import csv
from datetime import datetime
from matplotlib import pyplot as plt
filename = 'sitka_weather_07-2014.csv'
with open(filename) as f:
	reader = csv.reader(f)
	header_row = next(reader)
	#print(header_row)
	#for index,column_header in enumerate(header_row):
	#	print(index,column_header)
	dates,highs = [],[]
	for row in reader:
		current_date = datetime.strptime(row[0],'%Y-%m-%d')
		dates.append(current_date)
		
		high = int(row[1])
		highs.append(high)
	#print(highs)
	fig = plt.figure(dpi=128,figsize=(10,6))
	plt.plot(dates,highs,c='red')
	
	plt.title('Daily high temperatures,July 2014',fontsize = 24)
	plt.xlabel('',fontsize=16)
	fig.autofmt_xdate()
	plt.ylabel('Temperature(F)',fontsize = 16)
	plt.tick_params(axis='both',which='major',labelsize=16)
	
	plt.show()
	
	
	————————————————————————————————————————————————
#高低溫
# -*- coding: gbk -*-
import csv
from datetime import datetime
from matplotlib import pyplot as plt
filename = 'sitka_weather_2014.csv'
with open(filename) as f:
	reader = csv.reader(f)
	header_row = next(reader)
	#print(header_row)
	#for index,column_header in enumerate(header_row):
	#	print(index,column_header)
	dates,highs,lows = [],[],[]
	for row in reader:
		current_date = datetime.strptime(row[0],'%Y-%m-%d')
		dates.append(current_date)
		
		high = int(row[1])
		highs.append(high)
		
		low = int(row[3])
		lows.append(low)
	#print(highs)
	fig = plt.figure(dpi=128,figsize=(10,6))
	plt.plot(dates,highs,c='red',alpha = 0.5)
	plt.plot(dates,lows,c='blue',alpha = 0.5)
	plt.fill_between(dates,highs,lows,facecolor='blue',alpha=0.1)
	
	plt.title('Daily high and low temperatures- 2014',fontsize = 24)
	plt.xlabel('',fontsize=16)
	fig.autofmt_xdate()
	plt.ylabel('Temperature(F)',fontsize = 16)
	plt.tick_params(axis='both',which='major',labelsize=16)
	
	plt.show()
——————————————————————————————————————————————————————————————————
import csv
from datetime import datetime
from matplotlib import pyplot as plt
filename = 'sitka_weather_2014.csv'
with open(filename) as f:
	reader = csv.reader(f)
	header_row = next(reader)
	#print(header_row)
	#for index,column_header in enumerate(header_row):
	#	print(index,column_header)
	dates,highs,lows = [],[],[]
	for row in reader:
		try:
			current_date = datetime.strptime(row[0],'%Y-%m-%d')
			high = int(row[1])
			low = int(row[3])
		except ValueError:
			print(current_date,'missing data')	
		else:
			dates.append(current_date)
			highs.append(high)
			lows.append(low)
	#print(highs)
	fig = plt.figure(dpi=128,figsize=(10,6))
	plt.plot(dates,highs,c='red',alpha = 0.5)
	plt.plot(dates,lows,c='blue',alpha = 0.5)
	plt.fill_between(dates,highs,lows,facecolor='blue',alpha=0.1)
	
	plt.title('Daily high and low temperatures- 2014 Sitka',fontsize = 24)
	plt.xlabel('',fontsize=16)
	fig.autofmt_xdate()
	plt.ylabel('Temperature(F)',fontsize = 16)
	plt.tick_params(axis='both',which='major',labelsize=16)
	
	plt.show()

————————————————————————————————————————————————————————————
import json
from pygal_maps_world.i18n import COUNTRIES

#for country_code in sorted(COUNTRIES.keys()):
#	print(country_code,COUNTRIES[country_code])

def get_country_code(country_name):
	for code,name in COUNTRIES.items():
		if name == country_name:
			return code
		return None



filename = 'population_data.json'
with open(filename) as f:
	pop_data = json.load(f)

for pop_dict in pop_data:
	if pop_dict['Year'] == '2010':
		region = pop_dict['Country Name']
		population = pop_dict['Value']
		#print(region+":"+ str(population))

		code = get_country_code(region)
		if code:
			print(code +":"+ str(population))
		else:
			print('ERROR - '+region)
___________________________________
# -*- coding: gbk -*-
import pygal

import json
from pygal_maps_world.i18n import COUNTRIES
from pygal.style import RotateStyle, LightColorizedStyle

def get_country_code(country_name):
	for code,name in COUNTRIES.items():
		if name == country_name:
			return code
		return None



filename = 'population_data.json'
with open(filename) as f:
	pop_data = json.load(f)
cc_popuations = {}
for pop_dict in pop_data:
	if pop_dict['Year'] == '2010':
		region = pop_dict['Country Name']
		population = pop_dict['Value']
		code = get_country_code(region)
		if code:
			cc_popuations[code]= population

cc_pops_1,cc_pops_2,cc_pops_3 = {},{},{}
for cc,pop in cc_popuations.items():
	if int(pop)<10000000:
		cc_pops_1[cc] = pop
	elif int(pop)<1000000000:
		cc_pops_2[cc] = pop
	else:
		cc_pops_3[cc] = pop
print(len(cc_pops_1),len(cc_pops_2),len(cc_pops_3))

#wm_style = RotateStyle('#336699')
#wm_style = LightColorizedStyle
wm_style = RotateStyle('#336699',base_style=LightColorizedStyle)
wm = pygal.maps.world.World(style = wm_style)
wm.title = 'Worlds  Population in 2010'

wm.add('0-10m',cc_pops_1)
wm.add('10m-1bn',cc_pops_2)
wm.add('>1bn',cc_pops_3)


#wm.add('2010',cc_popuations)
#wm.add('North America', {'ca':34126000, 'mx':309349000, 'us':113423000})
#wm.add('Central America', ['bz', 'cr', 'gt', 'hn', 'ni', 'pa', 'sv'])
#wm.add('South America', ['ar', 'bo', 'br', 'cl', 'co', 'ec', 'gf',
#'gy', 'pe', 'py', 'sr','uy','ve'])

wm.render_to_file('world_pupulations.svg')