Fișier:Comparison gender life expectancy CIA factbook.svg

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Descriere
English: Comparison of male and female life expectancy at birth for countries and territories as defined in the 2011 CIA Factbook, with selected bubbles labelled. Hover over a bubble to highlight it and show its data. The green line corresponds to equal female and male life expectancy. The apparent 3D volumes of the bubbles are linearly proportional to their population, i.e. their radii are linearly proportional to the cube root of the population. Data is from https://www.cia.gov/library/publications/the-world-factbook/fields/2102.html and https://www.cia.gov/library/publications/the-world-factbook/fields/2119.html .
Sursă Operă proprie
Autor Cmglee
Alte versiuni Derivative chart based on data of WHO: File:Comparison gender life expectancy WHO.svg
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Python script to fetch data and update data table

import re, os, urllib2, time, datetime, collections

data_oldss = [line.split('|') for line in '''\
-1|WORLD|69|67|71.1|7323187457|-
-20|EUROPEAN UNION|80.2|77.4|83.2|515052778|-
20|China|75.5|73.5|77.9|1373541278|ea
10|India|68.5|67.3|69.8|1266883598|as
25|USA|79.8|77.5|82.1|323995528|na
|Indonesia|72.7|70.1|75.5|258316051|ea
|Brazil|73.8|70.2|77.5|205823665|sa
|Pakistan|67.7|65.8|69.8|201995540|as
-20|Nigeria|53.4|52.4|54.5|186053386|af
|Bangladesh|73.2|71|75.4|156186882|as
-10|Russia|70.8|65|76.8|142355415|eu
1|Japan|85|81.7|88.5|126702133|ea
|Mexico|75.9|73.1|78.8|123166749|na
|Philippines|69.2|65.7|72.9|102624209|ea
|Ethiopia|62.2|59.8|64.7|102374044|af
|Vietnam|73.4|70.9|76.2|95261021|ea
|Egypt|72.7|71.4|74.2|94666993|af
|Iran|71.4|69.8|73.1|82801633|me
-15|DR Congo|57.3|55.8|58.9|81331050|af
|Germany|80.7|78.4|83.1|80722792|eu
|Turkey|74.8|72.5|77.3|80274604|me
|Thailand|74.7|71.5|78|68200824|ea
|France|81.8|78.7|85.1|66836154|eu
12|UK|80.7|78.5|83|64430428|eu
|Italy|82.2|79.6|85|62007540|eu
|Burma|66.6|64.2|69.2|56890418|ea
|South Africa|63.1|61.6|64.6|54300704|af
|Tanzania|62.2|60.8|63.6|52482726|af
|Korea, South|82.4|79.3|85.8|50924172|ea
|Spain|81.7|78.7|84.9|48563476|eu
|Colombia|75.7|72.6|79|47220856|sa
|Kenya|64|62.6|65.5|46790758|af
|Ukraine|71.8|67.1|76.9|44209733|eu
|Argentina|77.1|74|80.4|43886748|sa
|Algeria|76.8|75.5|78.2|40263711|af
|Poland|77.6|73.7|81.7|38523261|eu
|Uganda|55.4|54|56.9|38319241|af
|Iraq|74.9|72.6|77.2|38146025|me
|Sudan|64.1|62|66.3|36729501|af
|Canada|81.9|79.2|84.6|35362905|na
|Morocco|76.9|73.8|80.1|33655786|af
-15|Afghanistan|51.3|49.9|52.7|33332025|as
|Malaysia|75|72.2|78|30949962|ea
|Venezuela|75.8|72.7|78.9|30912302|sa
|Peru|73.7|71.7|75.9|30741062|sa
|Uzbekistan|73.8|70.7|77|29473614|ca
|Nepal|70.7|70.1|71.3|29033914|as
|Saudi Arabia|75.3|73.2|77.4|28160273|me
|Yemen|65.5|63.4|67.8|27392779|me
|Ghana|66.6|64.1|69.1|26908262|af
|Mozambique|53.3|52.6|54.1|25930150|af
|Korea, North|70.4|66.6|74.5|25115311|ea
|Madagascar|65.9|64.4|67.4|24430325|af
|Cameroon|58.5|57.1|59.9|24360803|af
|Cote d'Ivoire|58.7|57.5|59.9|23740424|af
|Taiwan|80.1|77|83.5|23464787|ea
|Australia|82.2|79.8|84.8|22992654|oc
|Sri Lanka|76.8|73.3|80.4|22235000|as
|Romania|75.1|71.7|78.8|21599736|eu
|Angola|56|54.8|57.2|20172332|af
|Burkina Faso|55.5|53.4|57.6|19512533|af
|Niger|55.5|54.3|56.8|18638600|af
|Malawi|61.2|59.2|63.2|18570321|af
|Kazakhstan|70.8|65.6|75.7|18360353|ca
|Chile|78.8|75.7|81.9|17650114|sa
|Mali|55.8|53.9|57.7|17467108|af
|Syria|74.9|72.5|77.4|17185170|me
|Netherlands|81.3|79.2|83.6|17016967|eu
|Ecuador|76.8|73.8|79.9|16080778|sa
|Cambodia|64.5|62|67.1|15957223|ea
|Zambia|52.5|50.8|54.1|15510711|af
|Guatemala|72.3|70.3|74.4|15189958|la
|Zimbabwe|58|57.3|58.7|14546961|af
|Senegal|61.7|59.7|63.8|14320055|af
|Rwanda|60.1|58.5|61.7|12988423|af
|Guinea|60.6|59|62.2|12093349|af
-1|Chad|50.2|49|51.5|11852462|af
|Belgium|81|78.4|83.7|11409077|eu
|Cuba|78.7|76.4|81.1|11179995|la
|Tunisia|76.1|74|78.4|11134588|af
|Burundi|60.5|58.8|62.3|11099298|af
|Bolivia|69.2|66.4|72.1|10969649|sa
|Portugal|79.3|76.1|82.8|10833816|eu
|Somalia|52.4|50.3|54.5|10817354|af
|Greece|80.5|77.9|83.3|10773253|eu
|Benin|61.9|60.5|63.3|10741458|af
|Czechia|78.6|75.7|81.8|10644842|eu
|Dominican Republic|78.1|75.9|80.5|10606865|la
|Haiti|63.8|61.2|66.4|10485800|la
|Sweden|82.1|80.2|84.1|9880604|eu
|Hungary|75.9|72.2|79.8|9874784|eu
|Azerbaijan|72.5|69.5|75.8|9872765|me
-17|Belarus|72.7|67.2|78.6|9570376|eu
|Honduras|71.1|69.5|72.8|8893259|la
|Austria|81.5|78.9|84.3|8711770|eu
|Tajikistan|67.7|64.6|71|8330946|ca
|Jordan|74.6|73.2|76.1|8185384|me
|Switzerland|82.6|80.3|85|8179294|eu
|Israel|82.4|80.6|84.4|8174527|me
|Togo|65|62.3|67.7|7756937|af
|Hong Kong|82.9|80.3|85.8|7167403|ea
|Bulgaria|74.5|71.2|78|7144653|eu
|Serbia|75.5|72.6|78.5|7143921|eu
|Laos|64.3|62.2|66.4|7019073|ea
|Paraguay|77.2|74.5|80|6862812|sa
|Papua New Guinea|67.2|65|69.5|6791317|ea
|Libya|76.5|74.7|78.3|6541948|af
|Lebanon|77.6|76.3|78.9|6237738|me
|El Salvador|74.7|71.4|78.1|6156670|la
|Sierra Leone|58.2|55.6|60.9|6018888|af
|Nicaragua|73.2|71.1|75.5|5966798|la
|United Arab Emirates|77.5|74.8|80.2|5927482|me
|Eritrea|64.9|62.4|67.5|5869869|af
10|Singapore|85|82.3|87.8|5781728|ea
|Kyrgyzstan|70.7|66.5|75.1|5727553|ca
|Denmark|79.4|77|82|5593785|eu
|Central African Republic|52.3|51|53.7|5507257|af
|Finland|80.9|77.9|84|5498211|eu
|Slovakia|77.1|73.5|80.9|5445802|eu
|Turkmenistan|70.1|67.1|73.3|5291317|ca
|Norway|81.8|79.8|83.9|5265158|eu
|Ireland|80.8|78.5|83.2|4952473|eu
|Georgia|76.2|72.1|80.6|4928052|me
|Costa Rica|78.6|75.9|81.4|4872543|la
|Congo, Republic of the|59.3|58.1|60.6|4852412|af
|New Zealand|81.2|79.1|83.3|4474549|oc
|Croatia|75.9|72.7|79.2|4313707|eu
|Liberia|59|57.3|60.8|4299944|af
|Bosnia and Herzegovina|76.7|73.7|80|3861912|eu
|Panama|78.6|75.8|81.6|3705246|la
|Mauritania|63|60.7|65.4|3677293|af
|Puerto Rico|79.4|75.8|83.1|3578056|la
|Moldova|70.7|66.9|74.8|3510485|eu
|Oman|75.5|73.5|77.5|3355262|me
|Uruguay|77.2|74.1|80.5|3351016|sa
|Armenia|74.6|71.4|78.3|3051250|me
|Albania|78.3|75.7|81.2|3038594|eu
|Mongolia|69.6|65.4|74.1|3031330|ea
|Jamaica|73.6|72|75.3|2970340|la
|Lithuania|74.9|69.5|80.6|2854235|eu
|Kuwait|78|76.6|79.4|2832776|me
|West Bank|75|73|77.1|2697687|me
|Namibia|63.6|62.1|65.1|2436469|af
|Qatar|78.7|76.7|80.8|2258283|me
1|Botswana|54.5|56.3|52.6|2209208|af
|Macedonia|76.2|73.6|79|2100025|eu
|Gambia, The|64.9|62.5|67.3|2009648|af
|Slovenia|78.2|74.6|82|1978029|eu
|Latvia|74.5|69.9|79.3|1965686|eu
|Lesotho|53|52.9|53.1|1953070|af
-2|Guinea-Bissau|50.6|48.6|52.7|1759159|af
|Gaza Strip|73.9|72.3|75.7|1753327|me
|Gabon|52.1|51.6|52.5|1738541|af
1|Swaziland|51.6|52.2|51|1451428|af
|Bahrain|78.9|76.7|81.1|1378904|me
|Mauritius|75.6|72.2|79.2|1348242|af
|Timor-Leste|68.1|66.5|69.7|1261072|ea
|Estonia|76.7|71.9|81.7|1258545|eu
|Trinidad and Tobago|72.9|69.9|75.9|1220479|la
|Cyprus|78.7|75.8|81.6|1205575|eu
|Fiji|72.7|70|75.5|915303|oc
|Djibouti|63.2|60.7|65.8|846687|af
|Comoros|64.2|61.9|66.6|794678|af
|Equatorial Guinea|64.2|63.1|65.4|759451|af
|Bhutan|70.1|69.1|71.1|750125|as
|Guyana|68.4|65.4|71.5|735909|sa
|Solomon Islands|75.3|72.7|78.1|635027|oc
-10|Macau|84.5|81.6|87.6|597425|ea
|Western Sahara|63|60.7|65.4|587020|af
|Suriname|72.2|69.8|74.8|585824|sa
|Luxembourg|82.3|79.8|84.9|582291|eu
|Cabo Verde|72.1|69.8|74.5|553432|af
|Brunei|77.2|74.8|79.6|436620|ea
|Malta|80.4|78|82.8|415196|eu
|Maldives|75.6|73.3|78|392960|as
|Belize|68.7|67.2|70.4|353858|la
|Iceland|83|80.9|85.3|335878|eu
|Bahamas, The|72.4|70|74.8|327316|la
|Barbados|75.3|73|77.7|291495|la
|French Polynesia|77.2|74.9|79.6|285321|oc
|Vanuatu|73.4|71.8|75.1|277554|oc
|New Caledonia|77.7|73.7|81.9|275355|oc
|Samoa|73.7|70.8|76.8|198926|oc
|Sao Tome and Principe|64.9|63.6|66.3|197541|af
|Saint Lucia|77.8|75|80.7|164464|la
|Guam|79.1|76.1|82.4|162742|oc
|Curacao|78.3|76|80.7|149035|la
|Aruba|76.8|73.7|79.9|113648|la
|Grenada|74.3|71.7|77.1|111219|la
|Kiribati|66.2|63.7|68.8|106925|oc
|Tonga|76.2|74.7|77.8|106513|oc
|Micronesia, Federated States of|72.9|70.8|75|104719|oc
|Virgin Islands|80|77|83.2|102951|la
|Saint Vincent and the Grenadines|75.3|73.3|77.4|102350|la
|Jersey|81.9|79.4|84.5|98069|eu
|Antigua and Barbuda|76.5|74.4|78.8|93581|la
|Seychelles|74.7|70.2|79.4|93186|af
|Isle of Man|81.2|79.5|83|88195|eu
|Andorra|82.8|80.6|85.1|85660|eu
|Dominica|77|74|80.1|73757|la
|Marshall Islands|73.1|70.9|75.4|73376|oc
|Bermuda|81.3|78.1|84.5|70537|na
|Guernsey|82.5|79.9|85.4|66297|eu
|Greenland|72.4|69.7|75.2|57728|na
|Cayman Islands|81.2|78.5|84|57268|la
|American Samoa|75.4|72.4|78.5|54194|oc
|Northern Mariana Islands|78|75.3|80.8|53467|oc
|Saint Kitts and Nevis|75.7|73.3|78.2|52329|la
|Turks and Caicos Islands|79.8|77.1|82.7|51430|la
|Faroe Islands|80.4|77.8|83.1|50456|eu
|Sint Maarten|78.1|75.8|80.6|41486|la
|Liechtenstein|81.9|79.7|84.6|37937|eu
|British Virgin Islands|78.6|77.2|80.1|34232|la
|San Marino|83.3|80.7|86.1|33285|eu
-1|Monaco|89.5|85.6|93.5|30581|eu
|Gibraltar|79.4|76.6|82.5|29328|eu
|Palau|73.1|69.9|76.5|21347|oc
|Anguilla|81.4|78.8|84.1|16752|la
|Wallis and Futuna|79.7|76.7|82.8|15664|oc
|Tuvalu|66.5|64.3|68.8|10959|oc
|Nauru|67.1|63|70.5|9591|oc
|Cook Islands|75.8|73|78.8|9556|oc
|Saint Helena, Ascension, and Tristan da Cunha|79.5|76.6|82.6|7795|af
|Saint Pierre and Miquelon|80.5|78.2|83|5595|na
1|Montserrat|74.4|75.8|72.9|5267|la
|Falkland Islands (Islas Malvinas)|77.9|75.6|79.6|2931|sa
|Svalbard|NA|NA|NA|2667|eu
|Norfolk Island|NA|NA|NA|2210|oc
|Christmas Island|NA|NA|NA|2205|oc
|Tokelau|NA|NA|NA|1285|oc
|Niue|NA|NA|NA|1190|oc
|Cocos (Keeling) Islands|NA|NA|NA|596|oc
|Pitcairn Islands|NA|NA|NA|54|oc
'''.strip().split('\n')]

# do_refresh_cache = True

def read_url(url, headers={}, path_cache=None, is_verbose=True):
 if (path_cache is None):
  file_cache = os.path.basename(url)
  path_cache = os.path.join('%s.cache' % (os.path.splitext(__file__)[0]),
                            file_cache if (len(file_cache) > 0) else
                            '%s.htm' % (os.path.basename(url.rstrip('/'))))
 if (('do_refresh_cache' in globals() and do_refresh_cache) or
     (not os.path.isfile(path_cache))):
  request = urllib2.Request(url, headers=headers)
  try:                           html = urllib2.urlopen(request).read()
  except urllib2.HTTPError as e: html = ''; print(e)
  try:            os.makedirs(os.path.dirname(path_cache))
  except OSError: pass
  with open(path_cache, 'wb') as f_html: f_html.write(html)
  if (is_verbose): print('%s > %s' % (url, path_cache))
  time.sleep(1) ## avoid rate-limit-exceeded error
 else:
  with open(path_cache) as f_html: html = f_html.read()
  if (is_verbose): print('< %s' % (path_cache))
 try:                       html = html.decode('utf-8')
 except UnicodeDecodeError: pass
 return html
def fmt(string): ## string.format(**vars()) using tags {expression!format} by CMG Lee
 def f(tag): i_sep = tag.rfind('!'); return (re.sub('\.0+$', '', str(eval(tag[1:-1])))
  if (i_sep < 0) else ('{:%s}' % tag[i_sep + 1:-1]).format(eval(tag[1:i_sep])))
 return (re.sub(r'(?<!{){[^{}]+}', lambda m:f(m.group()), string)
         .replace('{{', '{').replace('}}', '}'))
def append(obj, string): return obj.append(fmt(string))
def format_tab(*arg): return '\t'.join([str(el) for el in (arg if len(arg) > 1 else arg[0])])
def tabbify(cellss, separator='|'):
 cellpadss = [list(rows) + [''] * (len(max(cellss, key=len)) - len(rows)) for rows in cellss]
 fmts = ['%%%ds' % (max([len(str(cell)) for cell in cols])) for cols in zip(*cellpadss)]
 return '\n'.join([separator.join(fmts) % tuple(rows) for rows in cellpadss])
def hex_rgb(colour): ## convert [#]RGB to #RRGGBB and [#]RRGGBB to #RRGGBB
 return '#%s' % (colour if len(colour) > 4 else ''.join([c * 2 for c in colour])).lstrip('#')
def try_int_float(field):
 try:     return int(field)
 except:
  try:    return float(field)
  except: return field
def roundm(x, multiple=1):
 try: x[0]; return [roundm(element, multiple) for element in x] ## x[0] checks if x is iterable
 except:    return int(math.floor(float(x) / multiple + 0.5)) * multiple

def findall(regex, string):
 return re.findall(regex, string, flags=re.I|re.DOTALL)
def sub(regex_replace, regex_with, string):
 return str(re.sub(regex_replace, regex_with, string, flags=re.DOTALL).strip())

def make_serial(name): return sub(r'[^a-z]', '', name.lower())
def make_table(datass):
 return '\n'.join(['|'.join([str(data) for data in datas]) for datas in datass])

data_newss = {}

html_expectancy = read_url('http://cia.gov/library/publications/resources/the-world-factbook/fields/355.html')
html_expectancyss = findall(r'(<td.+?</td>)\s*(<td.+?</td>)', html_expectancy)
for html_expectancys in html_expectancyss:
 html_divs = findall(r'<div.+?</div>', html_expectancys[1])
 name      = sub(r'<.*?>', '', html_expectancys[0])
 serial    = make_serial(name)
 # expectancy_male   = None
 # expectancy_female = None
 # try:              expectancy_male   = float(findall(r'[\d.]+(?= years)', html_divs[1])[0])
 # except Exception: pass
 # try:              expectancy_female = float(findall(r'[\d.]+(?= years)', html_divs[2])[0])
 # except Exception: pass
 # if (not serial in data_newss): data_newss[serial] = {}
 # data_newss[serial]['male'  ] = expectancy_male
 # data_newss[serial]['female'] = expectancy_female
 try:
  expectancy_overall = float(findall(r'(?:[\d.]+(?= years)|\d+\.\d+)', html_divs[0])[0])
  expectancy_male    = float(findall(r'(?:[\d.]+(?= years)|\d+\.\d+)', html_divs[1])[0])
  expectancy_female  = float(findall(r'(?:[\d.]+(?= years)|\d+\.\d+)', html_divs[2])[0])
  if (not serial in data_newss): data_newss[serial] = {}
  data_newss[serial]['overall'] = expectancy_overall
  data_newss[serial]['male'   ] = expectancy_male
  data_newss[serial]['female' ] = expectancy_female
 except Exception: pass

html_population = read_url('http://cia.gov/library/publications/resources/the-world-factbook/fields/335.html')
html_populationss = findall(r'(<td.+?</td>)\s*(<td.+?</td>)', html_population)
for html_populations in html_populationss:
 name   = sub(r'<.*?>', '', html_populations[0])
 serial = make_serial(name)
 # population = None
 # if (not 'no indigenous' in html_populations[1]):
 #  try:              population = int(sub(',','',findall(r'[\d,]+', html_populations[1])[0]))
 #  except Exception: pass
 # if (not serial in data_newss): data_newss[serial] = {}
 # data_newss[serial]['population'] = population
 if (not 'no indigenous' in html_populations[1]):
  try:
   population = int(sub(',','',findall(r'[\d,]+', html_populations[1])[0]))
   if (not serial in data_newss): data_newss[serial] = {}
   data_newss[serial]['name']       = name
   data_newss[serial]['population'] = population
  except Exception: pass

outss = []
for serial in sorted(data_newss):
 data_news = data_newss[serial]
 try: outss.append([serial, data_news['name'], data_news['population'],
                    data_news['overall'], data_news['male'], data_news['female']])
                    # data_news['population'] if ('population' in data_news) else None,
                    # data_news['male']       if ('male'       in data_news) else None,
                    # data_news['female']     if ('female'     in data_news) else None])
 except Exception: pass
  # print(data_newss.pop(serial))
# print(tabbify(outss))

outss = []
# print(tabbify(data_oldss))
map_keeps   = {'usa':'unitedstates', 'uk':'unitedkingdom', 'drcongo':'congodemocraticrepublicofthe'}
map_changes = {'swaziland':'eswatini'}

for data_olds in data_oldss:
 name      = data_olds[1]
 serial    = make_serial(name)
 data_news = None
 try:
  if (serial in map_keeps): serial = map_keeps[serial]
  if (serial in map_changes):
   serial    = map_changes[serial]
   data_news = data_newss[serial]
   name      = data_news['name']
  else:
   data_news = data_newss[serial]
 except Exception: pass
 outss.append([data_olds[0],
               name,
               # data_news['name'      ] if ('name'       in data_news) else 'NA',
               data_news['overall'   ] if ('overall'    in data_news) else 'NA',
               data_news['male'      ] if ('male'       in data_news) else 'NA',
               data_news['female'    ] if ('female'     in data_news) else 'NA',
               data_news['population'] if ('population' in data_news) else 'NA',
               data_olds[6]])
 # outss.append(data_olds)
 if (name != data_news['name']): print(name, data_news['name'])
# print(tabbify(outss))
outss = outss[:2] + sorted(outss[2:], key=lambda lines:lines[5], reverse=True)

dir_cache = '%s.cache' % (os.path.splitext(__file__)[0])
with open(os.path.join(dir_cache, 'old.txt'), 'w') as f: f.write(make_table(data_oldss))
with open(os.path.join(dir_cache, 'new.txt'), 'w') as f: f.write(make_table(outss))

Licențiere

Eu, deținătorul drepturilor de autor ale acestei opere, prin prezenta îmi public lucrarea sub următoarele licențe:
w:ro:Creative Commons
atribuind partajând în condiții identice
Sunteți liber:
  • să partajați cu alții – aveți dreptul de a copia, distribui și transmite opera
  • să adaptați – aveți dreptul de a adapta opera
În următoarele condiții:
  • atribuind – Trebuie să atribuiți opera corespunzător, introducând o legătură către licență și indicând dacă ați făcut schimbări. Puteți face asta prin orice metodă rezonabilă, dar nu într-un fel care ar sugera faptul că persoana ce a licențiat conținutul v-ar susține sau ar aproba folosirea de către dumneavoastră a operei sale.
  • partajând în condiții identice – Dacă modificați, transformați sau creați pe baza acestei opere, trebuie să distribuiți opera rezultată doar sub aceeași licență sau sub o licență similară acesteia.
GNU head Se permite copierea, distribuirea și/sau modificarea acestui document conform termenilor Documentației de licență liberă GNU, versiunea 1.2 sau orice altă versiune ulterioară publicată de Free Software Foundation, fără părți neschimbabile, texte de pe copertele principale și finale. O copie a acestei licențe este inclusă în secțiunea numită Documentația de licență liberă GNU.
Puteți alege licența pe care o doriți.

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actuală28 februarie 2019 01:21Miniatură pentru versiunea din 28 februarie 2019 01:21512x448 (127 KB)CmgleeUpdate with 2018 data.
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20 noiembrie 2011 23:21Miniatură pentru versiunea din 20 noiembrie 2011 23:21512x512 (59 KB)Cmglee{{Information |Description ={{en|1=Comparison of male and female life expectancy at birth for countries and territories as defined in the 2011 CIA Factbook, with selected bubbles labelled. The dotted line corresponds to equal female and male life expec

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