temperature

temperature.py

import requests
import sqlite3 as lite
import time
import datetime
import collections
import pandas as pd

#Cities to analyze
cities = {"Los_Angeles": "34.0522,-118.2437",
		  "Miami": "25.7617,-80.1918",
		  "Salt_Lake_City": "40.7608,-111.8910",
		  "San_Francisco": "37.7749,-123.4194",
		  "Seattle": "47.6062,-122.3321",
		   }

#My api key
apiKey = '05733033ea7b4253bf6224ef6a919782/'

url = 'https://api.darksky.net/forecast/' + apiKey

#Day to stop collection data
end_date = datetime.datetime.now()

#Create and connect to weather database
con = lite.connect('weather.db')
cur = con.cursor()

#Create daily temperature table
cities.keys()
with con:
	cur.execute('CREATE TABLE daily_temp ( day_of_reading INT, Los_Angeles REAL, Miami REAL, Salt_Lake_City REAL, San_Francisco REAL, Seattle REAL);')

#Set start date to collect 30 days of data
query_date = end_date - datetime.timedelta(days=30)

#Insert blank date rows to daily temperature table
with con:
	while query_date < end_date:
		 cur.execute("INSERT INTO daily_temp(day_of_reading) VALUES (?)", (int(time.mktime(query_date.timetuple())),))
		 query_date += datetime.timedelta(days=1)


for k, v in cities.items():
	query_date = end_date - datetime.timedelta(days=30)
	while query_date < end_date:
		r = requests.get(url + v + ',' + query_date.strftime('%Y-%m-%dT12:00:00'))

		with con:
			cur.execute('UPDATE daily_temp SET ' + k + ' = ' + str(r.json()['daily']['data'][0]['temperatureMax']) + ' WHERE day_of_reading = ' + str(time.mktime(query_date.timetuple())))
		query_date += datetime.timedelta(days=1)

con.close()

#Analysis
con = lite.connect('weather.db')
cur = con.cursor()

df = pd.read_sql_query('SELECT * FROM daily_temp ORDER BY day_of_reading', con)

city_list = list(df.columns.values[1:])

for i in city_list:
	max_temp = max(df[i])
	min_temp = min(df[i])
	avg_temp = df[i].mean()
	temp_range = max_temp - min_temp
	deviation = df[i].std()
	print (str(i) + ": Max temp: " + str(max_temp) + ", Min temp: " + str(min_temp) + \
		", Temp range: " + str(temp_range) + ', Avg temp: ' + str(avg_temp) +  \
		". Standard deviation: " + str(deviation))


month_change = collections.defaultdict(int)
for i in city_list:
	temps = df[i].tolist()
	temp_change = 0
	for k,v in enumerate(temps):
		if k < len(temps) - 1:
			temp_change += abs(temps[k] - temps[k + 1])
	month_change[i] = int(temp_change)

def keywithmaxval(d):
	v = list(d.values())
	k = list(d.keys())
	return k[v.index(max(v))]

max_city = keywithmaxval(month_change)

print ("Max city: " + max_city)
print ("Month change: " + str(month_change[max_city]))