WeatherPy.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import the dependencies.\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<zip at 0x2222f515a80>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create a set of random latitude and longitude combinations.\n",
    "lats = np.random.uniform(low=-90.000, high=90.000, size=1500)\n",
    "lngs = np.random.uniform(low=-180.000, high=180.000, size=1500)\n",
    "lat_lngs = zip(lats, lngs)\n",
    "lat_lngs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a practice set of random latitude and longitude combinations.\n",
    "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)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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"
     ]
    }
   ],
   "source": [
    "# Use the tuple() function to display the latitude and longitude combinations.\n",
    "for coordinate in coordinates:\n",
    "    print(coordinate[0], coordinate[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Add the latitudes and longitudes to a list.\n",
    "coordinates = list(lat_lngs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Use the citipy module to determine city based on latitude and longitude.\n",
    "from citipy import citipy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "devonport au\n",
      "hithadhoo mv\n",
      "rikitea pf\n",
      "ndiekro ci\n",
      "new norfolk au\n",
      "heze cn\n",
      "saint-philippe re\n",
      "qaanaaq gl\n",
      "torbay ca\n",
      "castro cl\n",
      "mataura pf\n",
      "busselton au\n",
      "corn island ni\n",
      "belushya guba ru\n",
      "kapaa us\n",
      "gravdal no\n",
      "demmin de\n",
      "codrington ag\n",
      "nikolskoye ru\n",
      "punta arenas cl\n",
      "simpang id\n",
      "peace river ca\n",
      "merauke id\n",
      "vaini to\n",
      "barrow us\n",
      "haguenau fr\n",
      "hushitai cn\n",
      "port alfred za\n",
      "castro cl\n",
      "lufilufi ws\n",
      "narsaq gl\n",
      "vanavara ru\n",
      "illoqqortoormiut gl\n",
      "hermanus za\n",
      "mudon mm\n",
      "illoqqortoormiut gl\n",
      "huangnihe cn\n",
      "komsomolskiy ru\n",
      "nikolskoye ru\n",
      "mys shmidta ru\n",
      "talawdi sd\n",
      "comodoro rivadavia ar\n",
      "bluff nz\n",
      "kaitangata nz\n",
      "samarai pg\n",
      "garissa ke\n",
      "karakendzha tj\n",
      "sao filipe cv\n",
      "coquimbo cl\n",
      "rikitea pf\n",
      "meulaboh id\n",
      "urfa tr\n",
      "westport ie\n",
      "quebrada larga hn\n",
      "vaini to\n",
      "kodiak us\n",
      "busselton au\n",
      "kieta pg\n",
      "puerto ayora ec\n",
      "isangel vu\n",
      "bom sucesso br\n",
      "bredasdorp za\n",
      "karratha au\n",
      "yabelo et\n",
      "griffith au\n",
      "east london za\n",
      "kathu th\n",
      "pueblo nuevo mx\n",
      "bengkulu id\n",
      "hermanus za\n",
      "mahebourg mu\n",
      "labutta mm\n",
      "ranfurly nz\n",
      "maceio br\n",
      "atlantis za\n",
      "ketchikan us\n",
      "takhtamygda ru\n",
      "marcona pe\n",
      "avarua ck\n",
      "hofn is\n",
      "saint anthony ca\n",
      "thompson ca\n",
      "port hedland au\n",
      "mungwi zm\n",
      "ribas do rio pardo br\n",
      "tuktoyaktuk ca\n",
      "tuatapere nz\n",
      "faanui pf\n",
      "taolanaro mg\n",
      "bathsheba bb\n",
      "bluff nz\n",
      "nabire id\n",
      "sfantu gheorghe ro\n",
      "visnes no\n",
      "kavieng pg\n",
      "kosonsoy uz\n",
      "kavaratti in\n",
      "geraldton ca\n",
      "mys shmidta ru\n",
      "bluff nz\n",
      "saryshagan kz\n",
      "rikitea pf\n",
      "goundam ml\n",
      "busselton au\n",
      "belushya guba ru\n",
      "murgasi ro\n",
      "kamenka ru\n",
      "pedernales do\n",
      "camacha pt\n",
      "kahului us\n",
      "hobart au\n",
      "nikolskoye ru\n",
      "busselton au\n",
      "belmonte br\n",
      "petropavlovsk-kamchatskiy ru\n",
      "dalbandin pk\n",
      "cap-aux-meules ca\n",
      "victoria sc\n",
      "ondorhaan mn\n",
      "jamestown sh\n",
      "busselton au\n",
      "mys shmidta ru\n",
      "kapaa us\n",
      "hamina fi\n",
      "yellowknife ca\n",
      "alta floresta br\n",
      "namatanai pg\n",
      "fort nelson ca\n",
      "cockburn town tc\n",
      "carthage us\n",
      "greenville us\n",
      "taolanaro mg\n",
      "houma cn\n",
      "altay cn\n",
      "mitu co\n",
      "nueva italia de ruiz mx\n",
      "airai pw\n",
      "blacksburg us\n",
      "machali cl\n",
      "avera pf\n",
      "hualmay pe\n",
      "airai pw\n",
      "vaini to\n",
      "tuktoyaktuk ca\n",
      "busselton au\n",
      "qaanaaq gl\n",
      "ponta do sol cv\n",
      "bluff nz\n",
      "busselton au\n",
      "saskylakh ru\n",
      "barrow us\n",
      "hobart au\n",
      "illoqqortoormiut gl\n",
      "nurota uz\n",
      "swellendam za\n",
      "lebu cl\n",
      "sao filipe cv\n",
      "bathsheba bb\n",
      "severo-kurilsk ru\n",
      "moose factory ca\n",
      "ushuaia ar\n",
      "shikarpur in\n",
      "vao nc\n",
      "langfang cn\n",
      "clyde river ca\n",
      "chokurdakh ru\n",
      "balikpapan id\n",
      "ushuaia ar\n",
      "mataura pf\n",
      "bay city us\n",
      "mbuji-mayi cd\n",
      "gushikawa jp\n",
      "zelenoborsk ru\n",
      "tupik ru\n",
      "samusu ws\n",
      "sao francisco do sul br\n",
      "belushya guba ru\n",
      "bystrzyca klodzka pl\n",
      "hobart au\n",
      "saint-philippe re\n",
      "hilo us\n",
      "albany au\n",
      "high level ca\n",
      "hamilton bm\n",
      "taolanaro mg\n",
      "qaanaaq gl\n",
      "margate za\n",
      "ushuaia ar\n",
      "rikitea pf\n",
      "rikitea pf\n",
      "alice springs au\n",
      "illoqqortoormiut gl\n",
      "taolanaro mg\n",
      "albany au\n",
      "tuktoyaktuk ca\n",
      "aklavik ca\n",
      "okhotsk ru\n",
      "shitanjing cn\n",
      "aflao gh\n",
      "ushuaia ar\n",
      "carnarvon au\n",
      "albany au\n",
      "illoqqortoormiut gl\n",
      "mataura pf\n",
      "manggar id\n",
      "kudahuvadhoo mv\n",
      "kerema pg\n",
      "kodiak us\n",
      "paradwip in\n",
      "saskylakh ru\n",
      "bathsheba bb\n",
      "dikson ru\n",
      "ushuaia ar\n",
      "ushuaia ar\n",
      "hobart au\n",
      "aban ru\n",
      "rikitea pf\n",
      "ushuaia ar\n",
      "namibe ao\n",
      "upernavik gl\n",
      "tuktoyaktuk ca\n",
      "college us\n",
      "gat ly\n",
      "tyulgan ru\n",
      "butaritari ki\n",
      "chenghai cn\n",
      "puerto ayora ec\n",
      "lishui cn\n",
      "belushya guba ru\n",
      "le port re\n",
      "wajima jp\n",
      "rikitea pf\n",
      "hithadhoo mv\n",
      "mataura pf\n",
      "manacor es\n",
      "port alfred za\n",
      "lolua tv\n",
      "saint-philippe re\n",
      "kapaa us\n",
      "laguna br\n",
      "auki sb\n",
      "hualmay pe\n",
      "bilibino ru\n",
      "saldanha za\n",
      "saldanha za\n",
      "kapaa us\n",
      "arraial do cabo br\n",
      "vaini to\n",
      "kurilsk ru\n",
      "ushuaia ar\n",
      "belushya guba ru\n",
      "rawson ar\n",
      "bluff nz\n",
      "yellowknife ca\n",
      "kupino ru\n",
      "kapaa us\n",
      "rikitea pf\n",
      "mizpe ramon il\n",
      "sao joao da barra br\n",
      "georgetown sh\n",
      "lompoc us\n",
      "ixtapa mx\n",
      "naze jp\n",
      "jumla np\n",
      "pacific grove us\n",
      "castro cl\n",
      "astipalaia gr\n",
      "mataura pf\n",
      "rikitea pf\n",
      "new norfolk au\n",
      "atuona pf\n",
      "qaanaaq gl\n",
      "saint-philippe re\n",
      "carnarvon au\n",
      "taolanaro mg\n",
      "illoqqortoormiut gl\n",
      "mount gambier au\n",
      "albany au\n",
      "mataura pf\n",
      "punta arenas cl\n",
      "illoqqortoormiut gl\n",
      "yerbogachen ru\n",
      "constitucion mx\n",
      "dikson ru\n",
      "isabela us\n",
      "ushuaia ar\n",
      "sangar ru\n",
      "qaanaaq gl\n",
      "birin dz\n",
      "atuona pf\n",
      "punta arenas cl\n",
      "albany au\n",
      "mataura pf\n",
      "norman wells ca\n",
      "ponta do sol cv\n",
      "bowen au\n",
      "aquiraz br\n",
      "kavaratti in\n",
      "mataura pf\n",
      "punta arenas cl\n",
      "bredasdorp za\n",
      "rikitea pf\n",
      "khatanga ru\n",
      "norman wells ca\n",
      "albany au\n",
      "mar del plata ar\n",
      "namestovo sk\n",
      "ancud cl\n",
      "punta arenas cl\n",
      "padang id\n",
      "marzuq ly\n",
      "haslett us\n",
      "samarai pg\n",
      "rikitea pf\n",
      "tanete id\n",
      "puerto ayora ec\n",
      "kavieng pg\n",
      "port alfred za\n",
      "barentsburg sj\n",
      "atuona pf\n",
      "mogadishu so\n",
      "illoqqortoormiut gl\n",
      "pangnirtung ca\n",
      "meyungs pw\n",
      "port lincoln au\n",
      "avarua ck\n",
      "bredasdorp za\n",
      "mindelo cv\n",
      "chebenki ru\n",
      "tuatapere nz\n",
      "hermanus za\n",
      "samarai pg\n",
      "olafsvik is\n",
      "mar del plata ar\n",
      "rikitea pf\n",
      "turayf sa\n",
      "tasiilaq gl\n",
      "ribeira grande pt\n",
      "jamestown sh\n",
      "mataura pf\n",
      "saint anthony ca\n",
      "bluff nz\n",
      "chokurdakh ru\n",
      "port lincoln au\n",
      "poprad sk\n",
      "tuatapere nz\n",
      "ushuaia ar\n",
      "barrow us\n",
      "pahuatlan mx\n",
      "flinders au\n",
      "ketchikan us\n",
      "butaritari ki\n",
      "mataura pf\n",
      "saint-philippe re\n",
      "klaksvik fo\n",
      "punta arenas cl\n",
      "hobart au\n",
      "imbituba br\n",
      "luganville vu\n",
      "sitka us\n",
      "new norfolk au\n",
      "butaritari ki\n",
      "hobart au\n",
      "la plaine dm\n",
      "presidencia roque saenz pena ar\n",
      "asfi ma\n",
      "carnarvon au\n",
      "qaanaaq gl\n",
      "rikitea pf\n",
      "chuy uy\n",
      "puerto del rosario es\n",
      "martapura id\n",
      "busselton au\n",
      "castro cl\n",
      "qaanaaq gl\n",
      "rikitea pf\n",
      "butaritari ki\n",
      "yellowknife ca\n",
      "hermanus za\n",
      "east london za\n",
      "tura ru\n",
      "upernavik gl\n",
      "bredasdorp za\n",
      "mount gambier au\n",
      "attawapiskat ca\n",
      "rikitea pf\n",
      "evensk ru\n",
      "monte alegre br\n",
      "taolanaro mg\n",
      "margate za\n",
      "torbay ca\n",
      "yellowknife ca\n",
      "aklavik ca\n",
      "nehe cn\n",
      "meihekou cn\n",
      "guerrero negro mx\n",
      "rikitea pf\n",
      "airai pw\n",
      "sao joao da barra br\n",
      "juneau us\n",
      "avarua ck\n",
      "taolanaro mg\n",
      "upernavik gl\n",
      "nizhneyansk ru\n",
      "mahebourg mu\n",
      "nizhneyansk ru\n",
      "taolanaro mg\n",
      "nanortalik gl\n",
      "tuktoyaktuk ca\n",
      "rikitea pf\n",
      "panyutyne ua\n",
      "busselton au\n",
      "punta arenas cl\n",
      "kodiak us\n",
      "ushuaia ar\n",
      "rawson ar\n",
      "encruzilhada do sul br\n",
      "taolanaro mg\n",
      "mets masrik am\n",
      "pochinki ru\n",
      "samusu ws\n",
      "qaanaaq gl\n",
      "hambantota lk\n",
      "punta arenas cl\n",
      "belushya guba ru\n",
      "liverpool ca\n",
      "pangnirtung ca\n",
      "puerto carreno co\n",
      "fairbanks us\n",
      "yarovoye ru\n",
      "castro cl\n",
      "krasnokholm ru\n",
      "avarua ck\n",
      "ushuaia ar\n",
      "hobart au\n",
      "hobart au\n",
      "tsihombe mg\n",
      "chornukhy ua\n",
      "ratnagiri in\n",
      "ostrovnoy ru\n",
      "ushuaia ar\n",
      "aljezur pt\n",
      "san patricio mx\n",
      "dashitou cn\n",
      "zhezkazgan kz\n",
      "louisbourg ca\n",
      "hilo us\n",
      "atuona pf\n",
      "bluff nz\n",
      "lorengau pg\n",
      "yellowknife ca\n",
      "punta arenas cl\n",
      "cape town za\n",
      "raudeberg no\n",
      "jamestown sh\n",
      "karabulak kz\n",
      "chokurdakh ru\n",
      "saint-philippe re\n",
      "hasaki jp\n",
      "kharovsk ru\n",
      "sept-iles ca\n",
      "vila franca do campo pt\n",
      "illoqqortoormiut gl\n",
      "lebu cl\n",
      "hermanus za\n",
      "busselton au\n",
      "verkhnyaya inta ru\n",
      "barrow us\n",
      "rikitea pf\n",
      "severo-kurilsk ru\n",
      "aflu dz\n",
      "arraial do cabo br\n",
      "bethel us\n",
      "sechura pe\n",
      "visnes no\n",
      "zhigansk ru\n",
      "kapaa us\n",
      "san policarpo ph\n",
      "taolanaro mg\n",
      "fort saint john ca\n",
      "nioro ml\n",
      "castro cl\n",
      "monrovia lr\n",
      "hobart au\n",
      "sao joao da barra br\n",
      "ruidoso us\n",
      "bingol tr\n",
      "cape town za\n",
      "nikolskoye ru\n",
      "praia da vitoria pt\n",
      "mar del plata ar\n",
      "jian cn\n",
      "thompson ca\n",
      "luderitz na\n",
      "san cristobal ec\n",
      "mataura pf\n",
      "sola vu\n",
      "kapaa us\n",
      "bambous virieux mu\n",
      "ulladulla au\n",
      "samana do\n",
      "jamestown sh\n",
      "new norfolk au\n",
      "nizhneyansk ru\n",
      "hermanus za\n",
      "saint-philippe re\n",
      "cherskiy ru\n",
      "xingtai cn\n",
      "hermanus za\n",
      "pisco pe\n",
      "barentsburg sj\n",
      "filadelfia py\n",
      "olafsvik is\n",
      "ribeira grande pt\n",
      "illoqqortoormiut gl\n",
      "codrington ag\n",
      "port alfred za\n",
      "rikitea pf\n",
      "waingapu id\n",
      "vaini to\n",
      "komsomolskiy ru\n",
      "tasiilaq gl\n",
      "castro cl\n",
      "georgetown sh\n",
      "vaini to\n",
      "kumluca tr\n",
      "klaksvik fo\n",
      "punta arenas cl\n",
      "bathsheba bb\n",
      "chokurdakh ru\n",
      "illoqqortoormiut gl\n",
      "yar-sale ru\n",
      "nikolskoye ru\n",
      "thompson ca\n",
      "touros br\n",
      "punta arenas cl\n",
      "east london za\n",
      "bury saint edmunds gb\n",
      "westerly us\n",
      "esperance au\n",
      "mutsamudu km\n",
      "benalla au\n",
      "amderma ru\n",
      "rikitea pf\n",
      "saint-leu re\n",
      "fortuna us\n",
      "belushya guba ru\n",
      "adrar dz\n",
      "busselton au\n",
      "castro cl\n",
      "ancud cl\n",
      "ostrovnoy ru\n",
      "khanpur pk\n",
      "kruisfontein za\n",
      "kawalu id\n",
      "bredasdorp za\n",
      "dingle ie\n",
      "airai pw\n",
      "maningrida au\n",
      "berlevag no\n",
      "dikson ru\n",
      "adrar dz\n",
      "hami cn\n",
      "castro cl\n",
      "muli mv\n",
      "loding no\n",
      "illoqqortoormiut gl\n",
      "ushuaia ar\n",
      "mildura au\n",
      "hithadhoo mv\n",
      "mataura pf\n",
      "miles city us\n",
      "georgetown sh\n",
      "mataura pf\n",
      "arman ru\n",
      "rikitea pf\n",
      "parnarama br\n",
      "cape town za\n",
      "punta arenas cl\n",
      "saint-francois gp\n",
      "barentsburg sj\n",
      "victoria sc\n",
      "kargasok ru\n",
      "busselton au\n",
      "saint-philippe re\n",
      "junin ar\n",
      "toledo es\n",
      "nyurba ru\n",
      "okandja ga\n",
      "rikitea pf\n",
      "hithadhoo mv\n",
      "nador ma\n",
      "belmonte br\n",
      "new norfolk au\n",
      "cape town za\n",
      "illoqqortoormiut gl\n",
      "ushuaia ar\n",
      "salinas mx\n",
      "suihua cn\n",
      "hobart au\n",
      "albany au\n",
      "lata sb\n",
      "sungairaya id\n",
      "busselton au\n",
      "sola vu\n",
      "sulmona it\n",
      "salinas ec\n",
      "tonantins br\n",
      "chuy uy\n",
      "vila franca do campo pt\n",
      "cabo san lucas mx\n",
      "torbay ca\n",
      "hobart au\n",
      "bengkulu id\n",
      "kenai us\n",
      "alta floresta br\n",
      "butaritari ki\n",
      "atuona pf\n",
      "carlsbad us\n",
      "airai pw\n",
      "cape town za\n",
      "sentyabrskiy ru\n",
      "wuwei cn\n",
      "hobart au\n",
      "nizhneyansk ru\n",
      "dudinka ru\n",
      "khatanga ru\n",
      "hermanus za\n",
      "mataura pf\n",
      "cape town za\n",
      "jamestown sh\n",
      "new norfolk au\n",
      "barrow us\n",
      "kholtoson ru\n",
      "anadyr ru\n",
      "ribeira grande pt\n",
      "namatanai pg\n",
      "illoqqortoormiut gl\n",
      "belushya guba ru\n",
      "tuktoyaktuk ca\n",
      "ventspils lv\n",
      "katsuura jp\n",
      "cape town za\n",
      "busselton au\n",
      "east london za\n",
      "constitucion mx\n",
      "byron bay au\n",
      "qaanaaq gl\n",
      "berlevag no\n",
      "green river us\n",
      "busselton au\n",
      "dolbeau ca\n",
      "asandh in\n",
      "mataura pf\n",
      "faya td\n",
      "bredasdorp za\n",
      "chupa ru\n",
      "busselton au\n",
      "tilichiki ru\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "mahebourg mu\n",
      "illoqqortoormiut gl\n",
      "ferme-neuve ca\n",
      "souillac mu\n",
      "thompson ca\n",
      "vestmannaeyjar is\n",
      "tumannyy ru\n",
      "yar-sale ru\n",
      "ushuaia ar\n",
      "springbok za\n",
      "albany au\n",
      "albury au\n",
      "alexandria eg\n",
      "bluff nz\n",
      "lebu cl\n",
      "ushuaia ar\n",
      "dabou ci\n",
      "tuktoyaktuk ca\n",
      "beitbridge zw\n",
      "belushya guba ru\n",
      "cape town za\n",
      "san cristobal ec\n",
      "pochutla mx\n",
      "armidale au\n",
      "tsihombe mg\n",
      "samdrup jongkhar bt\n",
      "mataura pf\n",
      "port keats au\n",
      "lamont us\n",
      "beyneu kz\n",
      "nakhon sawan th\n",
      "duekoue ci\n",
      "jamestown sh\n",
      "khatanga ru\n",
      "taolanaro mg\n",
      "mataura pf\n",
      "mlonggo id\n",
      "hilo us\n",
      "vaini to\n",
      "arraial do cabo br\n",
      "kuche cn\n",
      "santiago del estero ar\n",
      "marzuq ly\n",
      "rivadavia ar\n",
      "hithadhoo mv\n",
      "hobart au\n",
      "illoqqortoormiut gl\n",
      "dikson ru\n",
      "marcona pe\n",
      "ponta do sol cv\n",
      "jamestown sh\n",
      "belmonte br\n",
      "hermanus za\n",
      "tasiilaq gl\n",
      "butaritari ki\n",
      "hithadhoo mv\n",
      "barrow us\n",
      "palmer us\n",
      "alexander city us\n",
      "tuktoyaktuk ca\n",
      "vestmannaeyjar is\n",
      "jamestown sh\n",
      "punta arenas cl\n",
      "teguldet ru\n",
      "lamia gr\n",
      "atuona pf\n",
      "kahului us\n",
      "lompoc us\n",
      "lebu cl\n",
      "port alfred za\n",
      "busselton au\n",
      "hilo us\n",
      "barrow us\n",
      "bluff nz\n",
      "chifeng cn\n",
      "guaymas mx\n",
      "houffalize be\n",
      "bluff nz\n",
      "khatanga ru\n",
      "tiksi ru\n",
      "tsihombe mg\n",
      "rikitea pf\n",
      "zonguldak tr\n",
      "albany au\n",
      "sao felix do xingu br\n",
      "bluff nz\n",
      "georgetown sh\n",
      "tuktoyaktuk ca\n",
      "jamestown sh\n",
      "port alfred za\n",
      "hobart au\n",
      "busselton au\n",
      "ushuaia ar\n",
      "oistins bb\n",
      "srednekolymsk ru\n",
      "rikitea pf\n",
      "cabo san lucas mx\n",
      "lasa cn\n",
      "dikson ru\n",
      "staryy nadym ru\n",
      "severo-kurilsk ru\n",
      "hilo us\n",
      "bredasdorp za\n",
      "tasiilaq gl\n",
      "mataura pf\n",
      "saldanha za\n",
      "qaanaaq gl\n",
      "sinop tr\n",
      "kapaa us\n",
      "taolanaro mg\n",
      "taoudenni ml\n",
      "busselton au\n",
      "busselton au\n",
      "nuristan af\n",
      "hermanus za\n",
      "bonavista ca\n",
      "lasa cn\n",
      "tanah merah my\n",
      "rikitea pf\n",
      "sitka us\n",
      "rio grande br\n",
      "illoqqortoormiut gl\n",
      "tuktoyaktuk ca\n",
      "mbanza-ngungu cd\n",
      "hithadhoo mv\n",
      "fortuna us\n",
      "albany au\n",
      "tuktoyaktuk ca\n",
      "vaini to\n",
      "okhotsk ru\n",
      "sitka us\n",
      "cape town za\n",
      "avarua ck\n",
      "scottsburgh za\n",
      "punta arenas cl\n",
      "kampot kh\n",
      "tarauaca br\n",
      "flinders au\n",
      "bredasdorp za\n",
      "coquimbo cl\n",
      "ushuaia ar\n",
      "tasiilaq gl\n",
      "salinopolis br\n",
      "tacuarembo uy\n",
      "georgetown sh\n",
      "rikitea pf\n",
      "illoqqortoormiut gl\n",
      "busselton au\n",
      "ushuaia ar\n",
      "mahon es\n",
      "ushuaia ar\n",
      "coos bay us\n",
      "bredasdorp za\n",
      "albany au\n",
      "alappuzha in\n",
      "petropavlovsk-kamchatskiy ru\n",
      "brae gb\n",
      "khatanga ru\n",
      "youkounkoun gn\n",
      "rikitea pf\n",
      "bandarbeyla so\n",
      "belushya guba ru\n",
      "hobart au\n",
      "teavaro pf\n",
      "busselton au\n",
      "nizhneyansk ru\n",
      "taolanaro mg\n",
      "rikitea pf\n",
      "belushya guba ru\n",
      "mount isa au\n",
      "hermanus za\n",
      "faanui pf\n",
      "marcona pe\n",
      "hermanus za\n",
      "codrington ag\n",
      "pescara it\n",
      "chuy uy\n",
      "taolanaro mg\n",
      "kapaa us\n",
      "busselton au\n",
      "mataura pf\n",
      "aksarka ru\n",
      "sitka us\n",
      "jamestown sh\n",
      "taolanaro mg\n",
      "mount gambier au\n",
      "katsuura jp\n",
      "berlevag no\n",
      "lolua tv\n",
      "mandurah au\n",
      "jensen beach us\n",
      "ponta do sol pt\n",
      "sioux lookout ca\n",
      "yellowknife ca\n",
      "san pedro ar\n",
      "lavrentiya ru\n",
      "pierreville ca\n",
      "hobart au\n",
      "illoqqortoormiut gl\n",
      "fairbanks us\n",
      "okhotsk ru\n",
      "hilo us\n",
      "tasiilaq gl\n",
      "busselton au\n",
      "avarua ck\n",
      "arraial do cabo br\n",
      "islamkot pk\n",
      "norman wells ca\n",
      "vaitupu wf\n",
      "saldanha za\n",
      "ushuaia ar\n",
      "new norfolk au\n",
      "vaini to\n",
      "mataura pf\n",
      "castro cl\n",
      "atuona pf\n",
      "ayer itam my\n",
      "altay cn\n",
      "bluff nz\n",
      "olafsvik is\n",
      "buerarema br\n",
      "ushuaia ar\n",
      "denpasar id\n",
      "cabarroguis ph\n",
      "rikitea pf\n",
      "kodiak us\n",
      "taolanaro mg\n",
      "lavrentiya ru\n",
      "praia cv\n",
      "lompoc us\n",
      "oistins bb\n",
      "rikitea pf\n",
      "querendaro mx\n",
      "manokwari id\n",
      "atuona pf\n",
      "butaritari ki\n",
      "cabra ph\n",
      "boras se\n",
      "norman wells ca\n",
      "los llanos de aridane es\n",
      "taolanaro mg\n",
      "bluff nz\n",
      "altay cn\n",
      "rikitea pf\n",
      "mataura pf\n",
      "mataura pf\n",
      "hermanus za\n",
      "yulara au\n",
      "jamestown sh\n",
      "komsomolskiy ru\n",
      "ushuaia ar\n",
      "garissa ke\n",
      "mataura pf\n",
      "ushuaia ar\n",
      "lebu cl\n",
      "ouadda cf\n",
      "hami cn\n",
      "yellowknife ca\n",
      "port lincoln au\n",
      "yamethin mm\n",
      "saint-philippe re\n",
      "inongo cd\n",
      "kangaba ml\n",
      "georgetown sh\n",
      "saskylakh ru\n",
      "mataura pf\n",
      "vanimo pg\n",
      "busselton au\n",
      "goderich sl\n",
      "avarua ck\n",
      "ushuaia ar\n",
      "zhigansk ru\n",
      "kollam in\n",
      "taolanaro mg\n",
      "severnyy ru\n",
      "marcona pe\n",
      "sarakhs ir\n",
      "saint-pierre pm\n",
      "bethel us\n",
      "vaini to\n",
      "atuona pf\n",
      "puerto ayora ec\n",
      "norman wells ca\n",
      "port hardy ca\n",
      "alexandria eg\n",
      "carutapera br\n",
      "mecca sa\n",
      "nur ir\n",
      "taolanaro mg\n",
      "narsaq gl\n",
      "coromandel nz\n",
      "taolanaro mg\n",
      "butaritari ki\n",
      "rikitea pf\n",
      "leningradskiy ru\n",
      "marcona pe\n",
      "mataura pf\n",
      "bethel us\n",
      "atuona pf\n",
      "ituni gy\n",
      "mbandaka cd\n",
      "atuona pf\n",
      "rikitea pf\n",
      "manado id\n",
      "catamarca ar\n",
      "punta arenas cl\n",
      "tuktoyaktuk ca\n",
      "luderitz na\n",
      "tiksi ru\n",
      "dingli mt\n",
      "hobart au\n",
      "adrar dz\n",
      "albany au\n",
      "rikitea pf\n",
      "kodiak us\n",
      "camopi gf\n",
      "bluff nz\n",
      "bluff nz\n",
      "butaritari ki\n",
      "shwebo mm\n",
      "bredasdorp za\n",
      "new norfolk au\n",
      "vao nc\n",
      "luderitz na\n",
      "ponta do sol cv\n",
      "puerto madryn ar\n",
      "avarua ck\n",
      "busselton au\n",
      "shu kz\n",
      "huaral pe\n",
      "esso ru\n",
      "rio grande br\n",
      "kaitangata nz\n",
      "quchan ir\n",
      "siilinjarvi fi\n",
      "vardo no\n",
      "albany au\n",
      "hilo us\n",
      "tasiilaq gl\n",
      "mwanza mw\n",
      "ancud cl\n",
      "mys shmidta ru\n",
      "albany au\n",
      "taolanaro mg\n",
      "tasiilaq gl\n",
      "vaini to\n",
      "kulhudhuffushi mv\n",
      "katsuura jp\n",
      "hermanus za\n",
      "bluff nz\n",
      "mataura pf\n",
      "ipixuna br\n",
      "busselton au\n",
      "barrow us\n",
      "prieska za\n",
      "chokurdakh ru\n",
      "grand river south east mu\n",
      "jamestown sh\n",
      "alofi nu\n",
      "qaanaaq gl\n",
      "valdosta us\n",
      "ponta do sol cv\n",
      "faanui pf\n",
      "mataura pf\n",
      "hefei cn\n",
      "newark us\n",
      "avarua ck\n",
      "finschhafen pg\n",
      "georgetown sh\n",
      "butaritari ki\n",
      "marcona pe\n",
      "nizhneyansk ru\n",
      "kawalu id\n",
      "vao nc\n",
      "chokurdakh ru\n",
      "attawapiskat ca\n",
      "port alfred za\n",
      "atuona pf\n",
      "pizhanka ru\n",
      "taolanaro mg\n",
      "vaini to\n",
      "keetmanshoop na\n",
      "dondo mz\n",
      "margate za\n",
      "college us\n",
      "hithadhoo mv\n",
      "port elizabeth za\n",
      "albany au\n",
      "khatanga ru\n",
      "puerto ayora ec\n",
      "hermanus za\n",
      "acapulco mx\n",
      "lebu cl\n",
      "nikolskoye ru\n",
      "rikitea pf\n",
      "atuona pf\n",
      "bluff nz\n",
      "iralaya hn\n",
      "galgani sd\n",
      "villarrica cl\n",
      "saint-philippe re\n",
      "atuona pf\n",
      "hasaki jp\n",
      "rikitea pf\n",
      "samusu ws\n",
      "nyurba ru\n",
      "quatre cocos mu\n",
      "punta arenas cl\n",
      "general roca ar\n",
      "vaini to\n",
      "ushuaia ar\n",
      "grand river south east mu\n",
      "hobyo so\n",
      "taolanaro mg\n",
      "vaini to\n",
      "qaanaaq gl\n",
      "antofagasta cl\n",
      "marsa matruh eg\n",
      "baker city us\n",
      "ribeira grande pt\n",
      "bageshwar in\n",
      "cidreira br\n",
      "taolanaro mg\n",
      "urucara br\n",
      "mataura pf\n",
      "kapaa us\n",
      "butaritari ki\n",
      "hermanus za\n",
      "lebu cl\n",
      "umzimvubu za\n",
      "moussoro td\n",
      "busselton au\n",
      "punta arenas cl\n",
      "aklavik ca\n",
      "mehamn no\n",
      "ushuaia ar\n",
      "grand river south east mu\n",
      "bethel us\n",
      "thompson ca\n",
      "pemangkat id\n",
      "salalah om\n",
      "dukat ru\n",
      "coihaique cl\n",
      "cape town za\n",
      "albany au\n",
      "elk city us\n",
      "vestmannaeyjar is\n",
      "qaanaaq gl\n",
      "yar-sale ru\n",
      "lebu cl\n",
      "bethel us\n",
      "kaitangata nz\n",
      "ushuaia ar\n",
      "narsaq gl\n",
      "mataura pf\n",
      "albany au\n",
      "albany au\n",
      "broome au\n",
      "new norfolk au\n",
      "marystown ca\n",
      "marawi sd\n",
      "nikolskoye ru\n",
      "burica pa\n",
      "ushuaia ar\n",
      "taolanaro mg\n",
      "barentsburg sj\n",
      "ushuaia ar\n",
      "salalah om\n",
      "ushuaia ar\n",
      "cabo san lucas mx\n",
      "port alfred za\n",
      "sur om\n",
      "hovd mn\n",
      "yellowknife ca\n",
      "punta arenas cl\n",
      "mar del plata ar\n",
      "hithadhoo mv\n",
      "albany au\n",
      "merrill us\n",
      "homer us\n",
      "san policarpo ph\n",
      "mahebourg mu\n",
      "cape town za\n",
      "nanortalik gl\n",
      "port alfred za\n",
      "mardin tr\n",
      "busselton au\n",
      "mataura pf\n",
      "huoqiu cn\n",
      "saint-philippe re\n",
      "muscat om\n",
      "tromso no\n",
      "rikitea pf\n",
      "victoria sc\n",
      "labuan my\n",
      "ust-shonosha ru\n",
      "mys shmidta ru\n",
      "dikson ru\n",
      "vaini to\n",
      "masalli az\n",
      "vaini to\n",
      "nizhneyansk ru\n",
      "attawapiskat ca\n",
      "punta arenas cl\n",
      "camacha pt\n",
      "kapaa us\n",
      "bluff nz\n",
      "hofn is\n",
      "chadiza zm\n",
      "keshabpur bd\n",
      "rikitea pf\n",
      "tasiilaq gl\n",
      "punta arenas cl\n",
      "port blair in\n",
      "bethel us\n",
      "the valley ai\n",
      "airai pw\n",
      "upernavik gl\n",
      "ushuaia ar\n",
      "liku wf\n",
      "hobart au\n",
      "lompoc us\n",
      "georgetown sh\n",
      "kaeo nz\n",
      "hilo us\n",
      "mataura pf\n",
      "burnie au\n",
      "geraldton au\n",
      "busselton au\n",
      "cape town za\n",
      "tuapse ru\n",
      "maltahohe na\n",
      "new norfolk au\n",
      "rikitea pf\n",
      "ushuaia ar\n",
      "tofield ca\n",
      "lebu cl\n",
      "bluff nz\n",
      "dekoa cf\n",
      "fortuna us\n",
      "longyearbyen sj\n",
      "mataura pf\n",
      "nome us\n",
      "camacha pt\n",
      "novyye burasy ru\n",
      "new norfolk au\n",
      "araceli ph\n",
      "constitucion mx\n",
      "dikson ru\n",
      "havre-saint-pierre ca\n",
      "urusha ru\n",
      "bad wurzach de\n",
      "atuona pf\n",
      "rikitea pf\n",
      "rikitea pf\n",
      "hermanus za\n",
      "avera pf\n",
      "punta arenas cl\n",
      "bluff nz\n",
      "kendari id\n",
      "egvekinot ru\n",
      "vaitupu wf\n",
      "upernavik gl\n",
      "barentsburg sj\n",
      "yellowknife ca\n",
      "rikitea pf\n",
      "quatre cocos mu\n",
      "busselton au\n",
      "sitka us\n",
      "nikolskoye ru\n",
      "belushya guba ru\n",
      "busselton au\n",
      "mataura pf\n",
      "pisco pe\n",
      "takoradi gh\n",
      "punta arenas cl\n",
      "malanje ao\n",
      "port elizabeth za\n",
      "esperance au\n",
      "volosovo ru\n",
      "lyuban by\n",
      "huangnihe cn\n",
      "tigil ru\n",
      "maniitsoq gl\n",
      "kumluca tr\n",
      "pevek ru\n",
      "lebu cl\n",
      "hermanus za\n",
      "pisco pe\n",
      "the valley ai\n",
      "taolanaro mg\n",
      "lompoc us\n",
      "upernavik gl\n",
      "ushuaia ar\n",
      "caravelas br\n",
      "castro cl\n",
      "baherden tm\n",
      "haines junction ca\n",
      "halalo wf\n",
      "ribeira grande pt\n",
      "cabo san lucas mx\n",
      "marsa matruh eg\n",
      "bambous virieux mu\n",
      "broome au\n",
      "rikitea pf\n",
      "homer us\n",
      "mar del plata ar\n",
      "tura ru\n",
      "pemangkat id\n",
      "butaritari ki\n",
      "amderma ru\n",
      "vaini to\n",
      "san patricio mx\n",
      "rikitea pf\n",
      "jamestown sh\n",
      "punta arenas cl\n",
      "east london za\n",
      "nizhneyansk ru\n",
      "san cristobal ec\n",
      "lorengau pg\n",
      "kahului us\n",
      "pailon bo\n",
      "fare pf\n",
      "albany au\n",
      "pyaozerskiy ru\n",
      "ola ru\n",
      "berlevag no\n",
      "mahebourg mu\n",
      "katherine au\n",
      "saint george bm\n",
      "datong cn\n",
      "ribeira grande pt\n",
      "sitka us\n",
      "albany au\n",
      "camopi gf\n",
      "chokurdakh ru\n",
      "doctor pedro p. pena py\n",
      "kosh-agach ru\n",
      "bolungarvik is\n",
      "chardara kz\n",
      "cockburn town bs\n",
      "port lincoln au\n",
      "nanortalik gl\n",
      "campo maior pt\n",
      "ushuaia ar\n",
      "barrow us\n",
      "rikitea pf\n",
      "taolanaro mg\n",
      "kolobrzeg pl\n",
      "cherskiy ru\n",
      "ushuaia ar\n",
      "sterling us\n",
      "rikitea pf\n",
      "kot samaba pk\n",
      "hirara jp\n",
      "ilulissat gl\n",
      "kapaa us\n",
      "cape town za\n",
      "fortuna us\n",
      "ushuaia ar\n",
      "castro cl\n",
      "vaini to\n",
      "rawson ar\n",
      "hithadhoo mv\n",
      "san ramon bo\n",
      "ushuaia ar\n",
      "punta arenas cl\n",
      "lillooet ca\n",
      "richards bay za\n",
      "quepos cr\n",
      "hobart au\n",
      "kushmurun kz\n",
      "bluff nz\n",
      "krasnyy yar ru\n",
      "crib point au\n",
      "sangar ru\n",
      "coquimbo cl\n",
      "bredasdorp za\n",
      "atuona pf\n",
      "cabo san lucas mx\n",
      "seydi tm\n",
      "busselton au\n",
      "ancud cl\n",
      "victoria sc\n",
      "rikitea pf\n",
      "vaini to\n",
      "cape town za\n",
      "vaini to\n",
      "rikitea pf\n",
      "manzil tamim tn\n",
      "saint-joseph re\n",
      "rincon an\n",
      "gazimurskiy zavod ru\n",
      "port blair in\n",
      "karatau kz\n",
      "saint george bm\n",
      "dikson ru\n",
      "hasaki jp\n",
      "rikitea pf\n",
      "cidreira br\n",
      "butaritari ki\n",
      "dongzhen cn\n",
      "merauke id\n",
      "pemba mz\n",
      "broome au\n",
      "vaini to\n",
      "matara lk\n",
      "kaitangata nz\n",
      "vaitupu wf\n",
      "mar del plata ar\n",
      "ondorhaan mn\n",
      "cape town za\n",
      "saint-augustin ca\n",
      "port hardy ca\n",
      "katsuura jp\n",
      "hobart au\n",
      "jumla np\n",
      "qaanaaq gl\n",
      "kapaa us\n",
      "nikolskoye ru\n",
      "amderma ru\n",
      "fortuna us\n",
      "kaitangata nz\n",
      "tsihombe mg\n",
      "avarua ck\n",
      "qaanaaq gl\n",
      "rikitea pf\n",
      "guerrero negro mx\n",
      "siniscola it\n",
      "souillac mu\n",
      "sitka us\n",
      "saryozek kz\n",
      "rocha uy\n",
      "bambous virieux mu\n",
      "torbay ca\n",
      "krasnoyarsk-45 ru\n",
      "puerto ayora ec\n",
      "rikitea pf\n",
      "hermanus za\n",
      "mahebourg mu\n",
      "barrow us\n",
      "ushuaia ar\n",
      "videira br\n",
      "labuhan id\n",
      "dingle ie\n",
      "punta arenas cl\n",
      "punta arenas cl\n",
      "nichinan jp\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "pacific grove us\n",
      "vallenar cl\n",
      "longyearbyen sj\n",
      "emerald au\n",
      "nizhneyansk ru\n",
      "oranjemund na\n",
      "salalah om\n",
      "arraial do cabo br\n",
      "mataura pf\n",
      "pombas cv\n",
      "ushuaia ar\n",
      "punta arenas cl\n",
      "nuuk gl\n",
      "bluff nz\n",
      "san patricio mx\n",
      "pevek ru\n",
      "ondangwa na\n",
      "puerto ayora ec\n",
      "ushuaia ar\n",
      "torbay ca\n",
      "clyde river ca\n",
      "cape town za\n",
      "avarua ck\n",
      "tasiilaq gl\n",
      "tsihombe mg\n",
      "bluff nz\n",
      "constitucion mx\n",
      "albany au\n",
      "fez ma\n",
      "punta arenas cl\n",
      "port macquarie au\n",
      "busselton au\n",
      "hambantota lk\n",
      "georgetown sh\n",
      "voyinka ua\n",
      "mount pleasant us\n",
      "mataura pf\n",
      "khatanga ru\n",
      "vardo no\n",
      "bredasdorp za\n",
      "avarua ck\n",
      "hermanus za\n",
      "cascais pt\n",
      "alexandria us\n",
      "ixtlahuacan del rio mx\n",
      "kavieng pg\n",
      "atuona pf\n",
      "ternate id\n",
      "busselton au\n",
      "vestmannaeyjar is\n",
      "hilo us\n",
      "hanzhong cn\n",
      "ankang cn\n",
      "riohacha co\n",
      "nikolskoye ru\n",
      "maragogi br\n",
      "wakkanai jp\n",
      "kodiak us\n",
      "palabuhanratu id\n",
      "busselton au\n",
      "rikitea pf\n",
      "tongzi cn\n",
      "flin flon ca\n",
      "jamestown sh\n",
      "olga ru\n",
      "butaritari ki\n",
      "los llanos de aridane es\n",
      "port alfred za\n",
      "nantucket us\n",
      "albany au\n",
      "grand river south east mu\n",
      "jabinyanah tn\n",
      "pangoa pe\n",
      "punta arenas cl\n",
      "albany au\n",
      "mataura pf\n",
      "russell nz\n",
      "bredasdorp za\n",
      "skalistyy ru\n",
      "provideniya ru\n",
      "severo-kurilsk ru\n",
      "gladstone au\n",
      "umm kaddadah sd\n",
      "ketchikan us\n",
      "punta arenas cl\n",
      "norman wells ca\n",
      "noumea nc\n",
      "longyearbyen sj\n",
      "doha kw\n",
      "minab ir\n",
      "kaitangata nz\n",
      "tilichiki ru\n",
      "stratford-upon-avon gb\n"
     ]
    }
   ],
   "source": [
    "# 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)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "610"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 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": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['devonport', 'hithadhoo', 'rikitea', 'ndiekro', 'new norfolk']"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cities[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "import requests\n",
    "from config import weather_api_key"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "http://api.openweathermap.org/data/2.5/weather?units=Imperial&APPID=81faf3d9cf1c8b964d442888fc6ed4be\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)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "http://api.openweathermap.org/data/2.5/weather?units=Imperial&APPID=81faf3d9cf1c8b964d442888fc6ed4be&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": 13,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Response [200]>"
      ]
     },
     "execution_count": 13,
     "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": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Response [404]>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create an endpoint URL for a city.\n",
    "city_url = url + \"&q=\" + \"Bston\"\n",
    "city_weather = requests.get(city_url)\n",
    "city_weather"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Response [200]>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\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": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'{\"coord\":{\"lon\":-71.0598,\"lat\":42.3584},\"weather\":[{\"id\":701,\"main\":\"Mist\",\"description\":\"mist\",\"icon\":\"50d\"}],\"base\":\"stations\",\"main\":{\"temp\":34.7,\"feels_like\":27.5,\"temp_min\":32,\"temp_max\":37,\"pressure\":1018,\"humidity\":80},\"visibility\":9656,\"wind\":{\"speed\":5.75,\"deg\":360},\"clouds\":{\"all\":40},\"dt\":1610717991,\"sys\":{\"type\":1,\"id\":3486,\"country\":\"US\",\"sunrise\":1610712635,\"sunset\":1610746590},\"timezone\":-18000,\"id\":4930956,\"name\":\"Boston\",\"cod\":200}'"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get the text of the 'Get' request.\n",
    "city_weather.text"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'coord': {'lon': -71.0598, 'lat': 42.3584},\n",
       " 'weather': [{'id': 701,\n",
       "   'main': 'Mist',\n",
       "   'description': 'mist',\n",
       "   'icon': '50d'}],\n",
       " 'base': 'stations',\n",
       " 'main': {'temp': 34.7,\n",
       "  'feels_like': 27.5,\n",
       "  'temp_min': 32,\n",
       "  'temp_max': 37,\n",
       "  'pressure': 1018,\n",
       "  'humidity': 80},\n",
       " 'visibility': 9656,\n",
       " 'wind': {'speed': 5.75, 'deg': 360},\n",
       " 'clouds': {'all': 40},\n",
       " 'dt': 1610717991,\n",
       " 'sys': {'type': 1,\n",
       "  'id': 3486,\n",
       "  'country': 'US',\n",
       "  'sunrise': 1610712635,\n",
       "  'sunset': 1610746590},\n",
       " 'timezone': -18000,\n",
       " 'id': 4930956,\n",
       " 'name': 'Boston',\n",
       " 'cod': 200}"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get the JSON text of the 'Get' request.\n",
    "city_weather.json()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "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": 19,
   "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=\" + \"Bston\"\n",
    "city_weather = requests.get(city_url)\n",
    "if city_weather.json():\n",
    "    print(f\"City Weather found.\")\n",
    "else:\n",
    "    print(f\"City weather not found.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'coord': {'lon': -71.0598, 'lat': 42.3584},\n",
       " 'weather': [{'id': 701,\n",
       "   'main': 'Mist',\n",
       "   'description': 'mist',\n",
       "   'icon': '50d'}],\n",
       " 'base': 'stations',\n",
       " 'main': {'temp': 34.7,\n",
       "  'feels_like': 27.5,\n",
       "  'temp_min': 32,\n",
       "  'temp_max': 37,\n",
       "  'pressure': 1018,\n",
       "  'humidity': 80},\n",
       " 'visibility': 9656,\n",
       " 'wind': {'speed': 5.75, 'deg': 360},\n",
       " 'clouds': {'all': 40},\n",
       " 'dt': 1610717991,\n",
       " 'sys': {'type': 1,\n",
       "  'id': 3486,\n",
       "  'country': 'US',\n",
       "  'sunrise': 1610712635,\n",
       "  'sunset': 1610746590},\n",
       " 'timezone': -18000,\n",
       " 'id': 4930956,\n",
       " 'name': 'Boston',\n",
       " 'cod': 200}"
      ]
     },
     "execution_count": 20,
     "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": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'coord': {'lon': -71.0598, 'lat': 42.3584},\n",
       " 'weather': [{'id': 701,\n",
       "   'main': 'Mist',\n",
       "   'description': 'mist',\n",
       "   'icon': '50d'}],\n",
       " 'base': 'stations',\n",
       " 'main': {'temp': 34.7,\n",
       "  'feels_like': 27.5,\n",
       "  'temp_min': 32,\n",
       "  'temp_max': 37,\n",
       "  'pressure': 1018,\n",
       "  'humidity': 80},\n",
       " 'visibility': 9656,\n",
       " 'wind': {'speed': 5.75, 'deg': 360},\n",
       " 'clouds': {'all': 40},\n",
       " 'dt': 1610717991,\n",
       " 'sys': {'type': 1,\n",
       "  'id': 3486,\n",
       "  'country': 'US',\n",
       "  'sunrise': 1610712635,\n",
       "  'sunset': 1610746590},\n",
       " 'timezone': -18000,\n",
       " 'id': 4930956,\n",
       " 'name': 'Boston',\n",
       " 'cod': 200}"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get the JSON data.\n",
    "boston_data = city_weather.json()\n",
    "boston_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'US'"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "boston_data[\"sys\"][\"country\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5.75"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "boston_data[\"wind\"][\"speed\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "42.3584 -71.0598 37 80 40 5.75\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, humidity, clouds, wind)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "datetime.datetime(2021, 1, 15, 13, 39, 51)"
      ]
     },
     "execution_count": 25,
     "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": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import the datetime module from the datetime library.\n",
    "from datetime import datetime"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Beginning Data Retrieval     \n",
      "-----------------------------\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",
    "\n",
    "# Create counters.\n",
    "record_count = 1\n",
    "set_count = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Loop through all the cities in our list.\n",
    "for i in range(len(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",
    "    # Create endpoint URL with each city.\n",
    "    city_url = url + \"&q=\" + cities[i]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Processing Record 1 of Set 13 | devonport\n",
      "Processing Record 2 of Set 13 | hithadhoo\n",
      "Processing Record 3 of Set 13 | rikitea\n",
      "Processing Record 4 of Set 13 | ndiekro\n",
      "Processing Record 5 of Set 13 | new norfolk\n",
      "Processing Record 6 of Set 13 | heze\n",
      "Processing Record 7 of Set 13 | saint-philippe\n",
      "Processing Record 8 of Set 13 | qaanaaq\n",
      "Processing Record 9 of Set 13 | torbay\n",
      "Processing Record 10 of Set 13 | castro\n",
      "Processing Record 11 of Set 13 | mataura\n",
      "Processing Record 12 of Set 13 | busselton\n",
      "Processing Record 13 of Set 13 | corn island\n",
      "Processing Record 14 of Set 13 | belushya guba\n",
      "Processing Record 15 of Set 13 | kapaa\n",
      "Processing Record 16 of Set 13 | gravdal\n",
      "Processing Record 17 of Set 13 | demmin\n",
      "Processing Record 18 of Set 13 | codrington\n",
      "Processing Record 19 of Set 13 | nikolskoye\n",
      "Processing Record 20 of Set 13 | punta arenas\n",
      "Processing Record 21 of Set 13 | simpang\n",
      "Processing Record 22 of Set 13 | peace river\n",
      "Processing Record 23 of Set 13 | merauke\n",
      "Processing Record 24 of Set 13 | vaini\n",
      "Processing Record 25 of Set 13 | barrow\n",
      "Processing Record 26 of Set 13 | haguenau\n",
      "Processing Record 27 of Set 13 | hushitai\n",
      "Processing Record 28 of Set 13 | port alfred\n",
      "Processing Record 29 of Set 13 | lufilufi\n",
      "Processing Record 30 of Set 13 | narsaq\n",
      "Processing Record 31 of Set 13 | vanavara\n",
      "Processing Record 32 of Set 13 | illoqqortoormiut\n",
      "Processing Record 33 of Set 13 | hermanus\n",
      "Processing Record 34 of Set 13 | mudon\n",
      "Processing Record 35 of Set 13 | huangnihe\n",
      "Processing Record 36 of Set 13 | komsomolskiy\n",
      "Processing Record 37 of Set 13 | mys shmidta\n",
      "Processing Record 38 of Set 13 | talawdi\n",
      "Processing Record 39 of Set 13 | comodoro rivadavia\n",
      "Processing Record 40 of Set 13 | bluff\n",
      "Processing Record 41 of Set 13 | kaitangata\n",
      "Processing Record 42 of Set 13 | samarai\n",
      "Processing Record 43 of Set 13 | garissa\n",
      "Processing Record 44 of Set 13 | karakendzha\n",
      "Processing Record 45 of Set 13 | sao filipe\n",
      "Processing Record 46 of Set 13 | coquimbo\n",
      "Processing Record 47 of Set 13 | meulaboh\n",
      "Processing Record 48 of Set 13 | urfa\n",
      "Processing Record 49 of Set 13 | westport\n",
      "Processing Record 50 of Set 13 | quebrada larga\n",
      "Processing Record 1 of Set 14 | kodiak\n",
      "Processing Record 2 of Set 14 | kieta\n",
      "Processing Record 3 of Set 14 | puerto ayora\n",
      "Processing Record 4 of Set 14 | isangel\n",
      "Processing Record 5 of Set 14 | bom sucesso\n",
      "Processing Record 6 of Set 14 | bredasdorp\n",
      "Processing Record 7 of Set 14 | karratha\n",
      "Processing Record 8 of Set 14 | yabelo\n",
      "Processing Record 9 of Set 14 | griffith\n",
      "Processing Record 10 of Set 14 | east london\n",
      "Processing Record 11 of Set 14 | kathu\n",
      "Processing Record 12 of Set 14 | pueblo nuevo\n",
      "Processing Record 13 of Set 14 | bengkulu\n",
      "Processing Record 14 of Set 14 | mahebourg\n",
      "Processing Record 15 of Set 14 | labutta\n",
      "Processing Record 16 of Set 14 | ranfurly\n",
      "Processing Record 17 of Set 14 | maceio\n",
      "Processing Record 18 of Set 14 | atlantis\n",
      "Processing Record 19 of Set 14 | ketchikan\n",
      "Processing Record 20 of Set 14 | takhtamygda\n",
      "Processing Record 21 of Set 14 | marcona\n",
      "Processing Record 22 of Set 14 | avarua\n",
      "Processing Record 23 of Set 14 | hofn\n",
      "Processing Record 24 of Set 14 | saint anthony\n",
      "Processing Record 25 of Set 14 | thompson\n",
      "Processing Record 26 of Set 14 | port hedland\n",
      "Processing Record 27 of Set 14 | mungwi\n",
      "Processing Record 28 of Set 14 | ribas do rio pardo\n",
      "Processing Record 29 of Set 14 | tuktoyaktuk\n",
      "Processing Record 30 of Set 14 | tuatapere\n",
      "Processing Record 31 of Set 14 | faanui\n",
      "Processing Record 32 of Set 14 | taolanaro\n",
      "Processing Record 33 of Set 14 | bathsheba\n",
      "Processing Record 34 of Set 14 | nabire\n",
      "Processing Record 35 of Set 14 | sfantu gheorghe\n",
      "Processing Record 36 of Set 14 | visnes\n",
      "Processing Record 37 of Set 14 | kavieng\n",
      "Processing Record 38 of Set 14 | kosonsoy\n",
      "Processing Record 39 of Set 14 | kavaratti\n",
      "Processing Record 40 of Set 14 | geraldton\n",
      "Processing Record 41 of Set 14 | saryshagan\n",
      "Processing Record 42 of Set 14 | goundam\n",
      "Processing Record 43 of Set 14 | murgasi\n",
      "Processing Record 44 of Set 14 | kamenka\n",
      "Processing Record 45 of Set 14 | pedernales\n",
      "Processing Record 46 of Set 14 | camacha\n",
      "Processing Record 47 of Set 14 | kahului\n",
      "Processing Record 48 of Set 14 | hobart\n",
      "Processing Record 49 of Set 14 | belmonte\n",
      "Processing Record 50 of Set 14 | petropavlovsk-kamchatskiy\n",
      "Processing Record 1 of Set 15 | dalbandin\n",
      "Processing Record 2 of Set 15 | cap-aux-meules\n",
      "Processing Record 3 of Set 15 | victoria\n",
      "Processing Record 4 of Set 15 | ondorhaan\n",
      "Processing Record 5 of Set 15 | jamestown\n",
      "Processing Record 6 of Set 15 | hamina\n",
      "Processing Record 7 of Set 15 | yellowknife\n",
      "Processing Record 8 of Set 15 | alta floresta\n",
      "Processing Record 9 of Set 15 | namatanai\n",
      "Processing Record 10 of Set 15 | fort nelson\n",
      "Processing Record 11 of Set 15 | cockburn town\n",
      "Processing Record 12 of Set 15 | carthage\n",
      "Processing Record 13 of Set 15 | greenville\n",
      "Processing Record 14 of Set 15 | houma\n",
      "Processing Record 15 of Set 15 | altay\n",
      "Processing Record 16 of Set 15 | mitu\n",
      "Processing Record 17 of Set 15 | nueva italia de ruiz\n",
      "Processing Record 18 of Set 15 | airai\n",
      "Processing Record 19 of Set 15 | blacksburg\n",
      "Processing Record 20 of Set 15 | machali\n",
      "Processing Record 21 of Set 15 | avera\n",
      "Processing Record 22 of Set 15 | hualmay\n",
      "Processing Record 23 of Set 15 | ponta do sol\n",
      "Processing Record 24 of Set 15 | saskylakh\n",
      "Processing Record 25 of Set 15 | nurota\n",
      "Processing Record 26 of Set 15 | swellendam\n",
      "Processing Record 27 of Set 15 | lebu\n",
      "Processing Record 28 of Set 15 | severo-kurilsk\n",
      "Processing Record 29 of Set 15 | moose factory\n",
      "Processing Record 30 of Set 15 | ushuaia\n",
      "Processing Record 31 of Set 15 | shikarpur\n",
      "Processing Record 32 of Set 15 | vao\n",
      "Processing Record 33 of Set 15 | langfang\n",
      "Processing Record 34 of Set 15 | clyde river\n",
      "Processing Record 35 of Set 15 | chokurdakh\n",
      "Processing Record 36 of Set 15 | balikpapan\n",
      "Processing Record 37 of Set 15 | bay city\n",
      "Processing Record 38 of Set 15 | mbuji-mayi\n",
      "Processing Record 39 of Set 15 | gushikawa\n",
      "Processing Record 40 of Set 15 | zelenoborsk\n",
      "Processing Record 41 of Set 15 | tupik\n",
      "Processing Record 42 of Set 15 | samusu\n",
      "Processing Record 43 of Set 15 | sao francisco do sul\n",
      "Processing Record 44 of Set 15 | bystrzyca klodzka\n",
      "Processing Record 45 of Set 15 | hilo\n",
      "Processing Record 46 of Set 15 | albany\n",
      "Processing Record 47 of Set 15 | high level\n",
      "Processing Record 48 of Set 15 | hamilton\n",
      "Processing Record 49 of Set 15 | margate\n",
      "Processing Record 50 of Set 15 | alice springs\n",
      "Processing Record 1 of Set 16 | aklavik\n",
      "Processing Record 2 of Set 16 | okhotsk\n",
      "Processing Record 3 of Set 16 | shitanjing\n",
      "Processing Record 4 of Set 16 | aflao\n",
      "Processing Record 5 of Set 16 | carnarvon\n",
      "Processing Record 6 of Set 16 | manggar\n",
      "Processing Record 7 of Set 16 | kudahuvadhoo\n",
      "Processing Record 8 of Set 16 | kerema\n",
      "Processing Record 9 of Set 16 | paradwip\n",
      "Processing Record 10 of Set 16 | dikson\n",
      "Processing Record 11 of Set 16 | aban\n",
      "Processing Record 12 of Set 16 | namibe\n",
      "Processing Record 13 of Set 16 | upernavik\n",
      "Processing Record 14 of Set 16 | college\n",
      "Processing Record 15 of Set 16 | gat\n",
      "Processing Record 16 of Set 16 | tyulgan\n",
      "Processing Record 17 of Set 16 | butaritari\n",
      "Processing Record 18 of Set 16 | chenghai\n",
      "Processing Record 19 of Set 16 | lishui\n",
      "Processing Record 20 of Set 16 | le port\n",
      "Processing Record 21 of Set 16 | wajima\n",
      "Processing Record 22 of Set 16 | manacor\n",
      "Processing Record 23 of Set 16 | lolua\n",
      "Processing Record 24 of Set 16 | laguna\n",
      "Processing Record 25 of Set 16 | auki\n",
      "Processing Record 26 of Set 16 | bilibino\n",
      "Processing Record 27 of Set 16 | saldanha\n",
      "Processing Record 28 of Set 16 | arraial do cabo\n",
      "Processing Record 29 of Set 16 | kurilsk\n",
      "Processing Record 30 of Set 16 | rawson\n",
      "Processing Record 31 of Set 16 | kupino\n",
      "Processing Record 32 of Set 16 | mizpe ramon\n",
      "Processing Record 33 of Set 16 | sao joao da barra\n",
      "Processing Record 34 of Set 16 | georgetown\n",
      "Processing Record 35 of Set 16 | lompoc\n",
      "Processing Record 36 of Set 16 | ixtapa\n",
      "Processing Record 37 of Set 16 | naze\n",
      "Processing Record 38 of Set 16 | jumla\n",
      "Processing Record 39 of Set 16 | pacific grove\n",
      "Processing Record 40 of Set 16 | astipalaia\n",
      "Processing Record 41 of Set 16 | atuona\n",
      "Processing Record 42 of Set 16 | mount gambier\n",
      "Processing Record 43 of Set 16 | yerbogachen\n",
      "Processing Record 44 of Set 16 | constitucion\n",
      "Processing Record 45 of Set 16 | isabela\n",
      "Processing Record 46 of Set 16 | sangar\n",
      "Processing Record 47 of Set 16 | birin\n",
      "Processing Record 48 of Set 16 | norman wells\n",
      "Processing Record 49 of Set 16 | bowen\n",
      "Processing Record 50 of Set 16 | aquiraz\n",
      "Processing Record 1 of Set 17 | khatanga\n",
      "Processing Record 2 of Set 17 | mar del plata\n",
      "Processing Record 3 of Set 17 | namestovo\n",
      "Processing Record 4 of Set 17 | ancud\n",
      "Processing Record 5 of Set 17 | padang\n",
      "Processing Record 6 of Set 17 | marzuq\n",
      "Processing Record 7 of Set 17 | haslett\n",
      "Processing Record 8 of Set 17 | tanete\n",
      "Processing Record 9 of Set 17 | barentsburg\n",
      "Processing Record 10 of Set 17 | mogadishu\n",
      "Processing Record 11 of Set 17 | pangnirtung\n",
      "Processing Record 12 of Set 17 | meyungs\n",
      "Processing Record 13 of Set 17 | port lincoln\n",
      "Processing Record 14 of Set 17 | mindelo\n",
      "Processing Record 15 of Set 17 | chebenki\n",
      "Processing Record 16 of Set 17 | olafsvik\n",
      "Processing Record 17 of Set 17 | turayf\n",
      "Processing Record 18 of Set 17 | tasiilaq\n",
      "Processing Record 19 of Set 17 | ribeira grande\n",
      "Processing Record 20 of Set 17 | poprad\n",
      "Processing Record 21 of Set 17 | pahuatlan\n",
      "Processing Record 22 of Set 17 | flinders\n",
      "Processing Record 23 of Set 17 | klaksvik\n",
      "Processing Record 24 of Set 17 | imbituba\n",
      "Processing Record 25 of Set 17 | luganville\n",
      "Processing Record 26 of Set 17 | sitka\n",
      "Processing Record 27 of Set 17 | la plaine\n",
      "Processing Record 28 of Set 17 | presidencia roque saenz pena\n",
      "Processing Record 29 of Set 17 | asfi\n",
      "Processing Record 30 of Set 17 | chuy\n",
      "Processing Record 31 of Set 17 | puerto del rosario\n",
      "Processing Record 32 of Set 17 | martapura\n",
      "Processing Record 33 of Set 17 | tura\n",
      "Processing Record 34 of Set 17 | attawapiskat\n",
      "Processing Record 35 of Set 17 | evensk\n",
      "Processing Record 36 of Set 17 | monte alegre\n",
      "Processing Record 37 of Set 17 | nehe\n",
      "Processing Record 38 of Set 17 | meihekou\n",
      "Processing Record 39 of Set 17 | guerrero negro\n",
      "Processing Record 40 of Set 17 | juneau\n",
      "Processing Record 41 of Set 17 | nizhneyansk\n",
      "Processing Record 42 of Set 17 | nanortalik\n",
      "Processing Record 43 of Set 17 | panyutyne\n",
      "Processing Record 44 of Set 17 | encruzilhada do sul\n",
      "Processing Record 45 of Set 17 | mets masrik\n",
      "Processing Record 46 of Set 17 | pochinki\n",
      "Processing Record 47 of Set 17 | hambantota\n",
      "Processing Record 48 of Set 17 | liverpool\n",
      "Processing Record 49 of Set 17 | puerto carreno\n",
      "Processing Record 50 of Set 17 | fairbanks\n",
      "Processing Record 1 of Set 18 | yarovoye\n",
      "Processing Record 2 of Set 18 | krasnokholm\n",
      "Processing Record 3 of Set 18 | tsihombe\n",
      "Processing Record 4 of Set 18 | chornukhy\n",
      "Processing Record 5 of Set 18 | ratnagiri\n",
      "Processing Record 6 of Set 18 | ostrovnoy\n",
      "Processing Record 7 of Set 18 | aljezur\n",
      "Processing Record 8 of Set 18 | san patricio\n",
      "Processing Record 9 of Set 18 | dashitou\n",
      "Processing Record 10 of Set 18 | zhezkazgan\n",
      "Processing Record 11 of Set 18 | louisbourg\n",
      "Processing Record 12 of Set 18 | lorengau\n",
      "Processing Record 13 of Set 18 | cape town\n",
      "Processing Record 14 of Set 18 | raudeberg\n",
      "Processing Record 15 of Set 18 | karabulak\n",
      "Processing Record 16 of Set 18 | hasaki\n",
      "Processing Record 17 of Set 18 | kharovsk\n",
      "Processing Record 18 of Set 18 | sept-iles\n",
      "Processing Record 19 of Set 18 | vila franca do campo\n",
      "Processing Record 20 of Set 18 | verkhnyaya inta\n",
      "Processing Record 21 of Set 18 | aflu\n",
      "Processing Record 22 of Set 18 | bethel\n",
      "Processing Record 23 of Set 18 | sechura\n",
      "Processing Record 24 of Set 18 | zhigansk\n",
      "Processing Record 25 of Set 18 | san policarpo\n",
      "Processing Record 26 of Set 18 | fort saint john\n",
      "Processing Record 27 of Set 18 | nioro\n",
      "Processing Record 28 of Set 18 | monrovia\n",
      "Processing Record 29 of Set 18 | ruidoso\n",
      "Processing Record 30 of Set 18 | bingol\n",
      "Processing Record 31 of Set 18 | praia da vitoria\n",
      "Processing Record 32 of Set 18 | jian\n",
      "Processing Record 33 of Set 18 | luderitz\n",
      "Processing Record 34 of Set 18 | san cristobal\n",
      "Processing Record 35 of Set 18 | sola\n",
      "Processing Record 36 of Set 18 | bambous virieux\n",
      "Processing Record 37 of Set 18 | ulladulla\n",
      "Processing Record 38 of Set 18 | samana\n",
      "Processing Record 39 of Set 18 | cherskiy\n",
      "Processing Record 40 of Set 18 | xingtai\n",
      "Processing Record 41 of Set 18 | pisco\n",
      "Processing Record 42 of Set 18 | filadelfia\n",
      "Processing Record 43 of Set 18 | waingapu\n",
      "Processing Record 44 of Set 18 | kumluca\n",
      "Processing Record 45 of Set 18 | yar-sale\n",
      "Processing Record 46 of Set 18 | touros\n",
      "Processing Record 47 of Set 18 | bury saint edmunds\n",
      "Processing Record 48 of Set 18 | westerly\n",
      "Processing Record 49 of Set 18 | esperance\n",
      "Processing Record 50 of Set 18 | mutsamudu\n",
      "Processing Record 1 of Set 19 | benalla\n",
      "Processing Record 2 of Set 19 | amderma\n",
      "Processing Record 3 of Set 19 | saint-leu\n",
      "Processing Record 4 of Set 19 | fortuna\n",
      "Processing Record 5 of Set 19 | adrar\n",
      "Processing Record 6 of Set 19 | khanpur\n",
      "Processing Record 7 of Set 19 | kruisfontein\n",
      "Processing Record 8 of Set 19 | kawalu\n",
      "Processing Record 9 of Set 19 | dingle\n",
      "Processing Record 10 of Set 19 | maningrida\n",
      "Processing Record 11 of Set 19 | berlevag\n",
      "Processing Record 12 of Set 19 | hami\n",
      "Processing Record 13 of Set 19 | muli\n",
      "Processing Record 14 of Set 19 | loding\n",
      "Processing Record 15 of Set 19 | mildura\n",
      "Processing Record 16 of Set 19 | miles city\n",
      "Processing Record 17 of Set 19 | arman\n",
      "Processing Record 18 of Set 19 | parnarama\n",
      "Processing Record 19 of Set 19 | saint-francois\n",
      "Processing Record 20 of Set 19 | kargasok\n",
      "Processing Record 21 of Set 19 | junin\n",
      "Processing Record 22 of Set 19 | toledo\n",
      "Processing Record 23 of Set 19 | nyurba\n",
      "Processing Record 24 of Set 19 | okandja\n",
      "Processing Record 25 of Set 19 | nador\n",
      "Processing Record 26 of Set 19 | salinas\n",
      "Processing Record 27 of Set 19 | suihua\n",
      "Processing Record 28 of Set 19 | lata\n",
      "Processing Record 29 of Set 19 | sungairaya\n",
      "Processing Record 30 of Set 19 | sulmona\n",
      "Processing Record 31 of Set 19 | tonantins\n",
      "Processing Record 32 of Set 19 | cabo san lucas\n",
      "Processing Record 33 of Set 19 | kenai\n",
      "Processing Record 34 of Set 19 | carlsbad\n",
      "Processing Record 35 of Set 19 | sentyabrskiy\n",
      "Processing Record 36 of Set 19 | wuwei\n",
      "Processing Record 37 of Set 19 | dudinka\n",
      "Processing Record 38 of Set 19 | kholtoson\n",
      "Processing Record 39 of Set 19 | anadyr\n",
      "Processing Record 40 of Set 19 | ventspils\n",
      "Processing Record 41 of Set 19 | katsuura\n",
      "Processing Record 42 of Set 19 | byron bay\n",
      "Processing Record 43 of Set 19 | green river\n",
      "Processing Record 44 of Set 19 | dolbeau\n",
      "Processing Record 45 of Set 19 | asandh\n",
      "Processing Record 46 of Set 19 | faya\n",
      "Processing Record 47 of Set 19 | chupa\n",
      "Processing Record 48 of Set 19 | tilichiki\n",
      "Processing Record 49 of Set 19 | ferme-neuve\n",
      "Processing Record 50 of Set 19 | souillac\n",
      "Processing Record 1 of Set 20 | vestmannaeyjar\n",
      "Processing Record 2 of Set 20 | tumannyy\n",
      "Processing Record 3 of Set 20 | springbok\n",
      "Processing Record 4 of Set 20 | albury\n",
      "Processing Record 5 of Set 20 | alexandria\n",
      "Processing Record 6 of Set 20 | dabou\n",
      "Processing Record 7 of Set 20 | beitbridge\n",
      "Processing Record 8 of Set 20 | pochutla\n",
      "Processing Record 9 of Set 20 | armidale\n",
      "Processing Record 10 of Set 20 | samdrup jongkhar\n",
      "Processing Record 11 of Set 20 | port keats\n",
      "Processing Record 12 of Set 20 | lamont\n",
      "Processing Record 13 of Set 20 | beyneu\n",
      "Processing Record 14 of Set 20 | nakhon sawan\n",
      "Processing Record 15 of Set 20 | duekoue\n",
      "Processing Record 16 of Set 20 | mlonggo\n",
      "Processing Record 17 of Set 20 | kuche\n",
      "Processing Record 18 of Set 20 | santiago del estero\n",
      "Processing Record 19 of Set 20 | rivadavia\n",
      "Processing Record 20 of Set 20 | palmer\n",
      "Processing Record 21 of Set 20 | alexander city\n",
      "Processing Record 22 of Set 20 | teguldet\n",
      "Processing Record 23 of Set 20 | lamia\n",
      "Processing Record 24 of Set 20 | chifeng\n",
      "Processing Record 25 of Set 20 | guaymas\n",
      "Processing Record 26 of Set 20 | houffalize\n",
      "Processing Record 27 of Set 20 | tiksi\n",
      "Processing Record 28 of Set 20 | zonguldak\n",
      "Processing Record 29 of Set 20 | sao felix do xingu\n",
      "Processing Record 30 of Set 20 | oistins\n",
      "Processing Record 31 of Set 20 | srednekolymsk\n",
      "Processing Record 32 of Set 20 | lasa\n",
      "Processing Record 33 of Set 20 | staryy nadym\n",
      "Processing Record 34 of Set 20 | sinop\n",
      "Processing Record 35 of Set 20 | taoudenni\n",
      "Processing Record 36 of Set 20 | nuristan\n",
      "Processing Record 37 of Set 20 | bonavista\n",
      "Processing Record 38 of Set 20 | tanah merah\n",
      "Processing Record 39 of Set 20 | rio grande\n",
      "Processing Record 40 of Set 20 | mbanza-ngungu\n",
      "Processing Record 41 of Set 20 | scottsburgh\n",
      "Processing Record 42 of Set 20 | kampot\n",
      "Processing Record 43 of Set 20 | tarauaca\n",
      "Processing Record 44 of Set 20 | salinopolis\n",
      "Processing Record 45 of Set 20 | tacuarembo\n",
      "Processing Record 46 of Set 20 | mahon\n",
      "Processing Record 47 of Set 20 | coos bay\n",
      "Processing Record 48 of Set 20 | alappuzha\n",
      "Processing Record 49 of Set 20 | brae\n",
      "Processing Record 50 of Set 20 | youkounkoun\n",
      "Processing Record 1 of Set 21 | bandarbeyla\n",
      "Processing Record 2 of Set 21 | teavaro\n",
      "Processing Record 3 of Set 21 | mount isa\n",
      "Processing Record 4 of Set 21 | pescara\n",
      "Processing Record 5 of Set 21 | aksarka\n",
      "Processing Record 6 of Set 21 | mandurah\n",
      "Processing Record 7 of Set 21 | jensen beach\n",
      "Processing Record 8 of Set 21 | sioux lookout\n",
      "Processing Record 9 of Set 21 | san pedro\n",
      "Processing Record 10 of Set 21 | lavrentiya\n",
      "Processing Record 11 of Set 21 | pierreville\n",
      "Processing Record 12 of Set 21 | islamkot\n",
      "Processing Record 13 of Set 21 | vaitupu\n",
      "Processing Record 14 of Set 21 | ayer itam\n",
      "Processing Record 15 of Set 21 | buerarema\n",
      "Processing Record 16 of Set 21 | denpasar\n",
      "Processing Record 17 of Set 21 | cabarroguis\n",
      "Processing Record 18 of Set 21 | praia\n",
      "Processing Record 19 of Set 21 | querendaro\n",
      "Processing Record 20 of Set 21 | manokwari\n",
      "Processing Record 21 of Set 21 | cabra\n",
      "Processing Record 22 of Set 21 | boras\n",
      "Processing Record 23 of Set 21 | los llanos de aridane\n",
      "Processing Record 24 of Set 21 | yulara\n",
      "Processing Record 25 of Set 21 | ouadda\n",
      "Processing Record 26 of Set 21 | yamethin\n",
      "Processing Record 27 of Set 21 | inongo\n",
      "Processing Record 28 of Set 21 | kangaba\n",
      "Processing Record 29 of Set 21 | vanimo\n",
      "Processing Record 30 of Set 21 | goderich\n",
      "Processing Record 31 of Set 21 | kollam\n",
      "Processing Record 32 of Set 21 | severnyy\n",
      "Processing Record 33 of Set 21 | sarakhs\n",
      "Processing Record 34 of Set 21 | saint-pierre\n",
      "Processing Record 35 of Set 21 | port hardy\n",
      "Processing Record 36 of Set 21 | carutapera\n",
      "Processing Record 37 of Set 21 | mecca\n",
      "Processing Record 38 of Set 21 | nur\n",
      "Processing Record 39 of Set 21 | coromandel\n",
      "Processing Record 40 of Set 21 | leningradskiy\n",
      "Processing Record 41 of Set 21 | ituni\n",
      "Processing Record 42 of Set 21 | mbandaka\n",
      "Processing Record 43 of Set 21 | manado\n",
      "Processing Record 44 of Set 21 | catamarca\n",
      "Processing Record 45 of Set 21 | dingli\n",
      "Processing Record 46 of Set 21 | camopi\n",
      "Processing Record 47 of Set 21 | shwebo\n",
      "Processing Record 48 of Set 21 | puerto madryn\n",
      "Processing Record 49 of Set 21 | shu\n",
      "Processing Record 50 of Set 21 | huaral\n",
      "Processing Record 1 of Set 22 | esso\n",
      "Processing Record 2 of Set 22 | quchan\n",
      "Processing Record 3 of Set 22 | siilinjarvi\n",
      "Processing Record 4 of Set 22 | vardo\n",
      "Processing Record 5 of Set 22 | mwanza\n",
      "Processing Record 6 of Set 22 | kulhudhuffushi\n",
      "Processing Record 7 of Set 22 | ipixuna\n",
      "Processing Record 8 of Set 22 | prieska\n",
      "Processing Record 9 of Set 22 | grand river south east\n",
      "Processing Record 10 of Set 22 | alofi\n",
      "Processing Record 11 of Set 22 | valdosta\n",
      "Processing Record 12 of Set 22 | hefei\n",
      "Processing Record 13 of Set 22 | newark\n",
      "Processing Record 14 of Set 22 | finschhafen\n",
      "Processing Record 15 of Set 22 | pizhanka\n",
      "Processing Record 16 of Set 22 | keetmanshoop\n",
      "Processing Record 17 of Set 22 | dondo\n",
      "Processing Record 18 of Set 22 | port elizabeth\n",
      "Processing Record 19 of Set 22 | acapulco\n",
      "Processing Record 20 of Set 22 | iralaya\n",
      "Processing Record 21 of Set 22 | galgani\n",
      "Processing Record 22 of Set 22 | villarrica\n",
      "Processing Record 23 of Set 22 | quatre cocos\n",
      "Processing Record 24 of Set 22 | general roca\n",
      "Processing Record 25 of Set 22 | hobyo\n",
      "Processing Record 26 of Set 22 | antofagasta\n",
      "Processing Record 27 of Set 22 | marsa matruh\n",
      "Processing Record 28 of Set 22 | baker city\n",
      "Processing Record 29 of Set 22 | bageshwar\n",
      "Processing Record 30 of Set 22 | cidreira\n",
      "Processing Record 31 of Set 22 | urucara\n",
      "Processing Record 32 of Set 22 | umzimvubu\n",
      "Processing Record 33 of Set 22 | moussoro\n",
      "Processing Record 34 of Set 22 | mehamn\n",
      "Processing Record 35 of Set 22 | pemangkat\n",
      "Processing Record 36 of Set 22 | salalah\n",
      "Processing Record 37 of Set 22 | dukat\n",
      "Processing Record 38 of Set 22 | coihaique\n",
      "Processing Record 39 of Set 22 | elk city\n",
      "Processing Record 40 of Set 22 | broome\n",
      "Processing Record 41 of Set 22 | marystown\n",
      "Processing Record 42 of Set 22 | marawi\n",
      "Processing Record 43 of Set 22 | burica\n",
      "Processing Record 44 of Set 22 | sur\n",
      "Processing Record 45 of Set 22 | hovd\n",
      "Processing Record 46 of Set 22 | merrill\n",
      "Processing Record 47 of Set 22 | homer\n",
      "Processing Record 48 of Set 22 | mardin\n",
      "Processing Record 49 of Set 22 | huoqiu\n",
      "Processing Record 50 of Set 22 | muscat\n",
      "Processing Record 1 of Set 23 | tromso\n",
      "Processing Record 2 of Set 23 | labuan\n",
      "Processing Record 3 of Set 23 | ust-shonosha\n",
      "Processing Record 4 of Set 23 | masalli\n",
      "Processing Record 5 of Set 23 | chadiza\n",
      "Processing Record 6 of Set 23 | keshabpur\n",
      "Processing Record 7 of Set 23 | port blair\n",
      "Processing Record 8 of Set 23 | the valley\n",
      "Processing Record 9 of Set 23 | liku\n",
      "Processing Record 10 of Set 23 | kaeo\n",
      "Processing Record 11 of Set 23 | burnie\n",
      "Processing Record 12 of Set 23 | tuapse\n",
      "Processing Record 13 of Set 23 | maltahohe\n",
      "Processing Record 14 of Set 23 | tofield\n",
      "Processing Record 15 of Set 23 | dekoa\n",
      "Processing Record 16 of Set 23 | longyearbyen\n",
      "Processing Record 17 of Set 23 | nome\n",
      "Processing Record 18 of Set 23 | novyye burasy\n",
      "Processing Record 19 of Set 23 | araceli\n",
      "Processing Record 20 of Set 23 | havre-saint-pierre\n",
      "Processing Record 21 of Set 23 | urusha\n",
      "Processing Record 22 of Set 23 | bad wurzach\n",
      "Processing Record 23 of Set 23 | kendari\n",
      "Processing Record 24 of Set 23 | egvekinot\n",
      "Processing Record 25 of Set 23 | takoradi\n",
      "Processing Record 26 of Set 23 | malanje\n",
      "Processing Record 27 of Set 23 | volosovo\n",
      "Processing Record 28 of Set 23 | lyuban\n",
      "Processing Record 29 of Set 23 | tigil\n",
      "Processing Record 30 of Set 23 | maniitsoq\n",
      "Processing Record 31 of Set 23 | pevek\n",
      "Processing Record 32 of Set 23 | caravelas\n",
      "Processing Record 33 of Set 23 | baherden\n",
      "Processing Record 34 of Set 23 | haines junction\n",
      "Processing Record 35 of Set 23 | halalo\n",
      "Processing Record 36 of Set 23 | pailon\n",
      "Processing Record 37 of Set 23 | fare\n",
      "Processing Record 38 of Set 23 | pyaozerskiy\n",
      "Processing Record 39 of Set 23 | ola\n",
      "Processing Record 40 of Set 23 | katherine\n",
      "Processing Record 41 of Set 23 | saint george\n",
      "Processing Record 42 of Set 23 | datong\n",
      "Processing Record 43 of Set 23 | doctor pedro p. pena\n",
      "Processing Record 44 of Set 23 | kosh-agach\n",
      "Processing Record 45 of Set 23 | bolungarvik\n",
      "Processing Record 46 of Set 23 | chardara\n",
      "Processing Record 47 of Set 23 | campo maior\n",
      "Processing Record 48 of Set 23 | kolobrzeg\n",
      "Processing Record 49 of Set 23 | sterling\n",
      "Processing Record 50 of Set 23 | kot samaba\n",
      "Processing Record 1 of Set 24 | hirara\n",
      "Processing Record 2 of Set 24 | ilulissat\n",
      "Processing Record 3 of Set 24 | san ramon\n",
      "Processing Record 4 of Set 24 | lillooet\n",
      "Processing Record 5 of Set 24 | richards bay\n",
      "Processing Record 6 of Set 24 | quepos\n",
      "Processing Record 7 of Set 24 | kushmurun\n",
      "Processing Record 8 of Set 24 | krasnyy yar\n",
      "Processing Record 9 of Set 24 | crib point\n",
      "Processing Record 10 of Set 24 | seydi\n",
      "Processing Record 11 of Set 24 | manzil tamim\n",
      "Processing Record 12 of Set 24 | saint-joseph\n",
      "Processing Record 13 of Set 24 | rincon\n",
      "Processing Record 14 of Set 24 | gazimurskiy zavod\n",
      "Processing Record 15 of Set 24 | karatau\n",
      "Processing Record 16 of Set 24 | dongzhen\n",
      "Processing Record 17 of Set 24 | pemba\n",
      "Processing Record 18 of Set 24 | matara\n",
      "Processing Record 19 of Set 24 | saint-augustin\n",
      "Processing Record 20 of Set 24 | siniscola\n",
      "Processing Record 21 of Set 24 | saryozek\n",
      "Processing Record 22 of Set 24 | rocha\n",
      "Processing Record 23 of Set 24 | krasnoyarsk-45\n",
      "Processing Record 24 of Set 24 | videira\n",
      "Processing Record 25 of Set 24 | labuhan\n",
      "Processing Record 26 of Set 24 | nichinan\n",
      "Processing Record 27 of Set 24 | vallenar\n",
      "Processing Record 28 of Set 24 | emerald\n",
      "Processing Record 29 of Set 24 | oranjemund\n",
      "Processing Record 30 of Set 24 | pombas\n",
      "Processing Record 31 of Set 24 | nuuk\n",
      "Processing Record 32 of Set 24 | ondangwa\n",
      "Processing Record 33 of Set 24 | fez\n",
      "Processing Record 34 of Set 24 | port macquarie\n",
      "Processing Record 35 of Set 24 | voyinka\n",
      "Processing Record 36 of Set 24 | mount pleasant\n",
      "Processing Record 37 of Set 24 | cascais\n",
      "Processing Record 38 of Set 24 | ixtlahuacan del rio\n",
      "Processing Record 39 of Set 24 | ternate\n",
      "Processing Record 40 of Set 24 | hanzhong\n",
      "Processing Record 41 of Set 24 | ankang\n",
      "Processing Record 42 of Set 24 | riohacha\n",
      "Processing Record 43 of Set 24 | maragogi\n",
      "Processing Record 44 of Set 24 | wakkanai\n",
      "Processing Record 45 of Set 24 | palabuhanratu\n",
      "Processing Record 46 of Set 24 | tongzi\n",
      "Processing Record 47 of Set 24 | flin flon\n",
      "Processing Record 48 of Set 24 | olga\n",
      "Processing Record 49 of Set 24 | nantucket\n",
      "Processing Record 50 of Set 24 | jabinyanah\n",
      "Processing Record 1 of Set 25 | pangoa\n",
      "Processing Record 2 of Set 25 | russell\n",
      "Processing Record 3 of Set 25 | skalistyy\n",
      "Processing Record 4 of Set 25 | provideniya\n",
      "Processing Record 5 of Set 25 | gladstone\n",
      "Processing Record 6 of Set 25 | umm kaddadah\n",
      "Processing Record 7 of Set 25 | noumea\n",
      "Processing Record 8 of Set 25 | doha\n",
      "Processing Record 9 of Set 25 | minab\n",
      "Processing Record 10 of Set 25 | stratford-upon-avon\n"
     ]
    }
   ],
   "source": [
    "# Loop through all the cities in our list.\n",
    "for i in range(len(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",
    "    # Create endpoint URL with each city.\n",
    "    city_url = url + \"&q=\" + cities[i]# Loop through all the cities in our list.\n",
    "for i in range(len(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",
    "    # Create endpoint URL with each city.\n",
    "    city_url = url + \"&q=\" + cities[i]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Processing Record 11 of Set 25 | devonport\n",
      "Processing Record 12 of Set 25 | hithadhoo\n",
      "Processing Record 13 of Set 25 | rikitea\n",
      "Processing Record 14 of Set 25 | ndiekro\n",
      "City not found. Skipping...\n",
      "Processing Record 15 of Set 25 | new norfolk\n",
      "Processing Record 16 of Set 25 | heze\n",
      "Processing Record 17 of Set 25 | saint-philippe\n",
      "Processing Record 18 of Set 25 | qaanaaq\n",
      "Processing Record 19 of Set 25 | torbay\n",
      "Processing Record 20 of Set 25 | castro\n",
      "Processing Record 21 of Set 25 | mataura\n",
      "Processing Record 22 of Set 25 | busselton\n",
      "Processing Record 23 of Set 25 | corn island\n",
      "Processing Record 24 of Set 25 | belushya guba\n",
      "City not found. Skipping...\n",
      "Processing Record 25 of Set 25 | kapaa\n",
      "Processing Record 26 of Set 25 | gravdal\n",
      "Processing Record 27 of Set 25 | demmin\n",
      "Processing Record 28 of Set 25 | codrington\n",
      "Processing Record 29 of Set 25 | nikolskoye\n",
      "Processing Record 30 of Set 25 | punta arenas\n",
      "Processing Record 31 of Set 25 | simpang\n",
      "Processing Record 32 of Set 25 | peace river\n",
      "Processing Record 33 of Set 25 | merauke\n",
      "Processing Record 34 of Set 25 | vaini\n",
      "Processing Record 35 of Set 25 | barrow\n",
      "Processing Record 36 of Set 25 | haguenau\n",
      "Processing Record 37 of Set 25 | hushitai\n",
      "Processing Record 38 of Set 25 | port alfred\n",
      "Processing Record 39 of Set 25 | lufilufi\n",
      "Processing Record 40 of Set 25 | narsaq\n",
      "Processing Record 41 of Set 25 | vanavara\n",
      "Processing Record 42 of Set 25 | illoqqortoormiut\n",
      "City not found. Skipping...\n",
      "Processing Record 43 of Set 25 | hermanus\n",
      "Processing Record 44 of Set 25 | mudon\n",
      "Processing Record 45 of Set 25 | huangnihe\n",
      "Processing Record 46 of Set 25 | komsomolskiy\n",
      "Processing Record 47 of Set 25 | mys shmidta\n",
      "City not found. Skipping...\n",
      "Processing Record 48 of Set 25 | talawdi\n",
      "City not found. Skipping...\n",
      "Processing Record 49 of Set 25 | comodoro rivadavia\n",
      "Processing Record 50 of Set 25 | bluff\n",
      "Processing Record 51 of Set 25 | kaitangata\n",
      "Processing Record 52 of Set 25 | samarai\n",
      "Processing Record 53 of Set 25 | garissa\n",
      "Processing Record 54 of Set 25 | karakendzha\n",
      "City not found. Skipping...\n",
      "Processing Record 55 of Set 25 | sao filipe\n",
      "Processing Record 56 of Set 25 | coquimbo\n",
      "Processing Record 57 of Set 25 | meulaboh\n",
      "Processing Record 58 of Set 25 | urfa\n",
      "City not found. Skipping...\n",
      "Processing Record 59 of Set 25 | westport\n",
      "Processing Record 60 of Set 25 | quebrada larga\n",
      "Processing Record 1 of Set 26 | kodiak\n",
      "Processing Record 2 of Set 26 | kieta\n",
      "Processing Record 3 of Set 26 | puerto ayora\n",
      "Processing Record 4 of Set 26 | isangel\n",
      "Processing Record 5 of Set 26 | bom sucesso\n",
      "Processing Record 6 of Set 26 | bredasdorp\n",
      "Processing Record 7 of Set 26 | karratha\n",
      "Processing Record 8 of Set 26 | yabelo\n",
      "Processing Record 9 of Set 26 | griffith\n",
      "Processing Record 10 of Set 26 | east london\n",
      "Processing Record 11 of Set 26 | kathu\n",
      "Processing Record 12 of Set 26 | pueblo nuevo\n",
      "Processing Record 13 of Set 26 | bengkulu\n",
      "Processing Record 14 of Set 26 | mahebourg\n",
      "Processing Record 15 of Set 26 | labutta\n",
      "City not found. Skipping...\n",
      "Processing Record 16 of Set 26 | ranfurly\n",
      "Processing Record 17 of Set 26 | maceio\n",
      "Processing Record 18 of Set 26 | atlantis\n",
      "Processing Record 19 of Set 26 | ketchikan\n",
      "Processing Record 20 of Set 26 | takhtamygda\n",
      "Processing Record 21 of Set 26 | marcona\n",
      "City not found. Skipping...\n",
      "Processing Record 22 of Set 26 | avarua\n",
      "Processing Record 23 of Set 26 | hofn\n",
      "Processing Record 24 of Set 26 | saint anthony\n",
      "Processing Record 25 of Set 26 | thompson\n",
      "Processing Record 26 of Set 26 | port hedland\n",
      "Processing Record 27 of Set 26 | mungwi\n",
      "Processing Record 28 of Set 26 | ribas do rio pardo\n",
      "Processing Record 29 of Set 26 | tuktoyaktuk\n",
      "Processing Record 30 of Set 26 | tuatapere\n",
      "Processing Record 31 of Set 26 | faanui\n",
      "Processing Record 32 of Set 26 | taolanaro\n",
      "City not found. Skipping...\n",
      "Processing Record 33 of Set 26 | bathsheba\n",
      "Processing Record 34 of Set 26 | nabire\n",
      "Processing Record 35 of Set 26 | sfantu gheorghe\n",
      "Processing Record 36 of Set 26 | visnes\n",
      "Processing Record 37 of Set 26 | kavieng\n",
      "Processing Record 38 of Set 26 | kosonsoy\n",
      "Processing Record 39 of Set 26 | kavaratti\n",
      "Processing Record 40 of Set 26 | geraldton\n",
      "Processing Record 41 of Set 26 | saryshagan\n",
      "City not found. Skipping...\n",
      "Processing Record 42 of Set 26 | goundam\n",
      "Processing Record 43 of Set 26 | murgasi\n",
      "City not found. Skipping...\n",
      "Processing Record 44 of Set 26 | kamenka\n",
      "Processing Record 45 of Set 26 | pedernales\n",
      "Processing Record 46 of Set 26 | camacha\n",
      "Processing Record 47 of Set 26 | kahului\n",
      "Processing Record 48 of Set 26 | hobart\n",
      "Processing Record 49 of Set 26 | belmonte\n",
      "Processing Record 50 of Set 26 | petropavlovsk-kamchatskiy\n",
      "Processing Record 1 of Set 27 | dalbandin\n",
      "Processing Record 2 of Set 27 | cap-aux-meules\n",
      "Processing Record 3 of Set 27 | victoria\n",
      "Processing Record 4 of Set 27 | ondorhaan\n",
      "City not found. Skipping...\n",
      "Processing Record 5 of Set 27 | jamestown\n",
      "Processing Record 6 of Set 27 | hamina\n",
      "Processing Record 7 of Set 27 | yellowknife\n",
      "Processing Record 8 of Set 27 | alta floresta\n",
      "Processing Record 9 of Set 27 | namatanai\n",
      "Processing Record 10 of Set 27 | fort nelson\n",
      "Processing Record 11 of Set 27 | cockburn town\n",
      "Processing Record 12 of Set 27 | carthage\n",
      "Processing Record 13 of Set 27 | greenville\n",
      "Processing Record 14 of Set 27 | houma\n",
      "Processing Record 15 of Set 27 | altay\n",
      "Processing Record 16 of Set 27 | mitu\n",
      "Processing Record 17 of Set 27 | nueva italia de ruiz\n",
      "Processing Record 18 of Set 27 | airai\n",
      "Processing Record 19 of Set 27 | blacksburg\n",
      "Processing Record 20 of Set 27 | machali\n",
      "Processing Record 21 of Set 27 | avera\n",
      "Processing Record 22 of Set 27 | hualmay\n",
      "Processing Record 23 of Set 27 | ponta do sol\n",
      "Processing Record 24 of Set 27 | saskylakh\n",
      "Processing Record 25 of Set 27 | nurota\n",
      "Processing Record 26 of Set 27 | swellendam\n",
      "Processing Record 27 of Set 27 | lebu\n",
      "Processing Record 28 of Set 27 | severo-kurilsk\n",
      "Processing Record 29 of Set 27 | moose factory\n",
      "Processing Record 30 of Set 27 | ushuaia\n",
      "Processing Record 31 of Set 27 | shikarpur\n",
      "Processing Record 32 of Set 27 | vao\n",
      "Processing Record 33 of Set 27 | langfang\n",
      "Processing Record 34 of Set 27 | clyde river\n",
      "Processing Record 35 of Set 27 | chokurdakh\n",
      "Processing Record 36 of Set 27 | balikpapan\n",
      "Processing Record 37 of Set 27 | bay city\n",
      "Processing Record 38 of Set 27 | mbuji-mayi\n",
      "Processing Record 39 of Set 27 | gushikawa\n",
      "Processing Record 40 of Set 27 | zelenoborsk\n",
      "Processing Record 41 of Set 27 | tupik\n",
      "Processing Record 42 of Set 27 | samusu\n",
      "City not found. Skipping...\n",
      "Processing Record 43 of Set 27 | sao francisco do sul\n",
      "Processing Record 44 of Set 27 | bystrzyca klodzka\n",
      "Processing Record 45 of Set 27 | hilo\n",
      "Processing Record 46 of Set 27 | albany\n",
      "Processing Record 47 of Set 27 | high level\n",
      "Processing Record 48 of Set 27 | hamilton\n",
      "Processing Record 49 of Set 27 | margate\n",
      "Processing Record 50 of Set 27 | alice springs\n",
      "Processing Record 1 of Set 28 | aklavik\n",
      "Processing Record 2 of Set 28 | okhotsk\n",
      "Processing Record 3 of Set 28 | shitanjing\n",
      "Processing Record 4 of Set 28 | aflao\n",
      "Processing Record 5 of Set 28 | carnarvon\n",
      "Processing Record 6 of Set 28 | manggar\n",
      "Processing Record 7 of Set 28 | kudahuvadhoo\n",
      "Processing Record 8 of Set 28 | kerema\n",
      "Processing Record 9 of Set 28 | paradwip\n",
      "City not found. Skipping...\n",
      "Processing Record 10 of Set 28 | dikson\n",
      "Processing Record 11 of Set 28 | aban\n",
      "Processing Record 12 of Set 28 | namibe\n",
      "Processing Record 13 of Set 28 | upernavik\n",
      "Processing Record 14 of Set 28 | college\n",
      "Processing Record 15 of Set 28 | gat\n",
      "Processing Record 16 of Set 28 | tyulgan\n",
      "Processing Record 17 of Set 28 | butaritari\n",
      "Processing Record 18 of Set 28 | chenghai\n",
      "Processing Record 19 of Set 28 | lishui\n",
      "Processing Record 20 of Set 28 | le port\n",
      "Processing Record 21 of Set 28 | wajima\n",
      "Processing Record 22 of Set 28 | manacor\n",
      "Processing Record 23 of Set 28 | lolua\n",
      "City not found. Skipping...\n",
      "Processing Record 24 of Set 28 | laguna\n",
      "Processing Record 25 of Set 28 | auki\n",
      "Processing Record 26 of Set 28 | bilibino\n",
      "Processing Record 27 of Set 28 | saldanha\n",
      "Processing Record 28 of Set 28 | arraial do cabo\n",
      "Processing Record 29 of Set 28 | kurilsk\n",
      "Processing Record 30 of Set 28 | rawson\n",
      "Processing Record 31 of Set 28 | kupino\n",
      "Processing Record 32 of Set 28 | mizpe ramon\n",
      "City not found. Skipping...\n",
      "Processing Record 33 of Set 28 | sao joao da barra\n",
      "Processing Record 34 of Set 28 | georgetown\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Processing Record 35 of Set 28 | lompoc\n",
      "Processing Record 36 of Set 28 | ixtapa\n",
      "Processing Record 37 of Set 28 | naze\n",
      "Processing Record 38 of Set 28 | jumla\n",
      "Processing Record 39 of Set 28 | pacific grove\n",
      "Processing Record 40 of Set 28 | astipalaia\n",
      "City not found. Skipping...\n",
      "Processing Record 41 of Set 28 | atuona\n",
      "Processing Record 42 of Set 28 | mount gambier\n",
      "Processing Record 43 of Set 28 | yerbogachen\n",
      "Processing Record 44 of Set 28 | constitucion\n",
      "Processing Record 45 of Set 28 | isabela\n",
      "Processing Record 46 of Set 28 | sangar\n",
      "Processing Record 47 of Set 28 | birin\n",
      "Processing Record 48 of Set 28 | norman wells\n",
      "Processing Record 49 of Set 28 | bowen\n",
      "Processing Record 50 of Set 28 | aquiraz\n",
      "Processing Record 1 of Set 29 | khatanga\n",
      "Processing Record 2 of Set 29 | mar del plata\n",
      "Processing Record 3 of Set 29 | namestovo\n",
      "Processing Record 4 of Set 29 | ancud\n",
      "Processing Record 5 of Set 29 | padang\n",
      "Processing Record 6 of Set 29 | marzuq\n",
      "Processing Record 7 of Set 29 | haslett\n",
      "Processing Record 8 of Set 29 | tanete\n",
      "Processing Record 9 of Set 29 | barentsburg\n",
      "City not found. Skipping...\n",
      "Processing Record 10 of Set 29 | mogadishu\n",
      "Processing Record 11 of Set 29 | pangnirtung\n",
      "Processing Record 12 of Set 29 | meyungs\n",
      "City not found. Skipping...\n",
      "Processing Record 13 of Set 29 | port lincoln\n",
      "Processing Record 14 of Set 29 | mindelo\n",
      "Processing Record 15 of Set 29 | chebenki\n",
      "Processing Record 16 of Set 29 | olafsvik\n",
      "Processing Record 17 of Set 29 | turayf\n",
      "Processing Record 18 of Set 29 | tasiilaq\n",
      "Processing Record 19 of Set 29 | ribeira grande\n",
      "Processing Record 20 of Set 29 | poprad\n",
      "Processing Record 21 of Set 29 | pahuatlan\n",
      "City not found. Skipping...\n",
      "Processing Record 22 of Set 29 | flinders\n",
      "Processing Record 23 of Set 29 | klaksvik\n",
      "Processing Record 24 of Set 29 | imbituba\n",
      "Processing Record 25 of Set 29 | luganville\n",
      "Processing Record 26 of Set 29 | sitka\n",
      "Processing Record 27 of Set 29 | la plaine\n",
      "Processing Record 28 of Set 29 | presidencia roque saenz pena\n",
      "Processing Record 29 of Set 29 | asfi\n",
      "Processing Record 30 of Set 29 | chuy\n",
      "Processing Record 31 of Set 29 | puerto del rosario\n",
      "Processing Record 32 of Set 29 | martapura\n",
      "Processing Record 33 of Set 29 | tura\n",
      "Processing Record 34 of Set 29 | attawapiskat\n",
      "City not found. Skipping...\n",
      "Processing Record 35 of Set 29 | evensk\n",
      "Processing Record 36 of Set 29 | monte alegre\n",
      "Processing Record 37 of Set 29 | nehe\n",
      "Processing Record 38 of Set 29 | meihekou\n",
      "Processing Record 39 of Set 29 | guerrero negro\n",
      "Processing Record 40 of Set 29 | juneau\n",
      "Processing Record 41 of Set 29 | nizhneyansk\n",
      "City not found. Skipping...\n",
      "Processing Record 42 of Set 29 | nanortalik\n",
      "Processing Record 43 of Set 29 | panyutyne\n",
      "Processing Record 44 of Set 29 | encruzilhada do sul\n",
      "Processing Record 45 of Set 29 | mets masrik\n",
      "Processing Record 46 of Set 29 | pochinki\n",
      "Processing Record 47 of Set 29 | hambantota\n",
      "Processing Record 48 of Set 29 | liverpool\n",
      "Processing Record 49 of Set 29 | puerto carreno\n",
      "Processing Record 50 of Set 29 | fairbanks\n",
      "Processing Record 1 of Set 30 | yarovoye\n",
      "Processing Record 2 of Set 30 | krasnokholm\n",
      "Processing Record 3 of Set 30 | tsihombe\n",
      "City not found. Skipping...\n",
      "Processing Record 4 of Set 30 | chornukhy\n",
      "Processing Record 5 of Set 30 | ratnagiri\n",
      "Processing Record 6 of Set 30 | ostrovnoy\n",
      "Processing Record 7 of Set 30 | aljezur\n",
      "Processing Record 8 of Set 30 | san patricio\n",
      "Processing Record 9 of Set 30 | dashitou\n",
      "Processing Record 10 of Set 30 | zhezkazgan\n",
      "Processing Record 11 of Set 30 | louisbourg\n",
      "City not found. Skipping...\n",
      "Processing Record 12 of Set 30 | lorengau\n",
      "Processing Record 13 of Set 30 | cape town\n",
      "Processing Record 14 of Set 30 | raudeberg\n",
      "Processing Record 15 of Set 30 | karabulak\n",
      "Processing Record 16 of Set 30 | hasaki\n",
      "Processing Record 17 of Set 30 | kharovsk\n",
      "Processing Record 18 of Set 30 | sept-iles\n",
      "Processing Record 19 of Set 30 | vila franca do campo\n",
      "Processing Record 20 of Set 30 | verkhnyaya inta\n",
      "Processing Record 21 of Set 30 | aflu\n",
      "City not found. Skipping...\n",
      "Processing Record 22 of Set 30 | bethel\n",
      "Processing Record 23 of Set 30 | sechura\n",
      "Processing Record 24 of Set 30 | zhigansk\n",
      "Processing Record 25 of Set 30 | san policarpo\n",
      "Processing Record 26 of Set 30 | fort saint john\n",
      "City not found. Skipping...\n",
      "Processing Record 27 of Set 30 | nioro\n",
      "Processing Record 28 of Set 30 | monrovia\n",
      "Processing Record 29 of Set 30 | ruidoso\n",
      "Processing Record 30 of Set 30 | bingol\n",
      "Processing Record 31 of Set 30 | praia da vitoria\n",
      "Processing Record 32 of Set 30 | jian\n",
      "Processing Record 33 of Set 30 | luderitz\n",
      "Processing Record 34 of Set 30 | san cristobal\n",
      "Processing Record 35 of Set 30 | sola\n",
      "Processing Record 36 of Set 30 | bambous virieux\n",
      "Processing Record 37 of Set 30 | ulladulla\n",
      "Processing Record 38 of Set 30 | samana\n",
      "Processing Record 39 of Set 30 | cherskiy\n",
      "Processing Record 40 of Set 30 | xingtai\n",
      "Processing Record 41 of Set 30 | pisco\n",
      "Processing Record 42 of Set 30 | filadelfia\n",
      "Processing Record 43 of Set 30 | waingapu\n",
      "Processing Record 44 of Set 30 | kumluca\n",
      "Processing Record 45 of Set 30 | yar-sale\n",
      "Processing Record 46 of Set 30 | touros\n",
      "Processing Record 47 of Set 30 | bury saint edmunds\n",
      "City not found. Skipping...\n",
      "Processing Record 48 of Set 30 | westerly\n",
      "Processing Record 49 of Set 30 | esperance\n",
      "Processing Record 50 of Set 30 | mutsamudu\n",
      "City not found. Skipping...\n",
      "Processing Record 1 of Set 31 | benalla\n",
      "Processing Record 2 of Set 31 | amderma\n",
      "City not found. Skipping...\n",
      "Processing Record 3 of Set 31 | saint-leu\n",
      "Processing Record 4 of Set 31 | fortuna\n",
      "Processing Record 5 of Set 31 | adrar\n",
      "Processing Record 6 of Set 31 | khanpur\n",
      "Processing Record 7 of Set 31 | kruisfontein\n",
      "Processing Record 8 of Set 31 | kawalu\n",
      "Processing Record 9 of Set 31 | dingle\n",
      "Processing Record 10 of Set 31 | maningrida\n",
      "Processing Record 11 of Set 31 | berlevag\n",
      "Processing Record 12 of Set 31 | hami\n",
      "Processing Record 13 of Set 31 | muli\n",
      "Processing Record 14 of Set 31 | loding\n",
      "Processing Record 15 of Set 31 | mildura\n",
      "Processing Record 16 of Set 31 | miles city\n",
      "Processing Record 17 of Set 31 | arman\n",
      "Processing Record 18 of Set 31 | parnarama\n",
      "Processing Record 19 of Set 31 | saint-francois\n",
      "Processing Record 20 of Set 31 | kargasok\n",
      "Processing Record 21 of Set 31 | junin\n",
      "Processing Record 22 of Set 31 | toledo\n",
      "Processing Record 23 of Set 31 | nyurba\n",
      "Processing Record 24 of Set 31 | okandja\n",
      "City not found. Skipping...\n",
      "Processing Record 25 of Set 31 | nador\n",
      "Processing Record 26 of Set 31 | salinas\n",
      "Processing Record 27 of Set 31 | suihua\n",
      "Processing Record 28 of Set 31 | lata\n",
      "Processing Record 29 of Set 31 | sungairaya\n",
      "Processing Record 30 of Set 31 | sulmona\n",
      "Processing Record 31 of Set 31 | tonantins\n",
      "Processing Record 32 of Set 31 | cabo san lucas\n",
      "Processing Record 33 of Set 31 | kenai\n",
      "Processing Record 34 of Set 31 | carlsbad\n",
      "Processing Record 35 of Set 31 | sentyabrskiy\n",
      "City not found. Skipping...\n",
      "Processing Record 36 of Set 31 | wuwei\n",
      "Processing Record 37 of Set 31 | dudinka\n",
      "Processing Record 38 of Set 31 | kholtoson\n",
      "Processing Record 39 of Set 31 | anadyr\n",
      "Processing Record 40 of Set 31 | ventspils\n",
      "Processing Record 41 of Set 31 | katsuura\n",
      "Processing Record 42 of Set 31 | byron bay\n",
      "Processing Record 43 of Set 31 | green river\n",
      "Processing Record 44 of Set 31 | dolbeau\n",
      "City not found. Skipping...\n",
      "Processing Record 45 of Set 31 | asandh\n",
      "Processing Record 46 of Set 31 | faya\n",
      "Processing Record 47 of Set 31 | chupa\n",
      "Processing Record 48 of Set 31 | tilichiki\n",
      "Processing Record 49 of Set 31 | ferme-neuve\n",
      "Processing Record 50 of Set 31 | souillac\n",
      "Processing Record 1 of Set 32 | vestmannaeyjar\n",
      "Processing Record 2 of Set 32 | tumannyy\n",
      "City not found. Skipping...\n",
      "Processing Record 3 of Set 32 | springbok\n",
      "Processing Record 4 of Set 32 | albury\n",
      "Processing Record 5 of Set 32 | alexandria\n",
      "Processing Record 6 of Set 32 | dabou\n",
      "Processing Record 7 of Set 32 | beitbridge\n",
      "Processing Record 8 of Set 32 | pochutla\n",
      "Processing Record 9 of Set 32 | armidale\n",
      "Processing Record 10 of Set 32 | samdrup jongkhar\n",
      "Processing Record 11 of Set 32 | port keats\n",
      "Processing Record 12 of Set 32 | lamont\n",
      "Processing Record 13 of Set 32 | beyneu\n",
      "Processing Record 14 of Set 32 | nakhon sawan\n",
      "Processing Record 15 of Set 32 | duekoue\n",
      "Processing Record 16 of Set 32 | mlonggo\n",
      "Processing Record 17 of Set 32 | kuche\n",
      "City not found. Skipping...\n",
      "Processing Record 18 of Set 32 | santiago del estero\n",
      "Processing Record 19 of Set 32 | rivadavia\n",
      "Processing Record 20 of Set 32 | palmer\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Processing Record 21 of Set 32 | alexander city\n",
      "Processing Record 22 of Set 32 | teguldet\n",
      "Processing Record 23 of Set 32 | lamia\n",
      "Processing Record 24 of Set 32 | chifeng\n",
      "Processing Record 25 of Set 32 | guaymas\n",
      "Processing Record 26 of Set 32 | houffalize\n",
      "Processing Record 27 of Set 32 | tiksi\n",
      "Processing Record 28 of Set 32 | zonguldak\n",
      "Processing Record 29 of Set 32 | sao felix do xingu\n",
      "Processing Record 30 of Set 32 | oistins\n",
      "Processing Record 31 of Set 32 | srednekolymsk\n",
      "Processing Record 32 of Set 32 | lasa\n",
      "Processing Record 33 of Set 32 | staryy nadym\n",
      "Processing Record 34 of Set 32 | sinop\n",
      "Processing Record 35 of Set 32 | taoudenni\n",
      "Processing Record 36 of Set 32 | nuristan\n",
      "Processing Record 37 of Set 32 | bonavista\n",
      "Processing Record 38 of Set 32 | tanah merah\n",
      "Processing Record 39 of Set 32 | rio grande\n",
      "Processing Record 40 of Set 32 | mbanza-ngungu\n",
      "Processing Record 41 of Set 32 | scottsburgh\n",
      "City not found. Skipping...\n",
      "Processing Record 42 of Set 32 | kampot\n",
      "Processing Record 43 of Set 32 | tarauaca\n",
      "Processing Record 44 of Set 32 | salinopolis\n",
      "Processing Record 45 of Set 32 | tacuarembo\n",
      "Processing Record 46 of Set 32 | mahon\n",
      "Processing Record 47 of Set 32 | coos bay\n",
      "Processing Record 48 of Set 32 | alappuzha\n",
      "Processing Record 49 of Set 32 | brae\n",
      "Processing Record 50 of Set 32 | youkounkoun\n",
      "Processing Record 1 of Set 33 | bandarbeyla\n",
      "Processing Record 2 of Set 33 | teavaro\n",
      "Processing Record 3 of Set 33 | mount isa\n",
      "Processing Record 4 of Set 33 | pescara\n",
      "Processing Record 5 of Set 33 | aksarka\n",
      "Processing Record 6 of Set 33 | mandurah\n",
      "Processing Record 7 of Set 33 | jensen beach\n",
      "Processing Record 8 of Set 33 | sioux lookout\n",
      "Processing Record 9 of Set 33 | san pedro\n",
      "Processing Record 10 of Set 33 | lavrentiya\n",
      "Processing Record 11 of Set 33 | pierreville\n",
      "Processing Record 12 of Set 33 | islamkot\n",
      "Processing Record 13 of Set 33 | vaitupu\n",
      "City not found. Skipping...\n",
      "Processing Record 14 of Set 33 | ayer itam\n",
      "City not found. Skipping...\n",
      "Processing Record 15 of Set 33 | buerarema\n",
      "Processing Record 16 of Set 33 | denpasar\n",
      "Processing Record 17 of Set 33 | cabarroguis\n",
      "Processing Record 18 of Set 33 | praia\n",
      "Processing Record 19 of Set 33 | querendaro\n",
      "Processing Record 20 of Set 33 | manokwari\n",
      "Processing Record 21 of Set 33 | cabra\n",
      "Processing Record 22 of Set 33 | boras\n",
      "Processing Record 23 of Set 33 | los llanos de aridane\n",
      "Processing Record 24 of Set 33 | yulara\n",
      "Processing Record 25 of Set 33 | ouadda\n",
      "Processing Record 26 of Set 33 | yamethin\n",
      "Processing Record 27 of Set 33 | inongo\n",
      "Processing Record 28 of Set 33 | kangaba\n",
      "Processing Record 29 of Set 33 | vanimo\n",
      "Processing Record 30 of Set 33 | goderich\n",
      "Processing Record 31 of Set 33 | kollam\n",
      "Processing Record 32 of Set 33 | severnyy\n",
      "Processing Record 33 of Set 33 | sarakhs\n",
      "Processing Record 34 of Set 33 | saint-pierre\n",
      "Processing Record 35 of Set 33 | port hardy\n",
      "Processing Record 36 of Set 33 | carutapera\n",
      "Processing Record 37 of Set 33 | mecca\n",
      "Processing Record 38 of Set 33 | nur\n",
      "Processing Record 39 of Set 33 | coromandel\n",
      "Processing Record 40 of Set 33 | leningradskiy\n",
      "Processing Record 41 of Set 33 | ituni\n",
      "City not found. Skipping...\n",
      "Processing Record 42 of Set 33 | mbandaka\n",
      "Processing Record 43 of Set 33 | manado\n",
      "Processing Record 44 of Set 33 | catamarca\n",
      "Processing Record 45 of Set 33 | dingli\n",
      "Processing Record 46 of Set 33 | camopi\n",
      "Processing Record 47 of Set 33 | shwebo\n",
      "Processing Record 48 of Set 33 | puerto madryn\n",
      "Processing Record 49 of Set 33 | shu\n",
      "Processing Record 50 of Set 33 | huaral\n",
      "Processing Record 1 of Set 34 | esso\n",
      "Processing Record 2 of Set 34 | quchan\n",
      "Processing Record 3 of Set 34 | siilinjarvi\n",
      "Processing Record 4 of Set 34 | vardo\n",
      "Processing Record 5 of Set 34 | mwanza\n",
      "Processing Record 6 of Set 34 | kulhudhuffushi\n",
      "Processing Record 7 of Set 34 | ipixuna\n",
      "Processing Record 8 of Set 34 | prieska\n",
      "Processing Record 9 of Set 34 | grand river south east\n",
      "City not found. Skipping...\n",
      "Processing Record 10 of Set 34 | alofi\n",
      "Processing Record 11 of Set 34 | valdosta\n",
      "Processing Record 12 of Set 34 | hefei\n",
      "Processing Record 13 of Set 34 | newark\n",
      "Processing Record 14 of Set 34 | finschhafen\n",
      "Processing Record 15 of Set 34 | pizhanka\n",
      "Processing Record 16 of Set 34 | keetmanshoop\n",
      "Processing Record 17 of Set 34 | dondo\n",
      "Processing Record 18 of Set 34 | port elizabeth\n",
      "Processing Record 19 of Set 34 | acapulco\n",
      "Processing Record 20 of Set 34 | iralaya\n",
      "Processing Record 21 of Set 34 | galgani\n",
      "City not found. Skipping...\n",
      "Processing Record 22 of Set 34 | villarrica\n",
      "Processing Record 23 of Set 34 | quatre cocos\n",
      "Processing Record 24 of Set 34 | general roca\n",
      "Processing Record 25 of Set 34 | hobyo\n",
      "Processing Record 26 of Set 34 | antofagasta\n",
      "Processing Record 27 of Set 34 | marsa matruh\n",
      "Processing Record 28 of Set 34 | baker city\n",
      "Processing Record 29 of Set 34 | bageshwar\n",
      "Processing Record 30 of Set 34 | cidreira\n",
      "Processing Record 31 of Set 34 | urucara\n",
      "Processing Record 32 of Set 34 | umzimvubu\n",
      "City not found. Skipping...\n",
      "Processing Record 33 of Set 34 | moussoro\n",
      "Processing Record 34 of Set 34 | mehamn\n",
      "Processing Record 35 of Set 34 | pemangkat\n",
      "Processing Record 36 of Set 34 | salalah\n",
      "Processing Record 37 of Set 34 | dukat\n",
      "Processing Record 38 of Set 34 | coihaique\n",
      "Processing Record 39 of Set 34 | elk city\n",
      "Processing Record 40 of Set 34 | broome\n",
      "Processing Record 41 of Set 34 | marystown\n",
      "Processing Record 42 of Set 34 | marawi\n",
      "Processing Record 43 of Set 34 | burica\n",
      "City not found. Skipping...\n",
      "Processing Record 44 of Set 34 | sur\n",
      "Processing Record 45 of Set 34 | hovd\n",
      "Processing Record 46 of Set 34 | merrill\n",
      "Processing Record 47 of Set 34 | homer\n",
      "Processing Record 48 of Set 34 | mardin\n",
      "Processing Record 49 of Set 34 | huoqiu\n",
      "Processing Record 50 of Set 34 | muscat\n",
      "Processing Record 1 of Set 35 | tromso\n",
      "Processing Record 2 of Set 35 | labuan\n",
      "Processing Record 3 of Set 35 | ust-shonosha\n",
      "Processing Record 4 of Set 35 | masalli\n",
      "Processing Record 5 of Set 35 | chadiza\n",
      "Processing Record 6 of Set 35 | keshabpur\n",
      "Processing Record 7 of Set 35 | port blair\n",
      "Processing Record 8 of Set 35 | the valley\n",
      "Processing Record 9 of Set 35 | liku\n",
      "Processing Record 10 of Set 35 | kaeo\n",
      "Processing Record 11 of Set 35 | burnie\n",
      "Processing Record 12 of Set 35 | tuapse\n",
      "Processing Record 13 of Set 35 | maltahohe\n",
      "Processing Record 14 of Set 35 | tofield\n",
      "Processing Record 15 of Set 35 | dekoa\n",
      "City not found. Skipping...\n",
      "Processing Record 16 of Set 35 | longyearbyen\n",
      "Processing Record 17 of Set 35 | nome\n",
      "Processing Record 18 of Set 35 | novyye burasy\n",
      "Processing Record 19 of Set 35 | araceli\n",
      "Processing Record 20 of Set 35 | havre-saint-pierre\n",
      "Processing Record 21 of Set 35 | urusha\n",
      "Processing Record 22 of Set 35 | bad wurzach\n",
      "Processing Record 23 of Set 35 | kendari\n",
      "Processing Record 24 of Set 35 | egvekinot\n",
      "Processing Record 25 of Set 35 | takoradi\n",
      "Processing Record 26 of Set 35 | malanje\n",
      "Processing Record 27 of Set 35 | volosovo\n",
      "Processing Record 28 of Set 35 | lyuban\n",
      "Processing Record 29 of Set 35 | tigil\n",
      "Processing Record 30 of Set 35 | maniitsoq\n",
      "Processing Record 31 of Set 35 | pevek\n",
      "Processing Record 32 of Set 35 | caravelas\n",
      "Processing Record 33 of Set 35 | baherden\n",
      "Processing Record 34 of Set 35 | haines junction\n",
      "Processing Record 35 of Set 35 | halalo\n",
      "City not found. Skipping...\n",
      "Processing Record 36 of Set 35 | pailon\n",
      "Processing Record 37 of Set 35 | fare\n",
      "Processing Record 38 of Set 35 | pyaozerskiy\n",
      "Processing Record 39 of Set 35 | ola\n",
      "Processing Record 40 of Set 35 | katherine\n",
      "Processing Record 41 of Set 35 | saint george\n",
      "Processing Record 42 of Set 35 | datong\n",
      "Processing Record 43 of Set 35 | doctor pedro p. pena\n",
      "City not found. Skipping...\n",
      "Processing Record 44 of Set 35 | kosh-agach\n",
      "Processing Record 45 of Set 35 | bolungarvik\n",
      "City not found. Skipping...\n",
      "Processing Record 46 of Set 35 | chardara\n",
      "Processing Record 47 of Set 35 | campo maior\n",
      "Processing Record 48 of Set 35 | kolobrzeg\n",
      "Processing Record 49 of Set 35 | sterling\n",
      "Processing Record 50 of Set 35 | kot samaba\n",
      "Processing Record 1 of Set 36 | hirara\n",
      "Processing Record 2 of Set 36 | ilulissat\n",
      "Processing Record 3 of Set 36 | san ramon\n",
      "Processing Record 4 of Set 36 | lillooet\n",
      "Processing Record 5 of Set 36 | richards bay\n",
      "Processing Record 6 of Set 36 | quepos\n",
      "Processing Record 7 of Set 36 | kushmurun\n",
      "Processing Record 8 of Set 36 | krasnyy yar\n",
      "Processing Record 9 of Set 36 | crib point\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Processing Record 10 of Set 36 | seydi\n",
      "Processing Record 11 of Set 36 | manzil tamim\n",
      "City not found. Skipping...\n",
      "Processing Record 12 of Set 36 | saint-joseph\n",
      "Processing Record 13 of Set 36 | rincon\n",
      "Processing Record 14 of Set 36 | gazimurskiy zavod\n",
      "Processing Record 15 of Set 36 | karatau\n",
      "Processing Record 16 of Set 36 | dongzhen\n",
      "Processing Record 17 of Set 36 | pemba\n",
      "Processing Record 18 of Set 36 | matara\n",
      "Processing Record 19 of Set 36 | saint-augustin\n",
      "Processing Record 20 of Set 36 | siniscola\n",
      "Processing Record 21 of Set 36 | saryozek\n",
      "Processing Record 22 of Set 36 | rocha\n",
      "Processing Record 23 of Set 36 | krasnoyarsk-45\n",
      "City not found. Skipping...\n",
      "Processing Record 24 of Set 36 | videira\n",
      "Processing Record 25 of Set 36 | labuhan\n",
      "Processing Record 26 of Set 36 | nichinan\n",
      "Processing Record 27 of Set 36 | vallenar\n",
      "Processing Record 28 of Set 36 | emerald\n",
      "Processing Record 29 of Set 36 | oranjemund\n",
      "Processing Record 30 of Set 36 | pombas\n",
      "Processing Record 31 of Set 36 | nuuk\n",
      "Processing Record 32 of Set 36 | ondangwa\n",
      "Processing Record 33 of Set 36 | fez\n",
      "Processing Record 34 of Set 36 | port macquarie\n",
      "Processing Record 35 of Set 36 | voyinka\n",
      "Processing Record 36 of Set 36 | mount pleasant\n",
      "Processing Record 37 of Set 36 | cascais\n",
      "Processing Record 38 of Set 36 | ixtlahuacan del rio\n",
      "Processing Record 39 of Set 36 | ternate\n",
      "Processing Record 40 of Set 36 | hanzhong\n",
      "Processing Record 41 of Set 36 | ankang\n",
      "Processing Record 42 of Set 36 | riohacha\n",
      "Processing Record 43 of Set 36 | maragogi\n",
      "Processing Record 44 of Set 36 | wakkanai\n",
      "Processing Record 45 of Set 36 | palabuhanratu\n",
      "City not found. Skipping...\n",
      "Processing Record 46 of Set 36 | tongzi\n",
      "Processing Record 47 of Set 36 | flin flon\n",
      "Processing Record 48 of Set 36 | olga\n",
      "Processing Record 49 of Set 36 | nantucket\n",
      "Processing Record 50 of Set 36 | jabinyanah\n",
      "Processing Record 1 of Set 37 | pangoa\n",
      "Processing Record 2 of Set 37 | russell\n",
      "Processing Record 3 of Set 37 | skalistyy\n",
      "City not found. Skipping...\n",
      "Processing Record 4 of Set 37 | provideniya\n",
      "Processing Record 5 of Set 37 | gladstone\n",
      "Processing Record 6 of Set 37 | umm kaddadah\n",
      "Processing Record 7 of Set 37 | noumea\n",
      "Processing Record 8 of Set 37 | doha\n",
      "Processing Record 9 of Set 37 | minab\n",
      "Processing Record 10 of Set 37 | stratford-upon-avon\n",
      "-----------------------------\n",
      "Data Retrieval Complete      \n",
      "-----------------------------\n"
     ]
    }
   ],
   "source": [
    "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",
    "    # 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",
    "    # 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[\"sys\"][\"country\"]\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": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "559"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(city_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>City</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",
       "      <th>Country</th>\n",
       "      <th>Date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Devonport</td>\n",
       "      <td>-41.1667</td>\n",
       "      <td>146.3500</td>\n",
       "      <td>50.00</td>\n",
       "      <td>92</td>\n",
       "      <td>0</td>\n",
       "      <td>8.97</td>\n",
       "      <td>AU</td>\n",
       "      <td>2021-01-15 13:44:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Hithadhoo</td>\n",
       "      <td>-0.6000</td>\n",
       "      <td>73.0833</td>\n",
       "      <td>82.06</td>\n",
       "      <td>78</td>\n",
       "      <td>98</td>\n",
       "      <td>15.14</td>\n",
       "      <td>MV</td>\n",
       "      <td>2021-01-15 13:42:42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Rikitea</td>\n",
       "      <td>-23.1203</td>\n",
       "      <td>-134.9692</td>\n",
       "      <td>77.50</td>\n",
       "      <td>70</td>\n",
       "      <td>0</td>\n",
       "      <td>6.89</td>\n",
       "      <td>PF</td>\n",
       "      <td>2021-01-15 13:44:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>New Norfolk</td>\n",
       "      <td>-42.7826</td>\n",
       "      <td>147.0587</td>\n",
       "      <td>54.00</td>\n",
       "      <td>65</td>\n",
       "      <td>89</td>\n",
       "      <td>3.00</td>\n",
       "      <td>AU</td>\n",
       "      <td>2021-01-15 13:44:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Heze</td>\n",
       "      <td>35.2431</td>\n",
       "      <td>115.4411</td>\n",
       "      <td>34.70</td>\n",
       "      <td>77</td>\n",
       "      <td>64</td>\n",
       "      <td>7.05</td>\n",
       "      <td>CN</td>\n",
       "      <td>2021-01-15 13:44:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Saint-Philippe</td>\n",
       "      <td>-21.3585</td>\n",
       "      <td>55.7679</td>\n",
       "      <td>84.20</td>\n",
       "      <td>74</td>\n",
       "      <td>20</td>\n",
       "      <td>17.27</td>\n",
       "      <td>RE</td>\n",
       "      <td>2021-01-15 13:44:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Qaanaaq</td>\n",
       "      <td>77.4840</td>\n",
       "      <td>-69.3632</td>\n",
       "      <td>11.35</td>\n",
       "      <td>85</td>\n",
       "      <td>100</td>\n",
       "      <td>1.34</td>\n",
       "      <td>GL</td>\n",
       "      <td>2021-01-15 13:44:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Torbay</td>\n",
       "      <td>47.6666</td>\n",
       "      <td>-52.7314</td>\n",
       "      <td>32.00</td>\n",
       "      <td>100</td>\n",
       "      <td>90</td>\n",
       "      <td>14.97</td>\n",
       "      <td>CA</td>\n",
       "      <td>2021-01-15 13:44:08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Castro</td>\n",
       "      <td>-24.7911</td>\n",
       "      <td>-50.0119</td>\n",
       "      <td>71.49</td>\n",
       "      <td>78</td>\n",
       "      <td>88</td>\n",
       "      <td>8.63</td>\n",
       "      <td>BR</td>\n",
       "      <td>2021-01-15 13:40:21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Mataura</td>\n",
       "      <td>-46.1927</td>\n",
       "      <td>168.8643</td>\n",
       "      <td>53.15</td>\n",
       "      <td>95</td>\n",
       "      <td>21</td>\n",
       "      <td>0.51</td>\n",
       "      <td>NZ</td>\n",
       "      <td>2021-01-15 13:44:08</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             City      Lat       Lng  Max Temp  Humidity  Cloudiness  \\\n",
       "0       Devonport -41.1667  146.3500     50.00        92           0   \n",
       "1       Hithadhoo  -0.6000   73.0833     82.06        78          98   \n",
       "2         Rikitea -23.1203 -134.9692     77.50        70           0   \n",
       "3     New Norfolk -42.7826  147.0587     54.00        65          89   \n",
       "4            Heze  35.2431  115.4411     34.70        77          64   \n",
       "5  Saint-Philippe -21.3585   55.7679     84.20        74          20   \n",
       "6         Qaanaaq  77.4840  -69.3632     11.35        85         100   \n",
       "7          Torbay  47.6666  -52.7314     32.00       100          90   \n",
       "8          Castro -24.7911  -50.0119     71.49        78          88   \n",
       "9         Mataura -46.1927  168.8643     53.15        95          21   \n",
       "\n",
       "   Wind Speed Country                 Date  \n",
       "0        8.97      AU  2021-01-15 13:44:07  \n",
       "1       15.14      MV  2021-01-15 13:42:42  \n",
       "2        6.89      PF  2021-01-15 13:44:07  \n",
       "3        3.00      AU  2021-01-15 13:44:07  \n",
       "4        7.05      CN  2021-01-15 13:44:07  \n",
       "5       17.27      RE  2021-01-15 13:44:07  \n",
       "6        1.34      GL  2021-01-15 13:44:07  \n",
       "7       14.97      CA  2021-01-15 13:44:08  \n",
       "8        8.63      BR  2021-01-15 13:40:21  \n",
       "9        0.51      NZ  2021-01-15 13:44:08  "
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Convert the array of dictionaries to a Pandas DataFrame.\n",
    "city_data_df = pd.DataFrame(city_data)\n",
    "city_data_df.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "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": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 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\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1610718286.9403646"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Import the time module.\n",
    "import time\n",
    "# Get today's date in seconds.\n",
    "today = time.time()\n",
    "today"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Import time module\n",
    "import time\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": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "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": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "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": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "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": 42,
   "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=\"red\")\n",
    "    plt.xlabel('Latitude')\n",
    "    plt.ylabel(y_label)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "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>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",
       "      <th>Country</th>\n",
       "      <th>Date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Heze</td>\n",
       "      <td>35.2431</td>\n",
       "      <td>115.4411</td>\n",
       "      <td>34.70</td>\n",
       "      <td>77</td>\n",
       "      <td>64</td>\n",
       "      <td>7.05</td>\n",
       "      <td>CN</td>\n",
       "      <td>2021-01-15 13:44:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Qaanaaq</td>\n",
       "      <td>77.4840</td>\n",
       "      <td>-69.3632</td>\n",
       "      <td>11.35</td>\n",
       "      <td>85</td>\n",
       "      <td>100</td>\n",
       "      <td>1.34</td>\n",
       "      <td>GL</td>\n",
       "      <td>2021-01-15 13:44:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Torbay</td>\n",
       "      <td>47.6666</td>\n",
       "      <td>-52.7314</td>\n",
       "      <td>32.00</td>\n",
       "      <td>100</td>\n",
       "      <td>90</td>\n",
       "      <td>14.97</td>\n",
       "      <td>CA</td>\n",
       "      <td>2021-01-15 13:44:08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Corn Island</td>\n",
       "      <td>12.1694</td>\n",
       "      <td>-83.0418</td>\n",
       "      <td>79.70</td>\n",
       "      <td>75</td>\n",
       "      <td>76</td>\n",
       "      <td>13.91</td>\n",
       "      <td>NI</td>\n",
       "      <td>2021-01-15 13:44:08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Kapaa</td>\n",
       "      <td>22.0752</td>\n",
       "      <td>-159.3190</td>\n",
       "      <td>69.80</td>\n",
       "      <td>100</td>\n",
       "      <td>90</td>\n",
       "      <td>8.05</td>\n",
       "      <td>US</td>\n",
       "      <td>2021-01-15 13:44:08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>552</th>\n",
       "      <td>Provideniya</td>\n",
       "      <td>64.3833</td>\n",
       "      <td>-173.3000</td>\n",
       "      <td>11.55</td>\n",
       "      <td>93</td>\n",
       "      <td>100</td>\n",
       "      <td>7.52</td>\n",
       "      <td>RU</td>\n",
       "      <td>2021-01-15 13:44:46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>554</th>\n",
       "      <td>Umm Kaddadah</td>\n",
       "      <td>13.6017</td>\n",
       "      <td>26.6876</td>\n",
       "      <td>82.65</td>\n",
       "      <td>15</td>\n",
       "      <td>26</td>\n",
       "      <td>11.61</td>\n",
       "      <td>SD</td>\n",
       "      <td>2021-01-15 13:44:46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>556</th>\n",
       "      <td>Doha</td>\n",
       "      <td>25.2867</td>\n",
       "      <td>51.5333</td>\n",
       "      <td>78.80</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>2.30</td>\n",
       "      <td>QA</td>\n",
       "      <td>2021-01-15 13:42:24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>557</th>\n",
       "      <td>Minab</td>\n",
       "      <td>27.1467</td>\n",
       "      <td>57.0801</td>\n",
       "      <td>73.40</td>\n",
       "      <td>35</td>\n",
       "      <td>40</td>\n",
       "      <td>4.61</td>\n",
       "      <td>IR</td>\n",
       "      <td>2021-01-15 13:44:46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>558</th>\n",
       "      <td>Stratford-Upon-Avon</td>\n",
       "      <td>52.1917</td>\n",
       "      <td>-1.7073</td>\n",
       "      <td>36.00</td>\n",
       "      <td>97</td>\n",
       "      <td>100</td>\n",
       "      <td>3.00</td>\n",
       "      <td>GB</td>\n",
       "      <td>2021-01-15 13:44:46</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>379 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                    City      Lat       Lng  Max Temp  Humidity  Cloudiness  \\\n",
       "4                   Heze  35.2431  115.4411     34.70        77          64   \n",
       "6                Qaanaaq  77.4840  -69.3632     11.35        85         100   \n",
       "7                 Torbay  47.6666  -52.7314     32.00       100          90   \n",
       "11           Corn Island  12.1694  -83.0418     79.70        75          76   \n",
       "12                 Kapaa  22.0752 -159.3190     69.80       100          90   \n",
       "..                   ...      ...       ...       ...       ...         ...   \n",
       "552          Provideniya  64.3833 -173.3000     11.55        93         100   \n",
       "554         Umm Kaddadah  13.6017   26.6876     82.65        15          26   \n",
       "556                 Doha  25.2867   51.5333     78.80        13           0   \n",
       "557                Minab  27.1467   57.0801     73.40        35          40   \n",
       "558  Stratford-Upon-Avon  52.1917   -1.7073     36.00        97         100   \n",
       "\n",
       "     Wind Speed Country                 Date  \n",
       "4          7.05      CN  2021-01-15 13:44:07  \n",
       "6          1.34      GL  2021-01-15 13:44:07  \n",
       "7         14.97      CA  2021-01-15 13:44:08  \n",
       "11        13.91      NI  2021-01-15 13:44:08  \n",
       "12         8.05      US  2021-01-15 13:44:08  \n",
       "..          ...     ...                  ...  \n",
       "552        7.52      RU  2021-01-15 13:44:46  \n",
       "554       11.61      SD  2021-01-15 13:44:46  \n",
       "556        2.30      QA  2021-01-15 13:42:24  \n",
       "557        4.61      IR  2021-01-15 13:44:46  \n",
       "558        3.00      GB  2021-01-15 13:44:46  \n",
       "\n",
       "[379 rows x 9 columns]"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "city_data_df.loc[(city_data_df[\"Lat\"] >= 0)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "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": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "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 Hemisphere \\\n",
    "                        for Maximum Temperature', 'Max Temp',(10,40))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "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 \\\n",
    "                        for Maximum Temperature', 'Max Temp',(-50,90))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "ename": "SyntaxError",
     "evalue": "EOL while scanning string literal (<ipython-input-47-871646c8acf0>, line 6)",
     "output_type": "error",
     "traceback": [
      "\u001b[1;36m  File \u001b[1;32m\"<ipython-input-47-871646c8acf0>\"\u001b[1;36m, line \u001b[1;32m6\u001b[0m\n\u001b[1;33m    'Linear Regression on the Northern\u001b[0m\n\u001b[1;37m                                             ^\u001b[0m\n\u001b[1;31mSyntaxError\u001b[0m\u001b[1;31m:\u001b[0m EOL while scanning string literal\n"
     ]
    }
   ],
   "source": [
    "x_values = northern_hemi_df[\"Lat\"]\n",
    "\n",
    "y_values = northern_hemi_df[\"Humidity\"]\n",
    "\n",
    "plot_linear_regression(x_values, y_values , \n",
    "                       'Linear Regression on the Northern       \n",
    "                        Hemisphere \\n \n",
    "                        for % Humidity', '%Humidity',(40,10))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "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 \\\n",
    "                        for % Humidity', '% Humidity',(40,10))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "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 \\\n",
    "                        for % Humidity', '% Humidity',(-50,15))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Linear regression on the Northern 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 Northern Hemisphere \\\n",
    "                    for % Cloudiness', '% Cloudiness',(10,55))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "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 \\\n",
    "                        for Wind Speed', 'Wind Speed',(40,35))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "# 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 \\\n",
    "                        for Wind Speed', 'Wind Speed',(-50,35))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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