def rendermap():
message = ''
result = ''
leaderitems = {}
cc = ''
logging.info("POST request path /rendermap")
if request.method == 'POST':
cc = request.form.get('countryCode')
if cc == '':
message = "Please enter a 2 letter ISO country code"
cc = cc.lower()
ccupper = cc.upper()
logging.info("ISO country code entered:" + cc)
#Load the country json
with open('data/leaders.json') as leaders_json_file:
leadersdata = json.load(leaders_json_file)
#for w in leadersdata:
# print("%s: %d" % (w, leadersdata[w]))
if ccupper not in leadersdata:
message = "Wrong country code. Click Home link and enter a valid 2-letter ISO code!"
else:
leaderitems[cc] = float(leadersdata[ccupper])
result = cc + ":" + str(leadersdata[ccupper])
with open('data/neighbours.json') as neighbours_json_file:
nd = json.load(neighbours_json_file)
#for n in nd:
# print("%s: %s" % (n, str(nd[n])))
narr = nd[cc]
for neighbour in narr:
nupper = neighbour.upper()
if nupper in leadersdata:
leaderitems[neighbour] = float(leadersdata[nupper])
result += "," + str(neighbour) + ":" + str(
leadersdata[nupper])
else:
message += "Data not available for neighbouring country ISO Code:" + str(
neighbour) + "\n"
#Create world map with result
wm_style = RotateStyle('#34126000')
wm = World()
wm.force_uri_protocol = 'http'
wm.title = "Women Political leaders (%)"
wm.add('', leaderitems)
wm.render_to_file('templates/lmap.svg')
svg = render_template('lmap.svg')
print("Result " + result)
print("Message " + message)
print(len(leaderitems))
#svgf = open("templates/lmap.svg", "r").read()
#svg_io = StringIO()
#svg_io.write(svgf)
#svg_io.seek(0)
#return send_file(svg_io, mimetype='image/svg+xml')
img = './static/lmap.svg'
return render_template('leadersmap.html', message=message, img=img)
def view_world_map():
wm = World()
wm.title = 'North, Central, and South America'
wm.add('North America', ['ca', 'mx', 'us'])
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('americas.svg')
def world_country_map():
"""绘制世界地图"""
wm_c = World()
# wm_c.force_url_protocol = 'http'
wm_c.title = 'World Map'
for code, name in COUNTRIES.items():
wm_c.add(name, code)
wm_c.add('Yemen', {'ye': 'Yemen'})
wm_c.render_to_file('world_map.svg')
def main():
# collect the data from a given file and store it in a dictionary
birthRate = collect_birth_rate_data("birth_rate.csv")
# Create a map and fill it with data
wm = World()
wm.title = "Countries birth rate, 2018"
wm.add("birth rates", birthRate)
wm.render_to_file('world_birth_rate.svg')
def GET(self):
user_data = web.input()
prd = user_data.product
pg = user_data.data
from pygal.maps.world import World
wm = World(height=400)
wm.force_uri_protocol = 'http'
wm.title = "產品 " + prd + " 的 " + pg + " 在全球即時分佈的狀態"
d = getlist(prd, pg)
i = 0
for item in d:
x = {}
x[incl.countrycode[item[0]]] = item[1]
wm.add(str(i + 1) + ". " + item[0], x)
i = i + 1
#wm.render_to_file("static/map.svg")
wm.disable_xml_declaration = True
return '<html>\n <head>\n <title>全球即時分佈圖</title>\n<meta http-equiv="content-type" content="text/html;charset=utf-8"><meta http-equiv="refresh" content="30" />\n<script type="text/javascript" src="http://kozea.github.com/pygal.js/latest/pygal-tooltips.min.js"></script>\n</head>\n<body>\n' + wm.render(
is_unicode=True) + '\n </body>\n</html>'
def make_world_map():
# Load the data into a list
filename = 'population_data.json'
with open(filename) as f:
pop_data = json.load(f)
# Get the two digits cuntries codes
codes_and_names = get_country_list()
# Build a dictionary of population data
cc_populations = {}
for pop_dict in pop_data:
if pop_dict['Year'] == '2010':
country_name = pop_dict['Country Name']
population = int(float(pop_dict['Value']))
code = get_country_code(country_name, codes_and_names)
if code:
cc_populations[code] = population
# Make world map
wm = World()
wm.title = 'World population in 2010, by Country'
wm.add('2010', cc_populations)
# Convert it to file
wm.render_to_file("world_population.svg")
def draw_word_map(prob_predict: List[float],
countries: List[str],
output_file: str = 'word_map.svg'):
"""
> 0.5 accending => prob
< 0.5 descending => 1 - prob
"""
worldmap_chart = World()
worldmap_chart.title = 'Ｗorld Map'
accending = {}
descending = {}
for prob, country in zip(prob_predict, countries):
country_code = get_country_code(country)
if not country_code:
continue
if prob > 0.5:
accending[country_code] = prob
else:
descending[country_code] = prob
worldmap_chart.add('accending', accending)
worldmap_chart.add('descending', descending)
worldmap_chart.render_to_file(output_file)
for pop_dict in pop_data:
if pop_dict['Year'] == '2015':
country_name = pop_dict['Country Name']
population = int(float(pop_dict['Value']))
#print(country_name + ": " + str(population))
code = get_country_code(country_name)
if code:
#print(code + ": " + str(population))
cc_populations[code] = population
# else:
# print('ERROR - ' + country_name)
cc_pops_1, cc_pops_2, cc_pops_3 = {}, {}, {}
for cc, pop in cc_populations.items():
if pop < 10000000:
cc_pops_1[cc] = pop
elif 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 = RS('#336699', base_style=LS)
#wm_style = LightStyle
wm = World(style=wm_style)
wm.title = "World Population in 2015, by Country"
#wm.add('2015',cc_populations)
wm.add('0-10m', cc_pops_1)
wm.add('10m-1bn', cc_pops_2)
wm.add('>1bn', cc_pops_3)
wm.render_to_file('world_population.svg')
import pygal
from pygal.maps.world import World
wm = World()
wm.title = 'North , South and Central America'
wm.add('North America', ['ca', 'mx', 'us'])
wm.add('Canral 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('americas.svg')
from pygal.style import RotateStyle, LightColorizedStyle
# 根据用电量的范围分组, 统计数据到{国别码: 用电量}6个字典里
group1, group2, group3, group4, group5, group6 = {}, {}, {}, {}, {}, {}
for name, used in zip(country_names, eletri_used):
code = get_country_code(name)
if used > 20000:
group1[code] = used
elif used > 8000:
group2[code] = used
elif used > 3000:
group3[code] = used
elif used > 500:
group4[code] = used
elif used != 0:
group5[code] = used
else:
group6[code] = used
# 着色,加亮颜色主题
wm_style = RotateStyle('#336699', base_style=LightColorizedStyle)
wm = World(style=wm_style)
wm.title = title
wm.add('>20th', group1)
wm.add('20th-8th', group2)
wm.add('3th-8th', group3)
wm.add('0.5th-3th', group4)
wm.add('0-0.5th', group5)
wm.add('0', group6)
wm.render_to_file('power_used.svg')
for pop_dict in pop_data:
if pop_dict['Year'] == '2010':
country_name = pop_dict['Country Name']
population = int(float(pop_dict['Value']))
code = get_country_code(country_name)
if code:
cc_populations[code] = population
# Podzielenie państw na trzy grupy według liczebności populacji.
cc_pops_1, cc_pops_2, cc_pops_3 = {}, {}, {}
for cc, pop in cc_populations.items():
if pop < 10000000:
cc_pops_1[cc] = pop
elif pop < 1000000000:
cc_pops_2[cc] = pop
else:
cc_pops_3[cc] = pop
# Wyświetlenie liczby państw w każdej z trzech grup.
print(len(cc_pops_1), len(cc_pops_2), len(cc_pops_3))
wm_style = RS('#336699', base_style=LCS)
wm = World(style=wm_style)
wm.force_uri_protocol = 'http'
wm.title = 'Populacja na świecie w 2010 roku (dane dla poszczególnych państw)'
wm.add('0 - 10 mln', cc_pops_1)
wm.add('10 mln - 1 mld', cc_pops_2)
wm.add('>1 mld', cc_pops_3)
wm.render_to_file('world_population.svg')
# Open file and extract data
filename = "life_female.csv"
with open(filename) as f:
lifedata = csv.reader(f)
# Get to the proper column line on the csv
for n in range(1, 6):
next(lifedata)
# Make a new dictionary. Translate the country names
# to country_codes, and put them in as keys and the
# life expectancy data as values (taken from the 2014 data set)
lrates = {}
for rowdata in list(lifedata):
ccode = get_country_code(rowdata[0])
try:
lrates[ccode] = float(rowdata[58])
except ValueError:
continue
# Plot new graph and output to file
wm_style = RS('#336699', base_style=LCS)
wm = World(style=wm_style)
wm.force_uri_protocol = 'http'
wm.title = 'Female Life Expectancy in 2014, by Country'
wm.add('Years', lrates)
wm.render_to_file('female_mortality.svg')
filename = 'gdp.json'
with open(filename) as f:
gdp_data = json.load(f)
cc_gdp = {}
for gdp_dict in gdp_data:
if gdp_dict['Year'] == 2016:
country_name = gdp_dict['Country Name']
gdp = int(float(gdp_dict['Value']))
code = country_codes.get_country_code(country_name)
if code:
cc_gdp[code] = gdp
else:
print(country_name + " has no code.")
cc_gdp_1, cc_gdp_2 = {}, {}
for cc, gdp in cc_gdp.items():
if gdp < 1000000000000:
cc_gdp_1[cc] = gdp
else:
cc_gdp_2[cc] = gdp
wm_style = RotateStyle('#336699')
wm = World(style=wm_style)
wm.title = "GDP in 2016, by Country"
wm.add('0-1tr', cc_gdp_1)
wm.add('>1tr', cc_gdp_2)
wm.render_to_file('world_gdp.svg')
from pygal.maps.world import World
wm = World()
wm.title = "Populations of Countries in North America"
wm.add('North America', {'ca': 34126000, 'us': 309349000, 'mx': 113423000})
wm.render_to_file('na_populations.svg')
from pygal.maps.world import COUNTRIES, World
import pygal
def get_country_code(country_name):
for code, name in COUNTRIES.items():
if name == country_name:
return code
return None
wm = World()
wm.title = "North, Central and South America"
wm.add('North America', {'ca': 34126000, 'us': 309349000, 'mx': 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('america.svg')
# Build a dictionary of population data in 2010.
for pop_dict in population_data:
if pop_dict['Year'] == '2010':
country_name = pop_dict['Country Name']
population = int(float(pop_dict['Value']))
code = get_country_code(country_name)
if code:
cc_populations[code] = population
# Store countries in 3 groups according to population number
cc_pops1, cc_pops2, cc_pops3 = {}, {}, {}
for cc, pop in cc_populations.items():
if pop < 10000000:
cc_pops1[cc] = pop
elif pop < 1000000000:
cc_pops2[cc] = pop
else:
cc_pops3[cc] = pop
wm_style = RS('#336699', base_style=LCS)
wm = World(style=wm_style)
wm.force_uri_protocol = 'http'
wm.title = 'Populacja na świecie w 2010 r. (dane dla poszczególnych państw)'
wm.add('0-10 mln', cc_pops1)
wm.add('10 mln - 1 mld', cc_pops2)
wm.add('> 1 mld', cc_pops3)
wm.render_to_file('world_population.svg')
for pop_dict in pop_data:
if pop_dict['Year'] == '2010':
country_name = pop_dict['Country Name']
population = int(float(pop_dict['Value']))
code = get_country_code(country_name)
if code:
cc_populations[code] = population
# Podzielenie państw na trzy grupy według liczebności populacji
cc_pops_1, cc_pops_2, cc_pops_3 = {}, {}, {}
for cc, pop in cc_populations.items():
if pop < 10000000:
cc_pops_1[cc] = pop
elif pop < 1000000000:
cc_pops_2[cc] = pop
else:
cc_pops_3[cc] = pop
# Wyświetlenie liczby państw w każdej z tzech grup
print(len(cc_pops_1), len(cc_pops_2), len(cc_pops_3))
wm_style = RotateStyle('#336699', base_style=LightColorizedStyle)
wm = World(style=wm_style)
wm.force_uri_protocol = 'http'
wm.title = 'Populacja na świecie w 2010 roku'
wm.add('0 - 10 mln', cc_pops_1)
wm.add('10 - 1 mld', cc_pops_2)
wm.add('>1 mld', cc_pops_3)
wm.render_to_file('world_population.svg')
# Plot population data on the world map.
from pygal.maps.world import World
wm = World()
wm.title = "North American Populations"
wm.add("North America", {'ca': 34126000, 'mx': 113423000, 'us': 309349000})
wm.render_to_file('files/north_america.svg')
from pygal.maps.world import World
wm = World()
wm.title = 'Populations of the Countries of North America'
wm.add('North America', {'ca': 34126000, 'us': 309349000, 'mx': 113423000})
wm.render_to_file('na_populations.svg')
from pygal.maps.world import World
wm = World()
wm.title = 'North, Central amd South America'
wm.add('North America', ['ca', 'mx', 'us'])
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('americas.svg')
cc_gdp = {}
for gdp_dict in gdp_data:
if gdp_dict['Year'] == '2010':
country_name = gdp_dict['Country Name']
gdp = int(float(gdp_dict['Value']))
code = get_country_code(country_name)
if code:
cc_gdp[code] = gdp
# Group the countries into 3 gdp levels.
cc_gdp_1, cc_gdp_2, cc_gdp_3 = {}, {}, {}
for cc, gdp in cc_gdp.items():
if gdp < 1000000000:
cc_gdp_1[cc] = gdp
elif gdp < 10000000000000:
cc_gdp_2[cc] = gdp
else:
cc_gdp_3[cc] = gdp
# Plot and output to file
wm_style = RS('#336699', base_style=LCS)
wm = World(style=wm_style)
wm.force_uri_protocol = 'http'
wm.title = 'World GDP in 2010, by Country'
wm.add('0-1bn', cc_gdp_1)
wm.add('1bn-1tr', cc_gdp_2)
wm.add('>1tr', cc_gdp_3)
wm.render_to_file('world_gdp.svg')
if country == countryName:
return code
return None
with open("population_data.json") as file:
contents = json.load(file)
populations1, populations2, populations3 = {}, {}, {}
for dict in contents:
if dict['Year'] == '2010':
code = getCountryCode(dict['Country Name'])
if code:
population = int(float(dict['Value']))
if population < 10000000:
populations1[code] = population
elif population < 100000000:
populations2[code] = population
else:
populations3[code] = population
mapStyle = RS("#0088ff", base_style=LCS)
map = World(style=mapStyle)
map.title = "2010 Populations"
map.add("0-10m", populations1)
map.add("10-100m", populations2)
map.add("100m+", populations3)
map.render_to_file("populationMap.svg")
#now we create a worldmap of Continents
# like SA,NA,CA,ASIA
from pygal.maps.world import World
wm = World()
#wm.force_uri_protocol = 'http'
wm.title = 'North, Central, and South America,Asia,Arab'
wm.add('North America', ['ca', 'mx', 'us'])
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.add("Asia", ["in", "jp", "cn", "id", "th", "sg"])
wm.add("Arab", ["eg", "iq", "dz", "bh", "jo", "sa", "ae"])
wm.render_to_file('americas.svg')
cc_populations = {}
for pop_dict in pop_data:
if pop_dict['Year'] == '2010':
country_name = pop_dict['Country Name']
population = int(float(pop_dict['Value']))
code = get_country_code(country_name)
if code:
cc_populations[code] = population
else:
print('Error-' + country_name)
cc_pops_1, cc_pops_2, cc_pops_3 = {}, {}, {}
#group populations into categorys
for cc, pop in cc_populations.items():
if pop < 10000000:
cc_pops_1[cc] = pop
elif 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 = World(style=wm_style)
wm.title = 'World populations in 2010, by Country'
wm.add('0-10m', cc_pops_1)
wm.add('10m-1bn', cc_pops_2)
wm.add('>1bn', cc_pops_3)
wm.render_to_file('world_populations.svg')
from pygal.maps.world import World
wm = World()
wm.force_uri_protocol = 'http'
wm.title = 'Ameryka Północna, Środkowa i Południowa'
wm.add('Ameryka Północna', ['ca', 'mx', 'us'])
wm.add('Ameryka Środkowa', ['bz', 'cr', 'gt', 'hn', 'ni', 'pa', 'sv'])
wm.add('Ameryka Południowa', [
'ar', 'bo', 'br', 'cl', 'co', 'ec', 'gf', 'gy', 'pe', 'py', 'sr', 'uy',
've'
])
wm.render_to_file('americas.svg')
if gdp_dict['Year'] == '2014':
country_name = gdp_dict['Country Name']
gdp = int(float(gdp_dict['Value']))
code = get_country_code(country_name)
if code:
cc_gdps[code] = gdp
# Group the countries into 3 gdp levels.
# Less than 5 billion, less than 50 billion, >= 50 billion.
# Also, convert to billions for displaying values.
cc_gdps_1, cc_gdps_2, cc_gdps_3 = {}, {}, {}
for cc, gdp in cc_gdps.items():
if gdp < 5000000000:
cc_gdps_1[cc] = round(gdp / 1000000000)
elif gdp < 50000000000:
cc_gdps_2[cc] = round(gdp / 1000000000)
else:
cc_gdps_3[cc] = round(gdp / 1000000000)
# See how many countries are in each level.
print(len(cc_gdps_1), len(cc_gdps_2), len(cc_gdps_3))
wm_style = RS('#336699', base_style=LCS)
wm = World(style=wm_style)
wm.title = 'Global GDP in 2014, by Country (in billions USD)'
wm.add('0-5bn', cc_gdps_1)
wm.add('5bn-50bn', cc_gdps_2)
wm.add('>50bn', cc_gdps_3)
wm.render_to_file('global_gdp.svg')
from pygal.maps.world import World
wm = World()
wm.title = 'Population of Countries in North America'
wm.add('North America', {'ca': 34126000, 'us': 309349000, 'mx': 113423000})
wm.render_to_file('na_population.svg')
#
from pygal.maps.world import World
wm = World()
wm.title = 'North, Central, and South America'
wm.add('North America', ['ca', 'mx', 'us'])
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('americas.svg')
from pygal.maps.world import World
wm = World()
wm.title = 'Population in North America'
wm.add('North America', {'ca': 34126000, 'us': 309349000, 'mx': 113423000})
wm.render_to_file('na_population.svg')
if gdb_dict['Year'] == '2014':
country_name = gdb_dict['Country Name']
gdb_value = float(gdb_dict['Value'])
code = get_country_code(country_name)
if code:
cc_gdb[code] = gdb_value
else:
print('ERROR - ' + country_name)
cc_gdb_1, cc_gdb_2, cc_gdb_3, cc_gdb_4 = {}, {}, {}, {}
for cc, gdb in cc_gdb.items():
if gdb < 10000000000:
cc_gdb_1[cc] = gdb
elif gdb < 100000000000:
cc_gdb_2[cc] = gdb
elif gdb < 1000000000000:
cc_gdb_3[cc] = gdb
else:
cc_gdb_4[cc] = gdb
print(len(cc_gdb_1), len(cc_gdb_2), len(cc_gdb_3), len(cc_gdb_4))
wm_style = RotateStyle('#663399', base_style=LightColorizedStyle)
wm = World(style=wm_style)
wm.title = 'GDB in USD($) for world countries for year 2014'
wm.add('GDB: 0-10b', cc_gdb_1)
wm.add('GDB: 10b-100b', cc_gdb_2)
wm.add('GDB: 100b-1000b', cc_gdb_3)
wm.add('GDB: >1000b', cc_gdb_4)
wm.render_to_file('world_gdb.svg')
with open(filename) as f:
pop_data = json.load(f)
cc_populations = {}
for pop_dict in pop_data:
if pop_dict['Year'] == '2010':
country_name = pop_dict['Country Name']
population = int(float(pop_dict['Value']))
code = get_country_code(country_name)
if code:
cc_populations[code] = population
cc_pops_1, cc_pops_2, cc_pops_3 = {}, {}, {}
for cc, pop in cc_populations.items():
if pop < 10000000:
cc_pops_1[cc] = pop
elif pop < 1000000000:
cc_pops_2[cc] = pop
else:
cc_pops_3[cc] = pop
wm_style = RS('#336699', base_dtyle=LCS)
wm = World(style=wm_style)
wm.title = 'World population in 2010, by country'
wm.add('0-10m', cc_pops_1)
wm.add('10m-1bn', cc_pops_2)
wm.add('>1bn', cc_pops_3)
wm.render_to_file('world_population.svg')
from pygal.maps.world import World
wm = World()
wm.title = 'North, Center, and South America'
wm.add('North America', ['ca', 'mx', 'us'])
wm.add('Center 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('americas.svg')
from pygal.maps.world import World
wm = World()
wm.title = 'Populations of Countries in North America'
wm.add("North America", {"ca":3412600, 'us': 309349000, 'mx': 113423000})
wm.render_to_file("C:\\Users\\Asymmetry\\Desktop\\na_populations.svg")
for pop_dict in pop_data:
if pop_dict['Year'] == 2016:
country = pop_dict['Country Name']
population = int(float(pop_dict['Value']))
code = get_country_code(country)
if code:
cc_populations[code] = population
# Group the countries into 3 population levels
cc_pop_1, cc_pop_2, cc_pop_3 = {}, {}, {}
for cc, pop in cc_populations.items():
if pop < 10000000:
cc_pop_1[cc] = pop
elif 1000000000 > pop > 10000000:
cc_pop_2[cc] = pop
else:
cc_pop_3[cc] = pop
# See how many countries are in each level
print(len(cc_pop_1), len(cc_pop_2), len(cc_pop_3))
wm = World()
wm_style = RotateStyle('#336699', base_style=LightColorizedStyle)
wm.force_uri_protocol = 'http'
wm.title = 'World Population in 2016, by Country'
wm.add('0-10m', cc_pop_1)
wm.add('10m-1bn', cc_pop_2)
wm.add('>1b', cc_pop_3)
wm.render_to_file('world_population.svg')
# json.load() converts the data into a format Python can work with
pop_data = json.load(f)
# build a dictionary of population data
cc_populations = {}
for pop_dict in pop_data:
if pop_dict['Year'] == '2010':
country_name = pop_dict['Country Name']
population = int(float(pop_dict['Value']))
code = get_country_code(country_name)
if code:
cc_populations[code] = population
# group the countries into 3 population levels
cc_pops_1, cc_pops_2, cc_pops_3 = {}, {}, {}
for cc, pop in cc_populations.items():
if pop < 10000000:
cc_pops_1[cc] = pop
elif pop < 10000000:
cc_pops_2[cc] = pop
else:
cc_pops_3[cc] = pop
wm = World()
wm.force_uri_protocol = 'http'
wm.title = 'World Population in 2010, by Country'
wm.add('0-10,', cc_pops_1)
wm.add('10m-1bn', cc_pops_2)
wm.add('>1bn', cc_pops_3)
wm.render_to_file('world_population.svg')
from pygal.maps.world import World
wm = World()
wm.title = "North, Center & South America"
wm.add('North America', ['ca', 'mx', 'us'])
wm.add('Center 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('americas.svg')
filename = 'population_data.json'
with open(filename) as f:
pop_data = json.load(f)
cc_populations = {}
for pop_dict in pop_data:
if pop_dict['Year'] == '2010':
country_name = pop_dict['Country Name']
population = int(float(pop_dict['Value']))
code = get_country_code(country_name)
if code:
cc_populations[code] = population
cc1, cc2, cc3 = {}, {}, {}
for cc, popu in cc_populations.items():
if popu < 10000000:
cc1[cc] = popu
elif popu < 1000000000:
cc2[cc] = popu
else:
cc3[cc] = popu
wm_style = RotateStyle('#336699', base_style=LightColorizedStyle)
wm = World(style=wm_style)
wm.title = 'Population in world'
wm.add('< 10m', cc1)
wm.add('10m - 1b', cc2)
wm.add('> 1b', cc3)
wm.render_to_file('world_populations_new.svg')
from pygal.maps.world import World
wm = World()
wm.title = 'North, Central, and South America'
wm.add('North America', ['ca', 'mx', 'us'])
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('americas.svg')
from pygal.maps.world import World
wm = World()
wm.force_uri_protocol = 'http'
wm.title = 'Wielkość populacji w krajach Ameryki Północnej'
wm.add('Ameryka Północna', {'ca': 34126000, 'us': 309349000, 'mx': 113423000})
wm.render_to_file('na_populations.svg')