pKHCOXsDUA4l3uvwXcTatSY7EaZbNlRyj4d8ujXsz3TFhUGXuAoyBO/lxIxWDM7LSlef4nppBaRfOD3wLtYv4mTgP9gLwVqjLk+tSLGRp3UNUd5eTkZGRl88cUXdOnSJfAMwo1evXqxxx578OabbwIVM4i33nqL/v2rPiEnm7y8PMaMGcOwYcOqbOs2dnbEXh/GlJWw5qE/knvsuayZ80KkvUePHkjTlmzrfTPFJWXIJ6+y+sPJ/Abk2PtM6HkWtyx6i1YnXUX7XmexdUcpJeWxn/XLdxWz5qEhtDx+KC2PPIcyY9i69D1+e3sS+w5/jYxG2VUcw/kFhZ4KzknQ8hvxOqRTVYNL17hIPskotfE6cBswF5gH3A78G1hkv5QUMHPmTDIyMli5cmWl9pUrV5KRkREZVGuajIzkRUbvscce7Nq1K65jFixYQFZWFs8880ykbdOmTey7775ceOGFSZNtzJmdq7SVbvwJs6uY0r0PjbTlFxTyc/PfseiTD9i+w5pkb2qUTXlmFgMufSSy3w0L36CRKefoVUvYuL0kkHIAkFATMrMac8vJB1Lu8TAX/YQ/oHuuZ0htpkjcPp14EvdSFf6qYbW1Q8z/dmPM836vmhCyIXLKKafQrl07nn++8i1+7rnnaNOmDaeddprnsWVlZZSWlvq+ysuTW3QuKKWlpRQVFfHSSy8xe/Zsrrrqqir7XHLJJWRmZtK2bVtuvPFGiosrBsCjjjqKESNGMHz4cFavtqqkXn/99ZSXl/OPf/wjaXIO6J5Ly6aVk85MmaXM2uzeDKgYtLaWCJSVUlr0EwBNf3cMGVmN+XzJO+x77YucPPBvDAdaAs9+M59V9/TniDVfeJ7bGIMpL6Ns60a2fvgc2Y2zGDJkSBVzUOHjl/PDvWfy09NX8fjjj1fa5jWo339+V1aOP535o07wVA7RCXBA4ICBVK1FoWtc1A4xfRBiecP+DnSw9xfAGGNapFi2Bk1mZibDhg3j+eefZ/To0YgIxhief/55LrroIrKyvL+6vn378sEHH/j2P3ToUJ577rkkS+3PggULOProowHIysri4YcfZkDYuQs0btyYa665hpNPPpkWLVowb9487rnnHlasWMEbb7wR2W/s2LHMnDmTSy+9lOuuu47Jkyczc+ZMWrZs6Xv+0tKqSWTl5eWV2jMzMxGxYnRGn9G5UqhtVs7egHBk841AxaC1c903AJQVbyUEZDXfg72GjOOXqWPZsugtfgTe360VJx0zhDazrVnFq/8aBcDpQyfxpcMBDbD506kUfWA9GLRouQfvznqHDh06MKJfliVPs5bsftyFNG77OxplwIFblnDVVVexfft2hg8fDlReOyNsHiouKeOmV5ew8IcN3Dmgi+s98lpLfNw5XQLlN6RqLQpd46J2COKD+A44B1hq0jSrrr76IL7//nsOPPBA5syZQ58+fXj//ffp27cvX3zxBZ07VzWBhFm+fDlbtmzx7bt169bk5eW5bjPGUFZW8bQmImRmVn4aTcQHsW3bNr7++muKioqYOXMmDz/8MJMnT2bIkCGexzz66KP8+c9/pqCggG7dukXaFy9ezBFHHEFGRgYXXXQRTz75ZMzzhwd+P5599tlKPolou3fWh/9g+eef8PLLLzM0/2e2fjWPje8/BeVl7H3R/TRu15HSrRv4+aWRhFq3p3l3a6a35fMZ7Pr5e/a+aAIvHbkHfxh2VqXz9r3sUVbssS8AZVs3UrrlVzJ3FLHnjx+wevlSPvzwQw455BBPO/ygQYN47733WL9+fSUz4B35S13Xo2hqly6PtuVXNwEuVQl0Xv22bBqiaaPkJP81RKq9HoSIzAX6GmNqxyYRgPqqIABOOOEE9tlnHyZPnsxFF13EN998w6effup7TFlZGbG+14yMDE9/wrx58+jTp0/k8x/+8AfmzZtXaZ9kOKkvvfRS3nvvvYipyI3169ez55578vTTT3PppZdG2o0xdO/enSVLlvD555/TvXv3mOeL/o2cfGp/mnXtR1lud9o0b8xFR3fgklOOZI899vCVZ9CgQcydOxeAzOZt2O2wk9g0/1/kXvU0WbvvxYY5T1L8zSe0u+IJJNOa6ZmyEgqfuII2nY9l3cfTyS8oZOr4Z3nx1f+r1P8xVz/D2hZ7Rj63a96I3yZfy5FHHsnkyZM95Xrttdc4//zzWbFiBfvvv3+k/YBb344UF/TC6azeb9RM1zDZ6CxvL6q72FE8/YYyBQyV/Dm67kV8JMNJfQvwtojcKiI3hl9JFDBTRApEZIb9uZWIvCsi39p//e0G9ZzLLruMadOmUVhYyPTp07nkkktiHtO3b19CoZDvyznYRtOjRw/++9//Rl7R9u1kcfjhh7NmzRpKStyX3YSKp/7op/9JkyaxbNkyOnXqxHXXXRfIp9KzZ8/I68fMtmwpMRQ3bkWjtgexabf2PL0sg49WW45mr0J0bdq04f3332fNmjU8+NocDrzuWcuR3KwlWbvvRXYok4Mab6brYYfStEnjiuvIDNGkTQdyMzcBlgloZfdjyBs5gysHVFSO/fjRS/nfxPPZY1sRAOu27KJLly58//33Ae5o1fsUSzlAZVt+ddcSD5LgmEiRP7d+mzXKquLsLy4p4waXulWJnrehEyQP4i5gK1YuRKMUyPAX4Gsg7NMYBcwxxowXkVH255EpOG+d4JxzzuGaa65h8ODBlJeXM3jw4JjHPP7444FMTF40b96cnj09HyqSxvz589lnn30IhbwrkE6dOhWwlFaY5cuXc/vtt3PnnXdyyimn0KNHDyZOnMhNN93k1U0VJsxaXiXh2TlQutnhocK2v88++3D9efuw9z4rGPbUe+x22Enk2iaOWb925O233+a+Mzoy6f2VrC0qZu/dMtm2bS1HHnZE5Hwj+nVkxGtLmNXRUhQD//cuE/79IC12bWfRwxeyeve9uOTah/n8888r5YW4MW3aNFq3bk2HDh0qtWeKBFISYVt+Mkqc+JUx8fJxhI+Lp9/9Rs303De63+qctyETREG0MsacnIqTi8g+wOlYSig8KzkL6G2/fx4rtLbBKogmTZpwwQUX8MgjjzBkyBBycnJiHtOxY+qyWRcuXMiqVatYs8ZaROeDDz7g119/JS8vL6JUJk+ezKWXXsqKFSvo0KEDP/zwA5dccgl//OMf2X///dm6dSuvv/46r7zyCo8++mik7zFjxrBlyxZ69epFixYt+PDDD5kwYQLnnHMOhx12GGCZz4YOHUr37t258cYbycjIYOzYsdxxxx2cfvrpdOrUKdB1+Dk9vSJmbpiymBHjHqbfwa05r08PVq9ezcSJEzlgzxZ8MvtpdtttNwD2vewynnrqKZ4bey23/fnPGGN45JEHKfr1F6644opIn289/Fe2zp5DkwsfwRh4LqsRj3buw6nGcM1X81i36Wd23TWQdSLc+OKLkePOPfdcjjjiCA477DDKysqYMmUKU6ZM4aGHHqpiNhxy5L6+a2KHCc8QnM7tVNj1Y9WXige/jPfofpN53oZEEAXxnoicbIyZnYLzT8IyYTV3tO1ljFkHYIxZJyJ7uh0oIlcAVwC0b98+BaKlDwMGDOCRRx7xNQvVFA8//HCl0NsxY8YAlaOiysvLK/lBcnJyaNeuHXfeeSc//fQTOTk5HHLIIcycObNSuG6nTp247777eOqppyguLqZ9+/aMGDGC22+/PbLPvffey9KlS1m8eHFkMBwxYgRvvPEGQ4cO5eOPP67iUHejXU42azza/SJjNm7byZMPT+SJ8b/SMmd3BgwYwN133x1RDmDNdt555x3Gjh3LRRddBECXLl1499136dq1a2S/srIyGmfCxPO7MXzKYrJa5VL+5Vym//wdUzOzaJXViBN3bmehMXTu1Yufj/oD559+K0vWZvL2fQ9TvvVXMoBDDjkk4qOKJhyt5KckomcIfjOA6pLMaCS32Y5Xv179FxYVk19QqErCgyBO6i1AM2CX/UpKmKsdPnuaMebPItIbuNkY019EiowxOY79NhpjfP0Q9dlJDXDLLbcwZcqUSJKcUn28nKnn9sjl5U/XxDTLtGwaouCvyZtY53mZS4zh/g+f5NwFFYmRbx58PDf0v4nMUBbNGmWxqbgk5pO+VwnznOwQY87snPQB0ivaKtlRTuHzeM0kwma/m15d4vmdBnVs18dM7mpHMaUKERkHXASUYvk3WgDTscp69LZnD22BecYYX5tJfVUQy5cv56uvvuLiiy9m9OjR3HzzzbUtUr0i+h++T6c2cdUxmjSoW9IGiFhrO2SWlzHprfs4Y9lHkbbnDz+d0SdeBbZjOtZAF2sNjGQNfn6RTECNRTmFFX6Q7zSWgkpVdFZtk4wwVwEuAPYzxvxdRPYF2hpjPkuikL2pmEFMAH5zOKlbGWNu8Tu+viqI3r178+mnn3LmmWfywgsv0KhRKmIElDDxLsCTzMVxvJ7wowmVlfD01L9x/KqCSNuDxwxm4nEX+srkfNIOO67DT9eQ3EE71iyhJms1+c0unMQK462vCyQlQ0E8ilVA8gRjzMF22OlsY8zvkyhkbyoUxB7Aq0B7YDUw0Bizwe/4+qoglJrFKwfAi6C5AUGJZS5x0qRkB6/+axSH/fRdpO1vJ1zOs78/q4pMfsonO5RJ46yMKoUJIfHBLxm5FNEzu7nL1iekUIJ+p7GutbrXlK4kIw/iSGPMNdjlvo0xG0lyuKsxZp4xpr/9/jdjTF9jzEH2X1/loCjJwivWv6YWxwmvQ+1VaM8px45QE84cOonD/vIKa3bfC4C/vv8kK+/pz10Db6kU6++1Qh5YkTxuygEqHLjxUp1cCreifC8uWJ1wkb4g5wwSxlvd/JC6ShAFUSIimdhrg4hIGypK0itKvcGrwN0FR7UPXM00GfTp1MZ1xbljDmhFpu1vyBDrn3dzk9047qqn6XntC2xp3BSA26dOYOU9/Tn0szmRwTZREqmYGk/112j8lFmYeIr0uckSyhBaNg3FVdW2OtdUl/E0MYnIc8aYYSJyATAIOBwrL+E84A5jzGs1J6Y/amJSkoWXfbwmIljyCwoZ+9aXbNxe+YlegGMOaMXnqzdVKTXhjGLatrOUZj8VMv+xyuHQFw6+k/906OZ53pZNQ+woKfccmBMxNTnvV07TEMZQKdoK3HMtgpqEvEw7bt+T17niRaOYKh/4uTHmcPt9J6Av1vcyxxjzdSqETRRVEEq6E2twieWk9sqIdg7ezsH1gF/XMOfpqyvtO+Ci+1ncrvITb9gZvfCHDZ65EtWxs8dbQymoD8ZNadXXSKNUUh0fRFMR6S4ihwNNgU+Aj4Fsu01RlADkFxQy4rUllezoI15bUsl0E8u04hXD70wAc9rDV7Tel7yRM+g/dFKFHC/cxKp7+vO79auAyuaVucvWe547p2ko4RpGbtdVUmZcayhNmLXc1ZQTjZdpR9eMSD5+mdS5wP24++gMUHdjuxSlBhnz5pdVBsSScsOYN7+MPNnGyiT2mkE4lYJbZvEXex9I3sgZHLl6KVNevhWA2c9ca21csQL2j33+rTtKI2avsHIb+9aXFG2PnaAXT4b02qJi11IfQaOYanrNiPpocorGT0F8Z4xRJaAo1SC/oNAzSsjZ7ldXyCvhy61EBlQeXMN9ftq+C3kjZ3DCd5/xzLS/WQcccAA7s0LMnfmJ5/lFcFVuToVxw5TFjHnzS9eM7Fj1kpzsnm3NVMKyT4wzEdHrXKmINGooxf/8fBAFxpjYRfbTAPVBKOlIkOS3SYO6RezuAlUctM5SGIk8sXYbO9tVQZ315VwenHF/5PPmlm04+dJH+CmraaQtO5QZOKs8vH+0vf+O/KW8tGB1pety80GEMgTEMj/59edHIj6IRGcBfolz4QS9ujCzqI6TOlUF+pKOKgglHYmVmd2sUSblhkoDWlhJ5CZpYAn7P6JnAWEu+nwGf3/3scjnFXvtx5l/vJecPVvFlYkcxuk8dhuwBbjgqPb07NAqMojunh1i844S3ESMN4IqngG/Ok5tv2iraMWazo7ytK3FlExUQSjpiN8gEg5RTSSDOd6nXuf+XvJc9/Er3PRRRUlxjj8eZs8m/6tfA5UACeOMeApSniLWLCuecNZ4B+DqlM+ozbIsySQZmdSKoiSAl+07U4QJ53Vlk4dvws+p6pZpHCuZLZyhvXL86Z5Z2tNPuwTKy2H4cKvhww+hSRMG/P06xp95cGQlt5zskGUi8sB5zUGcxrGit9zuods9GD5lMXfkL/XsJ5YcTgqLimNGa43o19H3PgQ9V7oTU0GISBOXNu/lyBRFAbyzb+8/vysDuucmVL6huqGcvhnBIvDAA1BWBsOGWRtff52zjshj/nf/YuXdp7J49MlMOK8rLZtWXQUw2mke5Pr8Bs54wlkN8NKC1XGF4Prd51iKd0D3XJo1CrKcjsXu2d6rJqYzQWYQ/xWRo8IfRORcrHwIRVF8iLU+cyLlG6obyhlkzWgyMuDZZ2HXLjjjDKvt6achMxNuuYUB3dpR8NeTmTSom28/Qa7Pb5blZrfPLyj0NO0YiCvnIVbORSzF6zUDdKOkrG5WJwpSzbUL8AzW0p/tgD2Ay4wxP6ZcuoCoD0Kpq8RrS6+VstM7dkDfvvCx47lw3DgYNSrmoYlkkHs5dYOWRI9nnY5YFXT9ssjj9UOsSsOqr0lxUovIAOAFYAtwvDHmO/8jahZVEEp9xKuuUK2Vk9iyBY44ApYtq2h77DG48spqdRu0vHfQATmR+5GI4g2qsMLURQURxAfxNHADcBhwCfCWiFyTNAkVRamClzMaiG0iShXNm8PXX8P69bCnvVT8VfaKdq+8EldX+QWFkfId4RIbK8efzoh+HZm2qNDVCR/UjFZcUsYNUxYHLguSX1DItp2lVdpjmfvC5rpwhV0/cuqoDyKIiWk4MMnYO4rI7sADxpg/1YB8gdAZhFIfcD5JZwQozlfrFBZChw6WUzvM22/Dqad6HuJVsTZWsb5w9FW8pcuDJMq5zQJaNg0x+oxga3XHmkmEMoQJA7vWyTyImDMIY8xE49AixphN6aQcFKU+ED1j8CrO5xwgnU/h8RbRSwq5uVBaCt9+W9F22mnWjOI//6mye/gao5UDVDiE/ZzwbutkxHp2j+Vo9gqzbdooK+aAHr7/w6cspkkog5zsUCQU2LneRLoqhyDEjNMSkYOAccAhQCTk1RizfwrlUpQGRZCFcoCIOSOtagEdeCAYA0uWQLduVttxx1l/CwoibbGusbComFyPekqhTKlSsgMgKwNKYgQI+ZmmEo0Ki77/G7eXkB3KjLt+VLoTJMz1WeBRoBToA0zGclgripIkgtrXwzOLVJa2Tnhm0rWrpSjmz69o697dmlF8803MaxSs1fTcEtB2lRnXLPBYygH88x0SXUq0oZQWD5LpkW2MmSMiYoz5ARgjIh8Bo1Msm6I0GIJWPQ3b4lNV2jopM5NjjrEUxaxZcMopVlvHjqwEjr76Wda1aON6mAHmLlvvWYIkCNEFD90czdGr3YUypMriRX7H+H1XdTVj2osgM4gdIpIBfCsi14rI2cCeKZZLURoUQRbKCT9hQ+JPvrFI6pNxv36Wonj11UjTJ49eQsGDQ2i1fZPrIWuLiuNKQIsmXOjQK8LrjvylDJ+yOOLr2bi9BISI/8DtGLeIMi9SUVq8Ngkyg7gBa0W564G/Yy0UNDSFMilKg8NtLYe8PbL5eMWGyBOxAaYtKqRnh1auiwPFCssMQkpmJgMHWoriqafg8stpuWMLn//jAla2bMsZQx9ka+OKEuPtEoxWChMrb8HNj1FSZmjWOIvFo092PS6ofyiUKdW+/+lGkCim/xpjthpjfjTGXGKMOccYs6C6JxaRfUVkroh8LSJfishf7PZWIvKuiHxr/21Z3XMpSl3AWVRv/qgTWPVb1eqr4ad5t5IZ5/bIZcKs5dWKakrVzAQgv8ep9Bo3h3G9LwFgv43r+GLS+bw++SYal+yMKLggsyk3YinICbOWe1azTcSRHU2zAJFPdQ3PGYSIvOl3oDHmzGqeuxS4yRjzuYg0BxaJyLvAMGCOMWa8iIwCRgEjq3kuRalzxHqaH9A9NzIgJSuqKVUzE6d8jx95Lo8fcQ4jP3qBqz95le7rlrP8gXP5qVcf9v7rLAhZSWVu2dVeM4umoQzujpEw6DfQx3JkB5nRVMc0lq74LRi0HlgDvAx8SlTIsTHmg6QKIvIG8LD96m2MWScibYF5xhjfX6cmyin1Eb/SEtELCiWzRlMq1lr2lG/3Jsxf9So88URF4wUXwOTJVtHAKA649W3XHJFMEVaMO833WrySDwV8w1ODltRIqyTGgFQnUW5v4DbgUOBB4CTgV2PMBylQDnlAdyxFtJcxZh2A/dfVIS4iV4jIQhFZuH79+mSKoyhpgZ+pJbocdTJ9B9GmrmSYTTzl27QDHn/cSrg77zyr8aWXrMqxf/mL5btw4JVA6NYeJPkwvMKd3zVGm/Na2pFPTpIxy0pHPBWEMabMGPOOMWYocBTwHTBPRK5LpgAishswDbjBGLM56HHGmCeMMT2NMT3btHEPm1OUuoxzYHLDGV2USt9BUPzyJ2LKl5kJr71mVY49wX4Kf+ghaxYxdmxkf6+6R27tXs7lTJGI32bioG7cOaBLzGtzKs2Cv57MhIFda6ceVg3j66QWkcYicg7wInAN8BAwPVknF5EQlnJ4yRgT7vdn27SE/feXZJ1PUeoa4YHJq6RE+Mk8kbUlkkmsle4Cy9e4McyZA1u3VmRljxljJdv94x8MOXJf1/O7tXvNWsqNqfbsKBWzrHTEU0GIyPNYCwMdDow1xvzeGPN3Y0xSCr6IiABPA18bYx5wbHqTijDaocAbyTifotRlYj2BB1oIKIXEyp+IW75mzawyHRs2wL724H/99dx59mHct2NJZMaQKcKFR7V3nQWkw6yqruPnpC4HttkfnTsJYIwxLap1YpFjgY+ApUA4Yf42LD/Eq0B7YDUw0Bizwa8vdVIr9Z14FtapDfYbNdM1hNRvwZ0wgZziP/1k1Xzats1xYD6cdZZvv+l8z9KBpCwYlO6oglAaAqmILkrWeb2ilDJFKDfG87i4B/GVK2H/ynVC//P4FI694vyEZW/IqIJQFCVhgg7gQUJB3Y6LNzw3fJ7cdSt57+k/V9742Wfw+9/HdW2pUh51RTFVez0IRVHqFslcJyJobaZoH4NbVJHbcfGG54bl+a51e/JGzuDMix3uyyOOsJzZX30V87piOdWrQyr7rmmC1GJSFKWOkOx1IrwG6sKiYvJGzQSsQndjzuxcKbN7P3tbrP68spS9HMnRx/+v7e/IGzmDo39Ywsuv3G41du5s/V25EvLyXPvxU3zVfdKPpVTrwswijM4gFKUekex1CoJE/BQVlzDitSXx5T3YxBue69XvJx26kjdyBpefc0dF4377WdFQP/1UZf9UlUv36yOsrOvSzEIVhKLUI5I98AUtnFdSbiopoaADf7zhr7Hkefego8gbOYO/D7TLt23fDm3bQvv2sHFjZL9UhsB69ZEpUucWGVIFoSj1iGQPfNEDuB9OJRTPwB9P0llQeZ7Z/zirTMeDD1oNa9ZAq1ZW8t22bSlNLPTq26tMSDovMqRRTIpSj7gjf2mVNQ9ixf7HE3ETq4BgTRerCxwFNXaslZFts/CA7rw17ineW1EUlz8g6L1y22/CrOVJK6iYLGJFMamTWlHqCfkFhUxbVFglq/XcHrm+yiEep/aIfh0ZMXUJJWWVHyxDGdVfLCeR0NCg5cnzz7yMW0uO4JZ3HuWSRW/Rc0UBPc/vwcCjT+Lq/iP4sai4Uta3l3xB75XTYe8kFaXUU4mamBSlnuDmoA6v8xzPMX528QHdc5lwXldaNg1F2nKyQ0wY2LVa0TjxhIY6w3gnzFrOuT1yY5qyJsxaTnFpOWNPvJL9bnmT6Z37AHDoJ+/y0e0nc+eshyncuN3XaVzdAIDaLoeSCGpiUpR6QiLlLqpTIiOZBDUVJVo+w+06s8pKeWL6nZzwfcXY8chRA3my359YPKZfoD6g5u9VMtFEOUVpICTioM5xzASCtKcKv9BQZ7Jfok/xbvegNDOLSweOoeON0yhoa5l5rlnwGovHnsIXw/8vUB9+7fUBVRCKUk9IJDLHy4CQKsOCV5a33yDrNDcFDeONPk+fTm2q3JtwFNTOUGPOvvh+utwwhe9btgPg0El3WlnZTz0V2T/W/U1mBnu6oApCUeoJidi4vdZRTsX6yn5+hlj5DeFZQpCneLfzTFtUWMVXccFR7Sv1saVxM0644gkOv+4lNjZpbjVefrmlKF57zff+1kZ5jZpQSBrFpCj1CK/oGS/iLXVRHfzMQ2E/g1coKFizhImDusWMBPI6z9xl66uEk8783zo2bq+sDDc03Z3+o/OZf8FBVoIdwPlWtdjXB46Fw4+tsoZ1Kkt3uJHskipe6AxCUeoZQZ8s8wsK2baztEp7qkIvY5mHwglzOdnu/o92OdmBZknxZJOPPqOzq+mpT6c21kJFxvDu6x9Gtj3/2mjm39qXKQ9OqXRfU1m6w41kl1TxQmcQilKPCPpk6VWeu2XTEKPP6JySp94gs5X8gkK27aqqtJx5FrFmSfHMigZ0z2XhDxsqJRcaYNqiQnp2aMWA7rmMWVbC5SNncMjP3/P2c9cD8PLzN8HzN8GSJXDYYTU6E4OaU0g6g1CUekTQJ0u3/QA2F5cyfMrilNi0gzjRJ8xaXiUJD2C3JtazbJCZUbzO+rnL1lcJX3Xes/Cg+9Ve+5M3cgbnXXBPxY5du4IIYw5uVKNrgtdURJUqCEWpRwR9svTar8yYlDlZq2Me2ri9JLATOB5nfX5Boa/PA6oOugv36UzeyBncNOzuSNtJA47jy3H96SpbayQJLpW1pJyoiUlR6hFBTR1e+zlJhZM1UfOQXyVUrwKAQeoqhc1vXrKAdzmP466/GJ69FaZMgcGDySgr443xg6FNG2vRotatfc9fHcLXluq1JXQGoSj1iD6d2lSpcur2ZBm0jHcQm3Ysp3g84Zg1WQnVy8wWPqfT5+E7Ixk0yEoceewx6/P69ZaSOPhg2LIlYfliEU8V3ETRGYSi1BPiKdYX/jzmzS8p8sl5iGXTjuUUjzcc0+vJ2Cv8NRGbe7gooN8MKto8FCh8+Morrdc998CoUbBsGbRoAcccA3PmQJMmccta26RtLSYROQV4EMgEnjLGjPfaV2sxKUocpa8DHAPBahx5Hd+yaYimjbKSVho8SA2mINVg8wsKGfHaEkrKvce9nOwQi0efHFg2V4yxlMS991a0nXEGTJ8OWenzXF4nazGJSCbwCHAqcAgwREQOqV2pFCW9SST0MZ6n6Hj63ri9xLfveE1Dscw8QTOZx7z5pa9yACtxutqIWDOJ8nK47DKr7a23IBSCYcOs9jpAWioI4AjgO2PM98aYXcArwFm1LJOipDXxhj7mFxR6rsqWayelJXrOVBznZ3P3Cu+9ISpk18+cFqZoe+x9AiMCTz4JJSVw9tlW2/PPQ2Ym3Hhj6opeJYl0VRC5wBrH5x/ttggicoWILBSRhevXe9e7V5SGQtDQx7DT+IYpiz3LVwcNlwzq7I4lU3WJNUuKJ2Q3JcltWVmWeWnHDvjDH6y2iRMhIwPuuiv550sS6aog3B5sKv2WjTFPGGN6GmN6tmnTpobEUpT0JUj8v9MU44UheD0ft3N6lcqAinDVCbOWJzXHItagHj5nyxhlzFO+wlvjxjBvnhXddOihVtsdd1gzjX/+M3XnTZC0dFKLyNHAGGNMP/vzrQDGmHFu+6uTWlGC4eeUDlPdNZLdHMqhDAGhUpZ0ECd4dc4ZjQATB3VzXTIVrOsOK4dU5xdE2LABunSBtWsr2l58ES64IDXni6JOOqmB/wIHich+ItIIGAy8WcsyKUqdJ5ZzOBlP0G6zit2aZFUZlJNZXM55Ti/Cxf4mnNe1kmyTBnVjle3XWPjDBoZPWRz30qcJlyZp1QoKC61X48ZW24UXWjOKt96Kv78kk5YzCAAROQ2YhBXm+owxxtNQpzMIRQmG3wwiN4VPyzW5XKfbbEKwTGd+15hfUMhwD79MspY+jT5flZnK7jvhgAMq7zhvXoXfIsnU1RkExpi3jTG/M8Yc4KccFEUJjpcje9KgbinLxoWaXa4zejYRVg7gPyOYMGu5q3KAqjOv6pbb9gzL3dTYimxa6igB0ru3NaNYtChQ38kkbRWEoijJx838c26PXCbMWp7SlclqqrhcmHBIbG5Otm+lVid+5rdoRVbdctsxFcyhh1qKYsGCih169rQUxbJlgc6RDNInpU9RlBrBWTaiplYmq6nictHEM5B7FQp0C/vNaRqqshJduD2pch15pKUo3nsPTjrJajv4YOvvqlXQoUOg8yWKKghFacDEepJN5oAe73KoySCehXzcqrYKcMFR7avI7eW6DerSjXuBoRNPtDp//XU45xyrLS8PmjeH779PWeVYNTEpSgPG60k2PJMIEs2TzviZtqKjkIAq5reJg7px54AuVfrd5JGR7dUej1y+nH22pSiefdb6vGULjHON/k8KOoNQlAaMl6kkQ4hr/YWaIEgxvmi8TFuAq2lt3DldAuWAVHeJ0Wqb3IYNs14ffFBhckoBqiAUpQHjZRLxqmeX7DWPg1IdX4mbaavX+PerpQC9FhGKx+meFJNbisJfw6iCUJQGTFCTSJiU1CkKgJ+vJJFBNh7ntd/Mpaad7jWNKghFacB4mUpyskPsLC2v1hNyMqluWGk0QU1EsWYu9U0hRKNOakVpwHg5S8ec2Tlm4b+aJFainVvZC79SGEGdxNVNiKvr6AxCURowbkuPNgllRLalyxOyn83f7Sl/xGtLKhUH9Hryj2UiSvbMpa6hCkJRFHaWVqxwtnF7SUqS5aqD34Du5nB2WzUu2mcRRAH6maISiaqqa6iCUJQGTrIdwKnCa0CP52k+3id/r+S5vD2yK61tHZm1kD5KNRmoglCUBk5dN6N4PeV77RsPA7rnsvCHDby0YHWkppMB5q/YUGXfknLDbdP/V69mFeqkVpQGTk1WWk0Fbg7nUIYQyqy8MGWiUVhzl633rPIazfaS8jqffe5EFYSiNHBqutJqsnGrUDthYNfIwkBQvaVOqzOTqusRT2piUpQGTn1I+vJzOFe3Wm08Jiw36oqpzg1VEIqipFVIazJJhgPezVEdyhDXSCk36oqpzg01MSmKUm9JhgPey4QVhLpkqnNDZxCKotRbqruwTxi3GdaEWctdTU+ZIpQbUydNddGoglAUpd5S3YV9/PDK7q7NkiTJRhWEoij1luou7ONHfXDux6JWFISITADOAHYBK4BLjDFF9rZbgT8BZcD1xphZtSGjoih1n+ou7BOrnEZ9de6HqS0n9bvAocaYw4BvgFsBROQQYDDQGTgF+KeIZHr2oiiK4kN1cjzCRQDrU+JbvNSKgjDGzDbGlNofFwD72O/PAl4xxuw0xqwEvgOOqA0ZFUWpewRZZzqojyBoqW+/suJ1nXTwQVwKTLHf52IpjDA/2m2Koii+eC3uE3Sd6WiChMhWZynUukDKZhAi8p6IfOHyOsuxz+1AKfBSuMmlK9d4AxG5QkQWisjC9evXJ/8CFEWpUyR7cZ8gNapinbOuzy5SNoMwxpzot11EhgL9gb7GRILOfgT2dey2D7DWo/8ngCcAevbsmYSgNUVR6jLJrkrrt0hRkHPWh9lFrfggROQUYCRwpjFmu2PTm8BgEWksIvsBBwGf1YaMiqLULZJdldYtgzraf+F3zvqwXGlt+SAeBhoD74oIwAJjzFXGmC9F5FXgKyzT0zXGmDKffhRFUYBgT/zRuIWxQrDchvyCQrbtLK3SHj7n8CmLXc9Zl4r31YqCMMYc6LPtLuCuGhRHUZR6QLyJa65rWU9dAoZKK8U5zUJhhVJYVIxQ1UHasmmI0Wd0ZkD3XM9SHHWpeF86RDEpiqIkhXgS19xMQCVl3mtZQ+XS4W6Oz6aNsiLnT2RGk26oglAUpUES71rWbgrFr8/6UIpDFYSiKA2SeNeyDqJQos1Hdb0Uh64HoShKg8R1LetMIZThvpZ1LN9BXTMfBUFnEIqiNEi8TEBubeF9o30KYUd1bh00HwVBTDIKo9cyPXv2NAsXLqxtMRRFqefEqu5a1xCRRcaYnl7bdQahKIoSkER8CnVZqaiCUBRFSRF1vdyGOqkVRVFSRF0vt6EKQlEUJUUku4BgTaMKQlEUJUXkNA3F1Z5uqIJQFEVJEV5BonUleFQVhKIoSorYVFwSV3u6oQpCURQlRSR7jYqaRhWEoihKinAr51GXSnJoHoSiKEqKqOsVXVVBKIqipJC6XNFVTUyKoiiKK6ogFEVRFFdUQSiKoiiuqIJQFEVRXFEFoSiKorhSLxYMEpH1wA9xHtYa+DUF4iQLlS9x0lk2SG/50lk2SG/50lk2cJevgzGmjdcB9UJBJIKILPRbSam2UfkSJ51lg/SWL51lg/SWL51lg8TkUxOToiiK4ooqCEVRFMWVhqwgnqhtAWKg8iVOOssG6S1fOssG6S1fOssGCcjXYH0QiqIoij8NeQahKIqi+KAKQlEURXGlQSoIETlFRJaLyHciMioN5HlGRH4RkS8cba1E5F0R+db+27KWZNtXROaKyNci8qWI/CVd5BORJiLymYgssWUbmy6yRcmZKSIFIjIj3eQTkVUislREFovIwnSST0RyRGSqiCyzf39Hp5FsHe17Fn5tFpEb0ki+4fb/xBci8rL9vxK3bA1OQYhIJvAIcCpwCDBERA6pXal4Djglqm0UMMcYcxAwx/5cG5QCNxljDgaOAq6x71c6yLcTOMEY0xXoBpwiIkeliWxO/gJ87ficbvL1McZ0c8TIp4t8DwLvGGM6AV2x7mFayGaMWW7fs25AD2A78Ho6yCciucD1QE9jzKFAJjA4IdmMMQ3qBRwNzHJ8vhW4NQ3kygO+cHxeDrS137cFlte2jLYsbwAnpZt8QFPgc+DIdJIN2Mf+ZzwBmJFu3y2wCmgd1Vbr8gEtgJXYgTTpJJuLrCcD89NFPiAXWAO0wlrzZ4YtY9yyNbgZBBU3L8yPdlu6sZcxZh2A/XfPWpYHEckDugOfkiby2eabxcAvwLvGmLSRzWYScAtQ7mhLJ/kMMFtEFonIFXZbOsi3P7AeeNY2zz0lIs3SRLZoBgMv2+9rXT5jTCFwH7AaWAdsMsbMTkS2hqggxKVNY31jICK7AdOAG4wxm2tbnjDGmDJjTfP3AY4QkUNrWaQIItIf+MUYs6i2ZfGhlzHmcCyT6zUicnxtC2STBRwOPGqM6Q5so/ZNcVUQkUbAmcBrtS1LGNu3cBawH9AOaCYiFybSV0NUED8C+zo+7wOsrSVZ/PhZRNoC2H9/qS1BRCSEpRxeMsZMTzf5AIwxRcA8LF9OusjWCzhTRFYBrwAniMiLaSQfxpi19t9fsGzoR6SJfD8CP9ozQoCpWAojHWRzcirwuTHmZ/tzOsh3IrDSGLPeGFMCTAeOSUS2hqgg/gscJCL72dp/MPBmLcvkxpvAUPv9UCzbf40jIgI8DXxtjHnAsanW5RORNiKSY7/PxvrHWJYOsgEYY241xuxjjMnD+p29b4y5MF3kE5FmItI8/B7LTv1FOshnjPkJWCMiHe2mvsBX6SBbFEOoMC9Besi3GjhKRJra/799sRz88ctW2w6e2ngBpwHfACuA29NAnpexbIUlWE9OfwL2wHJufmv/bVVLsh2LZYL7H7DYfp2WDvIBhwEFtmxfAH+122tdNhdZe1PhpE4L+bDs/Evs15fh/4U0kq8bsND+fvOBlukimy1fU+A3YHdHW1rIB4zFelj6AngBaJyIbFpqQ1EURXGlIZqYFEVRlACoglAURVFcUQWhKIqiuKIKQlEURXFFFYSiKIriiioIRYlCRLbGsW9vETnG8fkqEbnYfj9MRNolcP5VItI63uMUJdlk1bYAilLH6Q1sBT4GMMY85tg2DCsOPR0z9RUlJqogFCUAInIGcAfQCCs56gIgG7gKKLNr3VyHlbW6FatKak/gJREpxqoi/DVWCeZfRaQncJ8xpreI7IGVLNkG+AxHvTC73+vt834K/NkYU5b6K1YUNTEpSlD+AxxlrMJxrwC3GGNWAY8BE421NsBH4Z2NMVOxsoAvsLcV+/Q9GviP3febQHsAETkYGIRVUK8bUIalmBSlRtAZhKIEYx9gil3krBHWWgXJ4njgHABjzEwR2Wi398VajOa/Vkkdsqn94nRKA0IVhKIE4x/AA8aYN0WkNzAmgT5KqZi1N4na5lbzRoDnjTG3JnAuRak2amJSlGDsDhTa74c62rcAzT2Oid62CmtGAHCuo/1DbNORiJyKVZQOrIJq54nInva2ViLSIUH5FSVuVEEoSlWaisiPjteNWDOG10TkI+BXx75vAWfbC9cfF9XPc8Bj9rZsrAqbD9p9OB3NY4HjReRzrJLbqwGMMV9hOcZni8j/gHexlopUlBpBq7kqiqIorugMQlEURXFFFYSiKIriiioIRVEUxRVVEIqiKIorqiAURVEUV1RBKIqiKK6oglAURVFc+X+vuQdhT6v+nAAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "r value :-0.89\n"
     ]
    }
   ],
   "source": [
    "# Linear regression on the Northern Hemisphere\n",
    "x_values = northern_hemi_df[\"Lat\"]\n",
    "y_values = northern_hemi_df[\"Max Temp\"]\n",
    "# Call the function.\n",
    "plot_linear_regression(x_values, y_values,\n",
    "                       'Linear Regression on the Northern \\n Hemisphere for Maximum Temperature on ' \n",
    "                        +  time.strftime(\"%x\") , 'Max Temp',(10,40))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "r value :0.43\n"
     ]
    }
   ],
   "source": [
    "# Linear regression on the Southern Hemisphere\n",
    "x_values = southern_hemi_df[\"Lat\"]\n",
    "y_values = southern_hemi_df[\"Max Temp\"]\n",
    "# Call the function.\n",
    "plot_linear_regression(x_values, y_values,\n",
    "                       'Linear Regression on the Southern Hemisphere\\nfor Maximum Temperature on '+  time.strftime(\"%x\"), 'Max Temp',(-50,90))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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IjAQk/wcclC2q5YABA5R2V9XYUb20hhtnr6CufvcjVJYoZfIpfTz/uIVRRthEJVNcrt2LHHbHOHHOwK4M6NbR17V5KT9RIkw9vS9V/SqpXlrD2KeW09CY+dt6Tkw6BxFZopQa4Lg/nyExRKQ7MNfSMawFBiulPjQzZi1USvUyZwsopSabx70ETFJKve5Wvu4YNE4MmjKfmtrMbJ6V5WUsGj80sjLCJqhMbiNku31TX1ob+NqDzjTSzxvSuxPTF39Ag81vVFKO6qU1jJ253PYYO0pF2LdDW9trq2iXoF3rVilyA57LF/N/iYjj8aUivD/5BE+y5pNsHUPUC9z2UUp9CGB2Dt82t1cCb1iO20RqisYmROQS4BKArl3dklZpWjKbbV58t+35KiNsgsiUPuKtqa3jxtkrmvbb7XMaHWe7dre6sqlq0s978o2Njsdvrq1rOsdrpwDQoJTjNWz/sr5J/VRTW8e4p5aD4Ln85FFux/uRtZDEZeWz2GyzbUGl1MMYydsZMGBAcbSyJnK6lJfZjgq7lJdFWkbYOMlUliih541/o0GpDH361JfWZvzQ19U38ItnVvBVfWPGj5WbyiTbtTvVNfWltY4dg99RPxg/Dn7PAfcZQzr1NqqgXCkVu5+6+BG1V9LHpgopmXx9i7l9E6n5a/fDSMSu0QRi3PBelCVKU7aVJUqb1ANRlRE2djKVCHxp+YFvUIon39jIhGpjpO40Qt75TYOvH1Yv1+53RhNk1J8kyDmjjtrftg2jYtRR+2c/KAZE3THMAc43P58PPGvZfpaItBGRHsCBwL8ilk3TjKjqV8nkU/pQWV6GYOik/RpOwygjbOxkcvp5nL74AyCcGU6piKdrd6rLabvdDCMflIo0GX7t2rC8LBF6nZL2OS6GZy/k0111OjAY2FtENgETgSnATBG5ENgInA6glFopIjOBVcAuYEzQPLsaTZKqfpU5/4iHUUYQ3Ay46TJ1H/+8bRnJEfW44b24esaynORpVMpTO4wb3svW48dpppFve41XT6oRfTsza0lN1k4qUSKeVEyF9l7LlbzNGJRSo5RSnZVSCaXUfkqpPymlPlVKDVNKHWj+32Y5/g6lVE+lVC+l1Av5kkujiTtJ9UpNbR2K3Qbc6qU1tsc76a2T26v6VeY8IvY66/A7y8qnvaa8LGFbt137zlpSw6n9K6k05bFr0fKyBEf2qLCtK1Fi7I/LzDJXijqDm3ZX1TRH/LqkTqheYevBY1VdePHFL0uUcmr/yoyRcxij3+QMqKa2DmG3Z0n71qV8s6sxL4beJJVpMy6n9k26qzoZpivLy/jos69sbRtxcUP1StzcVTUaTRb8GnCTP/5Jn/90ryTY7Sqavk5gwZqtGeqqAd06hrriOb1Tsv6s7vymgdISobwsQW1dvX0BOZLuMuvFXdWOzeYMw45icUP1iu4YHIhLOIAoaYnXHCVe2zeIm+ztVX2yGjbt7CUTqlcwffEH1NTWMXbmct7asK3JQBsW2QzMDY2K9m1a0b6N82g9V6wus07tm40uWWYMzQkdRM8Gvzre5kBLvOYo8dO+UbnJJlVQTm6uYeHFwLy5ts72uhMlQqI0nB/dpBzjhvciUeKvzGT7O7mbFosbqld0x5BGcrGN0yKd5orbwiSNQfXSGgZNmU+P8c8zaMp8X52mn/aNyk026c7qdXtQvBiYS0S4ZsYy2rQqoaLdbiPu1NP7cub39g9lRK4w7AsAJT46Bmv7317Vh3MGdm2Sx+oG65VcnqOo0KokC9kW2xQyFEK+iWP4hzgRNNRDEr/tG4WbrNNzHra+3M6F1anO2rp6yhKl3HPm4U0B6WYtqQlNppraOscAd+kkSoWpp/XNuA9e1HZO5PocRYXuGCxk04XajXy86o3jrr+PY/iHOBEk1IOVMNo32zPkd3+JgNPv46Ap832X74TV8J3ulSQC6b/5dfUNjJ25vOkcPwvgrJ5FpQ7B7Lx0CgDtWxs/j4OmzM+45qBtketzFBW6Y7DgNjq20/F67f2LYZTgd2FSSyPXGVWu7ZvtGQqy302P7Lf8bDjNgHq4LM7zGko7SVmilIkjU/Mi9Bj/vKMnUTZq6+ptr/mtDdtSXHr9tEWxzMy1jcGC0+jNKRyAV71xMejv4xj+IU44PRslIp50xLm2b7ZnyGn/pDkrGTRlPlfPWJaxvzFLnV7Ktz7Dbrpzp31uM6a6+oasi/eS/53aM5cZb6mI7TU/+cbGwO+z35AhhULPGCw4jeqcXmCvvX+xjBIKFf6hGHDSkydHtpB9tJhL+2Z7hpzcL2vr6nNaH5AsP1v9QUJ7Q3b7Q4NSlCVKAy+4syu/tESyqpPS6/SCl/e5WGbmesZgIazl/Onbg4wSisFzoSWRfDbsRrBhzP6y3e9sz1C+/OiT5bvVn82TL5te3aldYfc7GHSmZfdO33163wzPokE9O2bUUelzFO9l1F8sM3MdEiMHvKY/9JsmMS5pFTWZOOmsBVg35cRAZQZNX2k9ximQXi5Yy3eq3y6EhpXkz322NovjM+8nZWihZfWLDomRJ5JeCUk9aINSGTFZkqR7ZSR1l8lRZrqXg11qwDh6LrQ0qpfWOKZtzEVH7MVTxS6khfVZqwy4mtdKemrLIb07MfWltVwzYxldyss4tX9lRggNr5582Tyysl2fG/ny+EuW4ZQQqFSERqVi6WWYK7pjCED6SCKpB3V7OJLbvXg5tMR1FHHHbY1LrjpirzYoNxuFl7UCbqR79NjZDGYtqckYFV/jEs7b2i5e9OpBbDD59vize2+hwDOEF1+Ee++Fu+6Cww7LSxW6YwhAUF9kp/OcEp6nk1y5GdfRSdzXauSC28g4ffbnlzDWOKSPuN0S0oN94nur7F6fcSfZ7Tz5gj4bbs9VPtcFWOvtUJagbaKE2i/rAz3bOb0bdXXw61/DpEmp2wcP1h1DnAjqZeS038+qzjiugYDiWKuRC9nubS7XG5aninXE7bQ+IFl2ur9/Ol6fca+efEE9srI9V/ny+EuvN31Fdi5leXpW3nsPrroKXrBJTXPggfDAAzBsmC85/KC9kgIQ1KfdbZ2EH+K2BgJg0pyVsV+rkQteRu9Brzcfnip+1+R4PT99uxfZ8xljyknODlkSE2WTyevaIy/X5qkspWDmTOjY0VgOftBBqZ3CuefC5s3Gcf/+d147BdAdQyCckoknfdqdHnynqJlBIjPGyd5QvbTG0Vc+TnLmgtcE8kGvt6pfJYvGD2XdlBNZNH5ozrMsp2ft7jMyY//4Od9uFuMme65Re7PNCJwipe78ZpdjHV5k8jIT8XptTmXt+PhTuO46oyMoKYEzz4Tt23cfcN99UF9vdAaPPw6dO9uWkw90xxCAoD7tTqOr26v6OKZedJpNxGmlpNsoOU5y5kL6vYv7fcl1FhLWLCbXVf/ZZi5V/SrZo22mRry+QTnW4UUmLzMmr9dmPefgLf/lqSevZ/2vRrDi3jPg7rt3H9i/P7zxhtERKAU//zm0Koy2X9sYAlLVr9LRI8Nt1Oika5100qGe/cQLvVIy3ZDm5iYZtxWduWC9dxOqV/CXNzZm+Od/aY5U821X8WLMzHUley7nW1N52hFmjKlah6xrNbV1tgHwvMwGvNTryb7R2Mh9dUs5bOp4Wjfuyjx4zBi47TZDhRQjdMeQA2FGJHXz4w471WIu2BnSrNEyrVS0SzQLw3M6yVDQdte8/cv6vBvd427o97IwzOs74mV9g9N7KOxeP2FtIy/vbS71Hpz4Bi65BB55BIAjLPvqWrXhrp9cTZ8bxlDVP77JffTK5xxwWw1ql0u3GEkfmX75zS7bvLh2nUNFu0RW75dixCmZvJXK8jIWjR8aaf251Bmmq3G29knmOYDgLqzpsqe/h06DleQiVKfj7RapOrWNtd7+m1Zx+8v3c/DW9ZmVDh5s2Avy5FoaBL3yOY/YjSqG9O4UOCRv3LAbmTqhICOhexSj50LgNVVl1PUHrTPsGUhWORQ5ha5Ox+49dFNhpUcisHYiXsONS309Vf+spur2a2zreeCo0/jjj/6Xm886siiffT1jCJl8jOaSRL2AzMvIOEky4Fi+rj1OxHnGkAxT4ecZCfuZ9dI+Tkl03Or08/w7yZAexmLSnJW2HnVJOazl7PP5J/xiwZ85afWrGcdvbV/OL/5nDC8fONDwMjKpaJdg6S3/Y98IBSTbjEF7JYVMvhfcBHX7C4JXmZNGuWIJL54r2VxX8+0c4ORKOqR3p0DPSNj3zcmF1IrfsC9+n383l/Lk+eOeWp7Vzbrn0kW8+uCFrP/VCBbfPzq1Uxg5kpef/QcHT3iB7/38SV4+6PspnQIYs+ZijIysO4aQ8eLmFmTBTyGS/ThdS3lZwtaNsViSkORKuitnRbsE5WUJT26dYYRTd3IlXbBma6BnJOz75uRCasWvu6/f59+Le3G9TU6GNru+4cpF01n3qxEgwuMzb6HrZx837f/1D8+j19jZDJo8D+bM4dZVX2eNT1WMizy1jSFksrm5BdXnFmI07nQtk06yNygXSxKSMCh0wDe7+oO4T0N+7puTC2mybL9u2EGef68hQrpt38wt8x5h2PtvZuz7Yr9uXPXDS5i3f19bOQttb8oXumMImWxubkGDfoXpGuuEnQ538il9POt1cwmdHLbccTT45TsRfNBnJB/3zUtwPT9u2Lk+/ynnK8Xxaxdxx8v307FuR8axz393KCe+8AR06cIewMilNaxJczBJhiPPFqzQj4xxQhufIyZoopd8JzKJY6IULxST3PlI8mMlTm0Rtiy5ljf3H2v5+PoJXPj607b7J/74Up7sdwKt27TOqgr0E948rs+idlfNgttoMx8j0TiN6qzkezQL+WnPuMudLQEThDeiLNSMLQpZ3MpzvD/vvGOElXjtNUaklffuPj25+difse6APojgOZy2U/j1pLdTh7KEr/LiSovuGIImMM/lRueiz801xIEb+bZh5Gu1bpzltkvolE7YNph8PiN+CVsWu/KsbSyqke+/9hwnTBgODTbhJy67jOfPGMN18zftfv98htN2eq4alQpl1hcXWnTH4DTaHDtzOXu2beV5JOpnRBmnUZ2VfNkw3GLmhDGyz7ftJZcZSbbRZaHvfT5mcH7KDKP+h2b/iwlzH+bsZS9m7mzTBh58EM47z4heCtw5ZX5OM8wobH1xoEV3DG6Jc5z8m9MfiiAjyjiN6pLkwzPFiz4215F9vj2hcpmRxHl0mY8ZnJ8yc6r/9dfhZz+D5ctJT2Pzxv6HMfHYy/h3p+62bZzrDLOleN4VpGMQkWuAizBWoq8ALgDaATOA7sB64Ayl1HaHInLGLbG7G+n+0FHouMMg2+gsHzOZbIniwd9IK1uKx3zMwHIZIcZ5dJmP59ZLmYFmkLt2wf33GxnNbHjwyFO47+iz2NmmXdO2Sps2dnvncwnqZ/VSKvQsMCwi7xhEpBK4EjhEKVUnIjOBs4BDgHlKqSkiMh4YD9yQDxncErtnI/2cYljt63V0FvZMJlsb+BlpZbuGfL2IuYwQ4zy6zMdzm61MXzPImhoYNw6mT888qFMnQ0X0k59QvWwzv/XQxm7vvN97Yn3e4h7pNiiFWvncCigTkVYYM4XNwMnAY+b+x4CqfFXuZSTrxqAp85lQvYJBU+bbuh+CMQIJY5VrGHhZNZoPWd1GYX4TvxRi5TfklrAml3PzTT5WqWcrM9t7N2j9Ml575BIjrMR++6V2CieeaORBVgq2bKG6x1EM+tUCrpmxjLaJkqwrz+1Sz4L3VKdOFOq5zDeRzxiUUjUichewEagDXlZKvSwi+yilPjSP+VBEvm13vohcAlwC0LVr10AyeBkVJUoExMgElU5NbR1PvrHR8Vxr3Jo4jCT8juTy7YEV5EUs5MwslxlJHO1JkJ/ZTLYy0+9Vm13fcPG/ZnPda0/aF/jLXxqpL9u2Tdmc/rxu/9Lds8gt9WyjUrH2iisUkc8YRKQCY3bQA+gCtBeRc7yer5R6WCk1QCk1oFOnToFkcEuUnhx1TD29L1NP62urq3Qj17g1+SDISC4MWcMcMbeUOExRkY/ZTLYyu5SX0XX7hzwy6zbW/2oEa+8+JaVT2FnZFV58cXdqywkTMjoF8P+85jP1bHN9LgthfP4xsE4ptRVARGYDRwMfi0hnc7bQGdiSLwH8jGSr+lU6rlhNR6ApZHDQuDW5Ymeg9TuS8yprFOklk8RZX19o4hQSJON+KwWzZ8Nll7Fo69aM4+ceOphWd0/luOEDaO+xDr/Pq9tznOvz01yfy0LYGDYCA0WknYgIMAxYDcwBzjePOR94Nl8C+B0t+YnHku2cfI4knEITA67X26EsYVue03a3uvJlR4mzvr6QBL0Peb1/X3wB48cbtoKSEjj1VLB0CveMGMMB455l0OR57HriSY4b7hiZwRa/75bT9jBSzzbX57IgsZJE5FbgTGAXsBTDdXUPYCbQFaPzOF0ptc2tnKhiJXnxpkifcRQibk3QhCv9bnvZNl2nW5KRsJO7nP3I6yx6f/ftHtSzI3+5+Pu+y/FC1CPsIPV5PSfofcjl/tnKlthuhJ/4+98zT+jb13A3Pfpo13K94vfdckv9aZfKM/3c9GuF+C1Q9UssYyUppSYCE9M2f40xe4gdTr7LbnmdC7HCOahKyClEslvo5DCNbumdAsCi97dx9iOvh945RO1eGKQ+P+cEvQ+5qA9vnL2Cr76p55R3F3DnS7+nzY02z8mll8Ltt8Pee7uWFwS/75b1+GypPK3Y3YdxTy1PcUppLu6p6bTolc9+CKIrj9ojJeiCKqfzyts5q5LCXLyV3ilk254LUS9IDFKfn3OC3IfAC722baPxZ5ezevGcjF31pa1IPPwQjB7dFH4ibPzOvOyOt1tc59S2dvfBLrmP1fBd7DOJJDqDWzPCKeVjNkPYuOG9SJRmZrj64qtdvlInFoPRLWr3wiD1+TnH733wvdBr8WI44gjDXvCtb3GKpVNYvN+hHH/B7+h+w1wOuq4afvrTvHYKfmwiTsc75aK2a1s/z4S1/KhS7+YT3TH4JC6L1uwIagir6ldJ+9aZk8f6RuU5dWKxGN2idgoIUp/TPgUZz5z1PoDhcp0cwdo9m26B/Saf0oeqPvvA739vdAQiMHAgLF3adNzjR5/KYVfPpPsNcznz7F+x+tvfyXo9YRDERdXueD8pRf1cU7LdvcoXd7QqyQfFsPw9qPrqsyxJ0cOsK51BPTvaqo0G9eyYc9npRO1eGKQ+u3OS2D1zyf9enk27+9npi238YsGfqZqyMGPf9rK9uOl/LueFXoNApGnhJ5aFn1HMFMNyUW1QirJEqaf7YXcf7Ba+ppfnRY640yI7hqBeKUH0xVF6wORSV1g2gyAy/OXi70fmlRS1U0CQ+tKNpenYPXNuIeStwd2S9/no9cu4/eX7+c72zZkCnHAC3Hsvg2Z9kFF/faOiLFFCY6PxI1sqwqn9829L8/t8Oh1fabE1ZLsfTvfObpvTvSrWhW4tLrVnLm6kflMzRumymmtdYcgap9SSzQWvz1y2RZitd9XzsyXVXLPwMdv9qy8by8G/+SWU7f4h87qwM4p7HIaLaj7lLLZnP5buqoUkF68Uv6OWoHUFGXXn6m0Txki6WEKQ54N8zQy9PnN2x+1X+xET5z3Csf9ZnHH+h+X7MP7Yy/nPET9wlNWp7nSiuMe5uKgmj+/+rTLGzlzO1TOWUSrCqKP25/aqPgWRL+60uI4hF68Uv/riIHUFtWOE4W2Tq82guQYUy0Y+bU9en7lxw3tx46x3OGbVIu54+Q902lmbUdZzvY9h8pCf8s/7R9OZ3aGM/dTtRByDGVqPn1C9IiXwZYNSTd/D7ByKtSNIp8V1DLno0v2OCoLU5aYrtsoQRl1hEwcZgpLLiN/pnk2aszKUkAvJOmxl27kT7riDqsmTbePU3zb0Yh4/4kR2lRqvup+gkOl1A65h5rNRyJhO0xd/4Lg9rI6hOdHiOoZcvVL8jAqC1OXmTeE2Co1DMK84yBCEXEf8Tvestq6e6qU1oXQOKWWsXAlDz4UFCzIP7tMH7r+f6vY9QrkXybqrl9ZwtUNgSMgejK7QHn1OSbmCJOtqCbS4jiEMXaDXkU+Qutz0um663DjoOP3IEMboMazE87naRtzuWSi6d6XgiSfgssugzqaeiy+GO+4wMpuZVFnqD+N5cPPHLy/LHowuDPtTLs9MqcNKb6d1DS2dFtcxQG66QL8jH791ZdPrRrGuIBe8yBDG6DHMxPNhJIh3Gk0H1r1v3w433wx/+EPmvtJSI7VllpXGYT4Pbtcx6aRDA5/vtX1yfWZGHbW/bXKtUUft76n+lkaL7Bj8Yh2p2MWYCdMrI1nG2JnLbUc45e0SDJoyP6dInU4BAKPSAfsZPTrJ5KeMbMfmahup6lfJrc+ttI1QWyLChOoVrgEXm/jXv+Dyy2HJksx9gwYZK5IPP9xVlqi9o7yGrs61jb2u03CSJWlHmL74g6b1F2F6JTU3dMeQhfSRipNOMkyvDLuVrACJUuGLr3Y1/QAFjdRpHTkly3hrwzZmLamJRAfsdfToNkr0MwLNdmwYtpGJIw+1nelZvV/Sr6Hqu/vCQw/BmDH2hV5zDUycCB06eJKhEN5RE0dmny24ne+1jd1sb+DtWm+v6qM7Ao/oWElZyJbAPEnYnjdV/TJjEbVv3SojumO2eCxe5K+rb+D/Ld4YWawXr/GD3EaJTpFf/cS8KRFpMg5PPqUPFZYy27Ty92oky8ims+70xXZuf+bXVB2xH7RqldopVFTAjBnQ2GjYFX7zG8+dAuQ3Mb3d8+hn8Vau53t5v6KKTeQULy3OcdT8omcMWfA6ExjSO1j+aTfSdcQ9xj9ve1yQSJ3p2EQT9nW+H7yOHt1GiV98tYtEqWTErPEa8yZZTnKUCfBVfWPT59q6et+j7ap+lba2htPfeYWpL/zW/qTjjoPf/hYOOshTHW7kex1JrjaLXM73uqYiitS5drOyKGfcUaA7hix4Xf25YM3WgsmSLVKnF/ndzg8br95LbrLXNyrKyxK0b9PKs3eYnd3GOsoMY9V2qQiJb+r4w7O/Ytj7b9oec++gUTw7/FwW3Hy853K9UMzrSLKR/swEyicRAk6zsqTtIn17sa761x1DFsIaqYRhFAw7Umc28rkGwcvoMZvsn9XVs2yifepRu/quCeA55HkEumwZ9OvH+w67J/74Uh7rPxIwY+iMCF/XXazrSJJke0esz4xTbKJ8X6vTQCUK22OU6I4hC2GMVMIyCgZZq2B3zradX1NnUZsk8ToCj4psHlp+R4fZRtS+RttKwV13wfXXO9b3Pz/9Pf/u1D1lW7Ycw7kQh7UsQQniBg7RXmv10pqUtKBWnNZJFOtsrcVFV82VIFEUc0m8ng+KLRJkWPK6lQOZXmAZCeN7tDdsAoszg9IBcNppzBk7hSur19jurmiXYOkt3mY4drIX4w++V+L2jtjhJKMAZw/smmJjgHi/Uzq6asgEGanELbhcsY0sw5LXSznpCeOP/OBdZv5qPNzoUOgTT8A55zR9PQkcO4Zam3UOXih0OIkoiNs7YoeTLArDFXZAt45F805lQ3cMAfDrXeHHKBjVyDAOq6S9EmabuF13Vb9KaGxky5hruGTxLPsCOnUyFqJ17+5YR2XIRmC/4SSKcXbh5R0p9HW5Jf+B4nqnsqHXMUSA14TtfhOetwQiaZOPPoIDDwQRqgZ0zegU/nL4cfQc9yw9bpgLW7a4dgrg/X57xc9oulifoWxtFofrCvu+xhk9YwgBL94UkF0V4jdUhDUMQ3lZgkknHRrpiCWKEVzekv/MmQMnn+y4e/RpE1nY83sp20pF6DH++UBJYry2jV2b+plx5tJehRyRZ2uzOCSBKjYVbC5k7RhE5OfAX5RS2yOQp+jwqv/1Ms30Eypi3NPLUxZ31dbVM+4p95wNYRKV3js03fOuXXDppfDnP9vv792b7/34F2xtX+FYhJ/wC0HUCk5temr/SlvDpt1INWh7xcGO4dZmcbFBNCd1kRteVEn7Am+KyEwROU5Ex6m14ha2we+SeT+hIqydQpL6RhVJSICkDFGE0PDaJra8/z71e3YAEUgkMjqFtRdeuTv8xOrVtK7s4lkuu2vNNSSCU5suWLPVcziJoO0V1f0MSk7PQQQ0p3AY4KFjUEpNAA4E/gSMBt4TkTtFpGeeZSsK3MI2WHWhE6pXZNWRetVhhrIgK0eiGsH51us+/rjREYjAAQeQ+GJHyu5Tz/413W+YS/cb5lLV+Xiql23OWpcT1msNQwfu1qZV/SpZNH4o66acyKLxQx1HrUH14HEZkTsRZ/1+HOwfYePJ+KyMxQ4fmX+7gArgaRH5dR5lKwq8BveavviDrCMyr4HGsoXAiIKoRnBZ26SuzrAVJDuD889POf9f+x1Cn6tnNHUGS/Y7pGmf1/Z3SodpvdYwRtxhtKndNZza3whT7jaajfuIPNcgfHaENcqP+2wrCF5sDFcC5wOfAH8Eximl6kWkBHgPcF762QLwGnLC65J5r6Ei0m0MAIkSiWwEFWX4hYw2Wb4cZD/nE+65B66+mh7jn3fMUZzEa/tnu9YwRtxhtalb6Agn20ExhNMIU78fpk0l7rOtIHjxStobOEUptcG6USnVKCIj8iNW8eA1ZIbTkvkgiXeS+wvplRS5h8ZvfgNjxzrvX74cvvvdlE1eAghaQ2874eVaneoqsXgyOSVIylYP4PsZSeLVm6c5e9zYeVuF6eXUHIMXZg2JISJPKKXOzbatEBQiJEY2nMIu2HmWJEoFFCk5FuK8jD5SPvsMjj8eXn/dfv9PfgJ/+QuUeY9R5UQYbe61Lr/15hoOxGnWJMC6KSd6lrVYcWo/p/sUpF2KLcQMZA+J4cXGkJKiSURKgf65CtZccdKF3l7VJ5TEO/mk4J4V//jHbltBeXlmp/DYY4YHkVIwe7ZrpwCZ96KiXQI7l7ow2jy9Li9J5r3Um6v+OluSouaOU/s53Z8go/x82D8KjaMqSURuBG4CykQk6dohwDfAwxHIVrQ46ULTtwdJvJMvCuLHrhTcdBNMmWK7e3vbPTnp/Hv4pFNl4Bctyja31uVUj996c9Vfe0lSVMw/YNlw8xpMnznkYlNpbusbHDsGpdRkYLKITFZKOYUQC4SIlGMYsg/DiEH1U2AtMAPoDqwHzmjui+ripJuMbGXpxx/DD38I//637e5nv3ci1w6+hIYSi2tiiHLkq83T9dgdyhLU1mUPmpet3lzlTbaZW5Ki5vSDlo5bfKOkraG52VTCwFGVJCK9zY9PicgR6X851vtb4EWlVG+gL7AaGA/MU0odCMwzvzdr4uSbnVfPiuef360i2nffzE5hzpwmFdHVQ3+W2imEKQf5aXM7P/ad3+wiUeKuTvJSbxjyVvWrpLGZJZLxilv7eV0b0hJx80oaC1wM3G2zTwGBgqSLyF7ADzEWy6GU+gb4RkROBgabhz0GLARuCFJHsRAnT5BQR9K7dsHll8Mjj9jvP+gg+PvfjU7Coxwdyvx7b9kRdptXL62xHY3XNygq2iVo13p34qNsXklhy2udxRQqFWahidM7VkxEnqhHRA7HsFGswpgtLAGuAmqUUuWW47YrpTIC14jIJcAlAF27du2/YcOG9EM0AcjZs2LdOhgwALZts98/fjzceacxa/ApR6JEQEhZtxEHr49snkiF9Pzx4iUVhzbUFIbAiXpE5BS3gpVSswPK1Ao4ArhCKbVYRH6LD7WRUuphTOP3gAEDijf9XMwINLJ64gk47zzn/a++Cscck7McX36zq2m9RpI46Mft7DJWCjkad5KtVIRGpfTIWeOKmypppPn/28DRwHzz+xAMNU/QjmETsEkplcyP+DRGx/CxiHRWSn0oIp2BLQHLjwWFTioShKyeFV99Bf/7v/DMM7a7P/1uf7719/8zXE1DlCOIJ1HY7W9Xnlv9UduK0uVzWtjXqFSLWL+gyQ03r6QLAERkLnCIUupD83tn4A9BK1RKfSQiH4hIL6XUWmAYhlppFUbojSnm/2eD1lFo4hDCODRWrMhYUWzll0Mu5E9H/gQwVRPrdlLVrzxUEcrbJTJmDMntdoTd/k7lOXkelYpEqqKxk88paX1ztylowsFLSIzuyU7B5GPgoBzrvQL4i4i0Bv4LXIDhITVTRC4ENgKn51hHwQjb9TPy2cdvfwtXX+28f+lSBr24LWNUmi/1jpMZzGl7ru1vbe8OZQl2fFVP2jpE6uobaJsosfWFD2MVtZ/7bXe9CjI6h7jFPtLEFy8dw0IReQmYjvGcnQUsyKVSpdQywM7wMSyXcuNCmK6fkcw+duyAE080Vh7bcdJJ8Ne/pqw03vzX6BbnfeawHsBpey7tn97ebmsRar+s554zDw9dZeX3frslqa8sLysqdaYmHmTtGJRSPzcN0Ukr4sNKKXslswYI1/UzbwvP/vlPGDTIef+0aTB6tOPuKBfn+a0rF9myGZTTywt7xWuQ++10veVlCRaND+RVrmnheM3HMFspdY35pzuFLIS5iCq02YdSMGHC7oVm6Z1Chw7w3nu7YxG5dAoQ7eI8v3XlIpvXds3XtQa53+OG97JdTLfzm10tIh6SJnzc3FX/oZT6gYh8TqqqUjBy9+yVd+mKlDAX1bgt+MrKli3wox/BmjX2+y+8EB54wEh76ZMoFw55rSvdNtA2UULtl/W+ZPMSqjts43KuC9Gq+lWmhGBPUt+gXGca+bZdhVF+MXr35Zso2iTyBW5hEsew22FTvbSGcU8tz4jCmigVpp7WN/OBeOEFOOEElwKrjYxnzYywQh9nWxgW9qIwr+G6zxnYldur+jju9xteO9+hosMovxjDWeebsNokjLDbiEiFiHw3xFhJGo9U9atkj7aZE7vkaJCGBrjsst0qovROoWdP2Lx5t4qoGXYKEF56xfQQyuVliaZw3fkIp+zVprFgzVbX/X5Tc+Y7HWUY5TfHlJm5ElWbeEnt+UuMuEb/BRrNzYFjJWn8U5umItjvs4+pfvxa9v7yM7CLeztunBHKusRTv98sCNMTLMoQyl7ly3ac39Sc+U5HGUb5zTFlZq5E1SZe3FXPAHqawe40BaBLeRldVrzJEzNvoe0uh9uwcKFhTwhAFKuE8/1Dmw8vqXxeR7Jsr4rcbNfh1+aTb6+yMMqPU1j6uBBVm3gZUr4LlIdaqyY79fVGnmMRFt04jKf+3/iUTmF5l148v/Dd3SqiHDqF9JDRN85eEdibJezyvBK2l1Q+r8Nathe8XoefMNL59ioLo/w4haWPC1G1iZcZw2RgqYi8C3yd3KiUOilUSTTwwQdGwvunnsrYVbf3Pkw6/ufM7Hw4XSraOY4Gw1g1m8s6icgS/qQRtpeU03Xc+tzKnK/Dza5QGTA8t1/y7VUWRvk6ZHYmUbVJVq8kEVkJPASsYLeNAaXU30OVJADNwivpxRfh0kth48bMfVVVxqyhRw9PRQXxWAg7WXxzST7vdB0A9555eE4vYnNpI03xEjjstoVPlFK/C1Gmlk1dHfzqV3Drrfb7J0+Ga66BNm18Fx3mqtmgOsvmohd2W8/gZ/ZjN4OLSxslZaupraPUXD9R6WMEqtcYNF+82BiWiMhkEfm+dlcNyHvvwfHHG+6k7dqldgoHHQTz5u22FYwfH6hTgOCrZsPUWTYXvbCbvF49QJzsFEN6dyp4G6XbOZKL6rzaUgplS9JEg5eOoR8wELgTI83n3cBd+RSq6FEKZs6Ejh2NzuCggwyVUZJzz929tmDtWhgajuevX192yPTbz9VXP+zyCkVVv0rKHVaXex3ZO83gFqzZmtJGFe0StGlVwjUzljFoyvxIflzd7Bxe/OL1GoPmjZcgekOiEKTo2bEDJk2Ce+6x3/+HP8All0ArL9q7YPj1ZU8Stt9+lOsA8smkkw4N1J5J3GZwyTYqVO6ObLOeoPtb8hqD5oSXBW632G1XSt0WvjhFxvLlMGYMLFqUua9/f7j/fjjyyMjEaeleHGHrvHNtTy+2BKeR99iZy1NkCJtsMaGyzYriYifR5Acvw9edls9tgRHA6vyIE3MaG+HPfzZCUDTYTMPHjIHbbjNUSAWiuYzW/ZKvkXcu7TmkdyeefCPT22xI705Nn51G2A1K5XXmYDe7TOJlVhR0dqopDryoku62fheRu4A5eZMobnzyCdx0EzzySOa+sjJ46CE45xzDlqApGIVaP+GGU3wj63a3kXs+5bfOhoJ4JbX02WlzJ4jCux3wnbAFiRWLFsHPfmbkO05nyBD43e/gsMM8F6fd+vJPHHXeXmRyG7knj83X85Pr7LKlzk5bAl5sDCvYnY+hFOgENC/7Qn29YRy+5hr7/TfcYCS52WMP30UXyrjY0oijztuLTMlnYOzM5bZ5GDqUJfTzo4kcLyufu1m+7gI+VkrtyqtUHslp5fOmTXDddTBjRua+ffaBBx80QlTnqCIaNGW+7Y9DZXlZrNIuFvusxuuq7yiv004mwRhlVbRLoJSRt7qLGQZj1pKaDPnbJkoyEvBA/J4fTXEReOWziCQtqJ+n7dpLRFBKbQtDwILw6aew//6p204+2Qg/8Z1wtWRxVHGk0xxmNV503lFfZ7oeP9kpACk/9jW1dcxaUsOp/SszYiRdM2OZbdlxen40zQ83VdISjOdYgM7AZvMz5vbitTNUVBgG5fbt4dproW3bvFUVRxVHOnE03AYhm867ENeZlMlp5miVY8GarRmzgGSnkk6cnh9N88Nx5bNSqodS6jtKqR7A6uTn5PYIZQyfkhK44w6jc8hjpwDFESKiGGY1YVDI6/RSh90xxfD8aJofXlN8FW9i6AJT1a+SU/tXUmraKkpFOLV/vLw5/IbSqF5aw6Ap8+kx/vnIQjiEQZCQIfmuO/2Y9LYFmkWIEU1x0XJyPxaI6qU1zFpS0+Rx0qAUs5bUxOrH1M+otJiDp1kXlnnZHibZRvhliVKG9O5k27aA5wQ8Gk0YOHYMInJt8g/4tvW7uU3jgWIINuYn8F2+rieKWYiXBWf5wi0oX6kIk0/pw4I1W2P/rGhaBm7G5z0tnx9J+67xSLHo770uVsrH9UTlLVToe+EUlC/ZCWsPJE1ccOwYlFIOmWQ0figGryQ/5ON6ovIWKvS9cHKpfWvDNsbOXO5oyAsqX7GvTdEUDm1jyDPNzaskH9cT1Ug+Dveiql9lir3grQ3bePKNjbarnnORr5htQZrCk7/kABqg+QUby8f1ZBvJhzXyjdu9qF5aYxt9NYlTQDsv7VGotSl6ltI8yBoSI87kFBJDExvcwlkAnkJdFBt215zO+iknejrPrj16jH/eVjUlwDqbcsPAq2yawpMtJIZnVZKIDBSR+SKySESqQpGumePkaVOs6wDyhZtXVDF4dfmlemkNY2cud+0USh1idHltj0Ks2WiO96ql4hYraV+l1EeWTdcCJ2EMOv4JVOdXtOLGydPmrQ3bUoKlFWNconzg5BVVaE+isEk+F042hSSjjtrfdrvX9ihEIp3mdq9aMm42hgdFZAkwVSn1FVAL/C/QCOzItWIRKQXeAmqUUiPMoH0zgO7AeuAMpdT2XOspFE6jp+mLP8j4USjGuERR4WR/6FCWYNCU+YF12YXShds9F+mcM7Art1f1sd3n1bOqEPaUQnt9acLDLVZSFbAMmCsi5wJXY3QK7YCqEOq+itQUoeOBeUqpA4F55veixS1lo5/jWzp2nkSJEmHnN7sCe9wU0mPH7T6XJUq598zDHTsF8OdZle4Ble+OLw5eX5pwcLUxKKWeA4YD5cBsYK1S6ndKqZyWiorIfsCJwB8tm08GHjM/P0Y4nU/BcBolOemO9ajKHjv7wx5tW1HfYD/r8kIhdeFuz4UXI62fVepRE2fZNP5w9EoSkZOA64EGYBKwFLgFIwT3BKXU+4ErFXkamIyxmvo6U5VUq5QqtxyzXSlVYXPuJcAlAF27du2/YcOGoGJ4IqjKwclD49T+lbYJWcJ4geLiKphvOXL1uCmEx04S7bmjiQOBE/UAtwPfB8qAvymljgSuFZEDgTuAswIKNALYopRaIiKD/Z6vlHoYeBgMd9UgMngll1ANbjreAd06hv7DGZdkO1HIkasuu5C68LitpdBo7HCbMbwGPIrRMRynlBoRSoUik4FzMdKEtgX2wlBTfQ8YrJT6UEQ6AwuVUq7KyXyvYyiWtJwQH1mjkCPXUXe2dRN2P9r5mgXFZZanaVnkMmP4CTAKqMfwRgoFpdSNwI2mcIMxVEnniMhU4Hxgivn/2bDqDEoxud/FRdYo5Mh11O10PhCpi3FcZnkaTTpuQfQ+Ae6LUJYpwEwRuRDYCJweYd22uKkc4jbSy1U9EuR67M6JSk2T/uOeNBz76RzSjx00ZX5oLsZxDluh0WSjoEH0lFILkyoqpdSnSqlhSqkDzf/bCikbOLvfOSVUKeQK5lxcBYO4bzqdM6R3p0hcFvPhchqWi7FX2eIyy9No0tHRVV1wcr+LY0KVXFwFg7hvOp2zYM3WSFwW8+FyGpaLcZzDVmg0XtDRVbNgp3KIa0IVr8l20gkycnU7J6gcfsjHaNspjISTi7HTLCjOYSs0Gi/oGUMAnEZ0CooyKF6QkWuhR7v5qN9p1nV7VR9fsyCvsukFYZq4osNuByBbyORiW7AUxP2z0Au1Cl2/G3GWTaOB3NxVNQ5YPWLsPHCKzbMkiPtnoRdqFbp+N+Ism0bjBT1jyJFChlfQaDSaIISWqEdjT6F17RqNRhM2umPIkSG9O/nartFoNHFH2xhyZMEa+wjkTts1xU/cVr1rNGGjO4Yc0atXWxY6vpGmJaA7hhxp6ekMk6Pnmto6SkVoUIrKCEfRueTLsJ43pHcnFqzZmrUcHd9I0xLQNoYcacnpDK0xgWB3TKGoYkcFjZdkd96Tb2z0VI6eIWpaArpjyJEwVq9WL61h0JT59Bj/fFGtnHZLbF9X38DVM5a5Xo/TdXttj6DxktzkzlaO9kLTtAS0KikEcokNVMw6ay+jZKfrcbpuP7kPgo7evY7u7Y7T8Y00LQE9YygwhUxMnyteR8l21+N03dMXf+C5PYKO3v2kAE1HxzfStAR0x1BgillnbWdfcSL9esLIfeBU/5ff7HJVx3mR220WUNWvkkXjh7JuyoksGj9UdwqaZofuGApMMeusraNncM5bAJnXE0bug2T95WWJlO3bv6x3NUInz3Oqq1REzwI0LRrdMYREUANysXs1JUfP66ecyPuTT+DeMw/3dD1O1z3qqP19tUdVv0rat8k0lWVTx1X1q+TuM/ra1nX3GX0BitIhQKMJA218DoFcDMjNLRKn1+txO25At46+2iOoOs5JBqBoHQI0mjDQ0VVDYNCU+baL3CrLy1g0fmgBJGpZOLV/qQiNSvnubPX91DR3dHTVCChmA3JzwMmY3KCUr4VvSfT91LR0dMcQAsVsQM6VOCzOS3chtTMq+3EBbsn3U6MB3TGEQrEbkIMSNCRFPrC6kDb6cHm1o6XeT40miTY+h0BzMyC7YQ0+V2IGzbMSh4ByuQY2bEn3U6OxQ3cMIZFLWIxiId37ys9itCgJI2xFS7ifGo0TumOImGJO8nLrcyuzBp+DwuvivYz4i/k+aDT5RncMEVLMAfOql9aw/cv6rMfFRRfvNuIv5vug0USBNj5HSDEHzHOTsVSkqALKFfN90GiiQM8YIsTOIOq2PU642Q3uPqNv7DsDK3qdgkbjju4YIqTUxosnub3QZNO5O3n6lJcliqpTAJ2OVaPJhlYlRYiTF4/T9qjwsh7Bybd/0kmHRixt7uh1ChqNO3rGECGVDiNVMOLzFMozxkuC+6h9+/PpNRT0WtJlGtK7EwvWbNWeTZpmhw6iFyHp3jDplCVKC2K87TH+eeyeAgHWTTkxUlnAvp0K1TZuMqVTaBk1Gq/ELoieiOwvIgtEZLWIrBSRq8ztHUXkFRF5z/xfEbVs+SY9sU06dfUNXD1jWaQxh6qX1lDiIzlOFAT1Gspn3CY7mdLRnk2a5kIhbAy7gLFKqYOBgcAYETkEGA/MU0odCMwzvzc7kjF93MzNUcUcSo6C7WwchdS5B/EaynfcJq8eS9qzSdMciLxjUEp9qJR62/z8ObAaqAROBh4zD3sMqIpatijJNhqPYvTpNAoudGrLINFN8702wevsSXs2aZoDBfVKEpHuQD9gMbCPUupDMDoP4NsO51wiIm+JyFtbt26NTNaw8ZKQPt+jT6fyG5UqqJ48iNdQvtcmeLlf2rNJ01woWMcgInsAs4CrlVI7vJ6nlHpYKTVAKTWgU6dO+RMwz2SzN0D+R59xzTuQnl/By4rqfF+LnUznDOzqS0aNplgoiLuqiCQwOoW/KKVmm5s/FpHOSqkPRaQzsKUQskVJMp6PkxdOvkefYUQhzRd+o5uGdS1ubrI64qqmpRB5xyAiAvwJWK2U+o1l1xzgfGCK+f/ZqGUrFIWK/9+c8g6EcS06uJ5GYxD5OgYR+QHwGrACaDQ334RhZ5gJdAU2Aqcrpba5lVVs6xg07hQ6FPagKfNtFyBWlpexaPzQyOTQaPJNtnUMkc8YlFL/AEdvzWFRyqKJD3EYrevgehqNgY6V5JE4JL1vzkyak5kEKOoFY3E1xms0UaM7Bg/EKel9c6R6aQ21dfZJgKIcrevgehqNgQ6i5wEvQeaaO/nU/7vNCqIcrTcnY7xGkwu6Y/BAS9c951v/79aOUY/WtUuqRqNVSZ6Is+453fYxoXpF6LaQQoWbqGiXPQmQtv34Y9WqVQwbNox27drRpUsXbrnlFhoa3IMDrl+/HhHJ+DvrrLMyjv3000+59NJL2XfffSkrK6N37948/vjj+bqcwDQ2NtK/f39EhLlz56bss7tWEaFNmzauZf7nP//h0ksvpW/fvpSWljJ48GDHY1esWMGIESPo0KEDe+65J0ceeSRLliwJ49JCQc8YPBDXhWB2I/kn39jYtD+skX0U4Sbs2nfiSPckQHHwZComtm/fzo9//GMOOeQQnn32Wd5//33Gjh1LY2Mjt99+e9bz77rrLgYNGtT0fe+9907Zv2PHDn74wx+yxx57cN9997H33nuzatUqvvnmm9CvJVf++Mc/UlNjP4h4/fXXM7aNHDky5drtWLlyJX/7298YOHCg6zUvW7aMY445hpNPPpkZM2YA8Oabb1JXFx8NhO4YPBBX3bOfUNC5yJrvVJhB2zdK20+h11iEwYMPPkhdXR2zZ89mr7324thjj2XHjh1MmjSJ66+/nr322sv1/F69ejFw4EDH/XfeeSdff/01b731FmVlxrMxZMiQUK8hyaOPPsqkSZNYv36973O3b9/OL37xC6ZMmcJFF12UsT/9Gt98800++eQTRo0a5VruyJEjOfnkkwE47bTT+OSTT2yPu+yyyxg5ciRPPvlk07bjjjvO72XkFa1K8kgyXPa6KSeyaPzQWPwoRBUKOgpvnSDtG5XtJyyvtOeff56SkhLWrVuXsn3dunWUlJQwZ86cEKXO5IUXXmD48OEpHcBZZ51FXV0df//733Muf9q0aVx44YVNnYIdI0aMoHfv3imj47vvvpu2bduycuXKnGXwws0338ygQYMYNszbsqnp06fTvn17Ro4c6XpcSUn2n9NVq1axePFirrjiCk91FwrdMRQxUYWCDhLULgqisv2EZWM57rjj6NKlC4899ljK9kcffZROnTpxwgknOJ7b0NDArl27XP8aGxsdzwdYs2YNvXv3TtnWtWtX2rVrx5o1a7LKf8EFF1BaWkrnzp259tprU37c161bx5YtWygvL+eEE06gdevWdOrUiWuvvTZFrfLII4+wdetWbrzxRgBWr17NhAkTuPXWWzn00PznD3/nnXeYNm0ad911l6fjlVI89dRTnHzyybRr1y7n+hcvXgwYs5a+ffvSqlUrevbsyZ/+9Kecyw4T3TEUMVGGgo7jjCmqdQdhzUxKS0sZPXo0jz32GMlQNEopHnvsMc4991xatXLW7A4bNoxEIuH699Of/tS1/u3bt1NeXp6xvaKigu3btzue16ZNG8aMGcOf/vQn5s2bx6WXXsoDDzyQYnz+6KOPALj++uuprKzkxRdf5KabbuKBBx5gwoQJTcd17tyZ3//+9/zud79j3rx5nH/++fTr14/rrrvOVfbGxkbbTtC6LZsRHeCKK65gzJgxHHDAAVmPBXjttdfYtGmTraE9CMl2Ou+88zj77LN55ZVXOO6447jooov429/+FkodYaBtDEWMnW4+3wnqs+nao9TFR2X7CdPG8tOf/pQ777yThQsXMmTIEBYsWMCGDRu44IILXM976KGH+Pzzz12PSTcG2yE2aVyVUrbbkyR/zJMMHjyYffbZh8svv5xly5Zx+OGHN/1QH3rooTzyyCMADB06lM8//5w777yTSZMmNY24R40axezZsznxxBMpKSlh+fLllJa6D3Buu+02br311oztiUSi6XO3bt1cbQ5//etfWbt2Lc8995xrXVamT59ORUUFw4cP93yOG8l2uuiii7j++usBww6zevVqJk+e7DprjBLdMRQ5UfrdZ/MCKoSXUBTXH6ZX2ne+8x0GDx7MtGnTGDJkCNOmTePII4/MqkY54IADyBbwMpuOu6Kigtra2oztn332me1Mwo3TTjuNyy+/nLfffpvDDz+cjh07ApnG5qFDhzJx4kTef/99+vTp07R91KhRPP3005x00kkceOCBWeu75JJLGDFiRNP3uXPn8vDDD6fYZdzcSevr6xk3bhw33HADjY2N1NbWsmOHkQZm586dfP755+y5554p5+zatYtZs2Zx6qmn0rp166wyesGtne65555Q6ggDrUrSeCabrj3f6x0KRdg2losuuohZs2ZRU1PD7Nmzs84WIBxVUu/evTNsCR988AE7d+7MsD1kIznDSP7v2bOn7Y9nsjOzdlo7duzgmmuuoV+/fsyZM4eXXnopa31dunRhwIABTX/du3endevWKdusHU86O3fuZNOmTVx77bVUVFRQUVFB3759AcMA369fv4xz5s2bx9atW7N6I/nh4IMPtt2ulPJkvI4KPWPQeCabrr05rxAPc2ZyyimnMGbMGM466ywaGxs96a/DUCUdf/zxTJ06NWV0PGPGDMrKyvjRj37k/QKAp59+GoD+/fsD0Lp1a4499ljmz5+fcty8efNo165dik7/6quvpqGhgfnz5zNmzBguuugi3n33XTp06OBLBj/sscceLFiwIGXbRx99xKhRo7jzzjsZOjQzrPr06dPZd999XReq+eXoo4+moqKCefPmpain5s2b19RRxQHdMWg8k03Xnu/1Ds2Ftm3bcvbZZ/OHP/yBUaNGeVLj9OqVu0H9sssu43e/+x2nnHIKN9xwA//973+ZNGkS1157bYoL6wEHHMCPfvSjJk+ZSZMm8fnnnzNo0CD22msvXn31VaZOncopp5zCd7/73abzbrnlFn7wgx9wwQUXMGrUKN555x2mTJnCzTff3KTmmTt3LtOmTeOFF16gvLyc++67j8MOO4yrrrqKRx99NOdrdKJVq1YZP/BJe0SfPn046qijUvZ9/fXXVFdXM3r0aNuR/IYNG+jZsyd//vOfOe+88wD48ssvmwzINTU17Nixo6kDPeGEE2jXrh2tW7fmlltu4frrr6e8vJzvfe97zJo1i1dffTUUl+HQUEoV7V///v1VMfPM25vU0ZPnqe43zFVHT56nnnl7UyjH5otn3t6kDrjpedXthrlNfwfc9HyTLM+8vUn1nvBCyv7eE14oiKxx55VXXlGAeuWVVyKtd+XKlWrIkCGqbdu2at9991UTJkxQu3btSjmmW7du6vzzz2/6Pn36dNW/f3+11157qUQioXr27Kluvvlm9dVXX2WU/+KLL6p+/fqp1q1bq/3220/ddtttqqGhQSml1Keffqo6d+6sLr744pRz5s6dqwA1Z84cz9cxbdo01a1bN+8XbsO6desUoJ577rmMfc8884wC1Ouvv+567rRp0zK22f2tW7cu5fy7775bde/eXSUSCXXYYYepWbNm5XQtfgHeUi6/rZFncAuTYs7g5pTn2U537efYfMs87qnl1DfufmYSJcLU0/s2ydEcVghHwfXXX8+MGTOaFrdpNFESuwxuGgM/4RziEvph6ktrUzoFgPpGlSKHjk7qztq1a1m1ahUPPPAAEydO1J2CJpbojqFA+DHURh36wcndtDkbl6Pi0ksvZfHixZx00klceeWVhRZHo7FFD1cKhJ9wDoUO/TBpzspI5WjOLFy4kLq6OmbMmBGab7xGEza6YygQfsI5FDr0Q21dvWFf0KkvNZoWge4YCoSfRVPJYyva7V7+36ZV+LfObeSftCPEMZieRqMJF21jKCB+DbVf1e+OnllbVx96uIlxw3tx9YxltvuSswltXNZomj96xlAkRBFuoqpfZcqsxIq2I2g0LQfdMRQJUXkETRx5qLYjaDQtHN0xFAlReQRpO4JGo9E2hiIhzNDP2dB2BI2mZaM7hiIhqqQ0Go1GozuGIkKP5DUaTRRoG4NGo9FoUtAdg0aj0WhS0B2DRqPRaFLQHYNGo9FoUtAdg0aj0WhSKOoMbiKyFdjg87S9gU/yIE5YaPmCE2fZIN7yxVk2iLd8cZYN7OXrppTq5HRCUXcMQRCRt9xS2hUaLV9w4iwbxFu+OMsG8ZYvzrJBMPm0Kkmj0Wg0KeiOQaPRaDQptMSO4eFCC5AFLV9w4iwbxFu+OMsG8ZYvzrJBAPlanI1Bo9FoNO60xBmDRqPRaFzQHYNGo9FoUmhRHYOIHCcia0XkPyIyPgby/FlEtojIu5ZtHUXkFRF5z/xfUSDZ9heRBSKyWkRWishVcZFPRNqKyL9EZLkp261xkS1NzlIRWSoic+Mmn4isF5EVIrJMRN6Kk3wiUi4iT4vIGvP5+36MZOtltlnyb4eIXB0j+a4x34l3RWS6+a74lq3FdAwiUgr8ATgeOAQYJSKHFFYqHgWOS9s2HpinlDoQmGd+LwS7gLFKqYOBgcAYs73iIN/XwFClVF/gcOA4ERkYE9msXAWstnyPm3xDlFKHW3zc4yLfb4EXlVK9gb4YbRgL2ZRSa802OxzoD3wJPBMH+USkErgSGKCUOgwoBc4KJJtSqkX8Ad8HXrJ8vxG4MQZydQfetXxfC3Q2P3cG1hZaRlOWZ4Fj4yYf0A54GzgqTrIB+5kv4VBgbtzuLbAe2DttW8HlA/YC1mE6xsRJNhtZ/wdYFBf5gErgA6AjRq6duaaMvmVrMTMGdjdakk3mtrixj1LqQwDz/7cLLA8i0h3oBywmJvKZapplwBbgFaVUbGQzuRe4Hmi0bIuTfAp4WUSWiMgl5rY4yPcdYCswzVTD/VFE2sdEtnTOAqabnwsun1KqBrgL2Ah8CHymlHo5iGwtqWMQm23aVzcLIrIHMAu4Wim1o9DyJFFKNShjOr8fcKSIHFZgkZoQkRHAFqXUkkLL4sIgpdQRGKrVMSLyw0ILZNIKOAJ4QCnVD9hJ4VVuGYhIa+Ak4KlCy5LEtB2cDPQAugDtReScIGW1pI5hE7C/5ft+wOYCyeLGxyLSGcD8v6VQgohIAqNT+ItSanbc5ANQStUCCzFsNXGRbRBwkoisB/4KDBWRJ2MkH0qpzeb/LRg68iNjIt8mYJM5AwR4GqOjiINsVo4H3lZKfWx+j4N8PwbWKaW2KqXqgdnA0UFka0kdw5vAgSLSw+ztzwLmFFgmO+YA55ufz8fQ7UeOiAjwJ2C1Uuo3ll0Fl09EOolIufm5DOOFWBMH2QCUUjcqpfZTSnXHeM7mK6XOiYt8ItJeRPZMfsbQQ78bB/mUUh8BH4hIL3PTMGBVHGRLYxS71UgQD/k2AgNFpJ35/g7DMNz7l63QBpyIjTMnAP8G3gd+EQN5pmPoAusxRkoXAt/CMFq+Z/7vWCDZfoChansHWGb+nRAH+YDvAktN2d4FbjG3F1w2G1kHs9v4HAv5MPT4y82/lcl3IUbyHQ68Zd7faqAiLrKZ8rUDPgU6WLbFQj7gVoxB0rvAE0CbILLpkBgajUajSaElqZI0Go1G4wHdMWg0Go0mBd0xaDQajSYF3TFoNBqNJgXdMWg0Go0mBd0xaDQmIvKFj2MHi8jRlu+Xich55ufRItIlQP3rRWRvv+dpNGHTqtACaDRFymDgC+CfAEqpBy37RmP4kcdxZb1GkxXdMWg0LojISGAC0BpjUdPZQBlwGdBgxqK5AmOV6RcYUUsHAH8RkTqMqL6rMUIhfyIiA4C7lFKDReRbGIscOwH/whLPyyz3SrPexcDlSqmG/F+xRqNVSRpNNv4BDFRGQLe/AtcrpdYDDwL3KCM2/2vJg5VST2Os2j3b3FfnUvZE4B9m2XOArgAicjBwJkagu8OBBowOSaOJBD1j0Gjc2Q+YYQYfa42RKyAsfgicAqCUel5Etpvbh2EkgXnTCHlDGYUPGqdpQeiOQaNx5z7gN0qpOSIyGJgUoIxd7J6dt03bZxeTRoDHlFI3BqhLo8kZrUrSaNzpANSYn8+3bP8c2NPhnPR96zFmAACnWra/iqkiEpHjMYLFgRHo7DQR+ba5r6OIdAsov0bjG90xaDS7aScimyx/12LMEJ4SkdeATyzHPgf8xEwIf0xaOY8CD5r7yjAiXv7WLMNqQL4V+KGIvI0R+nojgFJqFYbB+2UReQd4BSMlo0YTCTq6qkaj0WhS0DMGjUaj0aSgOwaNRqPRpKA7Bo1Go9GkoDsGjUaj0aSgOwaNRqPRpKA7Bo1Go9GkoDsGjUaj0aTw/wGbtPr8M11fdwAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "r value :0.47\n"
     ]
    }
   ],
   "source": [
    "# Linear regression on the Northern Hemisphere\n",
    "x_values = northern_hemi_df[\"Lat\"]\n",
    "y_values = northern_hemi_df[\"Humidity\"]\n",
    "# Call the function.\n",
    "plot_linear_regression(x_values, y_values,\n",
    "                       'Linear Regression on the Northern Hemisphere\\nfor % Humidity', '% Humidity',(40,10))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "r value :0.2\n"
     ]
    }
   ],
   "source": [
    "# Linear regression on the Southern Hemisphere\n",
    "x_values = southern_hemi_df[\"Lat\"]\n",
    "y_values = southern_hemi_df[\"Humidity\"]\n",
    "# Call the function.\n",
    "plot_linear_regression(x_values, y_values,\n",
    "                       'Linear Regression on the Southern Hemisphere\\nfor % Humidity', '% Humidity',(-50,15))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "r value :0.28\n"
     ]
    }
   ],
   "source": [
    "# Linear regression on the Southern Hemisphere\n",
    "x_values = northern_hemi_df[\"Lat\"]\n",
    "y_values = northern_hemi_df[\"Cloudiness\"]\n",
    "# Call the function.\n",
    "plot_linear_regression(x_values, y_values,\n",
    "                       'Linear Regression on the Southern Hemisphere\\nfor % Cloudiness', '% Cloudiness',(40,10))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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lb95HIvIv4CTgE1U9wD3WGScQWG9gNfBdVd3knhuPE/WyAfipqj6RL9nCyKwldUx5YiV1m7e3ONemQth5p9Zs/rye7tVVXD6sLyMG+And753Xus3bo+kBLY75zSNW9goRGlSpqa5i8H5dmb9ifYvjXmknki2bsgaNXJevWPUVn2/kWSeTo5jP1UvWtpWt+HJHI40KrQQqBOrdvfc6tatk4sn9mLFoDQve3RhNb1CfztzzoyMzLluquktVl9mSt4B4InIUTjjeu2OUwh9wNkqZLCLjgE6q+ks3bPE04DCcTUaeAr7mtZE6QG1trZaDS+qsJXWMf/B1ttf7i15cVVnBdSP7Z9RQEuVVWSGgUN/Y1Fb85pGu7F5pJ0orm7IGjVyXr1j15eeZx8pRzOeaSfuMRUi8iUdEMaRbtlz+XjzlFlmsqrWJzuXNfORuI7gx7vApwF3u97uAETHH73O3H1yFE4r4sHzJFjamPLEyrUayvb6BKU+szFle9Q3aTCGkk0e6snulnSitbMqaDbOW1DFo8jz2GjeHQZPnMWtJXeqbUpDr8iVLb9Ijy7KSPVXZ/Tzz2HJNemRZzsqd7nNJlHc6JOtSR0YOyZ7BZdNfSyhbLn8vmVLoxWu7q+qHAKr6oYjs5h6vAV6Kue4DkmxdKCLnA+cD9OyZ6YZU4WJdApNRPu5J9z4/1+ZSjmRpZZpHpsT35uo2b2f8g68DZNWzTWQa9DqeimT1sunzejZ9Xh9NOx3Z/ZTd7/NYt3k7s5bURWXxK382ssVfnyzvXJGsDA2qCWUrxO82FUGZaJYExxIqYVW9TVVrVbW2a9eEq7RLju7VVQW5J937/FybSzmSpZUqj1z36vM1YqmQRD+D5MdT4bfu05HdT9n95tu9usoz33TbTrrPpRAjTK8yJJKtEL/bVBRaKXwsIt0A3L+fuMc/AHrEXLcnzo5QBnD5sL5UVVb4vr6qsiI6OZyLvCorhMpWzV9MfvNIV3avtBOllUqOSO+xbvN2lKbeYzaKIV8jloYk83vJjqcinbpPp3ef6riffCPPzSvfdNtwus8lnyPMQX06A6nrIl6Gwful39HN5veeiEIrhdnA2e73s4GHY46fISI7ichewL7AfwssW2AZMaCG60b2pyZJb6BNhdCpXSUC1FRXZTVBF5tXJL0pow5iyuiDmh3zm0e87JFeb011FWOP6JnweLK0E8mWSo589OozHbGkItnzTXY8FYnqq7qqMuG16fTuUx0fMaCG0wbWRJ9phQiD+nRO+NySpVddVZl2G073ueSid92pXWVUAUSI9T6KPINko714GeavWJ92/rmekM+nS+o04Bigi4h8gLPX7GRguoj8EFgDjAZQ1WUiMh1YDuwALkrleVRujBhQUzAPm2R5ZaNociV7umnlo5d4+bC+CT1Ksu2t5SPd+PpK5g3jNw8/Ms5aUsfMxXXREU6DKq+s2ZLw5ZUsvauH90uvoD5lS3V9OlRVVjDx5H4p22PkvB/Z0m2XX0T8Y3NI3pSCqo5JcmpIkuuvBa7NlzxGeVLdrjLhZGI2vcTIjzzXfvX5SjeXefi532t0Fp9PtvLE+/SfNrDGtw9/bN6xa2U6tavky/oGPo954VZXVdKve3teem8TDapUiHDaQP8dFL/l7F5dlZZjQbJ6zYa8rVMoBOWyTsHIjFlL6rh8xmst3GkrK4Qpow4qibUNQWSvcXMSeokIsGryiTnLp5DrGwqVl1c+l9z/as7qtSjrFAyj2Ex5YmULhQCwc5vWphDySD5t+LEUct1KJnll4vWWaB7otIE1THliZdI1ER2TzBNliikFo2RJZp/dsj2/vunlTiZeYplQSK+idPPKxuttxIAaFow7llWTT+TyYX2ZubjO06S07asdOVk8GcGUglGyFKrHajQnEy+xTKhul50nVTqk25ZyNYrxs8K5vkFDvaLZMApGvryEjNTk21tu1pI6/vfFjhbHKyskL8833baUq1FMtutHMsFGCkbJUqgeq1F4Cj1flG5bytUoNdv1I5lgIwWjpCnk+g6jcBRjviidtpSrUaqftRS5Hv2aUjBKklLfd6EUyOYZJfPnD8p8Uap1CX7Lniid0O6nUAhsnYKRiFLfd6EUyPYZhfkZB0F2r3UKNlIwSo50VtQaxSHbZ+R3hXCudxHMBUFvn6YUjJIjKPsuGMnJxTNKZeNPtL/C5TNeA3HcOCPHcrEXRjoEvX2a95FRctj6hOCTy2eUbOVwwl0EGzWqECIUeve+oLdPUwpGyVGoFbVG5uTqGXmtHM71LoK5Iujt08xHRslRiGijRnbk6hl52efTiTiaTi89fp4iXW+gRNFZY0crxW6n5n1kGEZo8YrIesPpB7fw8qlsJc3mFCB7r6d4/KZXTC8ki5JqlBS53nPZCC9e9vmEuwiOPogpozLbRRD8xSLyO0dRyCiv6WDmIyNUJPIoKbT3iBEcUq0czvUugrmMRRRULyRTCmVO2Fb+Bt3HOwyE7Zl7kc7cRC7K7Xeews8cRVBXZZtSKGPC2OsOau8qLITxmafCT0yiXJXb777Og/frmlFaQfBCMqVQxoSx1x3U3lUQSdQzDuMzzwXpljvZqCJ+ZNLK3dc5nvkr1qeUKahecqYUypgw9rqD2rsKGsl6xsl6uEF+5rkgnbaealQRqxz2GjcnrfziCWIUX1MKZUwYe91B7V0FjWQ944okPdtMVxKH5Tmk09aT1d2kR5a1KG8Yf0OpMKVQxoS11x3E3lXQSNZTbVClqrIi62cetrmJdNp6srrb9Hk9mz539muIlPe0gTXMXFwXut+QF7ZOoQyJ+Pn//P5X+WJHU2Pu1K4yFKGHE2FrF5qTrKca8cvPdje6oPrYJyOdndP89vK31zcwf8X6ktvdz0YKZUZ8Dy/WkvBFfWORpMqOsPVaC4FXzzgXI60wzkf5LbdfDyNwyltqI1dTCmWG14rMMHmhxNqzE3mAhKks+SDfcy+laEuPkKjutn25g80JtvoshfLGY0qhzEjVkwtyTy9C/Mgg0cQphKMs+SSfPdiwzkf5Jb7uksUpKpXyxmJKocxItSIzDD0fP/FnIBxlyYZiev8E0Qssn/WRj/IG1XvLlEKZ4WUvDUvPx88IICxlyZQgzKMEyZZeiPrIZXmD8PySYd5HZUasFwZAhQhQOK+JXHgJJRsBVIiUjAdIKsLm/ZNvwlYfQZbXRgplSLF6ePmMP1OoOPRBIYzeP/kkbPURZHmLMlIQkUtEZJmIvCEi00SkrYh0FpG5IvK2+7dTMWQz8keuekfp+JyXKkHf57fQhK0+gixvwZWCiNQAPwVqVfUAoAI4AxgHPK2q+wJPu/8bJUQue0cjBtSwYNyxrJp8IgvGHVtWCgGCv89voQlbfQRZ3mLNKbQGqkSkNdAOWAecAtzlnr8LGFEc0Yx8EeTeUdiw0VJzwlYfQZa3KHs0i8jPgGuB7cCTqnqWiGxW1eqYazapagsTkoicD5wP0LNnz4Hvv/9+gaQ2sqWYe9IahtFEoPZoducKTgH2AroDO4vIWL/3q+ptqlqrqrVdu6beyMIIDkHuHRmG4VAM76OhwCpVXQ8gIg8C3wA+FpFuqvqhiHQDPimCbEaeCZJvu2EYLSmGUlgDHCEi7XDMR0OARcA24Gxgsvv34SLIZpQ4QV1FahhBoeBKQVUXisgDwCvADmAJcBuwCzBdRH6IozhGF1o2o7QJ8ipSwwgKRVm8pqoTgYlxh7/EGTUYRl4o1/2JDSMdLMyFUTYEeRWpYQSFsgxzYXblzAlL3SWSs5T3APDLhFmvc89La4g4ou/cpoJrT23uAZbsGRfj2cfnOXi/rsxfsT7w7S/MFGWdQq6ora3VRYsWpXWP+cpnTljqLpmcyfbTDZr8+WLCrNeZ+tKaFscrWgl/Gn1Q9MUflLpLJEs85fT8ckmg1ikUmyBHJww6Yam7ZHKW4n666TBt4dqExxsaNfoMk9XdtIVrC/7s/eybkU8ZynXf77IzH5ldOXPCUndecpbzOolkO9RBU50lq7ti7G7nN+18yFDOnmplN1Kw+DuZE5a6C4uchSayd0YiInXjtVeF1335wG/asdflqncfllFxPig7pRDk6IRBJyx1FxY5C82Yw3skPF7RSqJ1k6zuxhzeo+B1mkiWeGJliPTu6zZvR2nq3WeiGMIyKs4HZacULP5O5oSl7sIiZ6G5ZkR/xh7Rk9g+/85tKqKTzJC87q4Z0b/gdZpIlrFH9EwqQy579+U82iw77yPDMEqTvcbNIdHbTIBVk09MK62weNplipf3UdlNNBtGuRGWtSXZkmodSjr1EDv6KPV6i8dGCoZRwpR6jzcWr7ICZVMPfrB1CoZRppSTF43XXFI51UO2mPnIMEqYcvOiSbYOpdzqIRtMKRhGCZOLeE+lMCdhca/8Y+Yjwyhhsl2zkUvf/2Jia1f8Y0rBMEqYbNdslIotvqTWrqjCm29Cg3dcqEwx85FhlDDZmn5KyRYfyrhXmzbBjBkwdSo891zL83nwHjWlYBglSi6CupktvkA0NsJ//uO8/KdOhS+/9L6+Tx945JG8iGLmIyOUlGtY43TIhenHbPF54IMP4A9/gAMPBBHnU1EBgwfD7be3VAhjxsCjj8JXXzkjA1V45x3Yf/+8iGcjBSN0lHNY43TIhemnnFf2Zs2XX8Ljjzs9/5kzU18/cCCcdRacfjp0755/+ZJgSsEIHV49YHtZNZEr008obfGFZvly5+V/zz2wpuXuds1o3x7GjnUUwJFHQivHYBOd//nLErpXryia8k2pFERkZ2C7qjaKyNeA/YDHVbU+79IZRgJKafIzn1w+rG/C0A5m+smCzz6DBx90Xv5PPZX6+iFDnJf/yJHQsWPSy4I0+vUzp/AfoK2I1ABPA+cCd+ZTKCP3LF++nCFDhtCuXTu6d+/Or3/9axpSuLStXr0aEWnxOeOMM5pdN3fuXMaMGUPv3r0REa6++uo8liTzsMYPPvgghx56KFVVVey6664cd9xxbNu2LXr+q6++4je/+Q377LMPVVVV7LPPPkycOJEvU0z63XnnnQnr6ZZbbole88wzzyS8RkQYNmxYGqX3T0m5YRYaVXjhBbjwQudlHrH9d+wI557bUiH06AHjxsHSpU12f1XnunPP9VQIECzXXz/mI1HVz0Xkh8BfVfUPIrIk34IZuWPTpk0MHTqUr3/96zz88MO8++67XHbZZTQ2NnLNNdekvP+Pf/wjgwYNiv7fpUuXZuf//e9/s3TpUoYMGcJ9992Xc/njyaQH/M9//pOLL76YK664gilTprBp0ybmzZvHjh07oteMGzeOW265hWuuuYYBAwbwyiuvMGHCBDZv3syf//znlHLNmzePqqomxbT33ntHvx9yyCG8+OKLza5fs2YNp59+Oscff7yvcmeCmX588NFHcN99Tu/fT4DNkSOd3v8JJ0DbtjkRIVCjX1X1/ABLgCOBl4B+7rHXU91XiM/AgQPVSM3vfvc7ra6u1i1btkSP/f73v9eqqqpmx+JZtWqVAvrII494pt/Q0BD9vuuuu+rEiROzljkZd9xxh/bq1UsfeuUD/cZ1T2vvXz6q37juaX3olQ+S3rN+/XrdZZdd9LbbbvNMe/fdd9dLL7202bFLLrlEd9ttt5QyAbp161b/BVHVP/zhD9qqVSutq6tL6z4jQ776SnXOHNUzz4ztyyf/HHCA6nXXqa5enXfRvnHd09rrl4+2+Hzjuqfzkh+wSJO8V/2Yj34OjAceUtVlIrI3MD8P+qlkmTNnDq1atWLVqlXNjq9atYpWrVoxe/bsvOb/+OOPM2zYMDp06BA9dsYZZ7B9+3aeffbZrNNv1Sp1MzrppJPYb7/92L69qefzpz/9ibZt27Js2bK08xwxoIYF445l1eQTWTDuWM/e8PTp0wE4++yzPdOsr6+nY9wwv7q6OtI5yjnTpk3j6KOPpnsRPU1KlnfegUmT4GtfazL9tGkDJ54I997b/No2bRwTz9NPw44dTWrh9dcdk1CvXnkXN0iuvyl/zar6rKoOV9Xfi0grYIOq/rQAspUMxx13HN27d+euu+5qdvzOO++ka9eunHDCCUnvbWhoYMeOHZ6fxsZGz/xXrFjBfvvt1+xYz549adeuHStWrEgp/7nnnktFRQXdunXj0ksvbfZi98s//vEP1q9fz/jx4wF48803mTBhApMmTaJfv35pp5cOCxcupG/fvtx+++3sueeeVFZWcvjhh/PCCy80u+68887j1ltvZcGCBfzvf//jueee4+abb+biiy/2lU+fPn1o3bo1ffv25dZbb/W89u2332bJkiWMGTMm43IZwOefw7RpcNJJTS9/Edh3X7j6anj77ebXDxoEN98MGzY0vfy//BL+9S849lhnvUARCNT8T7IhROQD3At0AHYGVgAfApenuq8QnzCZj6688krt3bu3NjY2qqpqY2Oj9urVSy+77DLP+44++mgFPD9nn322ZxqtW7fWG264ocXxmpoaHT9+fNL71q1bpxdddJE+/PDDOn/+fJ04caK2bdtWhw8fnvQeL/PRvffeqyKiTz31lB566KF65JFH6o4dOzxlb2ho0Pr6+ujn9ttv1169ejU7liqN73znO7rLLrto9+7dderUqfr444/r4MGDtX379vrRRx9Fr2tsbNSf/OQnzer2wgsv9ExbVfXf//63/va3v9UnnnhCH3vsMf3e976ngF5//fVJ75k0aZJWVlbqp59+mjJ9Q1UbG1UXLVK95BLVrl1Tm3522825dvFi516jGXiYj/wohVfdv2cB1wOVwNJU9xXiEyal8O6776qI6Lx581RV9emnn1ZA33jjDc/7VqxYoS+//LLnZ9WqVZ5ptG7dWm+88cYWx7t3766/+tWv0irHTTfdpIAuWbIk4flUcwqjRo3SnXbaSauqqvStt95Kmd/EiRNTKsVevXp5pjF06FAF9PHHH48e27Jli1ZXV+uECROix37/+99rp06d9K9//as+++yz+pe//EU7duyoV111VUo54/nud7+rnTt3bjbfEsv++++vJ554YtrpBo105nZ8s2GD6k03qQ4a5M/2f+KJqtOmqW7bln3eZYKXUvDjfVQpIpXACOBvqlovIuHdw7NI7L333hxzzDHccccdDB48mDvuuIPDDjsspelkn332SWnTTmXT79SpE5s3b25xfMuWLVRXV6cSvRmjRo3iwgsv5JVXXuHggw9O616AMWPG8MADDzB8+HD23XfflNeff/75nHTSSdH/H330UW677bZm8zA77bSTZxqdO3cG4Jhjjoke69ChAwMHDmT58uUAbNiwgQkTJvD3v/+dH/3oRwAcddRRtGnThosvvpiLL76Y3XbbzXc5R40axfTp01m9enUzLySA1157jTfffJMrr7zSd3pBJGvf+oYGeOYZx+tn6lSoT7H0ad99nUVfZ54J++yTpfRGMvxMNN8KrMYxH/1HRHoBn2WTqYhUi8gDIrJCRN4UkSNFpLOIzBWRt92/nbLJI4icd955zJw5k7q6Oh588EHOPffclPcMGTKEyspKz88PfvADzzT222+/FnMHa9euZdu2bS3mGlIhIs3+psNnn33GJZdcwoABA5g9ezZPPPFEynu6d+9ObW1t9NO7d2/atGnT7Fj//v0909h///0RkRbKVVWjCvW9996jvr6+haIbMGAAO3bs4P3330+vsC6J6um+++6jqqqKU045JaM0g0JavvVr1sDkyXDAAU12/9atYehQuOOOlgrhrLOcEBH19U1jgrfegl//2hRCnkk5UlDVvwB/iTn0vogMzjLfPwP/VtVRItIGaAf8CnhaVSeLyDhgHPDLLPMJFCNHjuSiiy7ijDPOoLGxscUisETceuutbN261fOa+HUD8Rx//PFMmTKFrVu30r59ewDuv/9+qqqqOProo/0XAHjggQcAGDhwYFr3Afz85z+noaGBefPmcdFFF3HeeefxxhtvtPD4yTUnnXQSkyZNYv78+dFJ/S1btrB48WJ+8YtfANDL9TB55ZVXOPTQQ6P3Ll68GIDevXunlefMmTPp0qVLNN1Y7r//fk4++WR22WWXTIoTGBL50LfZUU//hS/AyL/BQw+lTuTQQ53e/+mnw+6750FKI22S2ZUiH2B34Hac0BYAXwd+mOo+j/Q6AKtwFsXFHl8JdHO/dwNWpkorTHMKES666CIFdMyYMQXLc+PGjbrHHnvo0KFDde7cuXrrrbfqzjvvrFdeeWWz6/r06aM/+MEPov9PnDhRL730Up05c6bOnTtXr7rqKm3btq2OHDmy2X2rV6/WGTNm6IwZM7R9+/Y6evRonTFjhj722GPRax555JFmdv1PP/1Uu3XrlnKSPJ7IOoV0OeWUU3SPPfbQO++8Ux999FE96qijtEuXLrpx48boNSNGjNCOHTvqjTfeqPPmzdPrr79eO3TooKNHj25W1oqKCr3rrruix0aOHKmTJ0/Wxx57TB955BEdO3asAvqXv/ylhRwvvviiAvrQQw+lXYagcdbP/qk3HT5K1+2ya2q7f8eOqhddpPriizbxGwDIcqL5ceC7wGvu/63JYvEacDDwX5xQGUuAf+KYpjbHXbcpyf3nA4uART179sxnveWFuXPnKqBz584taL7Lli3TwYMHa9u2bXWPPfbQCRMmtPDa6dWrV7OX9LRp03TgwIHaoUMHrays1D59+uhVV12lX3zxRbP7Iou34j+Rl3dEAfzoRz9qdt+jjz6qgM6ePdt3OTJVClu3btULLrhAO3furG3bttUhQ4bo0qVLm12zZcsWveyyy3TvvffWtm3bap8+ffTyyy/Xzz77LHpNZEHfHXfcET02fvx4/drXvqZVVVXatm1bPeSQQ/Tuu+9OKMfPfvYz7dixY4s6DDSbN6vefrvq4MG+Jn4/PuIo1bvuUo2pNyNYeCkF0RSTmCLysqoeKiJLVHWAe+xVVT04vTFJNL1anNXRg1R1oYj8GWeO4ieqWh1z3SZV9ZxXqK2t1UV+lqUHiCuuuIL7778/unDNMPJFsl3Xku7G1tjoxPuJbPQSExcqIb16sXLoKUzqcDAvttnNwmqHCBFZrKq1ic758T7aJiK74vT+EJEjgC1ZyPMB8IGqLnT/fwBn/uBjEemmqh+KSDfgkyzyCBwrV65k+fLl3HzzzUycONEUgpFXknkGLXp/IzMX17HLpvX8YPmznLr8GQ4Y/27qBEePdmz/xx3nrAB26YuzkMkoHfwohUuB2UAfEVkAdAVGZZqhqn4kImtFpK+qrgSGAMvdz9nAZPfvw5nmEUR+/OMfs3DhQoYPH85Pf2oLwo38EvEMat2wg6NWvcKpy+Zz8gpnj1/PEIgHHeS8/M84A/bcsyCyGsEipfkIQERa43QKBGcCOKu9FETkYJy5hDbAezjhuFsB04GewBpgtKpu9EonjOYjw8gbb73VZPqJi7MVz/bWO/FQv2OY1W8wL+/5dZBWrJp8YoEENYpNtuYjgMOA3u71h7g+33dnKpCqvgokEmhIpmkaRtnw1VewYoUTu3/pUpgyxfPyl3ocwEP9BvN430Fsq2pPQ4KOYE2au7EZpYufndf+H9AHeBWIrFRRIGOlYBiGD1Rh3bqml//rrzt/33zTieYJzez7dOsW3eZxVsOujH/ojRZ7TowZWMPMxXW2G5uRFD8jhVrg6+rHzmQYRmZs2wbLljV/+S9dChtjLKg9esCBBzoRQQ88EPr3d0JDV1a2SG4EgEhCL6PaXp0Tex+VIEk9rYyk+HFJnQH8VFU/LIxI/rE5BSN0NDY69v74l/877zgjA4Cdd3Ze+Ace2PTy798fOpVc5Je8Eu+BBc6oyLYkzX5OoQuwXET+C0Q3q1XV4TmSzzBKk02bnBd/7Mv/9deb/P9FnDg+Bx7omH0iimCvvSDOZXnWkjqm3LrEerxp4BWbyXO9RpnjRylcnW8hDCPU1Nc7nj+xL/+lS2Ht2qZrOnd2Xvg//GFT779fP2dUkIKso5GWKV77HludJsdPQLzs92s0jBxStB6eKnz8cUvTz/LljkcQOJE/998fjjqquQmoe3dnZJABqXq8RmK6V1dRl0AxdK+usjr1IKlSEJHnVfWbIrIVdzVz5BSgqtohya2GkTcK1sPbvt152cf3/tevb7qme3fnhf/tbze9/Pfbr7lHUA7w6vEaybl8WN+EcwqXD+vLJfe/mvAeq1MPpaCq33T/ti+cOIbhTc57eKrw/vstX/5vveVMCgNUVTn7AJx8cvPJ3xQhy3OFV4/XSE6kPSQaVU55YqXVaRK8RgqdvW5MtdrYMPJBVr3mzz6DN95o/vJ//XXneIS993Ze+KNHNymAPn2KtqE7ePd4DW9GDKhJ2FmwOk2O15zCYhyzkeCEntjkfq/GCUOxV76FM4x4fPWaGxocF8/Yl//SpbB6ddM1HTs6L/+xY5te/gccAO2DNzD26vEamWF1mhw/6xRuAWar6mPu/8cDQ1X1sgLI54mtUyg/4ucU+mxYy+gVz/D99xbQbsCBzkTwsmXwxRfODRUVzgKvyIs/8unRI+OJX8MIO17rFPwohcWqOjDu2KJkCRYSUwplxNat8OCDzibvc+cmv27o0OYv//33h7ZtCyenYYSAbBevbRCRCcBUHHPSWODTHMpnGE2owksvOZE+77kHtqTYumPPPZ1N3s86yzEHGYaRFX6UwhhgIhDZhfs/7jHDyI6PP4b77nNe/i+/nPr6U0915gBOOKGkev+2stYIEn4Wr20EflYAWYxSZccOx+Rzzz3OJxX9+jkv/zFjoFev/MtXRGxlrRE0/ITOnk/zxWsAqOqxeZHICDfvvuu8+KdOhbff9r62stJ5+Y8dC0cfXVS3z2JhK2uNoOHHfPSLmO9tgdOAHfkRxwgNn38Os2c7L/85c1JfP2iQ8/IfPRp23TX/8oUEW61sBA0/5qPFcYcWiIjFQyoXVGHJkqZtHmPDPCSia9foRi8ccoi5faagEKuVbc7CSAc/5qPYlc2tgIHAHnmTyCgen34KM2Y4L/8FC1Jff+KJzst/+HBf0T6NluR7Za3NWRjp4sd8FLuyeQewCvhhPoUy8kxDAzz7bFPvv77e+/p993V6/2ee6cT/N9ImWW89k5W16fT8bc7CSBc/5iMLZxFm1qyBe+91Xv7LlqW+PuLzP3Rowm0ejfRJ1VtPFp8nk7TisTkLI138mI8qgf8DjnIPPQPcqqopupdGQfnyS2fCd+pUeOih1Ncfeqjz8j/9dNjDrIH5JJe99XTTyuechc1VlCZ+zEc3A5XATe7/33OPnZcvoYwUvPFGk+mnrs772o4dnZf/2LFwxBE28VsEctlbTzetfM1Z2FxF6eJHKRyqqgfF/D9PRF7Ll0BGDFu2wMyZjt//vHmprx861FEAI0dCB9sDKSjksreeblrxcxbV7SpRhUvuf5UpT6zMuHdvcxWlS6vUl9AgIn0i/4jI3kCDx/VGuqjC88/D//2f8zIXcT7V1c6evvEKoWdPGD/eGTGoNn3mzoVzzjGFEDAuH9aXqsrmC/My7a1nktaIATUsGHcsN5x+MF/UN7J5ez1KU+9+1pIUo80E2FxF6eJnpHA5MF9E3sPxQOoFnJtXqUqZDz9sivezOH4JSAJOO80x/Rx/POy0U/7lCyFBt23nMnZ/Nj3/XPbubTe40sWP99HTIrIv0BdHKaxQ1S/zLlnYqa+HJ590Xv7TpqW+/sADHdPPmDFOrH/DF2GxbafjYeQ3rWJ6ItnOZaWL13acI5Oc6iMiqOqDeZIpfLz9dlO8n3ff9b62bdumid+jjoJWfix4RjLK2bZdTE8k27msdPEaKZzscU6B8lMK27bBrFmOAnj88dTXf+tbzst/1Cjo7LnltZEh5WzbLrYnUi5HP0ZwSKoUVLV85w1UYdGipt7/pyn2FNp996ZonwcdZG6fBaScbdvZeiJZ795IhJf56FJgi6reHnf8J0CFqt6YZ9kKw4YNMH268/J/8cXU1598svPyP/lkqCr9F0/QKWfbdiZlt969kQov89EPgEMSHL8NeBm4MZuMRaQCWATUqepJbuC9+4HewGrgu6q6KZs8kvL556kDuPXt2xTvZ++98yJGLiiE502QvXvKufebquyzltRx9exlbN7uBB/o1K6SiSf3K3r7KFR7KmS7zXdehSyLqLbYP8c5IfK6qibc9NbrnO+MnZFILdDBVQp/ADaq6mQRGQd0UtVfeqVRW1urixYtSj/zrVubfPlFmkw/xx4Lrf146QaDeO8TcHqK143sn7MGU4g8jNwza0kdl894jfrG5r/vygphyqiDitY+CtWeCtlu851XPtIXkcWqWpvonKfri4js7udYBgLtCZwI/DPm8CnAXe73u4AR2eaTlPbtmxZ8NTbC3XfDd74TKoUA3t4nYcrDyD1TnljZQiEA1DdoUdtHodpTIdttvvMq9G/QSylMAeaIyNEi0t79HAM8Avwxy3xvBK4AGmOO7a6qHwK4f3dLdKOInC8ii0Rk0fpUG76UOIXwvCln754w4/V8itk+CtWeCtlu851XoX+DSZWCqt4NXAX8BsfGvwqYBExU1buS3ZcKETkJ+CTBjm6+UNXbVLVWVWu7du2aqRglQTIvk1x63hQij2Ixa0kdgybPY69xcxg0eV5G4R6CitfzKWb7KFR7KmS7zXdehf4NepqPVPVxVT1aVXdV1S7udx8O+p4MAoaLyGrgPuBYEZkKfCwi3QDcv59kmU/Jk8uYOsXMoxhE7LR1m7dnHQcoiFw+rC+VrVq6RldWSFHbR6HaUyHbbb7zKvRvsODLaVV1vKruqaq9gTOAeao6FpgNnO1edjbwcKFlCxsjBtRw3cj+1FRXIUBNdVXOJ9IKkUcxKPW5khEDajj9sB7Nlsy0q2yV00nmSD7ptI9CtadCttt851Xo32BS76NC4M5R/ML1PtoVmA70BNYAo1V1o9f9GXsfGWXPXuPmkKjlC7Bq8omFFifnmNeY4YWX91FR3W1U9RmcndxQ1U+BIcWUxygfwrYSOl0/9SDFhAryOhejJb7NRyJyhIjME5EFIjIijzIZRt4J01xJJvMfQfEaK/W5m1LEK8zFHqr6UcyhS4HhOCPsF4BZ+RXNMBzy0dMM00roTHr96YyE8tmTD9KIxfCHl/noFhFZDExR1S+AzcCZOGsLPiuAbIaR1/0SwhIHKJNev9+4SPnejyIoIxbDP17rFEYArwKPisj3gJ/jKIR25HO1sWHEUOpeQn7IxE/dr8dKvuu31Na5lPLalgieE82q+oiIPAZciLN/wrWq+lxBJDMMrKcJmUeC9TMSynf9llIU27Ds8pctSUcKIjJcRJ4H5gFv4KwpOFVEpolIn0IJaJQ3pdbTzIR8+qnnu35LaZ1LuYxavUYK1wBHAlXAY6p6GHCpu1/ztThKwjDySin1NLMhX/MfhajfsMzdpKJcRq1eSmELzou/ipiQE6r6NqYQjAIRJi+hbCiWL38u6rdc1iEUc21LUPZT6AKMAeqBe1U1cB5HtqLZKAXCvPo4zLKnS7HKGpj9FFR1g6r+VVVvCaJCMMqLUvb6CLOtOsyyp0ux5kcKXcfh2lXGKEtK3esjzLbqMMueCcWYHwnMfgqGERRKvTcaZg+rMMseFgK1n4JhBIFS742GKQ5TPGGWPSwUuo7NfGQEnrBFNE2XMHtYhVn2sFDoOi7qfgrZYt5H5UE5ebgYRiEI7H4KhuGHUu6NlouPvxEeTCkYoaBUVsXGUupeVUY4sYlmwygSpe5VZYQTUwqGUSRK3avKCCdmPjJKhrDZ50vdq8rIHYVs2zZSMEqCMO4FbD7+hSeM4VIK3bZNKRglQRjt86W010AYCGPHASz2kWFkRFjt86XoVRVUvF6uQX4GFvvIMDLAYvAYqQhrx8FiHxlGBph9PjwUy64f1o5Dodu2KQWjJDD7fDgopl0/rB2HQrdti31kGEbBGDR5XkI33JrqKhaMOzbv+YfNbTlfWOwjwzACQbHt+jaxnxozHxmGUTDCatcvJ0wpGIZRMMJq1y8nCm4+EpEewN3AHkAjcJuq/llEOgP3A72B1cB3VXVToeWLYLbH8DBh1utMW7iWBlUqRBhzeA+uGdG/2GIFgkTtGFKHIY+/b/B+XZm/Yn3Wv4dChEHP9283Wfql8s4o+ESziHQDuqnqKyLSHlgMjADOATaq6mQRGQd0UtVfeqWVr4lm29QlPEyY9TpTX1rT4vjYI3qWvWJI1I4rWwkI1Dc0/e7j23ai++IJ6u8h37/dZOmfNrCGmYvrQvPO8JpoLrj5SFU/VNVX3O9bgTeBGuAU4C73srtwFEVRCGPIhHJl2sK1aR0vJxK14/pGbaYQoGXbTnRfPEH9PeT7t5ss/WkL15bMO6Oocwoi0hsYACwEdlfVD8FRHMBuSe45X0QWicii9evX50WuYntIGP5pSDLSTXa8nEinvcZe6/e+IP4e8v3bTZZOsvYWxDpKRdGUgojsAswEfq6qn/m9T1VvU9VaVa3t2rVrXmQzD4nwUCGS1vFyIp32Gnut3/uC+HtI9dvNdjV1svSTtbcg1lEqiqIURKQSRyHco6oPuoc/ducbIvMOnxRDNjAPiTAx5vAeaR0vJxK148pWQmVF8xdYfNtOdF88Qf09eP12c7GaOln6Yw7vUTLvjIIrBRER4HbgTVW9PubUbOBs9/vZwMOFli2ChUwID9eM6M/YI3pGe2oVIjbJ7JKoHU8ZfRBTRh3k2bYT3Tf2iJ6h+D14/XZzMd+QLP1rRvQvmXdGMbyPvgk8B7yO45IK8CuceYXpQE9gDTBaVTd6pWVhLgzD8Mte4+aQ6G0nwKrJJxZanKISqDAXqvo8znNIxJBCymIYRvkQ9u1PC7UOwlY0G4ZRFoR5rrCQ0WUtIJ4RekplJWmYCcMzKMRq6nxRyF3jTCkYoSZ+hWmkBwWE4sdeCoTpGYQ1Smoh106Z+cgINbb6vLjMWlLHZdNfs2eQZwq5dsqUghFqbPV58YiMEJKt5k00qWtkRiHnQ8x8ZISasHuUhJlUMZKCuKo8DHMfiSjkfIgpBSPUXD6sb8KolWHwKAk7qUZjQYs/Faa5j0QUaj7EzEdGqLHV58Uj1WisJmCjNZt/8oeNFIzQE1aPkrCTaJQWIYijNZt/8ocpBcMoA/JhS4+1c9dt3k6FCA2q1ATUVm/zT/4wpWAYJU4+belhGqXZ/JM/bE7BMEocs6U72PyTP2ykYBgljtnSmwjTyKZYmFIwjALg16afD9u/2dLDSbHWVJj5yDDyjN8Il/mKhBnm6KDlSiGjosZjSsEw8oxfm36+bP9mSw8fxZwHMvORYeQZvzb9fNr+zZYeLoo5D2RKwQglYYph49emb7Z/I0Ix24KZj4zQUUx7ayb4temb7d+IUMy2YCMFI3SksrcGbQThN8JlmHcGM3JLMduCaMAiGaZDbW2tLlq0qNhiGAVmr3FzSNZqqyorWqxYtUlVw2iOiCxW1dpE58x8ZISOZHbVChFbuWtEmbWkjkGT57HXuDkMmjwvsObFoGFKwQgdyeytyeL3l+PK3XInbPNOQcKUghE6kvndJ4vfHwTvnVLptYalHBbvKXNsotkIJcn87oMYBTPsO35FCFM5LN5T5thIwSgZgrpyt1R6rWEqR7LRYRBGjUHHRgpGSRHElbul0msNUzls74TMMaVgGHmmUKtT873KO0wrrm3NR+aYUjCMPFOIXmsh7P1h630HcdQYBkwpGEYCctnrjtx39exlbN5eD0DbytxM50XkTNSDj9j7c/VitN53eWBKwTDiyFev+8sdjdHvmz6vzzrNeDkTkWt7v/W+S5/AKQUROQ74M1AB/FNVJxdZJCNDYnvbHasqEYHNn9dn1cNM1oM/6x8vsuDdjc2urYnLJ7ZXXSFCg2qLayC5l83Vs5dFr5sw63XuWbiGyHq5dpWt+N3IA5OWyctzJ14+P7uzxY46vGglwqwldZ51HYSIs/EyDN6vK/NXrC/6iCQIdVNoAqUURKQC+DvwbeAD4GURma2qy4srmZEu8b3Y2BdYpj3vZD34v89/m7c/2dbi+th8oPkahsjq50SyJOtdb95ez6wldSx6fyNTX1rT7Nzn9Y1cOv3VpGVK5bnjd3Qya0kdl894jfpGfzHLGlQ96zoIaw8SyRBbv8VaDxGEuikGQVuncBjwjqq+p6pfAfcBpxRZJiMDEvWMY8nEvz1ZbzuRQojPx0ueeFm8vGmmPLGSaQvXJjzXqCQtUyq/+XR2Z/OrELzSiU2v2GsPUrUVKM56iCDUTTEImlKoAWJ/cR+4x6KIyPkiskhEFq1fv76gwhn+8WPLTtfenal9fN3m7SnvjT3v5U2zbvP2pDGW4tOJJVV8/Gx3Z0tFumsMCrn2wG9ehV4PEYS6KQZBUwqS4FizX6Cq3qaqtapa27Vr1wKJZaSLH9/1dP3bM/WH715dlfLe2PMjBtTQqV1l0usqJFEz9ZYx1WprvytwvcpRIeIpdy6O5wO/eRV6PUQQ6qYYBE0pfAD0iPl/T2BdkWQxsiBRzziWTPzbk/W2991t55T5eMmTSJaJJ/dL2rMfc3gPEtFKvEcZIwbUsGDcsayafCILxh3bzC6dzu5sla1aKqXKCuFP3z3IU+5EBGG3t1RtBYqzHiIIdVMMAjXRDLwM7CsiewF1wBnAmcUVyciEeJ/2XHgfefnJ+/E+itybyvsoVV6Rc+l4H2VTtkTXxXofdWpXycST+7Uopx+PmSCsPUgkQxC8j4JQN8UgcDuvicgJwI04Lqn/UtVrk11rO68ZhmGkj9fOa0EbKaCqjwGPFVsOwzCMciRocwqGYRhGETGlYBiGYUQxpWAYhmFEMaVgGIZhRAmc91E6iMh64P1iy+GDLsCGYguRR6x84aaUy1fKZYPMy9dLVROu/g21UggLIrIomftXKWDlCzelXL5SLhvkp3xmPjIMwzCimFIwDMMwophSKAy3FVuAPGPlCzelXL5SLhvkoXw2p2AYhmFEsZGCYRiGEcWUgmEYhhHFlEIeEZGrRaRORF51PyfEnBsvIu+IyEoRGVZMObNFRH4hIioiXWKOhbp8IvJbEVnqPrcnRaR7zLlQlw1ARKaIyAq3jA+JSHXMuVIo32gRWSYijSJSG3cu9OUDEJHj3DK8IyLjcpawqtonTx/gauAXCY5/HXgN2AnYC3gXqCi2vBmWsQfwBM4iwi6lUj6gQ8z3nwK3lErZ3HJ8B2jtfv898PsSK9/+QF/gGaA25niplK/ClX1voI1bpq/nIm0bKRSHU4D7VPVLVV0FvAMcVmSZMuUG4Aqab5sa+vKp6mcx/+5MU/lCXzYAVX1SVXe4/76Es8shlE753lTVlQlOlUT5cGR+R1XfU9WvgPtwypY1phTyz8XuEP1fItLJPVYDrI255gP3WKgQkeFAnaq+FneqVMp3rYisBc4Cfu0eLomyxfED4HH3eymWL5ZSKV/eyhG4TXbChog8BeyR4NSVwM3Ab3F6mb8F/oTzA0y083sgfYNTlO9XOGaIFrclOBa48nmVTVUfVtUrgStFZDxwMTCRkJQNUpfPveZKYAdwT+S2BNeHtnyJbktwLJDlS0HeymFKIUtUdaif60TkH8Cj7r8f4NjiI+wJrMuxaDkhWflEpD+OTfY1EQGnDK+IyGGEpHx+nx1wLzAHRymEomyQunwicjZwEjBEXUM1JVS+JISmfCnIWznMfJRHRKRbzL+nAm+432cDZ4jITiKyF7Av8N9Cy5cNqvq6qu6mqr1VtTdOIz1EVT+iBMonIvvG/DscWOF+D33ZwPFcAX4JDFfVz2NOlUT5PCiV8r0M7Csie4lIG+AMnLJljY0U8ssfRORgnGHdauDHAKq6TESmA8txhu4XqWpDsYTMNSVSvski0hdoxPGsugBKpmwAf8PxwJnrjvReUtULSqV8InIq8FegKzBHRF5V1WGlUj5V3SEiF+N4/lUA/1LVZblI28JcGIZhGFHMfGQYhmFEMaVgGIZhRDGlYBiGYUQxpWAYhmFEMaVgGIZhRDGlYBguIvK/NK49RkS+EfP/BSLyfff7ObFRVdNIc3VspFnDKAa2TsEwMuMY4H/ACwCqekvMuXNwFiqGcaWsUeaYUjAMD0TkZGACTnjiT3GC41XhLGZrEJGxwE+AIThKYjVQC9wjItuBI4E3ccI3b3Bj+/9RVY8RkV2BaTgLrP5LTDwbN92fuvkuBC4M4yIrI3yY+cgwvHkeOEJVB+CEJ75CVVcDtwA3qOrBqvpc5GJVfQBYBJzlntvukfZE4Hk37dlATwAR2R84HRikqgcDDTjKyDDyjo0UDMObPYH73ThWbYBVOUz7KGAkgKrOEZFN7vEhwEDgZTcERRXwSQ7zNYykmFIwDG/+ClyvqrNF5Bic3fTSZQdNo/K2cecSxZkR4C5VHZ9BXoaRFWY+MgxvOgJ17vezY45vBdonuSf+3Gqcnj/AaTHH/4NrFhKR44HIJkxPA6NEZDf3XGcR6ZWh/IaRFqYUDKOJdiLyQcznUpyRwQwReQ7YEHPtI8CpIvKqiHwrLp07gVvcc1XAJODPbhqxk8WTgKNE5BWczYrWAKjqcpzJ7SdFZCkwF4gNw24YecOipBqGYRhRbKRgGIZhRDGlYBiGYUQxpWAYhmFEMaVgGIZhRDGlYBiGYUQxpWAYhmFEMaVgGIZhRPn/jIBkBNGG4jMAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "r value :0.18\n"
     ]
    }
   ],
   "source": [
    "# Linear regression on the Southern Hemisphere\n",
    "x_values = southern_hemi_df[\"Lat\"]\n",
    "y_values = southern_hemi_df[\"Cloudiness\"]\n",
    "# Call the function.\n",
    "plot_linear_regression(x_values, y_values,\n",
    "                       'Linear Regression on the Southern Hemisphere \\n for % Cloudiness', '% Cloudiness',(-50,60))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "r value :0.04\n"
     ]
    }
   ],
   "source": [
    "# Linear regression on the Northern Hemisphere\n",
    "x_values = northern_hemi_df[\"Lat\"]\n",
    "y_values = northern_hemi_df[\"Wind Speed\"]\n",
    "# Call the function.\n",
    "plot_linear_regression(x_values, y_values,\n",
    "                       'Linear Regression on the Northern Hemisphere\\nfor Wind Speed', 'Wind Speed',(40,35))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "r value :-0.28\n"
     ]
    }
   ],
   "source": [
    "# Linear regression on the Southern Hemisphere\n",
    "x_values = southern_hemi_df[\"Lat\"]\n",
    "y_values = southern_hemi_df[\"Wind Speed\"]\n",
    "# Call the function.\n",
    "plot_linear_regression(x_values, y_values,\n",
    "                       'Linear Regression on the Southern Hemisphere\\nfor Wind Speed', 'Wind Speed',(-40,15))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "interpreter": {
   "hash": "fbdc92d7232e214d4832efe890561077eb750748953cc72ebba203555034ac8b"
  },
  "kernelspec": {
   "display_name": "Python 3.7.11 ('PythonData')",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.11"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}