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๐ถ 35-year old
๐ณ๏ธโ๐ Progressive
๐ซ Not religious
๐ Single
โ๐ป White
๐ Heterosexual
๐จ โ Man
๐
with a
Bachelor's
๐ป
works as a
Software Dev
๐ก
from
a Home office
๐ฐ
makes
$85,000 / y
โ๏ธ
loves
Coffee
๐ฅฉ eats meat
๐ฅพ
works out by
Hiking
๐ฏ๐ต
loves
Tokyo most
๐
is vaccinated
๐
produces 73% less COโ
7๏ธโฃ
and stays for
7 months
Remote work is now on an exponential trajectory and growing fast. With its growth, hundreds of millions of people who are now newly working remotely from home, a cafe, or coworking space, will realize they've become location independent and travel or move to new places. In this report, we try to figure out who these people are, what work do they do, and how they spend their life based on data from tens of thousands of Nomads.com members.
This page is built LIVE with data pulled straight from the database every day, so it's always up-to-date. Conclusions you can derive from this are always limited and merely indicative but possibly interesting. Nomads.com is a paid membership community, which means there's a selection bias as people who do not or cannot pay are not in the dataset. On the other hand, free digital nomad communities, like on Facebook, require no commitment to join, therefore it's not clear if these people are merely aspirational or active nomads or not. On Nomads.com we can confirm they are active based on their travel logs.
The title of this report is inspired by Buffer's amazing annual remote work report (and used with permission).
You can freely use this page's data, as long as you reference us as "Nomads.com" (with space in between) and use our logo and link back on every data mention! Thanks!. If you like this, also see the live network graph of all travels on Nomads.com and the fastest growing remote work hubs of 2024.
Last updated: 31 minutes ago
๐ถ Nomads by age |
||||
Age | % | |||
19 |
0.2%
|
|||
21 |
0.2%
|
|||
22 |
0.2%
|
|||
23 |
0.4%
|
|||
24 |
1%
|
|||
25 |
1%
|
|||
26 |
1%
|
|||
27 |
2%
|
|||
28 |
2%
|
|||
29 |
3%
|
|||
30 |
4%
|
|||
31 |
6%
|
|||
32 |
7%
|
|||
33 |
6%
|
|||
34 |
6%
|
|||
35 |
7%
|
|||
36 |
6%
|
|||
37 |
6%
|
|||
38 |
5%
|
|||
39 |
5%
|
|||
40 |
4%
|
|||
41 |
3%
|
|||
42 |
3%
|
|||
43 |
2%
|
|||
44 |
2%
|
n=1,238 |
โณ๏ธ Nomads by nationality |
||||
# | Country | People | % | |
1 | ๐บ๐ธ United States | 39,117,795 | 45% | |
2 | ๐ฌ๐ง United Kingdom | 6,139,282 | 7% | |
3 | ๐ท๐บ Russia | 4,042,685 | 5% | |
4 | ๐จ๐ฆ Canada | 4,014,684 | 5% | |
5 | ๐ฉ๐ช Germany | 3,402,156 | 4% | |
6 | ๐ซ๐ท France | 2,877,132 | 3% | |
7 | ๐ง๐ท Brazil | 2,159,599 | 2% | |
8 | ๐ฆ๐บ Australia | 2,047,594 | 2% | |
9 | ๐ณ๐ฑ Netherlands | 1,571,572 | 2% | |
10 | ๐ช๐ธ Spain | 1,501,569 | 2% | |
11 | ๐ฎ๐ณ India | 1,288,059 | 1% | |
12 | ๐บ๐ฆ Ukraine | 1,183,054 | 1% | |
13 | ๐ฎ๐น Italy | 1,102,551 | 1% | |
14 | ๐ต๐ฑ Poland | 1,008,046 | 1% | |
15 | ๐จ๐ญ Switzerland | 857,539 | 1% | |
16 | ๐ฆ๐น Austria | 689,532 | 1% | |
17 | ๐ธ๐ช Sweden | 598,527 | 1% | |
18 | ๐ฏ๐ต Japan | 574,026 | 1% | |
19 | ๐ฎ๐ช Ireland | 563,526 | 1% | |
20 | ๐น๐ท Turkey | 546,025 | 1% | |
21 | ๐ฎ๐ฑ Israel | 546,025 | 1% | |
22 | ๐ง๐ช Belgium | 479,522 | 1% | |
23 | ๐จ๐ฟ Czechia | 476,022 | 1% | |
24 | ๐ฐ๐ท South Korea | 462,021 | 1% | |
25 | ๐ฟ๐ฆ South Africa | 448,021 | 1% | |
26 | ๐ฒ๐ฝ Mexico | 423,519 | 0% | |
27 | ๐ธ๐ฌ Singapore | 416,519 | 0% | |
28 | ๐ต๐น Portugal | 413,019 | 0% | |
29 | ๐ฆ๐ท Argentina | 409,519 | 0% | |
30 | ๐ณ๐ฟ New Zealand | 392,018 | 0% | n=24,926 |
๐ถ Nomads by gender |
||||
Gender | % | |||
๐จโ Men |
89%
|
|||
๐ฑโโ๏ธ Women |
11%
|
|||
๐ง Other |
1%
|
Last 30 days. n=166 |
๐ Nomads by sexuality |
||||
Sexuality | % | |||
๐ Heterosexual |
87%
|
|||
๐ฆ Bisexual |
8%
|
|||
๐ณ๏ธโ๐ Gay or lesbian |
5%
|
n=14,852 |
๐ Nomads by beliefs |
||||
Religion | % | |||
๐ซ Not religious |
53%
|
|||
๐ Spirituality |
28%
|
|||
โช๏ธ Christianity |
9%
|
|||
๐ Buddhism |
3%
|
|||
โจ Astrology |
2%
|
|||
๐ Islam |
2%
|
|||
๐ Judaism |
2%
|
|||
๐ Hinduism |
1%
|
|||
๐ณ Sikhism |
0%
|
n=7,649 |
โ Nomads by ethnicity |
||||
Ethnicity | % | |||
โ๐ป White |
59%
|
|||
โ๐พ Non-white |
41%
|
|||
↱โ๐ผ Asian |
14%
|
|||
↱โ๐ฝ Latin |
12%
|
|||
↱โ๐ฟ Black |
7%
|
|||
↱โ๐ฝ Indian |
5%
|
|||
↱โ๐พ Middle Eastern |
3%
|
|||
↱โ๐ฝ Pacific |
1%
|
n=6,839 |
๐ Education |
||||
Education | % | |||
๐ High School |
10%
|
|||
๐ Higher education |
90%
|
|||
↱๐ Bachelor's |
54%
|
|||
↱๐ Master's |
34%
|
|||
↱๐ฉโ๐ซ PhD |
3%
|
n=15,601 |
โค๏ธ Nomads by relationship |
||||
Relationship | % | |||
๐ Single |
67%
|
|||
๐ In a relationship |
33%
|
n=8,441 |
๐ Nomads looking for |
||||
Looking for | % | |||
๐ค Friends |
35%
|
|||
๐ Travel buddies |
32%
|
|||
๐น Casual dating |
15%
|
|||
โค๏ธ Relationship |
13%
|
|||
๐ Poly dating |
4%
|
n=52,313 |
๐ฐ Nomads by income |
||||
Income | % | |||
< $25k / y |
6%
|
|||
$25k - $50k / y |
15%
|
|||
$50k - $100k / y |
34%
|
|||
$100k - $250k / y |
35%
|
|||
> $250k - $1M / y |
8%
|
|||
> $1M / y |
2%
|
|||
Average | $123,896 / y | |||
Median | $85,000 / y | n=4,367 |
๐ฐ Nomads by employment |
||||
Employment type | % | |||
Full time |
40%
|
|||
Freelance |
18%
|
|||
Startup founder |
17%
|
|||
Full time contractor |
9%
|
|||
Agency |
8%
|
|||
Other |
5%
|
|||
Part time |
2%
|
|||
Part time contractor |
1%
|
n=5,253 |
๐ก Where do nomads work from |
||||
Place | % | |||
๐ก Home office |
59%
|
|||
๐ฌ Coworking |
15%
|
|||
โ๏ธ Cafe |
8%
|
|||
๐ข Office |
6%
|
|||
๐ฝ Dining table |
4%
|
|||
๐ Couch |
3%
|
|||
๐ Bed |
2%
|
|||
๐ช Balcony |
1%
|
|||
๐ Van |
1%
|
|||
๐ช Kitchen |
0%
|
|||
๐ฆ Pool |
0%
|
|||
๐ชด Garden |
0%
|
|||
๐ฅ Boat |
0%
|
|||
๐ Library |
0%
|
|||
๐ก En รงok รงalฤฑลtฤฑฤฤฑnฤฑz yeri seรงin |
0%
|
n=4,229 |
๐ฌ What messaging apps nomads use? |
||||
Messaging app | % | |||
Telegram |
47%
|
|||
43%
|
||||
5%
|
||||
2%
|
||||
Snapchat |
2%
|
|||
0%
|
||||
LINE |
0%
|
|||
Slack |
0%
|
n=4,798 |
โ๏ธ Nomad men by politics |
||||
Politics | % | |||
๐ณ๏ธโ๐ Progressive |
47%
|
|||
โ๏ธ Non-progressive |
53%
|
|||
↱๐ฝ Libertarian |
26%
|
|||
↱โ๏ธ Centrist |
21%
|
|||
↱๐ด Conservative |
6%
|
n=3,351 |
โ๏ธ Nomad women by politics |
||||
Politics | % | |||
๐ณ๏ธโ๐ Progressive |
72%
|
|||
โ๏ธ Non-progressive |
28%
|
|||
↱๐ฝ Libertarian |
12%
|
|||
↱โ๏ธ Centrist |
12%
|
|||
↱๐ด Conservative |
3%
|
n=794 |
๐ฅฉ 75% of ๐จโ men eat meat
๐ฅฉ 56% of ๐ฑโโ๏ธwomen eat meat
๐ซ 38% of nomads don't eat meat
๐ฅ 12% are vegetarian
๐ฅ 11% are vegan
๐ 5% are pescetarian
๐ Nomad men by diet |
||||
Diet | % | |||
๐ฅฉ Eats meat |
75%
|
|||
๐ซ Does not eat meat |
25%
|
|||
↱๐ฅ Vegan |
10%
|
|||
↱๐ฅ Vegetarian |
10%
|
|||
↱๐ Pescetarian |
4%
|
n=5,212 |
๐ Nomad women by diet |
||||
Diet | % | |||
๐ฅฉ Eats meat |
56%
|
|||
๐ซ Does not eat meat |
44%
|
|||
↱๐ฅ Vegetarian |
18%
|
|||
↱๐ฅ Vegan |
15%
|
|||
↱๐ Pescetarian |
10%
|
n=1,188 |
๐ฅพ Hiking
๐ช Fitness
๐ Running
๐คธโโ๏ธ Yoga
๐ Swimming
๐ด Cycling
๐ Nomad men by sports |
||||
Sport | % | |||
๐ฅพ Hiking |
49%
|
|||
๐ช Fitness |
48%
|
|||
๐ Running |
29%
|
|||
๐ด Cycling |
25%
|
|||
๐ Swimming |
24%
|
|||
๐คธโโ๏ธ Yoga |
21%
|
|||
๐ Surfing |
18%
|
|||
โฐ Climbing |
16%
|
|||
๐ Snowboarding |
16%
|
|||
๐ Diving |
16%
|
|||
โท Skiing |
15%
|
|||
๐พ Tennis |
14%
|
|||
๐ Motorcycling |
13%
|
|||
๐ช Fight sports |
11%
|
|||
๐ช Crossfit |
9%
|
n=9,879 |
๐ Nomad women by sports |
||||
Sport | % | |||
๐ฅพ Hiking |
51%
|
|||
๐คธโโ๏ธ Yoga |
44%
|
|||
๐ช Fitness |
40%
|
|||
๐ Swimming |
24%
|
|||
๐ Running |
21%
|
|||
๐ด Cycling |
17%
|
|||
๐ Diving |
15%
|
|||
๐ Surfing |
14%
|
|||
โฐ Climbing |
13%
|
|||
โท Skiing |
12%
|
|||
๐พ Tennis |
10%
|
|||
๐ Snowboarding |
9%
|
|||
๐ช Crossfit |
6%
|
|||
๐ Motorcycling |
5%
|
|||
๐ช Fight sports |
5%
|
n=2,450 |
๐ฏ๐ต Tokyo
๐ต๐น Portimรฃo
๐ง๐ฆ Sarajevo
๐บ๐ธ Chicago
๐ง๐ฌ Varna
๐ญ๐ท Dubrovnik
๐ Most liked cities by men |
||||
# | City | Rating | ||
1 | ๐ฏ๐ต Tokyo | 4.62 | ||
2 | ๐ช๐ธ Madrid | 4.62 | ||
3 | ๐ต๐น Porto | 4.58 | ||
4 | ๐ฒ๐ฝ Mexico City | 4.55 | ||
5 | ๐ฐ๐ท Seoul | 4.50 | ||
6 | ๐จ๐ฟ Prague | 4.44 | ||
7 | ๐ต๐ฑ Warsaw | 4.44 | ||
8 | ๐ช๐ธ Valencia | 4.44 | ||
9 | ๐ฌ๐ท Athens | 4.44 | ||
10 | ๐บ๐ธ New York City | 4.38 | ||
11 | ๐ฉ๐ช Munich | 4.29 | ||
12 | ๐ฒ๐พ Penang | 4.29 | ||
13 | ๐น๐ญ Chiang Mai | 4.17 | ||
14 | ๐ญ๐บ Budapest | 4.17 | ||
15 | ๐ฏ๐ต Kyoto | 4.17 | n=7,173 |
๐ Most liked cities by women |
||||
# | City | Rating | ||
1 | ๐ญ๐บ Budapest | 3.75 | ||
2 | ๐ฉ๐ช Munich | 3.75 | ||
3 | ๐ง๐ฌ Sofia | 3.75 | ||
4 | ๐จ๐ด Medellรญn | 3.75 | ||
5 | ๐บ๐ธ Los Angeles | 3.75 | n=7,173 |
๐ Most visited cities |
||||
# | City | % visited | ||
1 | ๐ฌ๐ง London | 2.25% | ||
2 | ๐น๐ญ Bangkok | 2.06% | ||
3 | ๐บ๐ธ New York City | 1.54% | ||
4 | ๐ฉ๐ช Berlin | 1.5% | ||
5 | ๐ซ๐ท Paris | 1.49% | ||
6 | ๐ต๐น Lisbon | 1.48% | ||
7 | ๐ช๐ธ Barcelona | 1.48% | ||
8 | ๐ณ๐ฑ Amsterdam | 1.24% | ||
9 | ๐บ๐ธ San Francisco | 1.17% | ||
10 | ๐น๐ญ Chiang Mai | 1.08% | ||
11 | ๐ฒ๐ฝ Mexico City | 1% | ||
12 | ๐ธ๐ฌ Singapore | 0.9% | ||
13 | ๐ฎ๐ฉ Canggu | 0.9% | ||
14 | ๐บ๐ธ Los Angeles | 0.86% | ||
15 | ๐ฏ๐ต Tokyo | 0.86% | ||
16 | ๐น๐ท Istanbul | 0.85% | ||
17 | ๐ช๐ธ Madrid | 0.81% | ||
18 | ๐ญ๐บ Budapest | 0.8% | ||
19 | ๐ฒ๐พ Kuala Lumpur | 0.78% | ||
20 | ๐จ๐ฟ Prague | 0.73% | ||
21 | ๐ฆ๐ช Dubai | 0.72% | ||
22 | ๐ฆ๐ท Buenos Aires | 0.67% | ||
23 | ๐จ๐ด Medellรญn | 0.64% | ||
24 | ๐ท๐บ Moscow | 0.61% | ||
25 | ๐ฎ๐น Rome | 0.59% | ||
26 | ๐ฆ๐น Vienna | 0.59% | ||
27 | ๐ป๐ณ Ho Chi Minh City | 0.53% | ||
28 | ๐ญ๐ฐ Hong Kong | 0.52% | ||
29 | ๐ฎ๐ฉ Ubud | 0.52% | ||
30 | ๐น๐ญ Phuket | 0.52% | n=349,346 |
๐ Most visited countries |
||||
# | Country | % visited | ||
1 | ๐บ๐ธ United States | 14% | ||
2 | ๐ช๐ธ Spain | 5% | ||
3 | ๐น๐ญ Thailand | 5% | ||
4 | ๐ฌ๐ง United Kingdom | 4% | ||
5 | ๐ฉ๐ช Germany | 4% | ||
6 | ๐ฒ๐ฝ Mexico | 4% | ||
7 | ๐ซ๐ท France | 3% | ||
8 | ๐ฎ๐น Italy | 3% | ||
9 | ๐ต๐น Portugal | 3% | ||
10 | ๐ฎ๐ฉ Indonesia | 2% | ||
11 | ๐ง๐ท Brazil | 2% | ||
12 | ๐จ๐ฆ Canada | 2% | ||
13 | ๐ฏ๐ต Japan | 2% | ||
14 | ๐ณ๐ฑ Netherlands | 2% | ||
15 | ๐ป๐ณ Vietnam | 2% | ||
16 | ๐ท๐บ Russia | 2% | ||
17 | ๐จ๐ด Colombia | 1% | ||
18 | ๐น๐ท Turkey | 1% | ||
19 | ๐ต๐ฑ Poland | 1% | ||
20 | ๐ฆ๐บ Australia | 1% | ||
21 | ๐ฒ๐พ Malaysia | 1% | ||
22 | ๐ฌ๐ท Greece | 1% | ||
23 | ๐ฎ๐ณ India | 1% | ||
24 | ๐ฆ๐ท Argentina | 1% | ||
25 | ๐จ๐ญ Switzerland | 1% | ||
26 | ๐ฆ๐น Austria | 1% | ||
27 | ๐ญ๐ท Croatia | 1% | ||
28 | ๐ธ๐ฌ Singapore | 1% | n=349,346 |
๐ Avg. COโ by member traveling |
||||
Year | COโ | |||
2013 |
694 kg/y
|
|||
2014 |
1,018 kg/y
|
|||
2015 |
1,094 kg/y
|
|||
2016 |
1,312 kg/y
|
|||
2017 |
1,497 kg/y
|
|||
2018 |
1,598 kg/y
|
|||
2019 |
1,623 kg/y
|
|||
2020 |
1,011 kg/y
|
|||
2021 |
1,016 kg/y
|
|||
2022 |
1,622 kg/y
|
|||
2023 |
1,789 kg/y
|
|||
2024 |
1,930 kg/y
|
|||
Average | 1,305 kg/y | |||
Median | 1,350 kg/y |
Based on 349,346 trips by 13,883 members @ 115g/km COโ emitted. An average American spends ~5,000kg/y on commuting by car and flying. We'd assume nomads travel more internationally but on the other hand they don't commute to work since they work 100% remotely. Many walk to work or work from their home, hotel or Airbnb. That means on average nomads generate 1,350 kg/y, or 73% less COโ than the average American on travel and commuting. |
๐จ Where men go most |
||||
# | Tag | vs. ๐ฑโโ๏ธ | ||
1 | ๐น๐ญ Bangkok | +21% | ||
2 | ๐ต๐น Lisbon | -15% | ||
3 | ๐ช๐ธ Barcelona | -11% | ||
4 | ๐ฌ๐ง London | -21% | ||
5 | ๐ซ๐ท Paris | -19% | ||
6 | ๐ฉ๐ช Berlin | 0% | ||
7 | ๐ณ๐ฑ Amsterdam | +5% | ||
8 | ๐น๐ญ Chiang Mai | -5% | ||
9 | ๐ฎ๐ฉ Canggu | +3% | ||
10 | ๐น๐ท Istanbul | +7% | ||
11 | ๐ฒ๐ฝ Mexico City | -23% | ||
12 | ๐ธ๐ฌ Singapore | +10% | ||
13 | ๐ญ๐บ Budapest | +16% | ||
14 | ๐ฏ๐ต Tokyo | +13% | ||
15 | ๐ฒ๐พ Kuala Lumpur | +26% | median temp=18°C; n=349,346 |
๐ฑโโ๏ธ Where women go most |
||||
# | Tag | vs. ๐จ | ||
1 | ๐ต๐น Lisbon | +17% | ||
2 | ๐ฌ๐ง London | +26% | ||
3 | ๐ช๐ธ Barcelona | +12% | ||
4 | ๐ซ๐ท Paris | +23% | ||
5 | ๐น๐ญ Bangkok | -17% | ||
6 | ๐ฒ๐ฝ Mexico City | +29% | ||
7 | ๐น๐ญ Chiang Mai | +5% | ||
8 | ๐ฉ๐ช Berlin | +0% | ||
9 | ๐ณ๐ฑ Amsterdam | -5% | ||
10 | ๐ฎ๐ฉ Canggu | -3% | ||
11 | ๐ฎ๐น Rome | +23% | ||
12 | ๐น๐ท Istanbul | -7% | ||
13 | ๐ฎ๐ฉ Ubud | +27% | ||
14 | ๐บ๐ธ New York City | +10% | ||
15 | ๐ธ๐ฌ Singapore | -9% | median temp=18°C; n=349,346 |
๐จ Where men go more |
||||
# | Tag | vs. women | ||
1 | ๐บ๐ฆ Ukraine | +89% | ||
2 | ๐ต๐ฑ Poland | +73% | ||
3 | ๐ท๐บ Russia | +72% | ||
4 | ๐ท๐ด Romania | +59% | ||
5 | ๐ฌ๐ช Georgia | +46% | ||
6 | ๐ณ๐ฟ New Zealand | +30% | ||
7 | ๐ท๐ธ Serbia | +27% | ||
8 | ๐ญ๐ฐ Hong Kong | +25% | ||
9 | ๐ฆ๐ช United Arab Emirates | +24% | ||
10 | ๐จ๐ฟ Czechia | +21% | ||
11 | ๐ต๐ญ Philippines | +20% | ||
12 | ๐ฒ๐พ Malaysia | +19% | ||
13 | ๐ฏ๐ต Japan | +18% | ||
14 | ๐ฆ๐น Austria | +18% | ||
15 | ๐ธ๐ช Sweden | +17% | median temp=13°C; n=349,346 |
๐ฑโโ๏ธ Where women go more |
||||
# | Tag | vs. men | ||
1 | ๐ฟ๐ฆ South Africa | +49% | ||
2 | ๐จ๐ท Costa Rica | +45% | ||
3 | ๐ฒ๐ฝ Mexico | +40% | ||
4 | ๐ฌ๐ง United Kingdom | +27% | ||
5 | ๐ญ๐ท Croatia | +20% | ||
6 | ๐ซ๐ท France | +18% | ||
7 | ๐ฎ๐น Italy | +18% | ||
8 | ๐จ๐ฑ Chile | +18% | ||
9 | ๐ฌ๐ท Greece | +15% | ||
10 | ๐ต๐ช Peru | +11% | ||
11 | ๐ฆ๐บ Australia | +10% | ||
12 | ๐ต๐น Portugal | +10% | ||
13 | ๐ช๐ธ Spain | +8% | ||
14 | ๐ฆ๐ท Argentina | +5% | ||
15 | ๐ฎ๐ช Ireland | +5% | median temp=18°C; n=349,346 |
๐ Most liked countries |
||||
# | Country | Rating | ||
1 | ๐ฏ๐ต Japan | 4.85 | ||
2 | ๐ญ๐ท Croatia | 4.55 | ||
3 | ๐ง๐ฆ Bosnia | 4.5 | ||
4 | ๐จ๐ฟ Czechia | 4.5 | ||
5 | ๐ต๐ฑ Poland | 4.45 | ||
6 | ๐ฐ๐ท South Korea | 4.4 | ||
7 | ๐ฌ๐ท Greece | 4.4 | ||
8 | ๐ฟ๐ฆ South Africa | 4.3 | ||
9 | ๐ธ๐ฌ Singapore | 4.3 | ||
10 | ๐ญ๐บ Hungary | 4.3 | ||
11 | ๐จ๐ญ Switzerland | 4.3 | ||
12 | ๐จ๐ท Costa Rica | 4.25 | ||
13 | ๐ช๐ธ Spain | 4.2 | ||
14 | ๐ช๐ช Estonia | 4.15 | ||
15 | ๐ฎ๐ฑ Israel | 4.15 | n=4,419 |
๐คฎ Least liked countries |
||||
# | Country | Rating | ||
1 | ๐จ๐บ Cuba | 1 | ||
2 | ๐ช๐น Ethiopia | 1.65 | ||
3 | ๐ฎ๐ท Iran | 1.65 | ||
4 | ๐ญ๐ณ Honduras | 1.65 | ||
5 | ๐ฑ๐ฐ Sri Lanka | 1.8 | ||
6 | ๐จ๐พ Cyprus | 2.35 | ||
7 | ๐จ๐ฑ Chile | 2.4 | ||
8 | ๐ธ๐ด Somalia | 2.5 | ||
9 | ๐น๐ฟ Tanzania | 2.5 | ||
10 | ๐ป๐ช Venezuela | 2.5 | ||
11 | ๐ฑ๐บ Luxembourg | 2.5 | ||
12 | ๐ธ๐ณ Senegal | 2.5 | ||
13 | ๐ฌ๐ฎ Gibraltar | 2.5 | ||
14 | ๐ง๐ณ Brunei | 2.5 | ||
15 | ๐จ๐ป Cape Verde | 2.5 | n=4,419 |
โฐ How long do nomads stay in one city? |
||||
Duration | % | |||
< 7 days |
46%
|
|||
7 - 30 days |
33%
|
|||
30 - 90 days |
14%
|
|||
90+ days |
6%
|
|||
Average | 64 days (2 months) | |||
Median | 7 days | n=340,176 |
๐ก How long do nomads stay in one country? |
||||
Duration | % | |||
< 7 days |
0%
|
|||
7 - 30 days |
57%
|
|||
30 - 90 days |
29%
|
|||
90+ days |
14%
|
|||
Average | 202 days (7 months) | n=340,176 |
๐ป Software Dev
๐ Startup Founder
๐ธ Web Dev
๐ Marketing
๐ฉโ๐จ Creative
๐ SaaS
๐จ Nomad men work as |
||||
# | Work | % | vs. women | |
1 | ๐ป Software Dev | 34% | +248% | |
2 | ๐ธ Web Dev | 28% | +262% | |
3 | ๐ Startup Founder | 27% | +138% | |
4 | ๐ Marketing | 15% | = | |
5 | ๐ SaaS | 13% | +195% | |
6 | ๐ฉโ๐จ Creative | 12% | -18% | |
7 | ๐จ UI/UX Design | 11% | +39% | |
8 | ๐ค Product Manager | 11% | +69% | |
9 | ๐ฐ Crypto | 11% | +252% | |
10 | ๐ Data | 11% | +106% | |
11 | ๐ฑ Mobile Dev | 11% | +351% | |
12 | ๐ฐ Finance | 10% | +131% | |
13 | ๐ Ecommerce | 9% | +100% | |
14 | ๐ค Sales | 7% | +82% | |
15 | ๐จโ๐ซ Education | 6% | -9% | n=18,929 |
๐ฑโโ๏ธ Nomad women work as |
||||
# | Work | % | vs. men | |
1 | ๐ Marketing | 16% | +0% | |
2 | ๐ฉโ๐จ Creative | 15% | +23% | |
3 | ๐ Startup Founder | 11% | -58% | |
4 | ๐ป Software Dev | 10% | -71% | |
5 | ๐จ UI/UX Design | 8% | -28% | |
6 | ๐ธ Web Dev | 8% | -72% | |
7 | ๐ Blogging | 8% | +22% | |
8 | ๐ค Community | 8% | +23% | |
9 | ๐จโ๐ซ Education | 7% | +10% | |
10 | ๐ Coach | 7% | +24% | |
11 | ๐ค Product Manager | 7% | -41% | |
12 | ๐ Data | 5% | -52% | |
13 | ๐ SaaS | 5% | -66% | |
14 | ๐ Ecommerce | 4% | -50% | |
15 | ๐ฐ Finance | 4% | -57% | n=5,732 |
๐จ Nomad men vs. women |
||||
# | Tag | vs. women | ||
1 | ๐ฑ Mobile Dev | +351% | ||
2 | ๐พ Game Dev | +346% | ||
3 | ๐ Dev Ops | +331% | ||
4 | ๐ก Sysadmin | +311% | ||
5 | ๐ธ Web Dev | +262% | ||
6 | ๐ฐ Crypto | +252% | ||
7 | ๐ป Software Dev | +248% | ||
8 | ๐ SaaS | +195% | ||
9 | ๐ VR Dev | +158% | ||
10 | ๐ Sports | +144% | ||
11 | ๐บ Geo | +141% | ||
12 | ๐ Startup Founder | +138% | ||
13 | ๐ฐ Finance | +131% | ||
14 | ๐ OF | +112% | ||
15 | ๐ Data | +106% | n=23,580 |
๐ฑโโ๏ธ Nomad women vs. men |
||||
# | Tag | vs. men | ||
1 | ๐งโ๐ผ Human resources | +64% | ||
2 | ๐ฐ Journalism | +47% | ||
3 | ๐ง Psychologist | +44% | ||
4 | ๐จโโ๏ธ Medical | +37% | ||
5 | ๐ Support | +31% | ||
6 | ๐ Coach | +24% | ||
7 | ๐ค Community | +23% | ||
8 | ๐ Hospitality | +23% | ||
9 | ๐ฉโ๐จ Creative | +23% | ||
10 | ๐ Blogging | +22% | ||
11 | ๐ Recruitment | +14% | ||
12 | ๐ธ Model | +13% | ||
13 | ๐จโ๐ซ Education | +10% | ||
14 | ๐ฉโ๐ผ Law | +8% | n=23,580 |
โ๏ธ Coffee
๐ Optimist
๐ฌ๐ง Speaks English
โฐ Outdoors
๐ COVID vaccinated
๐ถ Dogs
๐จโ Nomad men |
||||
# | Tag | % | vs. ๐ฑโโ๏ธ | |
1 | โ๏ธ Coffee | 40% | +29% | |
2 | ๐ Optimist | 31% | +32% | |
3 | ๐ฌ๐ง Speaks English | 31% | +22% | |
4 | ๐ COVID vaccinated | 28% | +20% | |
5 | โฐ Outdoors | 27% | +8% | |
6 | ๐ฅพ Hiking | 26% | +18% | |
7 | ๐ช Fitness | 26% | +51% | |
8 | ๐ถ Dogs | 26% | +10% | |
9 | ๐บ Beer | 25% | +126% | |
10 | โ๏ธ Waking up early | 25% | +28% | |
11 | ๐ Staying up late | 25% | +55% | |
12 | ๐ง Open-minded | 24% | +21% | |
13 | ๐ Reading | 24% | +11% | |
14 | ๐ท Wine | 23% | +2% | |
15 | ๐ Single | 23% | +36% | n=18,929 |
๐ฑโโ๏ธ Nomad women |
||||
# | Tag | % | vs. ๐จโ | |
1 | โ๏ธ Coffee | 31% | -23% | |
2 | ๐ฌ๐ง Speaks English | 25% | -18% | |
3 | โฐ Outdoors | 25% | -8% | |
4 | ๐ถ Dogs | 24% | -9% | |
5 | ๐ Optimist | 24% | -24% | |
6 | ๐ COVID vaccinated | 23% | -16% | |
7 | ๐ท Wine | 23% | -2% | |
8 | ๐ฅพ Hiking | 22% | -15% | |
9 | ๐ Reading | 21% | -10% | |
10 | ๐ต Tea | 21% | 0% | |
11 | ๐ง Open-minded | 20% | -18% | |
12 | ๐คธโโ๏ธ Yoga | 20% | +71% | |
13 | โ๏ธ Waking up early | 19% | -22% | |
14 | โฑ Beach | 18% | +7% | |
15 | ๐ช Fitness | 17% | -34% | n=5,732 |
๐จ Nomad men vs. women |
||||
# | Tag | vs. ๐ฑโโ๏ธ | ||
1 | ๐ง Have a beard | +1,267% | ||
2 | ๐ช Roost Stand | +381% | ||
3 | โฝ๏ธ Football | +345% | ||
4 | ๐จ No beard | +339% | ||
5 | ๐งโ Short hair | +273% | ||
6 | ๐ Ice hockey | +233% | ||
7 | โ๏ธ Chess | +229% | ||
8 | ๐ Race sports | +228% | ||
9 | ๐ง Hardstyle music | +228% | ||
10 | ๐ช Dropout | +222% | ||
11 | ๐ Motorcycling | +211% | ||
12 | ๐ Basketball | +194% | ||
13 | ๐ Table tennis | +191% | ||
14 | ๐ด Conservative politics | +190% | ||
15 | ๐ Skateboarding | +173% | n=23,580 |
๐ฑโโ๏ธ Nomad women vs. men |
||||
# | Tag | vs. ๐จ | ||
1 | ๐ Makeup | +2,960% | ||
2 | ๐ฑโโ๏ธ Long hair | +281% | ||
3 | ๐ Dress up | +237% | ||
4 | โจ Astrology | +223% | ||
5 | โจ Believe in astrology | +199% | ||
6 | ๐ช Feminism | +196% | ||
7 | ๐ฆพ Disabled | +114% | ||
8 | ๐ฅ Red hair | +101% | ||
9 | ๐จ Drawing | +99% | ||
10 | ๐ Dancing | +88% | ||
11 | ๐ Shopping | +77% | ||
12 | ๐ป Gardening | +72% | ||
13 | ๐คธโโ๏ธ Yoga | +71% | ||
14 | โ๐ฟ Black | +65% | ||
15 | ๐ Pescetarian | +56% | n=23,580 |
๐ Nomads by vaccination |
||||
Vaccinated | % | |||
๐ COVID vaccinated |
94%
|
|||
๐ Not COVID vaccinated |
6%
|
n=7,429 |
โค๏ธ Nomads by family |
||||
Relationship | % | |||
โค๏ธ Close to parents |
81%
|
|||
๐ Not close to parents |
19%
|
n=1,954 |
๐ถ Nomads by childhood |
||||
Childhood | % | |||
๐ Happy childhood |
89%
|
|||
๐ Unhappy childhood |
11%
|
n=2,085 |
๐ก Homeownership amongst nomads |
||||
Homeownership | % | |||
๐ก Homeowner |
54%
|
|||
๐ก Not a homeowner |
46%
|
n=2,254 |
Attractiveness is based on the proportion of people liking or disliking a person based on their photo on Nomads.com's dating app. That does NOT mean people like or dislike specific traits. It's that people who are rated as attractive are more likely to have selected these traits on their profile. TL;DR hot people have specific traits, but those specific traits don't necessarily make you hot (you could always try though).
๐ Not COVID vaccinated
๐ My parents separated
๐ Table tennis
๐ In a relationship
๐ณ๏ธโ๐ LGBT
๐ Volleyball
๐จโ Attractive men's traits |
||||
# | Tag | Diff | ||
1 | ๐ธ Padel | +162% | ||
2 | ๐ In a relationship | +139% | ||
3 | โจ Believe in astrology | +115% | ||
4 | ๐ Not COVID vaccinated | +85% | ||
5 | ๐ Basketball | +76% | ||
6 | ๐งโ Short hair | +64% | ||
7 | ๐ถ Parent | +63% | ||
8 | ๐ก Homeowner | +62% | ||
9 | ๐ Free diving | +62% | ||
10 | ๐ฌ Twitter | +61% | ||
11 | ๐ง Dubstep music | +58% | ||
12 | ๐ฅ Soft boiled eggs | +53% | ||
13 | ๐ง Hardstyle music | +53% | ||
14 | ๐ง Hiphop music | +50% | ||
15 | ๐ iPhone | +46% | ||
16 | ๐ง House music | +46% | ||
17 | ๐ง Pessimist | +44% | ||
18 | โค๏ธ Happy childhood | +44% | ||
19 | ๐ช Crossfit | +44% | ||
20 | ๐ก Not a homeowner | +44% | ||
21 | ๐ฌ Facebook | +42% | ||
22 | ๐ Rugby | +41% | ||
23 | ๐ Volleyball | +40% | ||
24 | ๐ Kitesurfing | +40% | ||
25 | ๐ Table tennis | +39% | ||
26 | ๐๏ธโ Weightlifting | +39% | ||
27 | ๐ Massage | +37% | ||
28 | ๐ฐ Pop music | +36% | ||
29 | โณ๏ธ Golf | +36% | ||
30 | ๐ง Techno music | +35% | n=23,580 |
๐ฑโโ๏ธ Attractive women's traits |
||||
# | Tag | Diff | ||
1 | ๐ My parents separated | +362% | ||
2 | ๐ Not COVID vaccinated | +322% | ||
3 | ๐ Table tennis | +271% | ||
4 | ๐ณ๏ธโ๐ LGBT | +266% | ||
5 | ๐ Shopping | +261% | ||
6 | ๐ง Only child | +230% | ||
7 | ๐ Volleyball | +229% | ||
8 | ๐ Running | +215% | ||
9 | ๐ธ Punk music | +196% | ||
10 | ๐ฝ Libertarian politics | +189% | ||
11 | ๐ฌ Social smoker | +179% | ||
12 | ๐ Motorcycling | +176% | ||
13 | ๐งผ Clean freak | +171% | ||
14 | ๐จโ๐ค Partying | +164% | ||
15 | ๐ Makeup | +163% | ||
16 | โท Skiing | +162% | ||
17 | ๐ In a relationship | +155% | ||
18 | ๐ Dress up | +153% | ||
19 | ๐ Pescetarian | +139% | ||
20 | ๐ท Blues music | +136% | ||
21 | ๐ฑโโ๏ธ Long hair | +133% | ||
22 | โจ Astrology | +130% | ||
23 | ๐พ Drinking alcohol | +129% | ||
24 | ๐ช Fitness | +126% | ||
25 | โฌ๏ธ Has no tattoos | +126% | ||
26 | ๐บ Beer | +121% | ||
27 | ๐ฐ Pop music | +120% | ||
28 | ๐ Vanlife | +118% | ||
29 | ๐ Surfing | +117% | ||
30 | ๐ Staying up late | +116% | n=23,580 |
Attractiveness is based on the proportion of people liking or disliking a person based on their photo on Nomads.com's dating app. That does NOT mean people like or dislike specific traits. It's that people who are rated as unattractive are more likely to have selected these traits on their profile. TL;DR unattractive people have specific traits, but those specific traits don't necessarily make you unattractive.
๐ FetLife
๐ช Paragliding
๐ญ Swinging
๐ฌ Discord
๐ Makeup
๐ธ Anime
๐จโ Unattractive men's traits |
||||
# | Tag | Diff | ||
1 | ๐ FetLife | -1,487% | ||
2 | ๐ญ Swinging | -649% | ||
3 | ๐ Makeup | -561% | ||
4 | ๐ณ Bowling | -248% | ||
5 | ๐ช Skydiving | -220% | ||
6 | ๐ช Nexstand | -217% | ||
7 | ๐ฑ Pool | -95% | ||
8 | ๐ Religious | -78% | ||
9 | ๐ถโ๐ซ๏ธ Hang gliding | -72% | ||
10 | ๐ Urbex | -71% | ||
11 | ๐ช Paragliding | -65% | ||
12 | ๐ Single | -64% | ||
13 | ๐ป Gardening | -56% | ||
14 | ๐ Unhappy childhood | -53% | ||
15 | ๐ Sex positive | -52% | ||
16 | ๐ Paleo | -51% | ||
17 | ๐ Kink | -50% | ||
18 | โ๏ธ Private pilot | -47% | ||
19 | ๐ช Feminism | -44% | ||
20 | ๐จ Drawing | -44% | ||
21 | ๐ง Trance music | -42% | ||
22 | ๐ณ๏ธโ๐ Progressive politics | -40% | ||
23 | ๐ฌ Discord | -38% | ||
24 | ๐ฉ Samoyeds | -35% | ||
25 | ๐จโ๐ฆฒ Bald | -31% | ||
26 | ๐ฅ Hard boiled eggs | -31% | ||
27 | ๐ Film making | -26% | ||
28 | ๐ Third Culture Kid | -25% | ||
29 | ๐ Motorcycling | -24% | ||
30 | ๐บ Breakdance | -23% | n=23,580 |
๐ฑโโ๏ธ Unattractive women's traits |
||||
# | Tag | Diff | ||
1 | ๐ฅ Messy | -1,848% | ||
2 | ๐ช Paragliding | -1,005% | ||
3 | ๐ฌ Slack | -690% | ||
4 | ๐ฌ Discord | -532% | ||
5 | ๐ด Conservative politics | -479% | ||
6 | ๐ธ Anime | -347% | ||
7 | ๐ฐ๐ท K-pop music | -190% | ||
8 | ๐ช Roost Stand | -137% | ||
9 | ๐ถโ๐ซ๏ธ Hang gliding | -137% | ||
10 | ๐ฌ Snapchat | -137% | ||
11 | ๐ Kink | -113% | ||
12 | ๐ Skateboarding | -71% | ||
13 | ๐ Carnivore | -63% | ||
14 | ๐ Country music | -26% | ||
15 | ๐ฌ Facebook | -22% | ||
16 | ๐ถ Parent | -18% | ||
17 | ๐ Kitesurfing | -18% | ||
18 | ๐ณ Introvert | -15% | ||
19 | โค๏ธ Happy childhood | -11% | ||
20 | ๐ Paleo | -9% | ||
21 | ๐ช Fight sports | -8% | ||
22 | ๐ง Garage music | -5% | ||
23 | ๐ง Pessimist | -5% | ||
24 | ๐ Sustainability | -4% | ||
25 | ๐ธ Badminton | -1% | n=23,580 |
Attractiveness is based on the proportion of people liking or disliking a person based on their photo on Nomads.com's dating app. That does NOT mean people like or dislike specific jobs. It's that people who are rated as attractive are more likely to work in speciifc industries. TL;DR hot people work in specific industries, but those specific industries don't necessarily make you hot (you could always try though).
๐ฑ Mobile Dev
๐ค Community
๐จ UI/UX Design
๐ช Fitness
๐ SaaS
๐ Startup Founder
๐จโ Attractive men's jobs |
||||
# | Tag | Diff | ||
1 | ๐จโโ๏ธ Medical | +59% | ||
2 | ๐ Recruitment | +51% | ||
3 | ๐จ UI/UX Design | +36% | ||
4 | ๐ SaaS | +33% | ||
5 | ๐ฑ Mobile Dev | +32% | ||
6 | ๐ง Psychologist | +31% | ||
7 | ๐ค Product Manager | +29% | ||
8 | ๐ Ecommerce | +25% | ||
9 | ๐ Startup Founder | +20% | ||
10 | ๐ Logistics | +19% | ||
11 | ๐พ Game Dev | +16% | ||
12 | ๐ Dev Ops | +16% | ||
13 | ๐ป Software Dev | +15% | ||
14 | ๐ค Sales | +14% | ||
15 | ๐ช Fitness | +14% | ||
16 | ๐ Marketing | +13% | ||
17 | ๐ Coach | +13% | ||
18 | ๐ VR Dev | +12% | ||
19 | ๐ Data | +11% | ||
20 | ๐ฐ Finance | +8% | ||
21 | ๐ธ Web Dev | +8% | ||
22 | ๐ฐ Crypto | +3% | ||
23 | ๐ค Community | +2% | n=23,580 |
๐ฑโโ๏ธ Attractive women's jobs |
||||
# | Tag | Diff | ||
1 | ๐ค Community | +114% | ||
2 | ๐ฑ Mobile Dev | +109% | ||
3 | ๐ช Fitness | +100% | ||
4 | ๐ฉโ๐จ Creative | +93% | ||
5 | ๐ Blogging | +83% | ||
6 | ๐จ UI/UX Design | +78% | ||
7 | ๐ Startup Founder | +76% | ||
8 | ๐ SaaS | +69% | ||
9 | ๐ Coach | +64% | ||
10 | ๐ Ecommerce | +58% | ||
11 | ๐ Marketing | +56% | ||
12 | ๐ค Product Manager | +47% | ||
13 | ๐จโ๐ซ Education | +47% | ||
14 | ๐ฐ Finance | +45% | ||
15 | ๐ค Sales | +36% | ||
16 | ๐ป Software Dev | +19% | ||
17 | ๐ Data | +5% | n=23,580 |
Attractiveness is based on the proportion of people liking or disliking a person based on their photo on Nomads.com's dating app. That does NOT mean people like or dislike specific jobs. It's that people who are rated as unattractive are more likely to have selected these jobs on their profile. TL;DR unattractive people have specific jobs, but those specific jobs don't necessarily make you unattractive.
๐ฉ Politics
๐ OF
๐ Hospitality
๐ Sports
๐ฉโ๐ผ Law
๐ฐ Journalism
๐จโ Unattractive men's jobs |
||||
# | Tag | Diff | ||
1 | ๐ฉ Politics | -464% | ||
2 | ๐ OF | -208% | ||
3 | ๐ฉโ๐ผ Law | -100% | ||
4 | ๐ฐ Journalism | -73% | ||
5 | ๐ถ Adult | -42% | ||
6 | ๐ก Architecture | -41% | ||
7 | ๐ Hospitality | -26% | ||
8 | ๐ก Sysadmin | -25% | ||
9 | ๐ธ Model | -24% | ||
10 | ๐บ Geo | -20% | ||
11 | ๐ Support | -20% | ||
12 | ๐จโ๐ซ Education | -9% | ||
13 | ๐ฉโ๐จ Creative | -5% | ||
14 | ๐ Sports | -5% | ||
15 | ๐ Blogging | -1% | n=23,580 |
๐ฑโโ๏ธ Unattractive women's jobs |
||||
# | Tag | Diff | ||
1 | ๐ฉ Politics | -1,163% | ||
2 | ๐ VR Dev | -558% | ||
3 | ๐ Sports | -100% | ||
4 | ๐ Hospitality | -86% | ||
5 | ๐ Logistics | -42% | ||
6 | ๐ Support | -4% | ||
7 | ๐ธ Web Dev | -3% | n=23,580 |
๐จโ Where attractive men travel to |
||||
# | City | Attractiveness | ||
1 | ๐ฎ๐ฉ Uluwatu | 5 | ||
2 | ๐ต๐น Ericeira | 4.84 | ||
3 | ๐ฆ๐บ Brisbane | 4.84 | ||
4 | ๐ฌ๐ท Mykonos | 4.84 | ||
5 | ๐จ๐ท Tamarindo | 4.79 | ||
6 | ๐ฎ๐ธ Reykjavik | 4.73 | ||
7 | ๐ฒ๐ฝ Cabo San Lucas | 4.72 | ||
8 | ๐ณ๐ด Bergen | 4.69 | ||
9 | ๐ต๐น Faro | 4.68 | ||
10 | ๐น๐ญ Ko Phi Phi | 4.62 | ||
11 | ๐ฉ๐ช Frankfurt | 4.6 | ||
12 | ๐บ๐ธ Boston | 4.59 | ||
13 | ๐ฒ๐พ Langkawi | 4.5 | ||
14 | ๐ฆ๐บ Melbourne | 4.47 | ||
15 | ๐จ๐ณ Macau | 4.46 | ||
16 | ๐บ๐ธ Orlando | 4.46 | ||
17 | ๐ช๐ธ Ibiza | 4.46 | ||
18 | ๐ฐ๐ท Busan | 4.46 | ||
19 | ๐น๐ญ Ko Lanta | 4.45 | ||
20 | ๐ณ๐ฟ Queenstown | 4.41 | ||
21 | ๐ฆ๐น Innsbruck | 4.4 | ||
22 | ๐ฒ๐ฝ Sayulita | 4.4 | ||
23 | ๐ง๐ช Antwerp | 4.39 | ||
24 | ๐ณ๐ฟ Auckland | 4.37 | ||
25 | ๐ง๐ท Rio de Janeiro | 4.36 | ||
26 | ๐ป๐ณ Hoi An | 4.36 | ||
27 | ๐ช๐ธ Mallorca | 4.36 | ||
28 | ๐ฑ๐ฆ Luang Prabang | 4.36 | ||
29 | ๐ฟ๐ฆ Johannesburg | 4.34 | ||
30 | ๐ช๐ธ Seville | 4.32 | Based on attractiveness of visitors n=349,346 |
๐ฑโโ๏ธ Where attractive women travel to |
||||
# | City | Attractiveness | ||
1 | ๐น๐ญ Ko Phi Phi | 5 | ||
2 | ๐ง๐ฆ Mostar | 4.95 | ||
3 | ๐ญ๐ท Zadar | 4.9 | ||
4 | ๐ฎ๐น Genoa | 4.88 | ||
5 | ๐ต๐ฑ Warsaw | 4.83 | ||
6 | ๐ฒ๐ช Budva | 4.82 | ||
7 | ๐บ๐ธ Orlando | 4.82 | ||
8 | ๐บ๐ฆ Kyiv | 4.81 | ||
9 | ๐ฆ๐น Salzburg | 4.8 | ||
10 | ๐จ๐ฑ Valparaรญso | 4.74 | ||
11 | ๐น๐ญ Ko Samui | 4.73 | ||
12 | ๐ช๐ธ Fuerteventura | 4.72 | ||
13 | ๐ฉ๐ด Punta Cana | 4.71 | ||
14 | ๐ฎ๐น Amalfi | 4.69 | ||
15 | ๐จ๐พ Larnaca | 4.68 | ||
16 | ๐ฒ๐ฆ Casablanca | 4.68 | ||
17 | ๐ฎ๐ฑ Tel Aviv | 4.66 | ||
18 | ๐บ๐ธ Boston | 4.64 | ||
19 | ๐น๐ท Antalya | 4.62 | ||
20 | ๐ซ๐ท Strasbourg | 4.62 | ||
21 | ๐ฉ๐ช Dusseldorf | 4.62 | ||
22 | ๐ฌ๐ท Mykonos | 4.61 | ||
23 | ๐ฎ๐น Milan | 4.6 | ||
24 | ๐ท๐บ Moscow | 4.59 | ||
25 | ๐ธ๐ฐ Bratislava | 4.59 | ||
26 | ๐น๐ญ Krabi | 4.59 | ||
27 | ๐น๐ญ Pai | 4.59 | ||
28 | ๐ท๐บ Saint Petersburg | 4.59 | ||
29 | ๐ช๐ธ Ibiza | 4.59 | ||
30 | ๐ฎ๐ฉ Jakarta | 4.58 | Based on attractiveness of visitors n=349,346 |
๐จโ Where unattractive men travel to |
||||
# | City | Attractiveness | ||
1 | ๐น๐ญ Pattaya | 3.06 | ||
2 | ๐ฎ๐ณ Goa | 3.23 | ||
3 | ๐บ๐ธ Houston | 3.28 | ||
4 | ๐ฎ๐ณ Mumbai | 3.56 | ||
5 | ๐ต๐พ Asuncion | 3.6 | ||
6 | ๐ฒ๐ฝ Guadalajara | 3.63 | ||
7 | ๐จ๐ณ Guangzhou | 3.63 | ||
8 | ๐ฒ๐ช Podgorica | 3.63 | ||
9 | ๐ฐ๐ฟ Almaty | 3.63 | ||
10 | ๐ฎ๐ณ Bengaluru | 3.63 | ||
11 | ๐ถ๐ฆ Doha | 3.64 | ||
12 | ๐ณ๐ต Kathmandu | 3.65 | ||
13 | ๐ช๐ฌ Cairo | 3.66 | ||
14 | ๐ฐ๐ช Nairobi | 3.69 | ||
15 | ๐ฒ๐ฝ Merida | 3.7 | ||
16 | ๐น๐ท Antalya | 3.71 | ||
17 | ๐ท๐บ Moscow | 3.72 | ||
18 | ๐ง๐พ Minsk | 3.75 | ||
19 | ๐ฎ๐น Turin | 3.75 | ||
20 | ๐ฌ๐ช Batumi | 3.76 | ||
21 | ๐จ๐ณ Shenzhen | 3.76 | ||
22 | ๐ฐ๐ญ Phnom Penh | 3.76 | ||
23 | ๐บ๐ฆ Lviv | 3.76 | ||
24 | ๐ฌ๐ง Glasgow | 3.76 | ||
25 | ๐ฒ๐ฝ Oaxaca | 3.76 | ||
26 | ๐ฆ๐ช Dubai | 3.76 | ||
27 | ๐ต๐ฆ Panama City | 3.78 | ||
28 | ๐บ๐ธ Washington | 3.78 | ||
29 | ๐น๐ญ Pai | 3.78 | ||
30 | ๐ณ๐ฑ Rotterdam | 3.79 | Based on unattractiveness of visitors n=349,346 |
๐ฑโโ๏ธ Where unattractive women travel to |
||||
# | City | Attractiveness | ||
1 | ๐ฐ๐ช Nairobi | 3.09 | ||
2 | ๐ช๐จ Quito | 3.26 | ||
3 | ๐ฆ๐บ Perth | 3.42 | ||
4 | ๐บ๐ธ New Orleans | 3.43 | ||
5 | ๐ฌ๐ง Liverpool | 3.43 | ||
6 | ๐ฑ๐ฆ Vientiane | 3.44 | ||
7 | ๐ฌ๐ง Manchester | 3.45 | ||
8 | ๐ณ๐ฟ Wellington | 3.45 | ||
9 | ๐ฒ๐ฝ Guadalajara | 3.46 | ||
10 | ๐บ๐ธ Atlanta | 3.46 | ||
11 | ๐ง๐ช Antwerp | 3.48 | ||
12 | ๐ฏ๐ต Fukuoka | 3.48 | ||
13 | ๐จ๐ฆ Quebec City | 3.51 | ||
14 | ๐ต๐ท San Juan | 3.51 | ||
15 | ๐ณ๐ฎ San Juan del Sur | 3.53 | ||
16 | ๐ฐ๐ญ Phnom Penh | 3.61 | ||
17 | ๐ฏ๐ด Amman | 3.62 | ||
18 | ๐ต๐ฆ Panama City | 3.69 | ||
19 | ๐ฎ๐ฉ Denpasar | 3.69 | ||
20 | ๐ช๐จ Cuenca | 3.69 | ||
21 | ๐ฒ๐ฝ San Miguel de Allende | 3.72 | ||
22 | ๐ฒ๐ฝ Merida | 3.73 | ||
23 | ๐จ๐ณ Macau | 3.73 | ||
24 | ๐ณ๐ต Kathmandu | 3.74 | ||
25 | ๐ฆ๐บ Gold Coast | 3.75 | ||
26 | ๐ฎ๐ฉ Kuta | 3.76 | ||
27 | ๐ฌ๐ง Glasgow | 3.76 | ||
28 | ๐จ๐ด Bogota | 3.78 | ||
29 | ๐ฒ๐ฝ Puebla | 3.78 | ||
30 | ๐ฒ๐ฝ Guanajuato | 3.79 | Based on unattractiveness of visitors n=349,346 |
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