Web Design work- web visualization

{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import matplotlib.pyplot as plt\n", "import pandas as pd\n", "import numpy as np\n", "import requests\n", "import time\n", "from scipy.stats import linregress\n", "# Import API key\n", "# from api_keys import weather_api_key\n", "# Incorporated citipy to determine city based on latitude and longitude\n", "from citipy import citipy\n", "# Output File (CSV)\n", "output_data_file = \"output_data/cities.csv\"\n", "# Range of latitudes and longitudes\n", "lat_range = (-90, 90)\n", "lng_range = (-180, 180)\n", "api_key = '8ec952d4e4092c596aad13ddfae6d358'" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "622" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "lat_lngs = []\n", "cities = []\n", "# Create a set of random lat and lng combinations\n", "lats = np.random.uniform(lat_range[0], lat_range[1], size=1500)\n", "lngs = np.random.uniform(lng_range[0], lng_range[1], size=1500)\n", "lat_lngs = zip(lats, lngs)\n", "# Identify nearest city for each lat, lng combination\n", "for lat_lng in lat_lngs:\n", " city = citipy.nearest_city(lat_lng[0], lat_lng[1]).city_name\n", " # If the city is unique, then add it to a our cities list\n", " if city not in cities:\n", " cities.append(city)\n", "# Print the city count to confirm sufficient count\n", "len(cities)" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Beginning Data Retrieval \n", "-----------------------------\n", "Processing Record 1 of Set 1 | gorontalo\n", "Processing Record 2 of Set 1 | urumqi\n", "Processing Record 3 of Set 1 | saint george\n", "Processing Record 4 of Set 1 | bethel\n", "Processing Record 5 of Set 1 | east london\n", "Processing Record 6 of Set 1 | sapao\n", "City not found. Skipping...\n", "Processing Record 7 of Set 1 | busselton\n", "Processing Record 8 of Set 1 | ust-maya\n", "Processing Record 9 of Set 1 | henties bay\n", "Processing Record 10 of Set 1 | rikitea\n", "Processing Record 11 of Set 1 | codrington\n", "Processing Record 12 of Set 1 | kapaa\n", "Processing Record 13 of Set 1 | hermanus\n", "Processing Record 14 of Set 1 | puerto penasco\n", "Processing Record 15 of Set 1 | mataura\n", "Processing Record 16 of Set 1 | lavrentiya\n", "Processing Record 17 of Set 1 | vaini\n", "Processing Record 18 of Set 1 | atuona\n", "Processing Record 19 of Set 1 | barinitas\n", "Processing Record 20 of Set 1 | kawalu\n", "Processing Record 21 of Set 1 | tuktoyaktuk\n", "Processing Record 22 of Set 1 | breves\n", "Processing Record 23 of Set 1 | ushuaia\n", "Processing Record 24 of Set 1 | pochutla\n", "Processing Record 25 of Set 1 | illoqqortoormiut\n", "City not found. Skipping...\n", "Processing Record 26 of Set 1 | phalodi\n", "Processing Record 27 of Set 1 | port alfred\n", "Processing Record 28 of Set 1 | puerto escondido\n", "Processing Record 29 of Set 1 | albany\n", "Processing Record 30 of Set 1 | kadnikov\n", "Processing Record 31 of Set 1 | kirksville\n", "Processing Record 32 of Set 1 | ayr\n", "Processing Record 33 of Set 1 | nouadhibou\n", "Processing Record 34 of Set 1 | waipawa\n", "Processing Record 35 of Set 1 | ayni\n", "Processing Record 36 of Set 1 | san quintin\n", "Processing Record 37 of Set 1 | jamestown\n", "Processing Record 38 of Set 1 | asau\n", "Processing Record 39 of Set 1 | punta arenas\n", "Processing Record 40 of Set 1 | sumbe\n", "Processing Record 41 of Set 1 | roald\n", "Processing Record 42 of Set 1 | hithadhoo\n", "Processing Record 43 of Set 1 | bluff\n", "Processing Record 44 of Set 1 | butaritari\n", "Processing Record 45 of Set 1 | klaksvik\n", "Processing Record 46 of Set 1 | amderma\n", "City not found. Skipping...\n", "Processing Record 47 of Set 1 | maltahohe\n", "Processing Record 48 of Set 1 | marihatag\n", "Processing Record 49 of Set 1 | grindavik\n", "Processing Record 50 of Set 1 | jiuquan\n", "Processing Record 0 of Set 2 | dikson\n", "Processing Record 1 of Set 2 | kamenskoye\n", "City not found. Skipping...\n", "Processing Record 2 of Set 2 | puerto ayora\n", "Processing Record 3 of Set 2 | marevo\n", "Processing Record 4 of Set 2 | avarua\n", "Processing Record 5 of Set 2 | sao paulo de olivenca\n", "Processing Record 6 of Set 2 | guerrero negro\n", "Processing Record 7 of Set 2 | palimbang\n", "Processing Record 8 of Set 2 | tongliao\n", "Processing Record 9 of Set 2 | aklavik\n", "Processing Record 10 of Set 2 | castro\n", "Processing Record 11 of Set 2 | guajara-mirim\n", "City not found. Skipping...\n", "Processing Record 12 of Set 2 | kodiak\n", "Processing Record 13 of Set 2 | ilo\n", "Processing Record 14 of Set 2 | mahebourg\n", "Processing Record 15 of Set 2 | fabriano\n", "Processing Record 16 of Set 2 | yeletskiy\n", "City not found. Skipping...\n", "Processing Record 17 of Set 2 | natal\n", "Processing Record 18 of Set 2 | kavaratti\n", "Processing Record 19 of Set 2 | cherskiy\n", "Processing Record 20 of Set 2 | the pas\n", "Processing Record 21 of Set 2 | yellowknife\n", "Processing Record 22 of Set 2 | clyde river\n", "Processing Record 23 of Set 2 | bilma\n", "Processing Record 24 of Set 2 | hilo\n", "Processing Record 25 of Set 2 | faanui\n", "Processing Record 26 of Set 2 | calvinia\n", "Processing Record 27 of Set 2 | lata\n", "Processing Record 28 of Set 2 | stornoway\n", "Processing Record 29 of Set 2 | portland\n", "Processing Record 30 of Set 2 | ponta do sol\n", "Processing Record 31 of Set 2 | saleaula\n", "City not found. Skipping...\n", "Processing Record 32 of Set 2 | vanimo\n", "Processing Record 33 of Set 2 | chifeng\n", "Processing Record 34 of Set 2 | encruzilhada\n", "Processing Record 35 of Set 2 | necochea\n", "Processing Record 36 of Set 2 | souillac\n", "Processing Record 37 of Set 2 | isangel\n", "Processing Record 38 of Set 2 | kieta\n", "Processing Record 39 of Set 2 | karaul\n", "City not found. Skipping...\n", "Processing Record 40 of Set 2 | sept-iles\n", "Processing Record 41 of Set 2 | juneau\n", "Processing Record 42 of Set 2 | saskylakh\n", "Processing Record 43 of Set 2 | sisimiut\n", "Processing Record 44 of Set 2 | attawapiskat\n", "City not found. Skipping...\n", "Processing Record 45 of Set 2 | ulaangom\n", "Processing Record 46 of Set 2 | taywarah\n", "Processing Record 47 of Set 2 | norman wells\n", "Processing Record 48 of Set 2 | marzuq\n", "Processing Record 49 of Set 2 | ancud\n", "Processing Record 0 of Set 3 | daxian\n", "City not found. Skipping...\n", "Processing Record 1 of Set 3 | vila franca do campo\n", "Processing Record 2 of Set 3 | chhachhrauli\n", "Processing Record 3 of Set 3 | taolanaro\n", "City not found. Skipping...\n", "Processing Record 4 of Set 3 | eldorado\n", "Processing Record 5 of Set 3 | cape town\n", "Processing Record 6 of Set 3 | puri\n", "Processing Record 7 of Set 3 | turukhansk\n", "Processing Record 8 of Set 3 | gulshat\n", "City not found. Skipping...\n", "Processing Record 9 of Set 3 | barrow\n", "Processing Record 10 of Set 3 | doha\n", "Processing Record 11 of Set 3 | provideniya\n", "Processing Record 12 of Set 3 | san cristobal\n", "Processing Record 13 of Set 3 | chuy\n", "Processing Record 14 of Set 3 | lompoc\n", "Processing Record 15 of Set 3 | klyuchi\n", "Processing Record 16 of Set 3 | steinbach\n", "Processing Record 17 of Set 3 | cagliari\n", "Processing Record 18 of Set 3 | birin\n", "Processing Record 19 of Set 3 | buchanan\n", "Processing Record 20 of Set 3 | carnarvon\n", "Processing Record 21 of Set 3 | bolu\n", "Processing Record 22 of Set 3 | tombouctou\n", "Processing Record 23 of Set 3 | lazo\n", "Processing Record 24 of Set 3 | batticaloa\n", "Processing Record 25 of Set 3 | conceicao do araguaia\n", "Processing Record 26 of Set 3 | kaitangata\n", "Processing Record 27 of Set 3 | geraldton\n", "Processing Record 28 of Set 3 | new norfolk\n", "Processing Record 29 of Set 3 | margate\n", "Processing Record 30 of Set 3 | krasnoselkup\n", "Processing Record 31 of Set 3 | half moon bay\n", "Processing Record 32 of Set 3 | nikolskoye\n", "Processing Record 33 of Set 3 | ust-nera\n", "Processing Record 34 of Set 3 | qaqortoq\n", "Processing Record 35 of Set 3 | najran\n", "Processing Record 36 of Set 3 | krasnorechenskiy\n", "Processing Record 37 of Set 3 | georgetown\n", "Processing Record 38 of Set 3 | sitka\n", "Processing Record 39 of Set 3 | tonj\n", "Processing Record 40 of Set 3 | beringovskiy\n", "Processing Record 41 of Set 3 | saldanha\n", "Processing Record 42 of Set 3 | raudeberg\n", "Processing Record 43 of Set 3 | belushya guba\n", "City not found. Skipping...\n", "Processing Record 44 of Set 3 | mar del plata\n", "Processing Record 45 of Set 3 | ribeira grande\n", "Processing Record 46 of Set 3 | bredasdorp\n", "Processing Record 47 of Set 3 | makakilo city\n", "Processing Record 48 of Set 3 | kolpashevo\n", "Processing Record 49 of Set 3 | buin\n", "Processing Record 0 of Set 4 | olafsvik\n", "Processing Record 1 of Set 4 | zhangye\n", "Processing Record 2 of Set 4 | esperance\n", "Processing Record 3 of Set 4 | khatanga\n", "Processing Record 4 of Set 4 | inhambane\n", "Processing Record 5 of Set 4 | ust-ishim\n", "Processing Record 6 of Set 4 | vaitupu\n", "City not found. Skipping...\n", "Processing Record 7 of Set 4 | bargal\n", "City not found. Skipping...\n", "Processing Record 8 of Set 4 | huambo\n", "Processing Record 9 of Set 4 | rapid valley\n", "Processing Record 10 of Set 4 | walvis bay\n", "Processing Record 11 of Set 4 | tynaarlo\n", "Processing Record 12 of Set 4 | columbus\n", "Processing Record 13 of Set 4 | camocim\n", "Processing Record 14 of Set 4 | dicabisagan\n", "Processing Record 15 of Set 4 | barawe\n", "City not found. Skipping...\n", "Processing Record 16 of Set 4 | ambulu\n", "Processing Record 17 of Set 4 | hofn\n", "Processing Record 18 of Set 4 | saint anthony\n", "Processing Record 19 of Set 4 | ormara\n", "Processing Record 20 of Set 4 | college\n", "Processing Record 21 of Set 4 | zhigansk\n", "Processing Record 22 of Set 4 | airai\n", "Processing Record 23 of Set 4 | chagda\n", "City not found. Skipping...\n", "Processing Record 24 of Set 4 | nadym\n", "Processing Record 25 of Set 4 | zaysan\n", "Processing Record 26 of Set 4 | dzaoudzi\n", "Processing Record 27 of Set 4 | thompson\n", "Processing Record 28 of Set 4 | sao joao da barra\n", "Processing Record 29 of Set 4 | muroto\n", "Processing Record 30 of Set 4 | suluq\n", "Processing Record 31 of Set 4 | san francisco\n", "Processing Record 32 of Set 4 | samusu\n", "City not found. Skipping...\n", "Processing Record 33 of Set 4 | urengoy\n", "Processing Record 34 of Set 4 | hobart\n", "Processing Record 35 of Set 4 | carutapera\n", "Processing Record 36 of Set 4 | constitucion\n", "Processing Record 37 of Set 4 | sapa\n", "Processing Record 38 of Set 4 | kutum\n", "Processing Record 39 of Set 4 | tsabong\n", "Processing Record 40 of Set 4 | port lincoln\n", "Processing Record 41 of Set 4 | ishigaki\n", "Processing Record 42 of Set 4 | leningradskiy\n", "Processing Record 43 of Set 4 | tasiilaq\n", "Processing Record 44 of Set 4 | santa rosa\n", "Processing Record 45 of Set 4 | ishim\n", "Processing Record 46 of Set 4 | san pedro\n", "Processing Record 47 of Set 4 | nome\n", "Processing Record 48 of Set 4 | aktanysh\n", "Processing Record 49 of Set 4 | tiksi\n", "Processing Record 0 of Set 5 | cervo\n", "Processing Record 1 of Set 5 | miri\n", "Processing Record 2 of Set 5 | hasaki\n", "Processing Record 3 of Set 5 | te anau\n", "Processing Record 4 of Set 5 | frankenthal\n", "Processing Record 5 of Set 5 | tahe\n", "Processing Record 6 of Set 5 | naze\n", "Processing Record 7 of Set 5 | el sauzal\n", "Processing Record 8 of Set 5 | katsuura\n", "Processing Record 9 of Set 5 | ritchie\n", "Processing Record 10 of Set 5 | arkhangelsk\n", "Processing Record 11 of Set 5 | balangiga\n", "Processing Record 12 of Set 5 | shirokiy\n", "Processing Record 13 of Set 5 | kwinana\n", "Processing Record 14 of Set 5 | longyearbyen\n", "Processing Record 15 of Set 5 | gunjur\n", "Processing Record 16 of Set 5 | machali\n", "Processing Record 17 of Set 5 | alta floresta\n", "Processing Record 18 of Set 5 | vostok\n", "Processing Record 19 of Set 5 | lang suan\n", "Processing Record 20 of Set 5 | bambous virieux\n", "Processing Record 21 of Set 5 | rosario\n", "Processing Record 22 of Set 5 | vestmanna\n", "Processing Record 23 of Set 5 | kahului\n", "Processing Record 24 of Set 5 | yomou\n", "Processing Record 25 of Set 5 | tecoanapa\n", "Processing Record 26 of Set 5 | xai-xai\n", "Processing Record 27 of Set 5 | brae\n", "Processing Record 28 of Set 5 | bulancak\n", "Processing Record 29 of Set 5 | xining\n", "Processing Record 30 of Set 5 | morales\n", "Processing Record 31 of Set 5 | komsomolskiy\n", "Processing Record 32 of Set 5 | qasigiannguit\n", "Processing Record 33 of Set 5 | ironton\n", "Processing Record 34 of Set 5 | baillif\n", "Processing Record 35 of Set 5 | barentsburg\n", "City not found. Skipping...\n", "Processing Record 36 of Set 5 | kavali\n", "Processing Record 37 of Set 5 | nara\n", "Processing Record 38 of Set 5 | kruisfontein\n", "Processing Record 39 of Set 5 | cidreira\n", "Processing Record 40 of Set 5 | paamiut\n", "Processing Record 41 of Set 5 | westport\n", "Processing Record 42 of Set 5 | erzin\n", "Processing Record 43 of Set 5 | qaanaaq\n", "Processing Record 44 of Set 5 | tieli\n", "Processing Record 45 of Set 5 | arrecife\n", "Processing Record 46 of Set 5 | corner brook\n", "Processing Record 47 of Set 5 | mende\n", "Processing Record 48 of Set 5 | pantai remis\n", "Processing Record 49 of Set 5 | umm lajj\n", "Processing Record 0 of Set 6 | iqaluit\n", "Processing Record 1 of Set 6 | bathsheba\n", "Processing Record 2 of Set 6 | hami\n", "Processing Record 3 of Set 6 | tadine\n", "Processing Record 4 of Set 6 | olkhovka\n", "Processing Record 5 of Set 6 | tabou\n", "Processing Record 6 of Set 6 | talnakh\n", "Processing Record 7 of Set 6 | yar-sale\n", "Processing Record 8 of Set 6 | fortuna\n", "Processing Record 9 of Set 6 | chopda\n", "Processing Record 10 of Set 6 | vao\n", "Processing Record 11 of Set 6 | amga\n", "Processing Record 12 of Set 6 | kirakira\n", "Processing Record 13 of Set 6 | vila velha\n", "Processing Record 14 of Set 6 | sola\n", "Processing Record 15 of Set 6 | gari\n", "Processing Record 16 of Set 6 | karamea\n", "City not found. Skipping...\n", "Processing Record 17 of Set 6 | sawai madhopur\n", "Processing Record 18 of Set 6 | oranjemund\n", "Processing Record 19 of Set 6 | noumea\n", "Processing Record 20 of Set 6 | upernavik\n", "Processing Record 21 of Set 6 | lewisporte\n", "Processing Record 22 of Set 6 | mount isa\n", "Processing Record 23 of Set 6 | christchurch\n", "Processing Record 24 of Set 6 | alenquer\n", "Processing Record 25 of Set 6 | sainte-luce\n", "Processing Record 26 of Set 6 | sioux lookout\n", "Processing Record 27 of Set 6 | iwaki\n", "Processing Record 28 of Set 6 | luderitz\n", "Processing Record 29 of Set 6 | savonlinna\n", "Processing Record 30 of Set 6 | the valley\n", "Processing Record 31 of Set 6 | saint-philippe\n", "Processing Record 32 of Set 6 | khani\n", "Processing Record 33 of Set 6 | plettenberg bay\n", "Processing Record 34 of Set 6 | okhotsk\n", "Processing Record 35 of Set 6 | fenoarivo\n", "Processing Record 36 of Set 6 | baculin\n", "Processing Record 37 of Set 6 | andenes\n", "Processing Record 38 of Set 6 | thinadhoo\n", "Processing Record 39 of Set 6 | sorvag\n", "City not found. Skipping...\n", "Processing Record 40 of Set 6 | tanshui\n", "City not found. Skipping...\n", "Processing Record 41 of Set 6 | lethem\n", "Processing Record 42 of Set 6 | lasa\n", "Processing Record 43 of Set 6 | ambilobe\n", "Processing Record 44 of Set 6 | santa cruz\n", "Processing Record 45 of Set 6 | santa isabel do rio negro\n", "Processing Record 46 of Set 6 | nizhneyansk\n", "City not found. Skipping...\n", "Processing Record 47 of Set 6 | campos novos\n", "Processing Record 48 of Set 6 | namibe\n", "Processing Record 49 of Set 6 | san ramon\n", "Processing Record 0 of Set 7 | adre\n", "Processing Record 1 of Set 7 | jiwani\n", "Processing Record 2 of Set 7 | cavalcante\n", "Processing Record 3 of Set 7 | wuwei\n", "Processing Record 4 of Set 7 | rawson\n", "Processing Record 5 of Set 7 | sampang\n", "Processing Record 6 of Set 7 | barinas\n", "Processing Record 7 of Set 7 | itarema\n", "Processing Record 8 of Set 7 | kaeo\n", "Processing Record 9 of Set 7 | fort saint john\n", "City not found. Skipping...\n", "Processing Record 10 of Set 7 | emerald\n", "Processing Record 11 of Set 7 | vestmannaeyjar\n", "Processing Record 12 of Set 7 | tuatapere\n", "Processing Record 13 of Set 7 | atakpame\n", "Processing Record 14 of Set 7 | ballina\n", "Processing Record 15 of Set 7 | keetmanshoop\n", "Processing Record 16 of Set 7 | ilulissat\n", "Processing Record 17 of Set 7 | victoria\n", "Processing Record 18 of Set 7 | yerbogachen\n", "Processing Record 19 of Set 7 | grand river south east\n", "City not found. Skipping...\n", "Processing Record 20 of Set 7 | acapulco\n", "Processing Record 21 of Set 7 | torbay\n", "Processing Record 22 of Set 7 | dingle\n", "Processing Record 23 of Set 7 | kawana waters\n", "City not found. Skipping...\n", "Processing Record 24 of Set 7 | quincy\n", "Processing Record 25 of Set 7 | chacabuco\n", "Processing Record 26 of Set 7 | estacion coahuila\n", "Processing Record 27 of Set 7 | tual\n", "Processing Record 28 of Set 7 | enshi\n", "Processing Record 29 of Set 7 | morant bay\n", "Processing Record 30 of Set 7 | sinnamary\n", "Processing Record 31 of Set 7 | nago\n", "Processing Record 32 of Set 7 | peniche\n", "Processing Record 33 of Set 7 | conil\n", "Processing Record 34 of Set 7 | praya\n", "Processing Record 35 of Set 7 | cortez\n", "Processing Record 36 of Set 7 | arraial do cabo\n", "Processing Record 37 of Set 7 | lebu\n", "Processing Record 38 of Set 7 | mbumi\n", "Processing Record 39 of Set 7 | santa fe do sul\n", "Processing Record 40 of Set 7 | abu dhabi\n", "Processing Record 41 of Set 7 | pevek\n", "Processing Record 42 of Set 7 | dumka\n", "Processing Record 43 of Set 7 | port elizabeth\n", "Processing Record 44 of Set 7 | mahon\n", "Processing Record 45 of Set 7 | esso\n", "Processing Record 46 of Set 7 | vila\n", "Processing Record 47 of Set 7 | farah\n", "Processing Record 48 of Set 7 | derzhavinsk\n", "Processing Record 49 of Set 7 | north bend\n", "Processing Record 0 of Set 8 | alugan\n", "Processing Record 1 of Set 8 | san patricio\n", "Processing Record 2 of Set 8 | riverton\n", "Processing Record 3 of Set 8 | pangnirtung\n", "Processing Record 4 of Set 8 | lorengau\n", "Processing Record 5 of Set 8 | jalu\n", "Processing Record 6 of Set 8 | bandarbeyla\n", "Processing Record 7 of Set 8 | tarko-sale\n", "Processing Record 8 of Set 8 | aurillac\n", "Processing Record 9 of Set 8 | santa maria\n", "Processing Record 10 of Set 8 | trunovskoye\n", "Processing Record 11 of Set 8 | port blair\n", "Processing Record 12 of Set 8 | igarape-miri\n", "City not found. Skipping...\n", "Processing Record 13 of Set 8 | flin flon\n", "Processing Record 14 of Set 8 | chicama\n", "Processing Record 15 of Set 8 | chute-aux-outardes\n", "Processing Record 16 of Set 8 | gorno-chuyskiy\n", "City not found. Skipping...\n", "Processing Record 17 of Set 8 | maneadero\n", "Processing Record 18 of Set 8 | weinan\n", "Processing Record 19 of Set 8 | severo-kurilsk\n", "Processing Record 20 of Set 8 | kavieng\n", "Processing Record 21 of Set 8 | biltine\n", "Processing Record 22 of Set 8 | chapais\n", "Processing Record 23 of Set 8 | jizan\n", "Processing Record 24 of Set 8 | bakonycsernye\n", "Processing Record 25 of Set 8 | chokurdakh\n", "Processing Record 26 of Set 8 | bialystok\n", "Processing Record 27 of Set 8 | andijon\n", "Processing Record 28 of Set 8 | odoyev\n", "Processing Record 29 of Set 8 | jos\n", "Processing Record 30 of Set 8 | rocha\n", "Processing Record 31 of Set 8 | kralendijk\n", "Processing Record 32 of Set 8 | cabo san lucas\n", "Processing Record 33 of Set 8 | tuy hoa\n", "Processing Record 34 of Set 8 | matay\n", "Processing Record 35 of Set 8 | qandahar\n", "City not found. Skipping...\n", "Processing Record 36 of Set 8 | staryy nadym\n", "Processing Record 37 of Set 8 | gwadar\n", "Processing Record 38 of Set 8 | richards bay\n", "Processing Record 39 of Set 8 | skeldon\n", "Processing Record 40 of Set 8 | sentyabrskiy\n", "City not found. Skipping...\n", "Processing Record 41 of Set 8 | tsihombe\n", "City not found. Skipping...\n", "Processing Record 42 of Set 8 | alappuzha\n", "Processing Record 43 of Set 8 | ryotsu\n", "Processing Record 44 of Set 8 | buta\n", "Processing Record 45 of Set 8 | yingkou\n", "Processing Record 46 of Set 8 | atar\n", "Processing Record 47 of Set 8 | nasirabad\n", "Processing Record 48 of Set 8 | jonuta\n", "Processing Record 49 of Set 8 | laguna\n", "Processing Record 0 of Set 9 | barra do corda\n", "Processing Record 1 of Set 9 | mys shmidta\n", "City not found. Skipping...\n", "Processing Record 2 of Set 9 | dzhusaly\n", "City not found. Skipping...\n", "Processing Record 3 of Set 9 | umzimvubu\n", "City not found. Skipping...\n", "Processing Record 4 of Set 9 | coihueco\n", "Processing Record 5 of Set 9 | nexo\n", "Processing Record 6 of Set 9 | koungou\n", "Processing Record 7 of Set 9 | coquimbo\n", "Processing Record 8 of Set 9 | bijni\n", "Processing Record 9 of Set 9 | hokitika\n", "Processing Record 10 of Set 9 | hamilton\n", "Processing Record 11 of Set 9 | roma\n", "Processing Record 12 of Set 9 | formosa\n", "Processing Record 13 of Set 9 | limin khersonisou\n", "Processing Record 14 of Set 9 | port hardy\n", "Processing Record 15 of Set 9 | lolua\n", "City not found. Skipping...\n", "Processing Record 16 of Set 9 | kysyl-syr\n", "Processing Record 17 of Set 9 | menongue\n", "Processing Record 18 of Set 9 | west lafayette\n", "Processing Record 19 of Set 9 | loncoche\n", "Processing Record 20 of Set 9 | polyarnyy\n", "Processing Record 21 of Set 9 | svidnik\n", "Processing Record 22 of Set 9 | melchor de mencos\n", "Processing Record 23 of Set 9 | newcastle\n", "Processing Record 24 of Set 9 | poum\n", "Processing Record 25 of Set 9 | oneonta\n", "Processing Record 26 of Set 9 | birnin kebbi\n", "Processing Record 27 of Set 9 | pisco\n", "Processing Record 28 of Set 9 | khorixas\n", "Processing Record 29 of Set 9 | eenhana\n", "Processing Record 30 of Set 9 | dasol\n", "Processing Record 31 of Set 9 | udachnyy\n", "Processing Record 32 of Set 9 | huilong\n", "Processing Record 33 of Set 9 | altay\n", "Processing Record 34 of Set 9 | nailsea\n", "Processing Record 35 of Set 9 | andros town\n", "Processing Record 36 of Set 9 | salalah\n", "Processing Record 37 of Set 9 | mandurah\n", "Processing Record 38 of Set 9 | sitrah\n", "Processing Record 39 of Set 9 | kosa\n", "Processing Record 40 of Set 9 | dunedin\n", "Processing Record 41 of Set 9 | santa\n", "Processing Record 42 of Set 9 | kloulklubed\n", "Processing Record 43 of Set 9 | ibra\n", "Processing Record 44 of Set 9 | bria\n", "Processing Record 45 of Set 9 | ola\n", "Processing Record 46 of Set 9 | narsaq\n", "Processing Record 47 of Set 9 | road town\n", "Processing Record 48 of Set 9 | ouro preto do oeste\n", "Processing Record 49 of Set 9 | san lawrenz\n", "Processing Record 0 of Set 10 | temiscaming\n", "Processing Record 1 of Set 10 | desaguadero\n", "Processing Record 2 of Set 10 | mocuba\n", "Processing Record 3 of Set 10 | gushikawa\n", "Processing Record 4 of Set 10 | juanjui\n", "Processing Record 5 of Set 10 | camacha\n", "Processing Record 6 of Set 10 | tottori\n", "Processing Record 7 of Set 10 | ahipara\n", "Processing Record 8 of Set 10 | tabuk\n", "Processing Record 9 of Set 10 | hualmay\n", "Processing Record 10 of Set 10 | rochegda\n", "Processing Record 11 of Set 10 | tezu\n", "Processing Record 12 of Set 10 | genhe\n", "Processing Record 13 of Set 10 | tumannyy\n", "City not found. Skipping...\n", "Processing Record 14 of Set 10 | la union\n", "Processing Record 15 of Set 10 | mujiayingzi\n", "Processing Record 16 of Set 10 | san juan del sur\n", "Processing Record 17 of Set 10 | warqla\n", "City not found. Skipping...\n", "Processing Record 18 of Set 10 | sao filipe\n", "Processing Record 19 of Set 10 | wonthaggi\n", "Processing Record 20 of Set 10 | mount gambier\n", "Processing Record 21 of Set 10 | flinders\n", "Processing Record 22 of Set 10 | lufilufi\n", "Processing Record 23 of Set 10 | mitsamiouli\n", "Processing Record 24 of Set 10 | iquitos\n", "Processing Record 25 of Set 10 | helmsdale\n", "Processing Record 26 of Set 10 | nacala\n", "Processing Record 27 of Set 10 | yulara\n", "Processing Record 28 of Set 10 | pringsewu\n", "Processing Record 29 of Set 10 | lexington\n", "Processing Record 30 of Set 10 | prince rupert\n", "Processing Record 31 of Set 10 | caravelas\n", "Processing Record 32 of Set 10 | avera\n", "Processing Record 33 of Set 10 | bjornevatn\n", "Processing Record 34 of Set 10 | kamphaeng phet\n", "Processing Record 35 of Set 10 | san antonio\n", "Processing Record 36 of Set 10 | ronneby\n", "Processing Record 37 of Set 10 | haines junction\n", "Processing Record 38 of Set 10 | temaraia\n", "City not found. Skipping...\n", "Processing Record 39 of Set 10 | garowe\n", "Processing Record 40 of Set 10 | kurumoch\n", "Processing Record 41 of Set 10 | port-gentil\n", "Processing Record 42 of Set 10 | adrar\n", "Processing Record 43 of Set 10 | touros\n", "Processing Record 44 of Set 10 | letlhakane\n", "Processing Record 45 of Set 10 | ylojarvi\n", "Processing Record 46 of Set 10 | buckeye\n", "Processing Record 47 of Set 10 | lazaro cardenas\n", "Processing Record 48 of Set 10 | waingapu\n", "Processing Record 49 of Set 10 | baiyin\n", "Processing Record 0 of Set 11 | armacao dos buzios\n", "City not found. Skipping...\n", "Processing Record 1 of Set 11 | sikar\n", "Processing Record 2 of Set 11 | varkaus\n", "Processing Record 3 of Set 11 | sohbatpur\n", "Processing Record 4 of Set 11 | kosh-agach\n", "Processing Record 5 of Set 11 | corn island\n", "Processing Record 6 of Set 11 | erdenet\n", "Processing Record 7 of Set 11 | tukrah\n", "Processing Record 8 of Set 11 | karratha\n", "Processing Record 9 of Set 11 | ucluelet\n", "Processing Record 10 of Set 11 | omsukchan\n", "Processing Record 11 of Set 11 | diez\n", "Processing Record 12 of Set 11 | buala\n", "Processing Record 13 of Set 11 | igarka\n", "Processing Record 14 of Set 11 | marcona\n", "City not found. Skipping...\n", "Processing Record 15 of Set 11 | eregli\n", "Processing Record 16 of Set 11 | kendari\n", "Processing Record 17 of Set 11 | kostino\n", "Processing Record 18 of Set 11 | boa vista\n", "Processing Record 19 of Set 11 | metehara\n", "City not found. Skipping...\n", "Processing Record 20 of Set 11 | abilene\n", "Processing Record 21 of Set 11 | aksarka\n", "Processing Record 22 of Set 11 | nguiu\n", "City not found. Skipping...\n", "Processing Record 23 of Set 11 | port pirie\n", "Processing Record 24 of Set 11 | valparaiso\n", "Processing Record 25 of Set 11 | bowen\n", "Processing Record 26 of Set 11 | ternate\n", "Processing Record 27 of Set 11 | tubinskiy\n", "Processing Record 28 of Set 11 | santa cruz del sur\n", "Processing Record 29 of Set 11 | miandrivazo\n", "Processing Record 30 of Set 11 | wahran\n", "City not found. Skipping...\n", "Processing Record 31 of Set 11 | pueblo bello\n", "Processing Record 32 of Set 11 | cartersville\n", "Processing Record 33 of Set 11 | bengkulu\n", "Processing Record 34 of Set 11 | mezen\n", "Processing Record 35 of Set 11 | khandyga\n", "Processing Record 36 of Set 11 | acajutla\n", "Processing Record 37 of Set 11 | hambantota\n", "Processing Record 38 of Set 11 | turayf\n", "Processing Record 39 of Set 11 | lodja\n", "Processing Record 40 of Set 11 | nizhneivkino\n", "Processing Record 41 of Set 11 | nosy varika\n", "Processing Record 42 of Set 11 | havelock\n", "Processing Record 43 of Set 11 | jhikargachha\n", "City not found. Skipping...\n", "Processing Record 44 of Set 11 | padang\n", "Processing Record 45 of Set 11 | huaihua\n", "Processing Record 46 of Set 11 | baghdad\n", "Processing Record 47 of Set 11 | tuim\n", "Processing Record 48 of Set 11 | kattivakkam\n", "Processing Record 49 of Set 11 | voh\n", "Processing Record 0 of Set 12 | jiddah\n", "City not found. Skipping...\n", "Processing Record 1 of Set 12 | langxiang\n", "Processing Record 2 of Set 12 | bolivar\n", "Processing Record 3 of Set 12 | vargem grande\n", "Processing Record 4 of Set 12 | iberia\n", "Processing Record 5 of Set 12 | alcudia\n", "Processing Record 6 of Set 12 | los llanos de aridane\n", "Processing Record 7 of Set 12 | osakarovka\n", "Processing Record 8 of Set 12 | comodoro rivadavia\n", "Processing Record 9 of Set 12 | sri aman\n", "Processing Record 10 of Set 12 | straumen\n", "Processing Record 11 of Set 12 | korem\n", "Processing Record 12 of Set 12 | bereda\n", "Processing Record 13 of Set 12 | emba\n", "Processing Record 14 of Set 12 | eureka\n", "Processing Record 15 of Set 12 | sakakah\n", "Processing Record 16 of Set 12 | belmonte\n", "Processing Record 17 of Set 12 | orlovskiy\n", "Processing Record 18 of Set 12 | cairns\n", "Processing Record 19 of Set 12 | kaduqli\n", "Processing Record 20 of Set 12 | madimba\n", "Processing Record 21 of Set 12 | pathein\n", "Processing Record 22 of Set 12 | moron\n", "Processing Record 23 of Set 12 | mahibadhoo\n", "Processing Record 24 of Set 12 | wanlaweyn\n", "Processing Record 25 of Set 12 | kargil\n", "Processing Record 26 of Set 12 | talara\n", "Processing Record 27 of Set 12 | bolungarvik\n", "City not found. Skipping...\n", "Processing Record 28 of Set 12 | tasbuget\n", "City not found. Skipping...\n", "Processing Record 29 of Set 12 | bandar\n", "Processing Record 30 of Set 12 | miandoab\n", "Processing Record 31 of Set 12 | sabang\n", "Processing Record 32 of Set 12 | broome\n", "Processing Record 33 of Set 12 | longlac\n", "City not found. Skipping...\n", "Processing Record 34 of Set 12 | meyungs\n", "City not found. Skipping...\n", "Processing Record 35 of Set 12 | novikovo\n", "Processing Record 36 of Set 12 | korla\n", "Processing Record 37 of Set 12 | sayyan\n", "Processing Record 38 of Set 12 | biak\n", "Processing Record 39 of Set 12 | kommunisticheskiy\n", "Processing Record 40 of Set 12 | maceio\n", "Processing Record 41 of Set 12 | pietersburg\n", "Processing Record 42 of Set 12 | kununurra\n", "Processing Record 43 of Set 12 | rudbar\n", "Processing Record 44 of Set 12 | vieques\n", "Processing Record 45 of Set 12 | maniitsoq\n", "Processing Record 46 of Set 12 | palabuhanratu\n", "City not found. Skipping...\n", "Processing Record 47 of Set 12 | dhidhdhoo\n", "Processing Record 48 of Set 12 | la ronge\n", "Processing Record 49 of Set 12 | albuquerque\n", "-----------------------------\n", "Data Retrieval Complete \n", "-----------------------------\n" ] } ], "source": [ "url = \"http://api.openweathermap.org/data/2.5/weather?units=Imperial&APPID=\" + api_key \n", "# List of city data\n", "city_data = []\n", "# Print to logger\n", "print(\"Beginning Data Retrieval \")\n", "print(\"-----------------------------\")\n", "# Create counters\n", "record_count = 1\n", "set_count = 1\n", "# Loop through all the cities in our list\n", "for i, city in enumerate(cities[:600]):\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 = 0\n", " # Create endpoint URL with each city\n", " city_url = url + \"&q=\" + city\n", " # Log the url, record, and set numbers\n", " print(\"Processing Record %s of Set %s | %s\" % (record_count, 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", " 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", " city_date = city_weather[\"dt\"]\n", " # Append the City information into city_data list\n", " city_data.append({\"City\": city, \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", " # If an error is experienced, skip the city\n", " except:\n", " print(\"City not found. Skipping...\")\n", " pass\n", "# Indicate that Data Loading is complete \n", "print(\"-----------------------------\")\n", "print(\"Data Retrieval Complete \")\n", "print(\"-----------------------------\")\n", "\n", " " ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>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>gorontalo</td>\n", " <td>0.54</td>\n", " <td>123.06</td>\n", " <td>75.36</td>\n", " <td>89</td>\n", " <td>69</td>\n", " <td>2.80</td>\n", " <td>ID</td>\n", " <td>1595256634</td>\n", " </tr>\n", " <tr>\n", " <th>1</th>\n", " <td>urumqi</td>\n", " <td>43.80</td>\n", " <td>87.60</td>\n", " <td>82.40</td>\n", " <td>34</td>\n", " <td>100</td>\n", " <td>4.47</td>\n", " <td>CN</td>\n", " <td>1595256634</td>\n", " </tr>\n", " <tr>\n", " <th>2</th>\n", " <td>saint george</td>\n", " <td>37.10</td>\n", " <td>-113.58</td>\n", " <td>84.99</td>\n", " <td>20</td>\n", " <td>1</td>\n", " <td>5.82</td>\n", " <td>US</td>\n", " <td>1595256634</td>\n", " </tr>\n", " <tr>\n", " <th>3</th>\n", " <td>bethel</td>\n", " <td>41.37</td>\n", " <td>-73.41</td>\n", " <td>84.00</td>\n", " <td>69</td>\n", " <td>1</td>\n", " <td>8.05</td>\n", " <td>US</td>\n", " <td>1595256634</td>\n", " </tr>\n", " <tr>\n", " <th>4</th>\n", " <td>east london</td>\n", " <td>-33.02</td>\n", " <td>27.91</td>\n", " <td>73.40</td>\n", " <td>25</td>\n", " <td>0</td>\n", " <td>5.82</td>\n", " <td>ZA</td>\n", " <td>1595256635</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>545</th>\n", " <td>vieques</td>\n", " <td>18.43</td>\n", " <td>-65.83</td>\n", " <td>87.80</td>\n", " <td>66</td>\n", " <td>40</td>\n", " <td>13.87</td>\n", " <td>PR</td>\n", " <td>1595256750</td>\n", " </tr>\n", " <tr>\n", " <th>546</th>\n", " <td>maniitsoq</td>\n", " <td>65.42</td>\n", " <td>-52.90</td>\n", " <td>48.97</td>\n", " <td>79</td>\n", " <td>100</td>\n", " <td>5.23</td>\n", " <td>GL</td>\n", " <td>1595256751</td>\n", " </tr>\n", " <tr>\n", " <th>547</th>\n", " <td>dhidhdhoo</td>\n", " <td>6.88</td>\n", " <td>73.10</td>\n", " <td>83.08</td>\n", " <td>76</td>\n", " <td>100</td>\n", " <td>20.07</td>\n", " <td>MV</td>\n", " <td>1595256751</td>\n", " </tr>\n", " <tr>\n", " <th>548</th>\n", " <td>la ronge</td>\n", " <td>55.10</td>\n", " <td>-105.28</td>\n", " <td>62.60</td>\n", " <td>88</td>\n", " <td>75</td>\n", " <td>3.36</td>\n", " <td>CA</td>\n", " <td>1595256751</td>\n", " </tr>\n", " <tr>\n", " <th>549</th>\n", " <td>albuquerque</td>\n", " <td>35.08</td>\n", " <td>-106.65</td>\n", " <td>77.00</td>\n", " <td>64</td>\n", " <td>40</td>\n", " <td>5.82</td>\n", " <td>US</td>\n", " <td>1595256687</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "<p>550 rows � 9 columns</p>\n", "</div>" ], "text/plain": [ " City Lat Lng Max Temp Humidity Cloudiness Wind Speed \\\n", "0 gorontalo 0.54 123.06 75.36 89 69 2.80 \n", "1 urumqi 43.80 87.60 82.40 34 100 4.47 \n", "2 saint george 37.10 -113.58 84.99 20 1 5.82 \n", "3 bethel 41.37 -73.41 84.00 69 1 8.05 \n", "4 east london -33.02 27.91 73.40 25 0 5.82 \n", ".. ... ... ... ... ... ... ... \n", "545 vieques 18.43 -65.83 87.80 66 40 13.87 \n", "546 maniitsoq 65.42 -52.90 48.97 79 100 5.23 \n", "547 dhidhdhoo 6.88 73.10 83.08 76 100 20.07 \n", "548 la ronge 55.10 -105.28 62.60 88 75 3.36 \n", "549 albuquerque 35.08 -106.65 77.00 64 40 5.82 \n", "\n", " Country Date \n", "0 ID 1595256634 \n", "1 CN 1595256634 \n", "2 US 1595256634 \n", "3 US 1595256634 \n", "4 ZA 1595256635 \n", ".. ... ... \n", "545 PR 1595256750 \n", "546 GL 1595256751 \n", "547 MV 1595256751 \n", "548 CA 1595256751 \n", "549 US 1595256687 \n", "\n", "[550 rows x 9 columns]" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "citydf= pd.DataFrame(city_data)\n", "citydf" ] }, { "cell_type": "code", "execution_count": 5, "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>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>Date</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>count</th>\n", " <td>550.000000</td>\n", " <td>550.000000</td>\n", " <td>550.000000</td>\n", " <td>550.000000</td>\n", " <td>550.000000</td>\n", " <td>550.00000</td>\n", " <td>5.500000e+02</td>\n", " </tr>\n", " <tr>\n", " <th>mean</th>\n", " <td>19.407873</td>\n", " <td>20.106836</td>\n", " <td>72.379345</td>\n", " <td>66.749091</td>\n", " <td>50.530909</td>\n", " <td>7.84720</td>\n", " <td>1.595257e+09</td>\n", " </tr>\n", " <tr>\n", " <th>std</th>\n", " <td>33.320904</td>\n", " <td>89.551897</td>\n", " <td>14.337919</td>\n", " <td>22.303396</td>\n", " <td>37.118453</td>\n", " <td>5.10221</td>\n", " <td>6.189054e+01</td>\n", " </tr>\n", " <tr>\n", " <th>min</th>\n", " <td>-54.800000</td>\n", " <td>-175.200000</td>\n", " <td>26.600000</td>\n", " <td>3.000000</td>\n", " <td>0.000000</td>\n", " <td>0.16000</td>\n", " <td>1.595256e+09</td>\n", " </tr>\n", " <tr>\n", " <th>25%</th>\n", " <td>-8.082500</td>\n", " <td>-60.302500</td>\n", " <td>62.500000</td>\n", " <td>54.000000</td>\n", " <td>17.000000</td>\n", " <td>4.07000</td>\n", " <td>1.595257e+09</td>\n", " </tr>\n", " <tr>\n", " <th>50%</th>\n", " <td>22.790000</td>\n", " <td>24.700000</td>\n", " <td>75.200000</td>\n", " <td>71.000000</td>\n", " <td>46.500000</td>\n", " <td>6.93000</td>\n", " <td>1.595257e+09</td>\n", " </tr>\n", " <tr>\n", " <th>75%</th>\n", " <td>46.930000</td>\n", " <td>97.932500</td>\n", " <td>82.400000</td>\n", " <td>83.000000</td>\n", " <td>90.000000</td>\n", " <td>10.29000</td>\n", " <td>1.595257e+09</td>\n", " </tr>\n", " <tr>\n", " <th>max</th>\n", " <td>78.220000</td>\n", " <td>179.320000</td>\n", " <td>116.600000</td>\n", " <td>100.000000</td>\n", " <td>100.000000</td>\n", " <td>28.07000</td>\n", " <td>1.595257e+09</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " Lat Lng Max Temp Humidity Cloudiness Wind Speed \\\n", "count 550.000000 550.000000 550.000000 550.000000 550.000000 550.00000 \n", "mean 19.407873 20.106836 72.379345 66.749091 50.530909 7.84720 \n", "std 33.320904 89.551897 14.337919 22.303396 37.118453 5.10221 \n", "min -54.800000 -175.200000 26.600000 3.000000 0.000000 0.16000 \n", "25% -8.082500 -60.302500 62.500000 54.000000 17.000000 4.07000 \n", "50% 22.790000 24.700000 75.200000 71.000000 46.500000 6.93000 \n", "75% 46.930000 97.932500 82.400000 83.000000 90.000000 10.29000 \n", "max 78.220000 179.320000 116.600000 100.000000 100.000000 28.07000 \n", "\n", " Date \n", "count 5.500000e+02 \n", "mean 1.595257e+09 \n", "std 6.189054e+01 \n", "min 1.595256e+09 \n", "25% 1.595257e+09 \n", "50% 1.595257e+09 \n", "75% 1.595257e+09 \n", "max 1.595257e+09 " ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ " citydf.describe()\n", " " ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Int64Index([], dtype='int64')" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "cityhumidity=citydf[citydf[\"Humidity\"]>100].index\n", "cityhumidity" ] }, { "cell_type": "code", "execution_count": 7, "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>0</th>\n", " <td>gorontalo</td>\n", " <td>0.54</td>\n", " <td>123.06</td>\n", " <td>75.36</td>\n", " <td>89</td>\n", " <td>69</td>\n", " <td>2.80</td>\n", " <td>ID</td>\n", " <td>1595256634</td>\n", " </tr>\n", " <tr>\n", " <th>1</th>\n", " <td>urumqi</td>\n", " <td>43.80</td>\n", " <td>87.60</td>\n", " <td>82.40</td>\n", " <td>34</td>\n", " <td>100</td>\n", " <td>4.47</td>\n", " <td>CN</td>\n", " <td>1595256634</td>\n", " </tr>\n", " <tr>\n", " <th>2</th>\n", " <td>saint george</td>\n", " <td>37.10</td>\n", " <td>-113.58</td>\n", " <td>84.99</td>\n", " <td>20</td>\n", " <td>1</td>\n", " <td>5.82</td>\n", " <td>US</td>\n", " <td>1595256634</td>\n", " </tr>\n", " <tr>\n", " <th>3</th>\n", " <td>bethel</td>\n", " <td>41.37</td>\n", " <td>-73.41</td>\n", " <td>84.00</td>\n", " <td>69</td>\n", " <td>1</td>\n", " <td>8.05</td>\n", " <td>US</td>\n", " <td>1595256634</td>\n", " </tr>\n", " <tr>\n", " <th>4</th>\n", " <td>east london</td>\n", " <td>-33.02</td>\n", " <td>27.91</td>\n", " <td>73.40</td>\n", " <td>25</td>\n", " <td>0</td>\n", " <td>5.82</td>\n", " <td>ZA</td>\n", " <td>1595256635</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>545</th>\n", " <td>vieques</td>\n", " <td>18.43</td>\n", " <td>-65.83</td>\n", " <td>87.80</td>\n", " <td>66</td>\n", " <td>40</td>\n", " <td>13.87</td>\n", " <td>PR</td>\n", " <td>1595256750</td>\n", " </tr>\n", " <tr>\n", " <th>546</th>\n", " <td>maniitsoq</td>\n", " <td>65.42</td>\n", " <td>-52.90</td>\n", " <td>48.97</td>\n", " <td>79</td>\n", " <td>100</td>\n", " <td>5.23</td>\n", " <td>GL</td>\n", " <td>1595256751</td>\n", " </tr>\n", " <tr>\n", " <th>547</th>\n", " <td>dhidhdhoo</td>\n", " <td>6.88</td>\n", " <td>73.10</td>\n", " <td>83.08</td>\n", " <td>76</td>\n", " <td>100</td>\n", " <td>20.07</td>\n", " <td>MV</td>\n", " <td>1595256751</td>\n", " </tr>\n", " <tr>\n", " <th>548</th>\n", " <td>la ronge</td>\n", " <td>55.10</td>\n", " <td>-105.28</td>\n", " <td>62.60</td>\n", " <td>88</td>\n", " <td>75</td>\n", " <td>3.36</td>\n", " <td>CA</td>\n", " <td>1595256751</td>\n", " </tr>\n", " <tr>\n", " <th>549</th>\n", " <td>albuquerque</td>\n", " <td>35.08</td>\n", " <td>-106.65</td>\n", " <td>77.00</td>\n", " <td>64</td>\n", " <td>40</td>\n", " <td>5.82</td>\n", " <td>US</td>\n", " <td>1595256687</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "<p>550 rows � 9 columns</p>\n", "</div>" ], "text/plain": [ " City Lat Lng Max Temp Humidity Cloudiness Wind Speed \\\n", "0 gorontalo 0.54 123.06 75.36 89 69 2.80 \n", "1 urumqi 43.80 87.60 82.40 34 100 4.47 \n", "2 saint george 37.10 -113.58 84.99 20 1 5.82 \n", "3 bethel 41.37 -73.41 84.00 69 1 8.05 \n", "4 east london -33.02 27.91 73.40 25 0 5.82 \n", ".. ... ... ... ... ... ... ... \n", "545 vieques 18.43 -65.83 87.80 66 40 13.87 \n", "546 maniitsoq 65.42 -52.90 48.97 79 100 5.23 \n", "547 dhidhdhoo 6.88 73.10 83.08 76 100 20.07 \n", "548 la ronge 55.10 -105.28 62.60 88 75 3.36 \n", "549 albuquerque 35.08 -106.65 77.00 64 40 5.82 \n", "\n", " Country Date \n", "0 ID 1595256634 \n", "1 CN 1595256634 \n", "2 US 1595256634 \n", "3 US 1595256634 \n", "4 ZA 1595256635 \n", ".. ... ... \n", "545 PR 1595256750 \n", "546 GL 1595256751 \n", "547 MV 1595256751 \n", "548 CA 1595256751 \n", "549 US 1595256687 \n", "\n", "[550 rows x 9 columns]" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "cleandata=citydf.drop(cityhumidity,inplace=False)\n", "cleandata" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "cleandata.to_csv(output_data_file,index_label=\"city_id\")" ] }, { "cell_type": "code", "execution_count": 9, "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": [ "plt.scatter(cleandata[\"Lat\"],cleandata[\"Max Temp\"])\n", "plt.xlabel(\"Latitude\")\n", "plt.ylabel(\"Max Temperature\")\n", "plt.title(\"City Latitude VS. Max Temperature 4/1/20\")\n", "plt.savefig(\"images/Max_temerature.png\", bbox_inches = \"tight\")" ] }, { "cell_type": "code", "execution_count": 10, "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": [ "#Latitude vs. Humidity Plot\n", "plt.scatter(cleandata[\"Lat\"],cleandata[\"Humidity\"])\n", "plt.xlabel(\"Latitude\")\n", "plt.ylabel(\"Humidity\")\n", "plt.title(\"City Latitude VS. Humidity 4/1/20\")\n", "plt.savefig(\"images/humidity.png\", bbox_inches = \"tight\")" ] }, { "cell_type": "code", "execution_count": 11, "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": [ "#Latitude vs. Cloudiness Plot\n", "plt.scatter(cleandata[\"Lat\"],cleandata[\"Cloudiness\"])\n", "plt.xlabel(\"Latitude\")\n", "plt.ylabel(\"Cloudiness\")\n", "plt.title(\"City Latitude VS. Cloudiness 4/1/20\")\n", "plt.savefig(\"images/cloudiness.png\", bbox_inches = \"tight\")" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 12, "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": [ "#Latitude vs. Wind Speed Plot\n", "plt.scatter(cleandata[\"Lat\"],cleandata[\"Wind Speed\"])\n", "plt.xlabel(\"Latitude\")\n", "plt.ylabel(\"Wind Speed\")\n", "plt.title(\"City Latitude VS. Wind Speed 4/1/2020\")\n", "plt.savefig(\"images/wind_speed.png\", bbox_inches = \"tight\")" ] }, { "cell_type": "code", "execution_count": 13, "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>0</th>\n", " <td>gorontalo</td>\n", " <td>0.54</td>\n", " <td>123.06</td>\n", " <td>75.36</td>\n", " <td>89</td>\n", " <td>69</td>\n", " <td>2.80</td>\n", " <td>ID</td>\n", " <td>1595256634</td>\n", " </tr>\n", " <tr>\n", " <th>1</th>\n", " <td>urumqi</td>\n", " <td>43.80</td>\n", " <td>87.60</td>\n", " <td>82.40</td>\n", " <td>34</td>\n", " <td>100</td>\n", " <td>4.47</td>\n", " <td>CN</td>\n", " <td>1595256634</td>\n", " </tr>\n", " <tr>\n", " <th>2</th>\n", " <td>saint george</td>\n", " <td>37.10</td>\n", " <td>-113.58</td>\n", " <td>84.99</td>\n", " <td>20</td>\n", " <td>1</td>\n", " <td>5.82</td>\n", " <td>US</td>\n", " <td>1595256634</td>\n", " </tr>\n", " <tr>\n", " <th>3</th>\n", " <td>bethel</td>\n", " <td>41.37</td>\n", " <td>-73.41</td>\n", " <td>84.00</td>\n", " <td>69</td>\n", " <td>1</td>\n", " <td>8.05</td>\n", " <td>US</td>\n", " <td>1595256634</td>\n", " </tr>\n", " <tr>\n", " <th>6</th>\n", " <td>ust-maya</td>\n", " <td>60.42</td>\n", " <td>134.53</td>\n", " <td>68.68</td>\n", " <td>61</td>\n", " <td>100</td>\n", " <td>14.38</td>\n", " <td>RU</td>\n", " <td>1595256635</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>545</th>\n", " <td>vieques</td>\n", " <td>18.43</td>\n", " <td>-65.83</td>\n", " <td>87.80</td>\n", " <td>66</td>\n", " <td>40</td>\n", " <td>13.87</td>\n", " <td>PR</td>\n", " <td>1595256750</td>\n", " </tr>\n", " <tr>\n", " <th>546</th>\n", " <td>maniitsoq</td>\n", " <td>65.42</td>\n", " <td>-52.90</td>\n", " <td>48.97</td>\n", " <td>79</td>\n", " <td>100</td>\n", " <td>5.23</td>\n", " <td>GL</td>\n", " <td>1595256751</td>\n", " </tr>\n", " <tr>\n", " <th>547</th>\n", " <td>dhidhdhoo</td>\n", " <td>6.88</td>\n", " <td>73.10</td>\n", " <td>83.08</td>\n", " <td>76</td>\n", " <td>100</td>\n", " <td>20.07</td>\n", " <td>MV</td>\n", " <td>1595256751</td>\n", " </tr>\n", " <tr>\n", " <th>548</th>\n", " <td>la ronge</td>\n", " <td>55.10</td>\n", " <td>-105.28</td>\n", " <td>62.60</td>\n", " <td>88</td>\n", " <td>75</td>\n", " <td>3.36</td>\n", " <td>CA</td>\n", " <td>1595256751</td>\n", " </tr>\n", " <tr>\n", " <th>549</th>\n", " <td>albuquerque</td>\n", " <td>35.08</td>\n", " <td>-106.65</td>\n", " <td>77.00</td>\n", " <td>64</td>\n", " <td>40</td>\n", " <td>5.82</td>\n", " <td>US</td>\n", " <td>1595256687</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 Wind Speed \\\n", "0 gorontalo 0.54 123.06 75.36 89 69 2.80 \n", "1 urumqi 43.80 87.60 82.40 34 100 4.47 \n", "2 saint george 37.10 -113.58 84.99 20 1 5.82 \n", "3 bethel 41.37 -73.41 84.00 69 1 8.05 \n", "6 ust-maya 60.42 134.53 68.68 61 100 14.38 \n", ".. ... ... ... ... ... ... ... \n", "545 vieques 18.43 -65.83 87.80 66 40 13.87 \n", "546 maniitsoq 65.42 -52.90 48.97 79 100 5.23 \n", "547 dhidhdhoo 6.88 73.10 83.08 76 100 20.07 \n", "548 la ronge 55.10 -105.28 62.60 88 75 3.36 \n", "549 albuquerque 35.08 -106.65 77.00 64 40 5.82 \n", "\n", " Country Date \n", "0 ID 1595256634 \n", "1 CN 1595256634 \n", "2 US 1595256634 \n", "3 US 1595256634 \n", "6 RU 1595256635 \n", ".. ... ... \n", "545 PR 1595256750 \n", "546 GL 1595256751 \n", "547 MV 1595256751 \n", "548 CA 1595256751 \n", "549 US 1595256687 \n", "\n", "[379 rows x 9 columns]" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "NHemisphere= cleandata.loc[cleandata['Lat'] > 0]\n", "NHemisphere " ] }, { "cell_type": "code", "execution_count": 14, "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>east london</td>\n", " <td>-33.02</td>\n", " <td>27.91</td>\n", " <td>73.40</td>\n", " <td>25</td>\n", " <td>0</td>\n", " <td>5.82</td>\n", " <td>ZA</td>\n", " <td>1595256635</td>\n", " </tr>\n", " <tr>\n", " <th>5</th>\n", " <td>busselton</td>\n", " <td>-33.65</td>\n", " <td>115.33</td>\n", " <td>50.00</td>\n", " <td>60</td>\n", " <td>100</td>\n", " <td>10.18</td>\n", " <td>AU</td>\n", " <td>1595256635</td>\n", " </tr>\n", " <tr>\n", " <th>7</th>\n", " <td>henties bay</td>\n", " <td>-22.12</td>\n", " <td>14.28</td>\n", " <td>77.50</td>\n", " <td>23</td>\n", " <td>0</td>\n", " <td>9.24</td>\n", " <td>NA</td>\n", " <td>1595256635</td>\n", " </tr>\n", " <tr>\n", " <th>8</th>\n", " <td>rikitea</td>\n", " <td>-23.12</td>\n", " <td>-134.97</td>\n", " <td>68.47</td>\n", " <td>57</td>\n", " <td>85</td>\n", " <td>13.09</td>\n", " <td>PF</td>\n", " <td>1595256635</td>\n", " </tr>\n", " <tr>\n", " <th>9</th>\n", " <td>codrington</td>\n", " <td>-38.27</td>\n", " <td>141.97</td>\n", " <td>50.14</td>\n", " <td>77</td>\n", " <td>70</td>\n", " <td>6.91</td>\n", " <td>AU</td>\n", " <td>1595256636</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>531</th>\n", " <td>talara</td>\n", " <td>-4.58</td>\n", " <td>-81.27</td>\n", " <td>66.20</td>\n", " <td>77</td>\n", " <td>14</td>\n", " <td>23.04</td>\n", " <td>PE</td>\n", " <td>1595256748</td>\n", " </tr>\n", " <tr>\n", " <th>539</th>\n", " <td>biak</td>\n", " <td>-0.91</td>\n", " <td>122.88</td>\n", " <td>76.53</td>\n", " <td>83</td>\n", " <td>25</td>\n", " <td>5.23</td>\n", " <td>ID</td>\n", " <td>1595256749</td>\n", " </tr>\n", " <tr>\n", " <th>541</th>\n", " <td>maceio</td>\n", " <td>-9.67</td>\n", " <td>-35.74</td>\n", " <td>78.80</td>\n", " <td>74</td>\n", " <td>75</td>\n", " <td>21.92</td>\n", " <td>BR</td>\n", " <td>1595256750</td>\n", " </tr>\n", " <tr>\n", " <th>542</th>\n", " <td>pietersburg</td>\n", " <td>-23.90</td>\n", " <td>29.47</td>\n", " <td>66.20</td>\n", " <td>34</td>\n", " <td>0</td>\n", " <td>6.93</td>\n", " <td>ZA</td>\n", " <td>1595256750</td>\n", " </tr>\n", " <tr>\n", " <th>543</th>\n", " <td>kununurra</td>\n", " <td>-15.77</td>\n", " <td>128.73</td>\n", " <td>64.40</td>\n", " <td>30</td>\n", " <td>10</td>\n", " <td>1.12</td>\n", " <td>AU</td>\n", " <td>1595256750</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "<p>171 rows � 9 columns</p>\n", "</div>" ], "text/plain": [ " City Lat Lng Max Temp Humidity Cloudiness Wind Speed \\\n", "4 east london -33.02 27.91 73.40 25 0 5.82 \n", "5 busselton -33.65 115.33 50.00 60 100 10.18 \n", "7 henties bay -22.12 14.28 77.50 23 0 9.24 \n", "8 rikitea -23.12 -134.97 68.47 57 85 13.09 \n", "9 codrington -38.27 141.97 50.14 77 70 6.91 \n", ".. ... ... ... ... ... ... ... \n", "531 talara -4.58 -81.27 66.20 77 14 23.04 \n", "539 biak -0.91 122.88 76.53 83 25 5.23 \n", "541 maceio -9.67 -35.74 78.80 74 75 21.92 \n", "542 pietersburg -23.90 29.47 66.20 34 0 6.93 \n", "543 kununurra -15.77 128.73 64.40 30 10 1.12 \n", "\n", " Country Date \n", "4 ZA 1595256635 \n", "5 AU 1595256635 \n", "7 NA 1595256635 \n", "8 PF 1595256635 \n", "9 AU 1595256636 \n", ".. ... ... \n", "531 PE 1595256748 \n", "539 ID 1595256749 \n", "541 BR 1595256750 \n", "542 ZA 1595256750 \n", "543 AU 1595256750 \n", "\n", "[171 rows x 9 columns]" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "SHemisphere=cleandata.loc[cleandata['Lat'] < 0]\n", "SHemisphere" ] }, { "cell_type": "code", "execution_count": 35, "metadata": {}, "outputs": [], "source": [ "def plot_linear(x_values,y_values,title,cordinates,filename):\n", " (slope, intercept, rvalue, pvalue, stderr) = linregress(x_values, y_values)\n", " regress_values = x_values * slope + intercept\n", " line_eq = \"y = \" + str(round(slope,2)) + \"x + \" + str(round(intercept,2))\n", " print(line_eq)\n", " plt.scatter(x_values,y_values)\n", " plt.plot(x_values,regress_values,\"r-\")\n", " plt.annotate(line_eq,cordinates,fontsize=15,color=\"red\")\n", " plt.xlabel('Latitude')\n", " plt.ylabel(title)\n", " plt.savefig(filename)\n", " plt.show()\n", " " ] }, { "cell_type": "code", "execution_count": 37, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "y = -0.46x + 91.77\n" ] }, { "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": [ "x_values = NHemisphere['Lat']\n", "y_values = NHemisphere['Max Temp']\n", "plot_linear(x_values,y_values,\"Max Temp\",(10,40),\"images/Nmaxtemp.png\")" ] }, { "cell_type": "code", "execution_count": 38, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "y = 0.83x + 86.4\n" ] }, { "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": [ "x_values = SHemisphere['Lat']\n", "y_values = SHemisphere['Max Temp']\n", "plot_linear(x_values,y_values,\"Max Temp\",(-50,30),\"images/Smaxtemp.png\")" ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "y = -0.04x + 68.51\n" ] }, { "data": { "image/png": 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gYgBnAfgqM99HRN8EcAWAO5OWLyq6tAk3n/K9+4fw3xt2wLk51e7+QWsvB6hl5vSz2Sfts66a+EyFtLc6VLE3+9ma3a53SyENVN8unTZvv+j4nn/5YKRrw3xXvO678zlWWU9TWctK+xlLmrQWmscAyBHRIIAmAC8BWAjg7wqf3wNgKQwcFLzym3jlJGFYu0o5UwGXl7FgRivWbd2FF/sGQASU70w46LFV4eAw46oVm3Ht/b3Fsr3k8MoXA6SbG75aksgX5Ee1WStV40icGrAJNDdli7mqnKhozzry96jcd+c5fpl4ddRVTyQ+KDBznohuA7ADwACAnwLYBKCPme0UnjsBuPY4EV0J4EoAmDLF3T4dF35aYZBWYtswt+96E0/u2OOpGUZxwnHmk/fSapbMacMDm/Ke8tWyfTRNr49qtV7V8w4yG/Mj1N2Tx5v7XLLtZtSy7erSvFXuezHx5MpeDLsoV6prWfXiWaRC4msKRNQC4DwA0wBMBjAOwIdcTnX9eWTmbzPzXGae29raGp+gLgRphU6brRfrn30ttHuoKvdueMHTdrysfSZuPX+mp2ZUr/bRuKnW3qz7vCToWrPNdfY6rlEt227SPv1da7a5DgjjGjPazJj1RBrmo/cD2M7MuwCAiB4EMA9AMxGNKcwWjgbwYgqyAfA2EQVphU5twmsj8jixzUNOOey2XL1iMyY353DJycdUzBj8tivM9w0UTU9tHtPmpDebT7o+P/y03nI5px6ew2/+vLtkZzEVu7dp9muv78Eel82bvPB6RpubsmC2ytJ1bz0j6Q/Eo5zFQZLPfBqDwg4ApxBREyzz0RkANgJYB+ACAPcBuAzAQynI5msiCmML9bPhh4VIzaxUPgtwa8sDm/JYMqetuIahsl2h3Q63RdSkNzU3bRN1L3szgAo5nc+O0+R36/kzPdeY0h703NCZ07/8fjrXKXTd2yT2IIiTpJ/5NNYUNhDRKgBPAhgC0APg2wBWA7iPiJYVjn03jvq7e/JY+vCW4paULU1Z3HTuCSVfbi8TURhbqNdG5McfMQ47d+9TNiFlGwjZDKF/8GDgueX2Ua+2rNu6y3Wjdr/rnNdH2ZpSF6Zsoh6kuals8QmUbiGpq+64y9DpjRO00O53b1XbUOveQ0k/86l4HzHzTQBuKjv8ZwAnxVlvd08eHSt7S+yh5a6dfiaiMF4Iy9pnYvuuNys2A9m5e1+Fpu7UDJ3T5wm5LPYeGKoYEFqasnjnUYdWmCLK7aNRF0HDfJ50YI8JgUQqmpuqPGFnkzq0xmrL0OmNE3YrVJuwG2PpkjcNkn7mR1XuI68FssFhDtxIvoEI0zpXl5gHlj68BVet2IyrVmwumXE47fHlqGjqNvOXry3OaJw0NY7BD//h1MDro06bg7anjLI1pS5MMAWoaG4qW3zazF++VvlHSofWqKOMoNgL1R/gsFuhBrXhmvs3F/M82du62rLWyiBQTtLP/KhKc+E3sjo3ki9PBwBYGp0dkt+xqhfXrNhc8oNtzzhu7H6qGMIfRQ6V81Svj5piwasP3K5POmWwCSmKve6t87hfH7pdp5rmQYfWGKfmGTaFRVA/ed1b7/QmI//3DQyiY2VvKvsr6CTpZ35UDQp+I6tzI/klc9p8g1oGhxluFv7BYWvxMMiWXK0bour1UV3/nNcB/ikwVOvQlSzQhBTFXs+G87ibnPOPm+h5rWqaBx0pF+JM2xA2hUV5P7U0ZV23Ci1/fpqb3JPvlTN4kGs+cV3Sz/yoMh91LJpesaYAlAbddPfk8cCmvDbPITcWzFCLr9CxQBZ12hzmuqBzdXtPpG0K8Ho2yo97yem1daOKpq7jmYhz4TXKLCTK82M7YPjl81Kpu1ZI8pkfVYOC3alhvY90s/p3LwUGzdh22YHB4aJ7a4aoROtyPiQ3dj+Feze8UPxhIljRfw0EHDKmAfsGD2JCLgsiy9QVFHsQFj87sikeQ9Vit9EL1fTkfutW3T153z7RsWgatQyVtYI47N+uyfcOMppzWYw7ZAxe7BtAg48LuEq/CiOMqkEBCB5xVbSKbIYw7GFCUsHeBlE1SZr9sHvFC9zY/VSF+6v99TjIwEDBe8m5BuIXexCWoJmACR5D1eKWqNBJGE3bK2BtmFnpXujQGsOWoTrbi2MW4hcst/mmDxbl61jV6zpzUO1XwWJUrSmo4JeS17bndV0wC1/58ImeG5fY5/vhp3GqzFacM4ZqtrK0y7r2/l6tG5445Ys79XASG7f73ZOwNl7bRtzg8oiYunmL6lpBHPZvleenfXYbui6YhRaPtQZT+9VERt1MIQiVlLw29gKY1/kAIm2DGNY7Scf6RzUzh6CZQJw27KSiPb3aSICSe7EbHslvlV1ZkyTMbE+3/Vv1+bHrrWbNRpBBoYKw9tag853rF06CPKFUfhjsMnSm1ADC2/uD7MhxBg8ltV6h21bup7VG3Zo0ToLa392Tx82PbCmmqchlGzA2m0Fff2UOo7DR1GGen+6evOf6wuTmnFF5s0xFBgUXwmo6fucvXXxCaC05bJI0r5Qa1aBjwxNnG+PynkhqvUL3bCdoq0jTCEr8V27PHxg8WFzLcs7egMqcULrWUexZo1v/5bIZLJjRalTeLFORQSFmomjJbtf4JUmzPZmieB95zTJ0b3gSF0lFe1bbxnINdUIu6zqDBNS9mJLEr/3zl68NdA112vRVZ3ZhtXqvdR97gyLVWWU1s4l6mIkQG6iVqDJ37lzeuHFj2mLUNH5rIrXwMNeC/G4yenmwZTOErgtmGSO7Cl42/HJso5jbuQRg+/Kzi++j3FcvOeyygz6PWm81MqcFEW1i5rlun8lMwUBUtA1dGol9jdMefMiYeJzS4tCidGvwcWh2Xpvcj2vMoP/AcPGHalxjBv/6t8n8gOhsd9g1MJWZXZS1oqBZo8qsspo1qnqJx5FBwTBUvGni8LjZ58jE2jcwqN3WGqeXUNT1irQ9l/aWbfLi5Y2kG93t7lg03TNGwMa5/qKyNhNlrSho3UdlXaiaNap6iMcBZFAwDhVtQ7dGkoSGY6IWFSRTkDbttjtdc2Hdxul1o6pJDwwO4+oVI1k+y6Ptk2p3WNxmm37eR7YMuiOjvdbinDsPBm0wVc0alQkZfHUgg4JhqGgbujWSJDQcE7UoP5mCtGmvqHPn4rF9zZI5bRVboHrh1LXL9/rQRRz3IsxsTeXcqN5ezrK9dh70s/FX42VW65v52EhEs2GoRG/qjhCOO+I4qTrC4idTUASvao4se/+MW8+fGSn+wN7rQycm3otydERGh83YWm29cURzp8HonCm88grwpS8Be/cCEye6v1pagMMPB8aO1Vp1kElCRdvQrZGELS/KIqVXHQtmtGL+8rWpuPD5tfvqgEj0KPsXRI0/CKor7P2oFY3Wa0ah2t6oM6JqYmriisdJktE5KHzqU8CDD6ZSdXvhVeSGys/PmtCMV8aMw2uNTRgY34y24ybjmN1HFwes9okTceQkxve2vo4/DWWRO2IS/uHcuTivigcZUI8YjRp8VF7HghmtJWaVpIOJ/NrttXNekCeLG81N2ZLgLTf8otL9NPgo9yPNuJJqCdPeerHxJ83ojFN44QXg8suB3l7gtdeA4XhTZdcrQ9SAvtyh2DP2UPSPPwwzZ04bmWX5zcBaWoBMBvOXr3X90rY154r5hNIKBgryOQ/Kmuq85pAxDZ6Bas48WV57ffjFLaj0oYlEva9e7c0Q4csXlfZTLcUNJI3EKZRzzDHAY495fhzmYQpzrh08M2Z4CIft34vmgTfQvO8NNO97E3ctPs4aoIJeBjGGD2JS/x5M6t8DvAZgx+9DXb/e78PCDCpoZqVMY6P3QOUykLUfeSQyHzoOy5/YgRf37Kv44XJq20HeR16mKAAVz4nfXh9umLiAH0Q1LrFe7XJLj13LM6I0GZ0zhQC8tJHmXLaYvz3oXDdNLW6tzkv7qioYbv9+YPfu4qB0/bd/juG//hUTBqzBrHnfG2geeANHDvXjpGYaGbz6+qpuTz2zP5PFwCE5NLe2AOPHh3+NGweMH48L/ut3+PM+wt7sWOwf0wg4tk41cabQ3ZPHtff3uprKVGT2+g6FKcNPttEygMhMISRe2kjfQOXmOGE0tTRSSG98/rVAu32g5vaWt1gvAKeOm+adKjzkFyholqWSlqCEgQH/WZZjcCt5vfGGu4C5nFVmDBwyPIhD+geB51+vqpxVfh9GnVWVk8tFG7jKXmu2v4F/W/s8MtSI4cyY4gBmE3U70rBluJFUIGMtIIOCC36LiOUBPmEWs+Kcznq53zmT5DmPRwmGs9Mjl58bNS1GUH949S3D0hgr+i6XA9rarJeDogbIA5g8NT4N0M/efcnJx4wETU0Yi+sXTMXit00A3nyz6tf+Pa8Db76JQ4bc1y2qZmDAeu3aVVUxiwovX/7N/+MKc2IZ/Y1jge9N8B2c/rCX8fP8AF4eHgOMH4e92Rx2IYtZjWOxN5tDv+PvV368RQYFwdJGVDfHCav9x+Wy5mdrDTpfZbbjt91hNWkx/PrDTytU1eSS1AD97oFn0NSkSVXXe0jVJfjAbA0IGgav/M6/YNzgAJoO7EPjwaFYxG06sA94ZZ/ldu7B2wsvZW6sVioXiKqbeU2ZArzrXTEIJoOCK+2z20pC9p2UzwBMWczy0qpVUmOrJgrzy20TR8qK8sXcKHWGTengZle2ywm6v34zzLRTekS2lxMBTU3W64gjRsr6xTa82HcIJjc3K5d1UQjPoaC2lG9e1ZzLYuk570D79BbfgWn5yt+C9u5F04F9GHdgAE2Dbn/3oenAAMYN7kPT4ADGHIy6G7sPzJbZ0st0qcKvfw2ceqo+mQrIoODBTeeqb45jQsCK14zFLcVClGC4ahKCVYPdt1G3WAyz5uM2q+hY1Qswiq6ifjONuOzd1aJztlRNWWG2uvWr3811d++BIaChYUST9rj2m1tbleqJIlsohoaA/v7oM6/jjwfe8x79ckEGBU9MmQGo4ifv3GMn+rZDpa0qwVpxBgVFDUQKc51XiutyvLR++72Xd01aQVM6E+B5lXXt/b3FpHNe3xPV75TfrKZrzbaKAQGw7tO19/vniQqTLqQt7u/7mDHAYYdZL8OQQcEHE2YAYfCSV6UdQecEpUeOO01CVM+tMNdFSV1Rjt2HJqWR0BnLELR2FTRzCHrOgmYiQduY+tWt0l4JbpNBYdTjlv7ZTUuy/3eutdhbfsahVblpi/aWim4apJd2Wa6dNjdlwQxcvWIzutZsU/J2ciNsCuc0Z5k60z2o9FHUWYhXDIOzvKD6/er2upYcn3ulRzfhPiaFBK+NYvxSNaSpMYVNT6B6fpTUFdkMlawpBMliIjrTPaim9/CMJYlYrl3ejd1P4Qe/2RGp7rieq1rEL3hNycGciDJ6RRJMwC/9c1CK4TgJm/JY9fyg89pnV6Y+7rpgFrounIWWpmzxGpW4jO6ePOYvX4tpnasxf/ladPfkA6+JC7d2Rf1hKy/LKx142FlIUCryBiJ09+SxbmtwrIRX3WH7IUrqbZPue1RUzUd/IqJVAO5m5nAJbgRjieq5EzdhbeCqx1XOc7N5d/fkQ21XamJ0rM71MWdZXtp02PWToGfNXi9QSUDoV3eYfgj7vJl436OgOii8G8DFAL5DRA0A7gJwHzNHitEnomYA3wHwLlhm6csBbAOwAsBUAM8BuIiZd0cp33RMsVMG2Wd1esuEaXNYG7jK+d09eTQoxGy4EXbbzv4DQ7FsParah0k+X27rJwtmtGLpw1tCbSuqulbhl2Jc99pW2Ih6E7ecjYKS+YiZ32Dm/2TmeQCuA3ATgJeI6B4ieluEer8G4CfMPAPALADPAOgE8DgzHw/g8cL7usPWJvJ9A2CMaBNpTDM7Fk1HLutuGdTpLRO2zW5y+ckTdL5dv9uPiUo7VbbtdLbNLejRrxwVVPswjeerfXYb1ncuxPblZ6Nj0XSs+L8XSgLL7G1F/WTwexadDDO73uvbP3wi1ncu1Prj6yeTW7/WYsZaN5TXFIhoMRH9CNYP+pcBvBXAIwB+HKZCIjoMwGkAvgsAzHyAmfsAnAfgnsJp98A/xUnNEsVOGRdOGyswYh/WvY1g2DaHtf0GnTaAsvoAACAASURBVO9lr84QKbUz7LadYctRQde6iR867OF+cQRhtsH0Wquw722Y9RG7XVM7Vxdfx93wY9zY7b/xUfn3o5zyfq2FbU5VUDUf/RHAOgBdzPxrx/FVRHRayDrfCmAXgLuJaBaATQA+D+BIZn4JAJj5JSI6wu1iIroSwJUAMGXKlJBVp49p2kQSsRhR2hxWLr/zvcwSw8xKdUTZtrOcamdeOtdN3NBlD/erJ8w2mH5rFWGeDS+vpmHmohfTsvaZgTJN7Vzt+rnz2aqVbU6DUE1v+ffMfIVzQCCi+QDAzJ8LWecYAO8BcCczzwawFyFMRcz8bWaey8xzW1vVQ9ZNoV60iTCk3WYvrdPreDl+MxGvNjTnslo3cFftw6h9rWsG61dPmPuty2MqaCZ374YXlMpReYZ0enmliepM4euwfsidfMPlmAo7Aexk5g2F96tgDQqvENFRhVnCUQBejVC28dSLNhGGtNvstTBpHy9fmF0wo3UkzbVLIJwTr7YtXey/sBoW1T5UPa+8zV6zqbAz2I5F0z23FQ17v6uZxTqDMv3wejZUzys/XmtZENzwHRSI6FQA8wC0EtE1jo8OAxApdoGZXyaiF4hoOjNvA3AGgN8XXpcBWF74+1CU8k3HtGjXJEi7zW0eP3ptzTlXs4kzOEolbQMQf9tU61E5z63NdnR6OWFnc3Y9YbcV1YlqgB2gPlv0e4bqDd+IZiL6GwCnA/hHAN90fPQGgEeY+Y+RKiU6EZZLaiOAPwP4OCxT1v0ApgDYAeBCZvbdlFgimgUV/CJTVbRJoHKbR1PciqPgtRlQ+cBgSvRu2L4O2rLTybjGDPoPDAeWW2/RzZG342TmJwA8QUTfY+bndQnEzJsBuAl0hq46BMHGT3tWXSgu33ColoOUvExCdh4rkwa6KH2tYvIiAA0NhL0H1MpNe7abJEHmo9uZ+SoAdxBRxZSCmRfHJpkgaMTL1quaBK98w6FaDlLyanM1m97HRZS+9mpfS1MWPf/yQQDus4mgcuthvUCFIO+j/yr8vQ1WbEL5SxBqGpWgKdUNh2olSClscGCaROnrjkXTrUSGZby5b6gYe1Hr9zBOgsxHmwp/n0hGHCEMtWzXNgWvNA1u3kc2OlNRA8nfxyimkLSetSh93T67rWK7TsDKdBuUgrvZkfhwtBJkPnoK7k4JAABmfrd2iQQlat2ubRJhzQI6XWzTuo/VBIAl+axF7es9ZQOCjT0T8No0yp5NjObvUFCcwjmFv58u/LXNSR8B0B+LRIISYZO06dLs0p6dpF0/oHfR0eT1CT9f/ygyRrl3Ufs6aIahMpsYrQSZj54HrOhlZp7v+KiTiNYD+EKcwgneqCRp063ZpT07Sbt+J7oWHU21bav4+oeRsZp7F6WvVWYYQbOJ0YpqRPM4InovM/8KAIhoHoBx8YklBOGnCcWlfeoqVzWCOI76TZhpONG9PqELlUR/YWTUde9Ug+JUZhjV9r1pz5IuVAeFKwDcRUQTCu/7YO2BIKRElCRt1WpAOrTaaiKIq63fpJmGTdopQLwI6tOwMuq4d+XpM+yU3IB3bIHffa2m7018lnShup/CJmaeBWuznVnMfCIzPxmvaIIfUZK0lW86EzZNso7EdioaqFcitmrr1522XEeqadOSqNlt8ssIFEVGHfcuSkpuP6rpe5NS4OsmyPvoUmb+QVneI1AhXwgzfyVG2YQAwiZpK990JqyWo0OrVdUM3c6rtn6d9nudmqIpQVFB6wjVpHWI694FfRZE1L43dS1IB0HmI3vd4NC4BRH0EWRPjWrf1eF1MyGXrfD4cMNNg6y2fp32e68+vPmRLUbYmaPYu29+ZIvngFDtVpdx3Tv7s6QxdS1IB0HeR98q/L05GXEEXfhpQNVoOdWmM957YCjwPD8Nspr6ddrvvfpqd/9gcTvOtOzMUWYx3T15z21ECdCS/qLae6crJbcOTF0L0oHSQjMRTQPwWQBTndfUa+6jpLwKailKVAdda7ZVBAsBQLYBOMjWhuwZIiyZE485RWd8gWrOpDRiDqLMBP1s4SZovyak5HaTx4RZoW5UvY+6Ye2p/AiAg/GJkz5JeRXUYpRotXhp14MHATtwfpgZD2zKY+6xE2MbGHSU69aHXiRtZ44yEwzKJWQCpqy92Jgmjy5Ut+Pcx8xfZ+Z1zPyE/YpVspRIyqsgTe+FtDxeVDXOWvDicOvD5px73pykNW3PLUKbsp7eUn7bitbjD5/gjepM4WtEdBOAnwLYbx+sR7dUL5OA6qYdqqTtvZCGlmOydh2F8j7022w+Sdz6OZshvLlvyHO9w29bUWF0oToozATwUQALMWI+4sL7uiJD5Lofq+q2farUs/eCF2522P4DQ64LnLXYD6bYmd3k2Lt/qMLry7nOYIrsQvr4bsdZPIloK4B3M/OB+EVSJ47tOKd2rvb87LnlZ2urp96294tKLfZDLaY3mNa52jMgzbTd1oT4ibwdp4NeAM0AXtUmlaEktUG3aGYWtdYPtZrewGtmShgxjdZKW4R4UZ0p/BxWiovfonRNIVWX1DhmCrWouQrJ4bUpvIlbWTpxe64J7pulmN4WJybP2kyWTcdM4SaN8hhNrWmuQrKk7SAQFbfn2st5wvS22Jg8azNZtiCUBoV6dT/1ohb9j03WSsJiclt0Ogh09+Rx8yNbigvtzbksli6OLxir/Ln2mvXUyiK/yRsUmSxbEEpxCkT0BhG9XnjtI6JhIno9buEENWytJN83AMaIVhIla2famN4WXZved/fk0bGqt8Tzqm9gEB0rexNrq662pIXJszaTZQtCNXX2ocx8WOE1FsASAHfEK5qgiklpfKtNJ21SW9zQFfjnlfLD3g4yCdpnt2HJnLaiu3WcKUbiQEcq97gwWbYgVNcUSmDmbiLq1C2MEA1TtBIddlRT2uKHDvNiXKmgw9Ddk8cDm/LFuJy4U4zoxuSkdCbLFoRqQrzzHW8bAMyFu+OCkAKmBMLpsKOa0pa4SSMVdPlaTf+BIePs3mHWk0x2CjFZtiBUZwrnOv4fAvAcgPO0SyNEwhStRIeWb0pb4qZj0XR0rOqtMCFlG+JJBe02i/MirVlZlJmmyU4hJsvmh6r30cfjFkSITlStRLeXjw4tP00NKw6vJ68y7XKT8j5S2QbVxu1+JeERZqLHTndP3ph03UkRtB3nN+BjJmLmz2mXSIhEWK0kDj9qXVp+GhpWHP0RVGaS7VTV/t3uV1I+96atJ3X35Cs29tndP4iOVb0AzI83iEqQ99FGAJsKr8WO/+2XEAIdG73rIg4vn7RScusgjv6IUma1z4jX9X6psYPuV1IeYaZ57HSt2Vax0xsADA4n5yGWBkHbcd5j/09EVznfC+EwLcIxLq2sVu2ocfRH2DKrfUb8rvdLjR1UdlIavGnrSSZ4iKWB6iY7gHgbVYVp/vemaWVpE0d/hC2z2mckyCYfdRaX1LNi2kzTr331/D2JFKcghMc0e6lpWlnaxNEfYcus9hkJuj7qLC7JZ8WkmWbHoum4ZsVm1/2HF8xoTVyepAhaaH4DIzOEJkdqCwLAzHxY1IqJKANrzSLPzOcQ0TQA9wGYCOBJAB81bf+GakjC/z5tH2+TcxYFEUd/hC2zmmekuyePBo8Noqp9xmrZ574a2me3lXiHOVm3dVcKEiWDUursWComugZWENxhhUHhfgAPMvN9RPRNAL3MfKdfGXGkzo6LuFNyp53yO+3664Gofeh2nZNLT5mCZe0ztcs7GvDanIgAbNe46VbS+KXODrOmoA0iOhrA2QC+U3hPsLb2XFU45R4A7WnIFhdx20vTXrNIu/56IOozEhSDUM9abdyMxrW3tNYUbgdwHYBDC+8PB9DHzEOF9zsBuH4TiOhKAFcCwJQpU2IWUy/V2kv9zDNpr1mkXX85tWrKivKMBPWx8/Na65e0g8dG49pb4jMFIjoHwKvM7IxzIJdTXe1azPxtZp7LzHNbW+t3saecoJTSaWs0adfvxPT027oJ6mP781rrFzt4zB4QgJHgsaRkNs0jKgnSMB/NB7CYiJ6DtbC8ENbMoZmI7JnL0QBeTEE2Ywkyz6SdGz/t+p2MNlOWW9/bOO9BrfWLKcFj7bPbsL5zIbYvPxvrOxfW9YAApDAoMPMNzHw0M08FcDGAtcz8EQDrAFxQOO0yAA8lLZvJqLgbpqnRpF2/E9NMWXHj7HsAxf0Ryu9BrfXLaA0eSxuT4hSuB3AfES0D0APguynLYxQq7opp+3inXb/NaEm/7USl72utX9JILy6k5H1kw8w/Z+ZzCv//mZlPYua3MfOFzLw/TdlMwyTzjOlIX7lTa/3SsWg6sg2Vy43ZTDzpxQULk2YKgg+jNYAoCtJX7pT3S3NTFszA1Ss2o2vNNuP6yJYlqveRm6cVIM9FEKkFr+mgloLXBMEk6j3Y0K192QYCCCUbG9VTm8NgXPCaIAjpUmueSGFxa9/gQa7Y6a6e2qwLGRQEYRRSa55IYQnTjnppsy5kTUEQoDfSt9qyunvysW/TGdUTqVYiov08l9zOFUaQmYIw6tEZ6VttWd09eXSs6i3JzNk3MIiOlXqjeKN4ItVSRLRb+7INhGym1JvJZO+rtJBBQRj16LSv69gop9zuDVj2cJ227yjBhrW0DuHWvq4LZ6HrgllGBFiajJiPhFGPTvt6XBvlRJXHj7DBhrW2DuHVPhkE/JFBoY6oFXuvaeiM9A1Tltv9SiuKV+XZqbWIaCEaYj6qE2rJ3msaOiN9Vcvyul8LZrRW2L0Byx4el+1b9dmptYhoIRoyKNQJtWTvjUJ3Tx7zl6/FtM7VmL98rdbBTmcyP9WyvO7Xuq270HXBLLQ0ZYvHm3NZdF04K7ZZn+qzY1LSQyE+xHxUJ9SavTcM5dGptiYL6LMP60zmp1KW3/1KOrFgmGfHlKSHQnzITKFOMGmTG93U4yzIpPsVJEucszTBPGRQqBPq2d5bj7Mgk+6XnyyyVjX6kEGhTqhne69JWrUuTLpffrLU4yxN8EeypArGU01GT9X0yW7H6mFArZZpnatdN0snANuXn520OIIm/LKkykKzYDxR90dwW6DuWNULMIp7/+b7BtCxsrckpXIcC9m1isQmjD5kUBBqgiheL67pkz1SSJRjm0hMGRTSCkzsWDTddZZWD2tVgjsyKAh1S7UL0aYsZCfhkuuF7GI3+pBBQahbwqRP9rpeB9Vq+X6Lve2z22KfRUhswuhCvI+EusU1fXKGKjaDjzOlsg6XTj+XXHEZFXQjg4JQt7imT75gFrounJVYSmUvLX/pw1uUy2h2pLxwMrk5Jy6jgnbEfCTUNWHSJ8dhIvHS8vsGBtHdk1fyoNrj2HDHyYIZrfjhb3aEqlcQgpCZgiDEiN+6hIo237VmGw56fLZu6666DOwT0kUGBUGIkQUzWj0/U9HmgzbdMSldhlAfyKAgBMMM3HILcMwxQC4HnHYasHmz2rUPPQTMnAmMHQu8853AihXe5x48CMyZAxABjz6qR3Zd/PWvwCc/CbzlLVYfzJgBfP/7peds3Ah88IPA4YcDEycC738/XvnpLzyLLGrzU6dabXa+3vKWknOO3f0ibvnJHfifuz6DZ7+0GPf9dycmN+eMSpch1AeypiAEs3w58MUvAl1d1o/hV74CvP/9wNNPF3+8XPnVr4AlS4BPfQr4+teBH/8YuOQSoKXF+vEs5zvfAfIGes28/ro1EI4fD3zjG8CkScDvfw8cODByzgsvWH3ynveMDBZdXfjyd6/Dhy6/A/kJR1QUW6LN/93fAZ/97Mj7xsbiOR0re/H2v+zA6X/eiJ7J05EdHgLRyKY74jIq6EQGBcGfffusQeGGG4DPfMY6duqplnZ7xx3AsmXe137xi9aP6de/br1fsADYsgX4whcqB4Xdu4F//merrk98IpamALDkXroU+NjH1K+55RZg/35rJpAraPcLFpSes3o18MYbwIMPAs3N1rF58zDu8ElY8OeN+MHss0pOb85lS3/IjzoKOOWUiqrtc27ubsC8463P7+y+BS39rxfXJGRAEHQi5iOTWL0aaGgAtm8vPb59u3X84YeTl+nXv7Y05YsuGjk2bhxw7rnA//yP93X79wPr1pVeBwAXXwz87/8Ce/aUHv9//w+YPx8444zKsn7zG2DMGOCuu0aO7dljmbMuvTR8m8Jy993AFVeMDAhuDA5aMo4fP3Js/HhgzBg0NlTGQCxdfIJy9e2z29Bz85m4/cMnIpfNwM5hKTEJQhzIoGASZ54JTJ4M3HNP6fHvfQ9obQXOOsv1MgDA8DAwNOT/Oujlx+LD1q1AJgMcf3zp8Xe8w/rMi2eftX4oZ8yovO7gQeAPfxg59rvfWT+8t93mXtYppwAdHcDVVwM7Ci6Yn/ucVc43vhG+TWHYvh149VVL+z/rLMus09oKXHNNqfloyRKgqQm49lrr/FdfBa6+GpmJLZjbcWWwzf+uu6yyJ0wALrgAeP75ClGqiUmQjXIEVcR8ZBKZjGXWuOce4KabrAVHZuv9Rz9qaaJenHEG8MQT/uVfdpk1wIRh925L482UerigpQXo77d+GAv274rrgBFTivM65+eAZUv/9KeBt70NeO45dzluvtmaSV1+uXX+979vvbfL82JoqPLYwYOlxzMZq6/dePll6+9111mznJ/8BOjtBf7pn6z78aUvWZ9PnmzNjM45Z8RcdtRRwJo1OGvWu3HWQh8ZzzvPGviOPhp45hmrre97H/DUU9YgUSDqZkNp5k4Sag8ZFEzj8sstG/bPf27Zrdets7TGj3/c/7pvfcuyafsxaZL3Z8zWbMOGaGQgcPvBtG0YXj+mznL8rrvvPmDbNuCRR/zLaWy0BoKTTrIWsD/xCf+Zk03WJRr4iiusl83dd3uvMdizqxNOAP7zP63/Fy60+vqWW6z1iaYm4KWXLA1/zhxrwRwA/v3fgbPPtkxwU6Z4y/i1r438/773AfPmASeeaMl11VXFj6KmsQ7KnSQITmRQMI23vhU4/XTrB2HBAuvvSSdZP0p+vO1tIz+4XjT4WAufeKJ08fRv/sYamFparB/A4eHS2UJfn/Vj6PajC4xo8H19pcft983NlnmpowO4/nrrx7evz1q/AIC9e616Dz105NpZsyy31t5ey6NJhd/+tvT94sXAlVdaGr3NtGne10+caP0tX1heuNCazT37rOVy29VlzT5WrRrpk4ULLbPbbbeNzB5UeNe7gOnTgSefLDlsp7F2ohKTUI/bmQrxkfiaAhEdQ0TriOgZItpCRJ8vHJ9IRI8R0R8LfwPsAnXMJz4BPPCA5Z754IPBswTAMh9ls/6vyy/3vn7OHOsH1H5961vW8RkzrAHhT38qPX/r1sr1AifHHWfVWb7usHWrNTi9/e3WD//OnZZ9vqXFes2aZZ138cXA7Nml195++0i9n/2s2hrJ3Lmlr8ZGywPJeezww/3b4TCP2bb5i+5cDwB4fNuukXadcELpINnYaB179tlgOd0om2XZMQm5RmtwVo1JkKhnIQxpzBSGAFzLzE8S0aEANhHRYwA+BuBxZl5ORJ0AOgFcn4J86XP++ZaN/eKLrR++iy8OvqZa89Ghh1o/kOXMmwccdhiwciVw443Wsf5+y9xz5ZXe5R1yiKVdr1xpBX3ZrFhhubROmGBp1uvWlV738stWLMMtt1iats22bZbL6rJl1oL8nDnAV79qLezGSWMj8IEPAGvXltjmL3y+F/3ZQ3D1pjfxhePyaD/2WCsOw7nGsn+/Fctx7rnh6nz6aau9zn4r0D67DZh+BPCXBqzv9FuoGEE2yhFCwcypvgA8BOADALYBOKpw7CgA24KunTNnDtctn/40M8B8ySVpS8J8yy3MuRzzHXcw/+xnzGedxXz44cwvvzxyzj33MGcyzM89N3Lsl7+0jn3+88zr1jF3dDATMa9Z413X9u1Wux95ZOTY0BDzySczz5vHPDxsHbv1VuaxY5mfeSZcW449lvnuu8Nds2EDczbLj85ZxJde9AVedvrlvC+T5S+976N87PWP8rxbH2feuJF5zBirbx591JL/zDOtY5s3j5R1+eXMxx038v7RR5kvvpj5Bz9gXruW+T/+g3nyZOZp05j37Bk5b+9e5pUrrdcppzC/850j7/fuDWzCj57cyfNufZynFuT90ZM7w/WBUFcA2Mhev8leHyTxAjAVwA4AhwHoK/tst8c1VwLYCGDjlClTYukwI3jsMev2PPZY2pIwHzzIvGwZc1ub9UP83vcyP/lk6Tl3323Ju3176fEf/Yj5hBOYGxuZp09nvvde/7rcBoVbbmFuamL+wx9Gjg0NWT+OJ51k/a9KlEGBmfknP+GnjjyO92XGcP7QSXzbez/CU697mI+9/lGeev2j1jk/+xnz+97H3NJivU47zRoMnVx2mSWDTW8v88KFzJMmWQPIkUda5+TzpdfZ/eL2Ku9zQQjAb1AgDlqcjAkiGg/gCQD/yswPElEfMzc7Pt/NzL7rCnPnzuWNGzfGLWo6XHedZWqxA9eE1Jm/fK2r909bc07ZlCMIJkBEm5jZxV6ckvcREWUBPADgh8z8YOHwK0R0FDO/RERHAXg1DdlSZ9s2K6/OnXda3i0GDAhpbRpvmixBtnmT+kkQopL4oEBEBOC7AJ5h5q84PnoYwGUAlhf+PpS0bEbwyU8CGzZYrpOf+1za0hgV+JS2LH6b2KctmyDoInHzERG9F8AvATwFFPcP+ScAGwDcD2AKrHWGC5n5Nb+y6tp8ZAgmmUx0yRKHRu8lmy2fzBoEkzDKfMTMvwLgFQbrkg1NSBOTAp90yBKXRu8ng8wahFoifYO1YDQmBT7pkCWuje6DZNBRhyAkgQwKgi8mbfeoQ5a4Zj5usumuQxCSQHIfCb44F1fzfQPIEJVovUmaQ/wWelWJmlQO8F+LKO8nr7qjlC0ISZJanIIOZKE5Ocpt8YClpdfafsBR2xHmurB11EvfCrWD30KzmI8EJeKyxauia5OYqBvdh2l/2DrS7ltBcCLmI0GJNL2QdHsMRdnoPmz7w9RhkoeXIMhMQVAiTS8kEzTpONtvkoeXIMigICiRpheSCZp0nO03ycNLEGRQEJRon92GJXPakCls/JIhwpI54c0wUTBBk466FpF22YIQFllTEJTo7snjgU15DBe81YaZ8cCmPOYeOzH2Hy9TNomJshZhQtmCEAYZFAQl0tz8PUp8gp/fv8QECII3MigISqRt1w+jSft5KwGQbKaC4IMMCkIRPw26mkjgpPGa1Vx7f2/R/FX+WZgZj8w0hHpGFpoFACPadb5vAIwRDdoOEqslDxmv2YvbgBB0TTlB/SQItY4MCgKA4FiAWvKQiTJ7Ub3GhJgJQYgTMR8JANTWDEz0kHEz5bh5K/kRZsaT9tqKIMSNzBQEAGbEAoTFy5QDoGRWY8dWuBF2xlOL/SQIYZBBQQBQW2sGNkFusus7F2L78rPx5Ytmubbt9g+fiPWdC0PNfmqxnwQhDGI+EgDo2asgaVRNOTrbVov9JAhhkP0UhJpl/vK1rm6ybc05rO9cmIJEglAbyH4KQl0iphxB0I8MCkLNkmaSPkGoV2RQEGoWryR9EkgmCNGRQUGoWSSQTBD0I4OCULNIIJkg6EcGBaFmkUAyQdCPDApCzSLeR4KgHwleE2oWCSQTBP3IoCDUNCYm6ROEWkbMR4IgCEIRGRQEQRCEIjIoCIIgCEVkUBAEQRCKyKAgCIIgFKnp1NlEtAvA8yEvmwTgLzGIowOTZQPMlk9ki4bIFg2TZQOC5TuWmVvdPqjpQSEKRLTRK4942pgsG2C2fCJbNES2aJgsG1CdfGI+EgRBEIrIoCAIgiAUGY2DwrfTFsAHk2UDzJZPZIuGyBYNk2UDqpBv1K0pCIIgCN6MxpmCIAiC4IEMCoIgCEKRUTUoENGZRLSNiP5ERJ0py3IXEb1KRE87jk0koseI6I+Fvy0pyXYMEa0jomeIaAsRfd4U+YhoLBH9HxH1FmS7uXB8GhFtKMi2gogak5bNIWOGiHqI6FEDZXuOiJ4ios1EtLFwLPX7WpCjmYhWEdHWwrN3qgmyEdH0Qn/Zr9eJ6CoTZCvId3Xhu/A0Ed1b+I5EfuZGzaBARBkA/w7gQwDeCeASInpniiJ9D8CZZcc6ATzOzMcDeLzwPg2GAFzLzO8AcAqATxf6ygT59gNYyMyzAJwI4EwiOgXAvwH4akG23QCuSEE2m88DeMbx3iTZAGABM5/o8GM34b4CwNcA/ISZZwCYBasPU5eNmbcV+utEAHMA9AP4kQmyEVEbgM8BmMvM7wKQAXAxqnnmmHlUvACcCmCN4/0NAG5IWaapAJ52vN8G4KjC/0cB2JZ2vxVkeQjAB0yTD0ATgCcBnAwrenOM271OWKajYf1ALATwKAAyRbZC/c8BmFR2LPX7CuAwANtRcH4xSbYyeT4IYL0psgFoA/ACgImw9sd5FMCiap65UTNTwEjn2ewsHDOJI5n5JQAo/D0iZXlARFMBzAawAYbIVzDPbAbwKoDHADwLoI+ZhwqnpHlvbwdwHYCDhfeHwxzZAIAB/JSINhHRlYVjJtzXtwLYBeDuguntO0Q0zhDZnFwM4N7C/6nLxsx5ALcB2AHgJQB7AGxCFc/caBoUyOWY+OP6QETjATwA4Cpmfj1teWyYeZitqfzRAE4C8A6305KVCiCicwC8ysybnIddTk3zuZvPzO+BZUb9NBGdlqIsTsYAeA+AO5l5NoC9SM+M5UrBLr8YwMq0ZbEprGOcB2AagMkAxsG6t+UoP3OjaVDYCeAYx/ujAbyYkixevEJERwFA4e+raQlCRFlYA8IPmflB0+QDAGbuA/BzWOsezURkby+b1r2dD2AxET0H4D5YJqTbDZENAMDMLxb+vgrLLn4SzLivOwHsZOYNhferYA0SJshm8yEATzLzK4X3Jsj2fgDbmXkXMw8CeBDAPFTxzI2mQeG3qTkbYAAAA0FJREFUAI4vrMo3wpoGPpyyTOU8DOCywv+XwbLlJw4REYDvAniGmb/i+Ch1+YiolYiaC//nYH0pngGwDsAFacrGzDcw89HMPBXW87WWmT9igmwAQETjiOhQ+39Y9vGnYcB9ZeaXAbxARNMLh84A8HsTZHNwCUZMR4AZsu0AcAoRNRW+t3a/RX/m0ly0SWFR5iwAf4Blg/7nlGW5F5YNcBCWlnQFLPvz4wD+WPg7MSXZ3gtruvk7AJsLr7NMkA/AuwH0FGR7GsC/FI6/FcD/AfgTrOn9ISnf39MBPGqSbAU5eguvLfZ3wIT7WpDjRAAbC/e2G0CLQbI1AfgrgAmOY6bIdjOArYXvw38BOKSaZ07SXAiCIAhFRpP5SBAEQQhABgVBEAShiAwKgiAIQhEZFARBEIQiMigIgiAIRWRQEIQCRPRmiHNPJ6J5jvf/SER/X/j/Y0Q0OUL9zxHRpLDXCYJOxgSfIgiCC6cDeBPArwGAmb/p+OxjsHzGTYuYF4RAZFAQBB+I6FwANwJohBW89BEAOQD/CGCYiC4F8FlYkaRvwspCOhfAD4loAFaGymdgpTb+CxHNBXAbM59ORIfDCmJshRVoRI56L4WVErkRVjLCTzHzcPwtFkY7Yj4SBH9+BeAUtpK03QfgOmZ+DsA3YeWrP5GZf2mfzMyrYEXlfqTw2YBP2TcB+FWh7IcBTAEAInoHgA/DSl53IoBhWIORIMSOzBQEwZ+jAawoJDxrhJXzXxenATgfAJh5NRHtLhw/A9ZmLr+10tkgh5STDwqjBxkUBMGfbwD4CjM/TESnA1gaoYwhjMzKx5Z95pZnhgDcw8w3RKhLEKpCzEeC4M8EAPnC/5c5jr8B4FCPa8o/ew6W5g8ASxzHf4GCWYiIPgQrARxgJVe7gIiOKHw2kYiOjSi/IIRCBgVBGKGJiHY6XtfAmhmsJKJfwtri0OYRAH9b2Mj9fWXlfA/ANwuf5WBlsfxaoQznYvHNAE4joidhpbHeAQDM/HtYi9s/JaLfwdpd7ijdjRUENyRLqiAIglBEZgqCIAhCERkUBEEQhCIyKAiCIAhFZFAQBEEQisigIAiCIBSRQUEQBEEoIoOCIAiCUOT/A2cqeS9QIPQKAAAAAElFTkSuQmCC\n", "text/plain": [ "<Figure size 432x288 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "x_values = NHemisphere['Lat']\n", "y_values = NHemisphere['Humidity']\n", "plot_linear(x_values,y_values,\"Humidity\",(10,20),\"images/Nhumidity.png\")" ] }, { "cell_type": "code", "execution_count": 39, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "y = -0.3x + 60.01\n" ] }, { "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": [ "x_values = SHemisphere['Lat']\n", "y_values = SHemisphere['Humidity']\n", "plot_linear(x_values,y_values,\"Humidity\",(-50,20),\"images/Shumidity.png\")" ] }, { "cell_type": "code", "execution_count": 40, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "y = -0.06x + 54.44\n" ] }, { "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": [ "x_values = NHemisphere['Lat']\n", "y_values = NHemisphere['Cloudiness']\n", "plot_linear(x_values,y_values,\"Cloudiness\",(10,20),\"images/NCloudiness.png\")" ] }, { "cell_type": "code", "execution_count": 41, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "y = -0.39x + 38.19\n" ] }, { "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": [ "x_values = SHemisphere['Lat']\n", "y_values = SHemisphere['Cloudiness']\n", "plot_linear(x_values,y_values,\"Cloudiness\",(-50,20),\"images/SCloudiness.png\")" ] }, { "cell_type": "code", "execution_count": 43, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "y = -0.02x + 8.36\n" ] }, { "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": [ "x_values = NHemisphere['Lat']\n", "y_values = NHemisphere['Wind Speed']\n", "plot_linear(x_values,y_values,\"Wind Speed\",(10,25),\"images/NWindspeed.png\")" ] }, { "cell_type": "code", "execution_count": 44, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "y = 0.03x + 9.15\n" ] }, { "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": [ "x_values = SHemisphere['Lat']\n", "y_values = SHemisphere['Wind Speed']\n", "plot_linear(x_values,y_values,\"Wind Speed\",(-50,25),\"images/SWindspeed.png\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Three observation trends: \n", " 1. The higher the latitue is, the lower the max temperature goes. The highest max temperatures occur within the latitude 20-40;\n", " 2. For the cloudiness, there is no clear correlation to the latitude.\n", " 3. There is no clear correlation ovbserved between wind speed and latitude. " ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.6" } }, "nbformat": 4, "nbformat_minor": 4 }