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')