def visual_map(countries_export_in):
""" Визуализируем данные на карте """
# визуализируем данные на карте мира
world_map = maps.World()
world_map.title = "Экспорт товаров и услуг (% от ВВП) за последние года"
world_map.add("Страны", countries_export_in)
world_map.render_to_file('export_countries.svg')
print("Файл карты успешно создан - октройте в браузере.")
def generate_result_file(year):
conn = create_connection()
with conn:
dataset = select_by_year(conn, str(year))
for data in dataset:
country_name = data[1]
population = data[3]
code = get_country_code(country_name)
if code:
cc_populations[code] = population
else:
cc_populations["na"] = 0
for data in dataset:
country_name = data[1]
population = data[3]
code = get_country_code(country_name)
if code:
cc_populations[code] = population
else:
cc_populations["na"] = 0
cc_pops_1, cc_pops_2, cc_pops_3 = {}, {}, {}
for cc, my_pop in cc_populations.items():
pop = int(float(my_pop))
if pop < 10000000:
cc_pops_1[cc] = pop
elif pop < 1000000000:
cc_pops_2[cc] = pop
else:
cc_pops_3[cc] = pop
wm_style = RotateStyle('#336699', base_style=LightColorizedStyle)
wm = maps.World(style=wm_style)
wm.title = 'World populations in ' + str(year) + ', by country'
wm.add('0 - 10m - ' + str(len(cc_pops_1)), cc_pops_1)
wm.add('10m - 1bn - ' + str(len(cc_pops_2)), cc_pops_2)
wm.add('>1bn - ' + str(len(cc_pops_3)), cc_pops_3)
return wm.render_to_file('visualize/static/visualize/map.svg')
population = int(float(pop_dict["Value"]))
#Some data are floats;
code = get_country_code(country)
if (code):
cc_populations[code] = population
else:
print("ERROR - " + country)
cc_pops_1, cc_pops_2, cc_pops_3 = {}, {}, {}
for cc, pops in cc_populations.items():
if (pops < 10000000):
cc_pops_1[cc] = pops
elif (pops < 1000000000):
cc_pops_2[cc] = pops
else:
cc_pops_3[cc] = pops
wm_style = RS("#336699", base_style=LCS)
#wm_style = LightColorizedStyle;
#wm_style = RotateStyle("#330000");#RGB
wm = MP.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)
#Darker color for larger number and vice versa;
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 == None:
print(country_name)
#打印每个国家2010年的人口数量
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 #这样就能直接添加进字典不需要append()方法,因为字典无序
# else: #这块没必要留着了
# print("Error - "+country_name)
#print(country_name+': '+str(population))
wm = pm.World()
wm.title = 'World Population in 2010,by Country'
# 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.add('2010', cc_populations)
wm.render_to_file('world_population.svg')
import json
from pygal_maps_world.i18n import COUNTRIES
def get_country_code(country_name):
"""Return the Pygal 2-digit country code for the given country."""
for code, name in COUNTRIES.items():
if name == country_name:
return code
# If the country wasn't found, return None.
return None
with open('C:/Users/孙林轩/Desktop/gdp_json.json') as gdpF:
data=json.load(gdpF)
indexnum=[]
for i in range(0,len(data)):
if data[i]['Year']==2010:
indexnum.append(i)
wm=pmw.World()
wm.title = 'World map'
GDP_dic={}
for i in indexnum:
GDP_dic[get_country_code(data[i]["Country Name"])]=data[i]['Value']
GDP1={}
GDP2={}
GDP3={}
for code,value in GDP_dic.items():
if value<(1/3)*max(GDP_dic.values()):
GDP1[code]=value
elif value<(2/3)*max(GDP_dic.values()):
GDP2[code]=value
else:
GDP3[code]=value
wm.add('2010 GDP under 1/3',GDP1)
from pygal_maps_world import maps
from pygal_maps_world.i18n import COUNTRIES
worldmap_chart=maps.World()
worldmap_chart.title='C Countries'
ccodes=[]
for each in COUNTRIES:
if each.startswith('c')==True:
ccodes.append(each)
worldmap_chart.add('C Countries',ccodes)
worldmap_chart.render_to_file('map.svg')
# encoding= utf-8
# @Time : 2020/5/8 9:10
# @Author : Yao
# @File : americas.py
# @Software: PyCharm
import pygal
import pygal_maps_world.maps as pwm
wm = pwm.World()
wm.title = 'North, Central, and the America'
wm.add('North America', ['ca', 'mx', 'us'])
wm.add('Central America', ['bz', 'zr', '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 = 'data/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
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 pop < 1000000000:
cc_pop_2[cc] = pop
else:
cc_pop_3[cc] = pop
wm = wm.World()
wm.title = 'World Population in 2010'
wm.add('0-10m', cc_pop_1)
wm.add('10m-1bn', cc_pop_2)
wm.add('>1bn', cc_pop_3)
wm.render_to_file('world_pop.svg')
import pygal_maps_world.maps as pyg
wm = pyg.World()
wm.title = 'Population of Countries in North America'
wm.add('North America', {'ca': 34126000, 'mx': 113423000, 'us': 309349000})
# render_to_file() 创建一个包含该图表的.svg文件
wm.render_to_file('num_population.svg')
# выводим население каждой страны за 2018 год
cc_population = {}
for pop_dict in pop_data:
if pop_dict['Year'] == 2018:
country_name = pop_dict["Country Name"]
population = int(pop_dict['Value'])
code = get_country_code(country_name)
if code:
cc_population[code] = population
else:
print(f"{country_name}")
# сгруппируем страны по уровням населения
cc_pops_1, cc_pops_2, cc_pops_3, = {}, {}, {}
for cc, pop in cc_population.items():
if pop < 10000000:
cc_pops_1[cc] = pop
elif pop < 1000000000:
cc_pops_2[cc] = pop
else:
cc_pops_3[cc] = pop
# визуализируем данные на карте мира
wm_style = style.RotateStyle('#336699')
world_map = maps.World(style=wm_style)
world_map.title = "Численность населения стран мира в 2018 году"
world_map.add("0-10m", cc_pops_1)
world_map.add("10m-1b", cc_pops_2)
world_map.add(">1b", cc_pops_3)
world_map.render_to_file('world_population.svg')
import pygal_maps_world.maps as WM
wm = 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')
import pygal_maps_world.maps as MP
wm = MP.World()
wm.title = "North, Central, and Sounth America"
wm.add("North America", ["ca", "mx", "us"])
#Each new add will change a different color;
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")
code = get_country_code(country)
if code:
cc_populations[code] = population
#根据人口数量将所有的国家分成三组
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 = RotateStyle('#336699') #改变地图颜色
wm = pymap.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')
# #打印每个国家2010年的人口数量
# for pop_dict in pop_data:
# if pop_dict['Year']=='2010':
# country=pop_dict['Country Name']
# population=int(float(pop_dict['Value'])) #'{:,}'.format(int(pop_dict['Value'])) # pop_dict['Value']
# code=get_country_code(country)
# if code:
# print(code + ': ' + str(population))
# else:
cc_pops_1, cc_pops_2, cc_pops_3 = {}, {}, {}
for cc, pop in cc_population.items():
if pop < 10000000:
cc_pops_1[cc] = pop
elif pop < 1000000000:
cc_pops_2[cc] = pop
else:
cc_pops_3[cc] = pop
print('人口小于10000000国家个数为: ', len(cc_pops_1))
print('人口大于等于10000000小于1000000000国家个数为: ', len(cc_pops_2))
print('人口大于等于1000000000国家个数为: ', len(cc_pops_3))
wm_style = RotateStyle('#336699',
base_style=LightColorizedStyle) # 为世界地图指定一种基色
wm = pywm.World(style=wm_style) # 创建世界地图
# wm.title = '北美、中美和南美' # 给图表设置属性
# wm.add('北美', ['ca', 'mx', 'us']) # 添加需要突出显示的国家和国别码
# wm.add('北美', {'ca': 34126000, 'us': 309349000, 'mx': 113423000}) # 不仅显示地区, 还显示地方对应的人口, 传递字典类型参数而非列表
# wm.add('中美', ['bz', 'cr', 'gt', 'hn', 'ni', 'pa', 'sv'])
# wm.add('南美', ['ar', 'bo', 'br', 'cl', 'co', 'ec', 'gf',
# 'gy', 'pe', 'py', 'sr', 'uy', 've'])
wm.title = '2010年世界人口地图'
# wm.add('2010', cc_population) # 直接将一个字典传入到图形中
wm.add('0-10m', cc_pops_1)
wm.add('10m-1bn', cc_pops_2)
wm.add('>1nb', cc_pops_3)
# 根据人口数量将所有的国家分为三组
cc_pops1,cc_pops2,cc_pops3={},{},{}
for cc,pop in cc_population.items():
if pop<10000000:
cc_pops1[cc]=pop
elif pop<1000000000:
cc_pops2[cc]=pop
else:
cc_pops3[cc]=pop
print(len(cc_pops1),len(cc_pops2),len(cc_pops3))
#wm=pyg.World()
#wm_style=RoteStyle('#336699')
wm_style=pygal.style.RotateStyle('#3399AA',base_style=pygal.style.LightColorizedStyle)
wm=pyg.World(style=wm_style)
wm.title = 'World Population in 2010,by Countries'
wm.add('0-10m',cc_pops1)
wm.add('10m-1bn',cc_pops2)
wm.add('>1bn',cc_pops3)
#wm.add('2010', cc_population)
# render_to_file() 创建一个包含该图表的.svg文件
wm.render_to_file('world_population.svg')
"""
常见错误
File "D:/Python/hoilday_codes/csv/4_json_world_map.py", line 13, in <module>
Caribbean small states:6880000
population = int(pop_dict['Value'])
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:
print(f"{code}: {population}")
else:
print(f"ERROR: {country_name}")
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 < 10_000_000:
cc_pops_1[cc] = pop
elif pop < 1_000_000_000:
cc_pops_2[cc] = pop
else:
cc_pops_3[cc] = pop
wm_style = RS('#336699', base_style=LCS)
wm = maps.World(style=wm_style)
wm.title = "Populations of Countries in North America"
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')
# 转化为浮点格式，并保存两位小数
proportion = round(float(row[60]), 2)
except ValueError:
proportion = 0
# 将国家代码和人口比例依次写入字典中
proportion_countries[country_code] = proportion
# 创建三个字典，将不同比例范围的数值写入三个字典中
dict_1, dict_2, dict_3 = {}, {}, {}
for name, value in proportion_countries.items():
if value >= 15:
dict_1[name] = value
elif value >= 10:
dict_2[name] = value
else:
dict_3[name] = value
# 初始化地图，设置颜色风格，添加标题
wm = pmw.World(style=RB)
wm.title = 'Proportion of 65+ population (2016)'
# 依次添加地图数据
wm.add('large than 15', dict_1)
wm.add('between 10 - 15', dict_2)
wm.add('smaller than 10', dict_3)
# 保存文件
wm.render_to_file('Proportion of 65+ population.svg')
from pygal_maps_world import maps
wm = maps.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('america.svg')
population = int(float(pop_dict['Value']))
code = get_country_code(country_name)
if code:
cc_populations[code] = population #这样就能直接添加进字典不需要append()方法,因为字典无序
#根据人口数量将所有国家分成三组
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 < 100000000:
cc_pops_2[cc] = pop
else:
cc_pops_3[cc] = pop
#分别显示每组有多少个国家
print(len(cc_pops_1), len(cc_pops_2), len(cc_pops_3))
#wm =pm.World()
wm_style = RotateStyle('#336699', base_style=LightColorizedStyle)
wm = pm.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')
