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๐ถ 36-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
๐ต๐น
loves
Portimรฃo most
๐
is vaccinated
๐
produces 74% less COโ
6๏ธโฃ
and stays for
6 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 2025.
Last updated: 2 minutes ago
๐ถ Nomads by age |
||||
Age | % | |||
20 |
0.1%
|
|||
22 |
0.3%
|
|||
23 |
0.3%
|
|||
24 |
1%
|
|||
25 |
1%
|
|||
26 |
1%
|
|||
27 |
2%
|
|||
28 |
2%
|
|||
29 |
2%
|
|||
30 |
3%
|
|||
31 |
5%
|
|||
32 |
7%
|
|||
33 |
7%
|
|||
34 |
6%
|
|||
35 |
6%
|
|||
36 |
8%
|
|||
37 |
6%
|
|||
38 |
6%
|
|||
39 |
5%
|
|||
40 |
5%
|
|||
41 |
4%
|
|||
42 |
4%
|
|||
43 |
3%
|
|||
44 |
2%
|
|||
45 |
2%
|
n=1,168 |
โณ๏ธ Nomads by nationality |
||||
# | Country | People | % | |
1 | ๐บ๐ธ United States | 43,403,476 | 44% | |
2 | ๐ฌ๐ง United Kingdom | 6,911,966 | 7% | |
3 | ๐จ๐ฆ Canada | 4,571,002 | 5% | |
4 | ๐ท๐บ Russia | 4,509,800 | 5% | |
5 | ๐ฉ๐ช Germany | 3,993,411 | 4% | |
6 | ๐ซ๐ท France | 3,377,568 | 3% | |
7 | ๐ง๐ท Brazil | 2,501,619 | 3% | |
8 | ๐ฆ๐บ Australia | 2,340,965 | 2% | |
9 | ๐ณ๐ฑ Netherlands | 1,805,450 | 2% | |
10 | ๐ช๐ธ Spain | 1,736,598 | 2% | |
11 | ๐ฎ๐ณ India | 1,552,993 | 2% | |
12 | ๐บ๐ฆ Ukraine | 1,380,863 | 1% | |
13 | ๐ฎ๐น Italy | 1,346,437 | 1% | |
14 | ๐ต๐ฑ Poland | 1,185,783 | 1% | |
15 | ๐จ๐ญ Switzerland | 1,009,828 | 1% | |
16 | ๐ฆ๐น Austria | 768,846 | 1% | |
17 | ๐ธ๐ช Sweden | 692,344 | 1% | |
18 | ๐ฏ๐ต Japan | 661,743 | 1% | |
19 | ๐ฎ๐ช Ireland | 657,918 | 1% | |
20 | ๐น๐ท Turkey | 654,093 | 1% | |
21 | ๐ฎ๐ฑ Israel | 612,017 | 1% | |
22 | ๐ง๐ช Belgium | 577,591 | 1% | |
23 | ๐ฐ๐ท South Korea | 573,766 | 1% | |
24 | ๐จ๐ฟ Czechia | 546,990 | 1% | |
25 | ๐ต๐น Portugal | 520,214 | 1% | |
26 | ๐ฟ๐ฆ South Africa | 516,389 | 1% | |
27 | ๐ฒ๐ฝ Mexico | 508,739 | 1% | |
28 | ๐ฆ๐ท Argentina | 497,264 | 1% | |
29 | ๐ธ๐ฌ Singapore | 462,838 | 0% | |
30 | ๐ท๐ด Romania | 459,013 | 0% | n=25,914 |
๐ถ Nomads by gender |
||||
Gender | % | |||
๐จโ Men |
87%
|
|||
๐ฑโโ๏ธ Women |
13%
|
Last 30 days. n=54 |
๐ Nomads by sexuality |
||||
Sexuality | % | |||
๐ Heterosexual |
87%
|
|||
๐ฆ Bisexual |
8%
|
|||
๐ณ๏ธโ๐ Gay or lesbian |
5%
|
n=15,723 |
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=8,118 |
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=7,355 |
๐ Education |
||||
Education | % | |||
๐ High School |
10%
|
|||
๐ Higher education |
90%
|
|||
↱๐ Bachelor's |
54%
|
|||
↱๐ Master's |
34%
|
|||
↱๐ฉโ๐ซ PhD |
3%
|
n=16,766 |
โค๏ธ Nomads by relationship |
||||
Relationship | % | |||
๐ Single |
67%
|
|||
๐ In a relationship |
33%
|
n=9,099 |
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=56,240 |
๐ฐ Nomads by income |
||||
Income | % | |||
< $25k / y |
6%
|
|||
$25k - $50k / y |
15%
|
|||
$50k - $100k / y |
34%
|
|||
$100k - $250k / y |
35%
|
|||
> $250k - $1M / y |
9%
|
|||
> $1M / y |
2%
|
|||
Average | $124,248 / y | |||
Median | $85,000 / y | n=4,910 |
๐ฐ Nomads by employment |
||||
Employment type | % | |||
Full time |
39%
|
|||
Freelance |
18%
|
|||
Startup founder |
18%
|
|||
Full time contractor |
9%
|
|||
Agency |
8%
|
|||
Other |
5%
|
|||
Part time |
2%
|
|||
Part time contractor |
1%
|
n=6,004 |
๐ก Where do nomads work from |
||||
Place | % | |||
๐ก Home office |
59%
|
|||
๐ฌ Coworking |
15%
|
|||
โ๏ธ Cafe |
8%
|
|||
๐ข Office |
7%
|
|||
๐ Couch |
3%
|
|||
๐ฝ Dining table |
3%
|
|||
๐ Bed |
2%
|
|||
๐ช Balcony |
1%
|
|||
๐ Van |
1%
|
|||
๐ช Kitchen |
0%
|
|||
๐ชด Garden |
0%
|
|||
๐ฆ Pool |
0%
|
|||
๐ฅ Boat |
0%
|
|||
๐ Library |
0%
|
|||
๐ก En รงok รงalฤฑลtฤฑฤฤฑnฤฑz yeri seรงin |
0%
|
n=4,931 |
๐ฌ What messaging apps nomads use? |
||||
Messaging app | % | |||
Telegram |
48%
|
|||
42%
|
||||
5%
|
||||
Snapchat |
2%
|
|||
2%
|
||||
LINE |
0%
|
|||
0%
|
||||
Slack |
0%
|
n=5,319 |
โ๏ธ Nomad men by politics |
||||
Politics | % | |||
๐ณ๏ธโ๐ Progressive |
46%
|
|||
โ๏ธ Non-progressive |
54%
|
|||
↱๐ฝ Libertarian |
27%
|
|||
↱โ๏ธ Centrist |
21%
|
|||
↱๐ด Conservative |
7%
|
n=3,452 |
โ๏ธ Nomad women by politics |
||||
Politics | % | |||
๐ณ๏ธโ๐ Progressive |
72%
|
|||
โ๏ธ Non-progressive |
28%
|
|||
↱๐ฝ Libertarian |
13%
|
|||
↱โ๏ธ Centrist |
13%
|
|||
↱๐ด Conservative |
3%
|
n=800 |
๐ฅฉ 76% of ๐จโ men eat meat
๐ฅฉ 57% of ๐ฑโโ๏ธwomen eat meat
๐ซ 37% of nomads don't eat meat
๐ฅ 11% are vegetarian
๐ฅ 11% are vegan
๐ 5% are pescetarian
๐ Nomad men by diet |
||||
Diet | % | |||
๐ฅฉ Eats meat |
76%
|
|||
๐ซ Does not eat meat |
24%
|
|||
↱๐ฅ Vegan |
10%
|
|||
↱๐ฅ Vegetarian |
10%
|
|||
↱๐ Pescetarian |
4%
|
n=5,491 |
๐ Nomad women by diet |
||||
Diet | % | |||
๐ฅฉ Eats meat |
57%
|
|||
๐ซ Does not eat meat |
43%
|
|||
↱๐ฅ Vegetarian |
18%
|
|||
↱๐ฅ Vegan |
15%
|
|||
↱๐ Pescetarian |
10%
|
n=1,205 |
๐ฅพ Hiking
๐ช Fitness
๐ Running
๐คธโโ๏ธ Yoga
๐ Swimming
๐ด Cycling
๐ Nomad men by sports |
||||
Sport | % | |||
๐ช Fitness |
49%
|
|||
๐ฅพ Hiking |
48%
|
|||
๐ Running |
29%
|
|||
๐ด Cycling |
25%
|
|||
๐ Swimming |
23%
|
|||
๐คธโโ๏ธ Yoga |
21%
|
|||
๐ Surfing |
18%
|
|||
โฐ Climbing |
16%
|
|||
๐ Snowboarding |
15%
|
|||
๐ Diving |
15%
|
|||
โท Skiing |
15%
|
|||
๐พ Tennis |
14%
|
|||
๐ Motorcycling |
13%
|
|||
๐ช Fight sports |
11%
|
|||
๐ช Crossfit |
8%
|
n=10,493 |
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 |
15%
|
|||
โฐ Climbing |
13%
|
|||
โท Skiing |
12%
|
|||
๐พ Tennis |
10%
|
|||
๐ Snowboarding |
9%
|
|||
๐ช Crossfit |
5%
|
|||
๐ Motorcycling |
5%
|
|||
๐ช Fight sports |
5%
|
n=2,521 |
๐ต๐น Portimรฃo
๐ฏ๐ต Tokyo
๐ง๐ฆ Sarajevo
๐บ๐ธ Chicago
๐ง๐ฌ Varna
๐ญ๐ท Dubrovnik
๐ Most liked cities by men |
||||
# | City | Rating | ||
1 | ๐ฏ๐ต Tokyo | 4.58 | ||
2 | ๐ฒ๐ฝ Mexico City | 4.58 | ||
3 | ๐ฌ๐ช Tbilisi | 4.50 | ||
4 | ๐ซ๐ท Paris | 4.50 | ||
5 | ๐ช๐ธ Madrid | 4.50 | ||
6 | ๐ต๐ฑ Warsaw | 4.44 | ||
7 | ๐ฌ๐ท Athens | 4.38 | ||
8 | ๐ฐ๐ท Seoul | 4.29 | ||
9 | ๐ฉ๐ช Munich | 4.29 | ||
10 | ๐บ๐ธ New York City | 4.29 | ||
11 | ๐ต๐น Porto | 4.29 | ||
12 | ๐ต๐ฑ Krakรณw | 4.17 | ||
13 | ๐ฌ๐น Antigua | 4.17 | ||
14 | ๐ง๐ฆ Sarajevo | 4.17 | ||
15 | ๐จ๐ฆ Montreal | 4.17 | n=6,637 |
๐ Most liked cities by women |
||||
# | City | Rating | ||
1 | ๐จ๐ด Medellรญn | 4.00 | ||
2 | ๐ญ๐บ Budapest | 3.75 | ||
3 | ๐บ๐ธ Los Angeles | 3.75 | ||
4 | ๐ฒ๐ฝ Mexico City | 3.33 | ||
5 | ๐ป๐ณ Da Nang | 3.00 | n=6,637 |
๐ Most visited cities |
||||
# | City | % visited | ||
1 | ๐ฌ๐ง London | 2.24% | ||
2 | ๐น๐ญ Bangkok | 2.15% | ||
3 | ๐บ๐ธ New York City | 1.51% | ||
4 | ๐ช๐ธ Barcelona | 1.5% | ||
5 | ๐ซ๐ท Paris | 1.48% | ||
6 | ๐ฉ๐ช Berlin | 1.47% | ||
7 | ๐ต๐น Lisbon | 1.46% | ||
8 | ๐ณ๐ฑ Amsterdam | 1.21% | ||
9 | ๐บ๐ธ San Francisco | 1.17% | ||
10 | ๐น๐ญ Chiang Mai | 1.08% | ||
11 | ๐ฒ๐ฝ Mexico City | 1.01% | ||
12 | ๐ธ๐ฌ Singapore | 0.91% | ||
13 | ๐ฎ๐ฉ Canggu | 0.91% | ||
14 | ๐ฏ๐ต Tokyo | 0.89% | ||
15 | ๐น๐ท Istanbul | 0.86% | ||
16 | ๐บ๐ธ Los Angeles | 0.84% | ||
17 | ๐ช๐ธ Madrid | 0.82% | ||
18 | ๐ฒ๐พ Kuala Lumpur | 0.8% | ||
19 | ๐ญ๐บ Budapest | 0.79% | ||
20 | ๐ฆ๐ช Dubai | 0.75% | ||
21 | ๐จ๐ฟ Prague | 0.71% | ||
22 | ๐ฆ๐ท Buenos Aires | 0.69% | ||
23 | ๐จ๐ด Medellรญn | 0.63% | ||
24 | ๐ท๐บ Moscow | 0.62% | ||
25 | ๐ฎ๐น Rome | 0.6% | ||
26 | ๐ฆ๐น Vienna | 0.58% | ||
27 | ๐ป๐ณ Ho Chi Minh City | 0.54% | ||
28 | ๐น๐ญ Phuket | 0.53% | ||
29 | ๐ฐ๐ท Seoul | 0.53% | ||
30 | ๐ญ๐ฐ Hong Kong | 0.52% | n=377,312 |
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 | ๐ฏ๐ต Japan | 2% | ||
13 | ๐จ๐ฆ Canada | 2% | ||
14 | ๐ณ๐ฑ Netherlands | 2% | ||
15 | ๐ป๐ณ Vietnam | 2% | ||
16 | ๐ท๐บ Russia | 2% | ||
17 | ๐น๐ท Turkey | 2% | ||
18 | ๐จ๐ด Colombia | 1% | ||
19 | ๐ต๐ฑ Poland | 1% | ||
20 | ๐ฆ๐บ Australia | 1% | ||
21 | ๐ฒ๐พ Malaysia | 1% | ||
22 | ๐ฎ๐ณ India | 1% | ||
23 | ๐ฌ๐ท Greece | 1% | ||
24 | ๐ฆ๐ท Argentina | 1% | ||
25 | ๐จ๐ญ Switzerland | 1% | ||
26 | ๐ฆ๐น Austria | 1% | ||
27 | ๐ธ๐ฌ Singapore | 1% | ||
28 | ๐ญ๐ท Croatia | 1% | ||
29 | ๐ฆ๐ช United Arab Emirates | 1% | ||
30 | ๐ญ๐บ Hungary | 1% | n=377,312 |
๐ Avg. COโ by member traveling |
||||
Year | COโ | |||
2013 |
674 kg/y
|
|||
2014 |
998 kg/y
|
|||
2015 |
1,087 kg/y
|
|||
2016 |
1,305 kg/y
|
|||
2017 |
1,490 kg/y
|
|||
2018 |
1,570 kg/y
|
|||
2019 |
1,611 kg/y
|
|||
2020 |
1,004 kg/y
|
|||
2021 |
1,009 kg/y
|
|||
2022 |
1,599 kg/y
|
|||
2023 |
1,763 kg/y
|
|||
2024 |
1,694 kg/y
|
|||
2025 |
2,823 kg/y
|
|||
Average | 1,264 kg/y | |||
Median | 1,304 kg/y |
Based on 377,312 trips by 14,787 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 1,304 kg/y, or 74% less COโ than the average American on travel and commuting. |
๐จ Where men go most |
||||
# | Tag | vs. ๐ฑโโ๏ธ | ||
1 | ๐น๐ญ Bangkok | +25% | ||
2 | ๐ต๐น Lisbon | -16% | ||
3 | ๐ช๐ธ Barcelona | -11% | ||
4 | ๐ฌ๐ง London | -20% | ||
5 | ๐ซ๐ท Paris | -19% | ||
6 | ๐น๐ญ Chiang Mai | -3% | ||
7 | ๐ณ๐ฑ Amsterdam | +7% | ||
8 | ๐ฉ๐ช Berlin | -1% | ||
9 | ๐ฎ๐ฉ Canggu | +1% | ||
10 | ๐น๐ท Istanbul | +8% | ||
11 | ๐ธ๐ฌ Singapore | +12% | ||
12 | ๐ฏ๐ต Tokyo | +12% | ||
13 | ๐ฒ๐ฝ Mexico City | -23% | ||
14 | ๐ฒ๐พ Kuala Lumpur | +31% | ||
15 | ๐ญ๐บ Budapest | +18% | median temp=18°C; n=377,312 |
๐ฑโโ๏ธ Where women go most |
||||
# | Tag | vs. ๐จ | ||
1 | ๐ต๐น Lisbon | +19% | ||
2 | ๐ฌ๐ง London | +25% | ||
3 | ๐ช๐ธ Barcelona | +13% | ||
4 | ๐น๐ญ Bangkok | -20% | ||
5 | ๐ซ๐ท Paris | +23% | ||
6 | ๐ฒ๐ฝ Mexico City | +30% | ||
7 | ๐น๐ญ Chiang Mai | +3% | ||
8 | ๐ฉ๐ช Berlin | +1% | ||
9 | ๐ณ๐ฑ Amsterdam | -7% | ||
10 | ๐ฎ๐ฉ Canggu | -1% | ||
11 | ๐ฎ๐น Rome | +21% | ||
12 | ๐น๐ท Istanbul | -7% | ||
13 | ๐บ๐ธ New York City | +10% | ||
14 | ๐ฎ๐ฉ Ubud | +30% | ||
15 | ๐ธ๐ฌ Singapore | -10% | median temp=18°C; n=377,312 |
๐จ Where men go more |
||||
# | Tag | vs. women | ||
1 | ๐ท๐บ Russia | +84% | ||
2 | ๐ต๐ฑ Poland | +72% | ||
3 | ๐ท๐ด Romania | +60% | ||
4 | ๐ฌ๐ช Georgia | +41% | ||
5 | ๐ญ๐ฐ Hong Kong | +28% | ||
6 | ๐ฆ๐ช United Arab Emirates | +27% | ||
7 | ๐ณ๐ฟ New Zealand | +26% | ||
8 | ๐จ๐ฟ Czechia | +24% | ||
9 | ๐จ๐ณ China | +24% | ||
10 | ๐ท๐ธ Serbia | +24% | ||
11 | ๐ต๐ญ Philippines | +21% | ||
12 | ๐ฒ๐พ Malaysia | +21% | ||
13 | ๐ฏ๐ต Japan | +19% | ||
14 | ๐ญ๐บ Hungary | +18% | ||
15 | ๐ฆ๐น Austria | +16% | median temp=13°C; n=377,312 |
๐ฑโโ๏ธ Where women go more |
||||
# | Tag | vs. men | ||
1 | ๐จ๐ท Costa Rica | +52% | ||
2 | ๐ฟ๐ฆ South Africa | +50% | ||
3 | ๐ฒ๐ฝ Mexico | +40% | ||
4 | ๐ฌ๐ง United Kingdom | +28% | ||
5 | ๐ญ๐ท Croatia | +20% | ||
6 | ๐จ๐ฑ Chile | +19% | ||
7 | ๐ซ๐ท France | +18% | ||
8 | ๐ฎ๐น Italy | +16% | ||
9 | ๐ต๐ช Peru | +14% | ||
10 | ๐ฌ๐ท Greece | +12% | ||
11 | ๐ต๐น Portugal | +10% | ||
12 | ๐ฎ๐ช Ireland | +8% | ||
13 | ๐ช๐ธ Spain | +8% | ||
14 | ๐ฆ๐บ Australia | +8% | ||
15 | ๐บ๐ธ United States | +7% | median temp=18°C; n=377,312 |
๐ Most liked countries |
||||
# | Country | Rating | ||
1 | ๐ฏ๐ต Japan | 4.8 | ||
2 | ๐ญ๐ท Croatia | 4.6 | ||
3 | ๐ง๐ฆ Bosnia | 4.55 | ||
4 | ๐จ๐ฟ Czechia | 4.5 | ||
5 | ๐ต๐ฑ Poland | 4.45 | ||
6 | ๐ช๐ช Estonia | 4.4 | ||
7 | ๐ญ๐บ Hungary | 4.4 | ||
8 | ๐ฐ๐ท South Korea | 4.4 | ||
9 | ๐ฌ๐ท Greece | 4.35 | ||
10 | ๐จ๐ญ Switzerland | 4.3 | ||
11 | ๐ฟ๐ฆ South Africa | 4.25 | ||
12 | ๐ฑ๐น Lithuania | 4.2 | ||
13 | ๐ซ๐ฎ Finland | 4.15 | ||
14 | ๐ฐ๐ฟ Kazakhstan | 4.15 | ||
15 | ๐ฌ๐น Guatemala | 4.15 | n=3,883 |
๐คฎ Least liked countries |
||||
# | Country | Rating | ||
1 | ๐จ๐บ Cuba | 1 | ||
2 | ๐ฎ๐ท Iran | 1.65 | ||
3 | ๐ฌ๐ฎ Gibraltar | 1.65 | ||
4 | ๐ฒ๐น Malta | 1.65 | ||
5 | ๐ญ๐ณ Honduras | 1.65 | ||
6 | ๐จ๐พ Cyprus | 1.9 | ||
7 | ๐จ๐ฑ Chile | 2.05 | ||
8 | ๐ฑ๐ฐ Sri Lanka | 2.35 | ||
9 | ๐ธ๐ด Somalia | 2.5 | ||
10 | ๐ช๐น Ethiopia | 2.5 | ||
11 | ๐น๐ฟ Tanzania | 2.5 | ||
12 | ๐ถ๐ฆ Qatar | 2.5 | ||
13 | ๐ธ๐ณ Senegal | 2.5 | ||
14 | ๐ฑ๐บ Luxembourg | 2.5 | ||
15 | ๐ป๐ช Venezuela | 2.5 | n=3,883 |
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 | 63 days (2 months) | |||
Median | 7 days | n=367,556 |
๐ก How long do nomads stay in one country? |
||||
Duration | % | |||
< 7 days |
0%
|
|||
7 - 30 days |
59%
|
|||
30 - 90 days |
28%
|
|||
90+ days |
14%
|
|||
Average | 181 days (6 months) | n=367,556 |
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 | 35% | +252% | |
2 | ๐ธ Web Dev | 28% | +263% | |
3 | ๐ Startup Founder | 28% | +136% | |
4 | ๐ Marketing | 16% | -1% | |
5 | ๐ SaaS | 14% | +193% | |
6 | ๐ฉโ๐จ Creative | 13% | -19% | |
7 | ๐จ UI/UX Design | 11% | +38% | |
8 | ๐ค Product Manager | 11% | +70% | |
9 | ๐ฐ Crypto | 11% | +247% | |
10 | ๐ฑ Mobile Dev | 11% | +347% | |
11 | ๐ Data | 11% | +105% | |
12 | ๐ฐ Finance | 10% | +126% | |
13 | ๐ Ecommerce | 9% | +99% | |
14 | ๐ค Sales | 7% | +80% | |
15 | ๐จโ๐ซ Education | 6% | -11% | n=19,783 |
๐ฑโโ๏ธ Nomad women work as |
||||
# | Work | % | vs. men | |
1 | ๐ Marketing | 16% | +1% | |
2 | ๐ฉโ๐จ Creative | 15% | +23% | |
3 | ๐ Startup Founder | 12% | -58% | |
4 | ๐ป Software Dev | 10% | -72% | |
5 | ๐จ UI/UX Design | 8% | -27% | |
6 | ๐ธ Web Dev | 8% | -72% | |
7 | ๐ค Community | 8% | +25% | |
8 | ๐ Blogging | 8% | +24% | |
9 | ๐จโ๐ซ Education | 7% | +13% | |
10 | ๐ Coach | 7% | +25% | |
11 | ๐ค Product Manager | 6% | -41% | |
12 | ๐ Data | 5% | -51% | |
13 | ๐ SaaS | 5% | -66% | |
14 | ๐ Ecommerce | 4% | -50% | |
15 | ๐ฐ Finance | 4% | -56% | n=5,804 |
๐จ Nomad men vs. women |
||||
# | Tag | vs. women | ||
1 | ๐ก๏ธ InfoSec | +633% | ||
2 | ๐ก Sysadmin | +358% | ||
3 | ๐ Dev Ops | +350% | ||
4 | ๐ฑ Mobile Dev | +347% | ||
5 | ๐พ Game Dev | +319% | ||
6 | ๐ธ Web Dev | +263% | ||
7 | ๐ป Software Dev | +252% | ||
8 | ๐ฐ Crypto | +247% | ||
9 | ๐ OF | +193% | ||
10 | ๐ SaaS | +193% | ||
11 | ๐ VR Dev | +171% | ||
12 | ๐ Startup Founder | +136% | ||
13 | ๐บ Geo | +128% | ||
14 | ๐ Sports | +127% | ||
15 | ๐ฐ Finance | +126% | n=24,534 |
๐ฑโโ๏ธ Nomad women vs. men |
||||
# | Tag | vs. men | ||
1 | ๐งโ๐ผ Human resources | +78% | ||
2 | ๐ฐ Journalism | +49% | ||
3 | ๐ง Psychologist | +46% | ||
4 | ๐จโโ๏ธ Medical | +41% | ||
5 | ๐ Support | +35% | ||
6 | ๐ค Community | +25% | ||
7 | ๐ Coach | +25% | ||
8 | ๐ Blogging | +24% | ||
9 | ๐ฉโ๐จ Creative | +23% | ||
10 | ๐ Hospitality | +22% | ||
11 | ๐ Recruitment | +18% | ||
12 | ๐ธ Model | +15% | ||
13 | ๐ฉโ๐ผ Law | +14% | ||
14 | ๐จโ๐ซ Education | +13% | ||
15 | ๐ Marketing | +1% | n=24,534 |
โ๏ธ Coffee
๐ฌ๐ง Speaks English
๐ Optimist
โฐ Outdoors
๐ COVID vaccinated
๐ถ Dogs
๐จโ Nomad men |
||||
# | Tag | % | vs. ๐ฑโโ๏ธ | |
1 | โ๏ธ Coffee | 40% | +28% | |
2 | ๐ฌ๐ง Speaks English | 32% | +24% | |
3 | ๐ Optimist | 32% | +32% | |
4 | ๐ COVID vaccinated | 27% | +20% | |
5 | โฐ Outdoors | 27% | +7% | |
6 | ๐ช Fitness | 27% | +51% | |
7 | ๐ฅพ Hiking | 26% | +15% | |
8 | ๐ถ Dogs | 26% | +10% | |
9 | โ๏ธ Waking up early | 25% | +27% | |
10 | ๐บ Beer | 25% | +128% | |
11 | ๐ Staying up late | 24% | +54% | |
12 | ๐ง Open-minded | 24% | +20% | |
13 | ๐ Reading | 24% | +10% | |
14 | ๐ Single | 24% | +36% | |
15 | ๐ท Wine | 23% | +1% | n=19,783 |
๐ฑโโ๏ธ Nomad women |
||||
# | Tag | % | vs. ๐จโ | |
1 | โ๏ธ Coffee | 31% | -22% | |
2 | ๐ฌ๐ง Speaks English | 26% | -19% | |
3 | โฐ Outdoors | 25% | -6% | |
4 | ๐ Optimist | 24% | -24% | |
5 | ๐ถ Dogs | 24% | -9% | |
6 | ๐ท Wine | 23% | -1% | |
7 | ๐ COVID vaccinated | 23% | -16% | |
8 | ๐ฅพ Hiking | 23% | -13% | |
9 | ๐ Reading | 22% | -9% | |
10 | ๐ต Tea | 21% | 0% | |
11 | ๐ง Open-minded | 20% | -17% | |
12 | ๐คธโโ๏ธ Yoga | 20% | +74% | |
13 | โ๏ธ Waking up early | 20% | -22% | |
14 | โฑ Beach | 18% | +9% | |
15 | ๐ช Fitness | 18% | -34% | n=5,804 |
๐จ Nomad men vs. women |
||||
# | Tag | vs. ๐ฑโโ๏ธ | ||
1 | ๐ง Have a beard | +1,529% | ||
2 | ๐ช Roost Stand | +421% | ||
3 | ๐จ No beard | +378% | ||
4 | โฝ๏ธ Football | +341% | ||
5 | ๐งโ Short hair | +285% | ||
6 | โ๏ธ Chess | +256% | ||
7 | ๐ช Dropout | +236% | ||
8 | ๐ Race sports | +222% | ||
9 | ๐ Ice hockey | +210% | ||
10 | ๐ Motorcycling | +208% | ||
11 | ๐ Basketball | +203% | ||
12 | ๐ง Hardstyle music | +197% | ||
13 | ๐ด Conservative politics | +187% | ||
14 | ๐ Table tennis | +178% | ||
15 | ๐ Hindu | +169% | n=24,534 |
๐ฑโโ๏ธ Nomad women vs. men |
||||
# | Tag | vs. ๐จ | ||
1 | ๐ Makeup | +3,309% | ||
2 | ๐ฑโโ๏ธ Long hair | +287% | ||
3 | ๐ Dress up | +232% | ||
4 | โจ Astrology | +225% | ||
5 | ๐ช Feminism | +204% | ||
6 | โจ Believe in astrology | +159% | ||
7 | ๐ฆพ Disabled | +121% | ||
8 | ๐จ Drawing | +105% | ||
9 | ๐ Dancing | +92% | ||
10 | ๐ฅ Red hair | +90% | ||
11 | ๐ Shopping | +83% | ||
12 | ๐ป Gardening | +74% | ||
13 | ๐คธโโ๏ธ Yoga | +74% | ||
14 | โ๐ฟ Black | +65% | ||
15 | ๐จ Blonde hair | +57% | n=24,534 |
๐ Nomads by vaccination |
||||
Vaccinated | % | |||
๐ COVID vaccinated |
93%
|
|||
๐ Not COVID vaccinated |
7%
|
n=7,888 |
โค๏ธ Nomads by family |
||||
Relationship | % | |||
โค๏ธ Close to parents |
81%
|
|||
๐ Not close to parents |
19%
|
n=2,160 |
๐ถ Nomads by childhood |
||||
Childhood | % | |||
๐ Happy childhood |
89%
|
|||
๐ Unhappy childhood |
11%
|
n=2,305 |
๐ก Homeownership amongst nomads |
||||
Homeownership | % | |||
๐ก Homeowner |
54%
|
|||
๐ก Not a homeowner |
46%
|
n=2,475 |
Attractiveness is based on the proportion of people liking or disliking a person based on their photo on Nomads.com's dating app. It does not show any of these traits in their profile when they rate them. People who are rated as attractive based on their photo are more likely to have these traits. TL;DR hot people have specific traits, but those specific traits don't necessarily make you hot (you could always try though).
๐ My parents separated
๐ In a relationship
๐ณ๏ธโ๐ LGBT
๐ง Only child
๐ Volleyball
๐ Table tennis
๐จโ Most attractive men's traits |
||||
# | Tag | Diff | ||
1 | ๐ In a relationship | +133% | ||
2 | ๐ง Dubstep music | +65% | ||
3 | ๐ก Homeowner | +59% | ||
4 | ๐ง Hiphop music | +59% | ||
5 | ๐ Basketball | +54% | ||
6 | ๐ฅ Soft boiled eggs | +52% | ||
7 | ๐ฅ Messy | +51% | ||
8 | ๐ Ice hockey | +47% | ||
9 | ๐งโ Short hair | +47% | ||
10 | ๐ Kitesurfing | +47% | ||
11 | ๐ฌ Twitter | +45% | ||
12 | ๐ก Not a homeowner | +43% | ||
13 | โจ Believe in astrology | +40% | ||
14 | ๐ช Crossfit | +40% | ||
15 | ๐ iPhone | +40% | ||
16 | ๐ถ Parent | +37% | ||
17 | ๐ COVID vaccinated | +36% | ||
18 | ๐ง House music | +35% | ||
19 | โฐ Climbing | +35% | ||
20 | ๐ Free diving | +35% | ||
21 | โฝ๏ธ Football | +34% | ||
22 | ๐ง Have a beard | +34% | ||
23 | ๐ผ Youngest child | +34% | ||
24 | ๐ Skateboarding | +33% | ||
25 | ๐ Not close to my parents | +33% | ||
26 | ๐ธ Padel | +31% | ||
27 | ๐ Extrovert | +31% | ||
28 | ๐งผ Clean freak | +31% | ||
29 | ๐ Massage | +30% | ||
30 | ๐ Reggae music | +30% | n=24,534 |
๐ฑโโ๏ธ Most attractive women's traits |
||||
# | Tag | Diff | ||
1 | ๐ My parents separated | +313% | ||
2 | ๐ณ๏ธโ๐ LGBT | +267% | ||
3 | ๐ Volleyball | +221% | ||
4 | ๐ง Only child | +217% | ||
5 | ๐ Shopping | +215% | ||
6 | ๐ Table tennis | +206% | ||
7 | ๐ธ Punk music | +190% | ||
8 | ๐ Running | +178% | ||
9 | ๐งผ Clean freak | +172% | ||
10 | ๐ In a relationship | +161% | ||
11 | ๐ฝ Libertarian politics | +153% | ||
12 | ๐ฌ Social smoker | +150% | ||
13 | โฌ๏ธ Has no tattoos | +147% | ||
14 | ๐ Pescetarian | +147% | ||
15 | ๐ Makeup | +146% | ||
16 | โท Skiing | +144% | ||
17 | ๐พ Tennis | +140% | ||
18 | ๐จโ๐ค Partying | +138% | ||
19 | โฝ๏ธ Football | +135% | ||
20 | ๐ Dress up | +126% | ||
21 | ๐ฑโโ๏ธ Long hair | +126% | ||
22 | ๐ Surfing | +125% | ||
23 | ๐ Film making | +120% | ||
24 | ๐พ Drinking alcohol | +117% | ||
25 | ๐ด Cycling | +115% | ||
26 | ๐ Motorcycling | +113% | ||
27 | โจ Astrology | +112% | ||
28 | ๐ Vanlife | +111% | ||
29 | ๐ซ Not religious | +109% | ||
30 | ๐ฅ Hard boiled eggs | +108% | n=24,534 |
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.
๐คฟ Snorkeling
๐ FetLife
๐ช Paragliding
๐ฌ Slack
๐ธ Anime
๐ญ Swinging
๐จโ Most unattractive men's traits |
||||
# | Tag | Diff | ||
1 | ๐คฟ Snorkeling | -2,496% | ||
2 | ๐ FetLife | -1,954% | ||
3 | ๐ญ Swinging | -791% | ||
4 | ๐ Makeup | -481% | ||
5 | ๐ Bodyboarding | -443% | ||
6 | ๐ณ Bowling | -284% | ||
7 | ๐ช Skydiving | -209% | ||
8 | ๐ช Nexstand | -179% | ||
9 | ๐ฑ Pool | -163% | ||
10 | ๐ฌ Snapchat | -148% | ||
11 | ๐ธ Anime | -138% | ||
12 | ๐ฌ Discord | -128% | ||
13 | ๐ช Paragliding | -123% | ||
14 | ๐ Religious | -109% | ||
15 | ๐ Single | -73% | ||
16 | ๐ฌ Instagram | -72% | ||
17 | ๐ง Garage music | -71% | ||
18 | โ๏ธ Chess | -69% | ||
19 | ๐ถโ๐ซ๏ธ Hang gliding | -63% | ||
20 | ๐ง Trance music | -59% | ||
21 | ๐ป Gardening | -57% | ||
22 | ๐ฐ๐ท K-pop music | -55% | ||
23 | ๐บ Breakdance | -47% | ||
24 | ๐ Unhappy childhood | -43% | ||
25 | ๐ Cricket | -42% | ||
26 | ๐ Sex positive | -41% | ||
27 | ๐ Urbex | -40% | ||
28 | ๐จ Drawing | -38% | ||
29 | โ๏ธ Private pilot | -38% | ||
30 | ๐ Kink | -37% | n=24,534 |
๐ฑโโ๏ธ Most unattractive women's traits |
||||
# | Tag | Diff | ||
1 | ๐ฅ Messy | -2,110% | ||
2 | ๐ช Paragliding | -1,179% | ||
3 | ๐ฌ Slack | -889% | ||
4 | ๐ธ Anime | -656% | ||
5 | ๐ด Conservative politics | -569% | ||
6 | ๐ฐ๐ท K-pop music | -307% | ||
7 | ๐ฌ Snapchat | -278% | ||
8 | ๐ถโ๐ซ๏ธ Hang gliding | -191% | ||
9 | ๐ช Roost Stand | -133% | ||
10 | ๐ง Bouldering | -133% | ||
11 | ๐ธ Badminton | -133% | ||
12 | ๐ Skateboarding | -98% | ||
13 | ๐ Carnivore | -91% | ||
14 | ๐ก Not a homeowner | -86% | ||
15 | โค๏ธ Happy childhood | -79% | ||
16 | โจ Believe in astrology | -69% | ||
17 | ๐ Kitesurfing | -42% | ||
18 | ๐ Country music | -42% | ||
19 | ๐ฌ Facebook | -37% | ||
20 | ๐ถ Parent | -32% | ||
21 | ๐ง Garage music | -22% | ||
22 | ๐ช Fight sports | -21% | ||
23 | ๐ Kink | -19% | ||
24 | ๐ Paleo | -18% | ||
25 | ๐ง Pessimist | -16% | ||
26 | ๐ Snowboarding | -10% | ||
27 | ๐ณ Introvert | -6% | ||
28 | ๐ Sex positive | -2% | n=24,534 |
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).
๐ค Community
๐จ UI/UX Design
๐ฑ Mobile Dev
๐ SaaS
๐ Blogging
๐ฉโ๐จ Creative
๐จโ Attractive men's jobs |
||||
# | Tag | Diff | ||
1 | ๐ Recruitment | +49% | ||
2 | ๐จโโ๏ธ Medical | +44% | ||
3 | ๐ SaaS | +37% | ||
4 | ๐จ UI/UX Design | +37% | ||
5 | ๐ Coach | +28% | ||
6 | ๐ค Product Manager | +27% | ||
7 | ๐ Ecommerce | +25% | ||
8 | ๐ฑ Mobile Dev | +25% | ||
9 | ๐ Logistics | +22% | ||
10 | ๐ Startup Founder | +17% | ||
11 | ๐ Marketing | +15% | ||
12 | ๐ Data | +15% | ||
13 | ๐ค Community | +13% | ||
14 | ๐ช Fitness | +13% | ||
15 | ๐ Dev Ops | +12% | ||
16 | ๐ค Sales | +12% | ||
17 | ๐ป Software Dev | +11% | ||
18 | ๐พ Game Dev | +8% | ||
19 | ๐ฐ Finance | +3% | ||
20 | ๐ธ Web Dev | +2% | ||
21 | ๐ Sports | +2% | n=24,534 |
๐ฑโโ๏ธ Attractive women's jobs |
||||
# | Tag | Diff | ||
1 | ๐ค Community | +113% | ||
2 | ๐ Blogging | +97% | ||
3 | ๐ฉโ๐จ Creative | +91% | ||
4 | ๐ฑ Mobile Dev | +82% | ||
5 | ๐จ UI/UX Design | +80% | ||
6 | ๐ช Fitness | +74% | ||
7 | ๐ Startup Founder | +70% | ||
8 | ๐ SaaS | +61% | ||
9 | ๐ Ecommerce | +56% | ||
10 | ๐ Marketing | +54% | ||
11 | ๐ฐ Journalism | +53% | ||
12 | ๐ Coach | +45% | ||
13 | ๐ฐ Finance | +41% | ||
14 | ๐ค Sales | +35% | ||
15 | ๐ป Software Dev | +32% | ||
16 | ๐ค Product Manager | +23% | ||
17 | ๐จโ๐ซ Education | +20% | n=24,534 |
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
๐ก๏ธ InfoSec
๐ VR Dev
๐ OF
๐ Hospitality
๐ฐ Journalism
๐จโ Most unattractive men's jobs |
||||
# | Tag | Diff | ||
1 | ๐ก๏ธ InfoSec | -869% | ||
2 | ๐ OF | -288% | ||
3 | ๐ฉ Politics | -241% | ||
4 | ๐ฐ Journalism | -58% | ||
5 | ๐ฉโ๐ผ Law | -51% | ||
6 | ๐ธ Model | -42% | ||
7 | ๐ก Architecture | -30% | ||
8 | ๐ถ Adult | -30% | ||
9 | ๐ Hospitality | -26% | ||
10 | ๐บ Geo | -21% | ||
11 | ๐ก Sysadmin | -20% | ||
12 | ๐ Support | -16% | ||
13 | ๐จโ๐ซ Education | -15% | ||
14 | ๐งโ๐ผ Human resources | -9% | ||
15 | ๐ VR Dev | -8% | ||
16 | ๐ฉโ๐จ Creative | -5% | ||
17 | ๐ฐ Crypto | -4% | ||
18 | ๐ Blogging | -4% | n=24,534 |
๐ฑโโ๏ธ Most unattractive women's jobs |
||||
# | Tag | Diff | ||
1 | ๐ฉ Politics | -1,296% | ||
2 | ๐ VR Dev | -627% | ||
3 | ๐ Hospitality | -106% | ||
4 | ๐ Logistics | -57% | ||
5 | ๐ฐ Crypto | -29% | ||
6 | ๐ Sports | -21% | ||
7 | ๐ Support | -19% | ||
8 | ๐ Data | -7% | ||
9 | ๐ธ Web Dev | -6% | n=24,534 |
๐จโ Where attractive men travel to |
||||
# | City | Attractiveness | ||
1 | ๐ฆ๐บ Brisbane | 5 | ||
2 | ๐ฌ๐ท Mykonos | 5 | ||
3 | ๐ณ๐ด Bergen | 4.88 | ||
4 | ๐ฎ๐ฉ Uluwatu | 4.88 | ||
5 | ๐ต๐น Ericeira | 4.87 | ||
6 | ๐ฒ๐ฝ Cabo San Lucas | 4.84 | ||
7 | ๐ช๐ธ Ibiza | 4.81 | ||
8 | ๐จ๐ท Tamarindo | 4.8 | ||
9 | ๐ณ๐ฟ Christchurch | 4.69 | ||
10 | ๐ฎ๐ธ Reykjavik | 4.67 | ||
11 | ๐ฎ๐น Pisa | 4.62 | ||
12 | ๐ต๐น Faro | 4.61 | ||
13 | ๐ช๐ธ Mallorca | 4.58 | ||
14 | ๐น๐ญ Ko Phi Phi | 4.58 | ||
15 | ๐ฆ๐บ Melbourne | 4.54 | ||
16 | ๐ต๐น Portimรฃo | 4.54 | ||
17 | ๐ช๐ธ Fuerteventura | 4.53 | ||
18 | ๐ง๐ช Bruges | 4.52 | ||
19 | ๐ณ๐ฟ Auckland | 4.5 | ||
20 | ๐ญ๐ท Zadar | 4.5 | ||
21 | ๐น๐ญ Ko Lanta | 4.5 | ||
22 | ๐น๐ญ Krabi | 4.5 | ||
23 | ๐ฆ๐น Salzburg | 4.5 | ||
24 | ๐บ๐ธ Boston | 4.5 | ||
25 | ๐ฌ๐ท Santorini | 4.5 | ||
26 | ๐ฒ๐พ Langkawi | 4.5 | ||
27 | ๐ฑ๐ฆ Luang Prabang | 4.5 | ||
28 | ๐จ๐ณ Macau | 4.5 | ||
29 | ๐ณ๐ฟ Queenstown | 4.49 | ||
30 | ๐ป๐ณ Hoi An | 4.49 | Based on attractiveness of visitors n=377,312 |
๐ฑโโ๏ธ Where attractive women travel to |
||||
# | City | Attractiveness | ||
1 | ๐ซ๐ท Cannes | 5 | ||
2 | ๐น๐ญ Ko Phi Phi | 4.71 | ||
3 | ๐ง๐ฆ Mostar | 4.68 | ||
4 | ๐ฎ๐น Genoa | 4.66 | ||
5 | ๐บ๐ธ Orlando | 4.66 | ||
6 | ๐ญ๐ท Zadar | 4.62 | ||
7 | ๐ฆ๐บ Cairns | 4.61 | ||
8 | ๐ฑ๐ฐ Galle | 4.61 | ||
9 | ๐ฒ๐ช Budva | 4.6 | ||
10 | ๐ช๐ธ Fuerteventura | 4.55 | ||
11 | ๐จ๐ฑ Valparaรญso | 4.51 | ||
12 | ๐บ๐ฆ Kyiv | 4.51 | ||
13 | ๐ท๐บ Moscow | 4.48 | ||
14 | ๐น๐ญ Ko Samui | 4.47 | ||
15 | ๐ช๐ธ Ibiza | 4.47 | ||
16 | ๐ฎ๐ฑ Tel Aviv | 4.46 | ||
17 | ๐ป๐ณ Nha Trang | 4.44 | ||
18 | ๐ฌ๐ท Rhodes | 4.44 | ||
19 | ๐ฎ๐น Catania | 4.43 | ||
20 | ๐ฎ๐น Milan | 4.43 | ||
21 | ๐ฌ๐ท Mykonos | 4.41 | ||
22 | ๐จ๐พ Larnaca | 4.41 | ||
23 | ๐ฉ๐ด Punta Cana | 4.4 | ||
24 | ๐ง๐ช Bruges | 4.4 | ||
25 | ๐น๐ท Antalya | 4.39 | ||
26 | ๐ฎ๐ฉ Jakarta | 4.38 | ||
27 | ๐น๐ท Izmir | 4.38 | ||
28 | ๐ต๐ฑ Warsaw | 4.38 | ||
29 | ๐ง๐ท Florianopolis | 4.38 | ||
30 | ๐ฆ๐น Salzburg | 4.37 | Based on attractiveness of visitors n=377,312 |
๐จโ Where unattractive men travel to |
||||
# | City | Attractiveness | ||
1 | ๐น๐ญ Pattaya | 3.13 | ||
2 | ๐ฎ๐ณ Goa | 3.32 | ||
3 | ๐ต๐พ Asuncion | 3.57 | ||
4 | ๐ฎ๐ณ Mumbai | 3.58 | ||
5 | ๐บ๐ธ Houston | 3.66 | ||
6 | ๐ท๐บ Moscow | 3.75 | ||
7 | ๐ฌ๐ช Batumi | 3.75 | ||
8 | ๐ฒ๐ช Podgorica | 3.75 | ||
9 | ๐ณ๐ต Kathmandu | 3.75 | ||
10 | ๐ฎ๐ณ Bengaluru | 3.75 | ||
11 | ๐ช๐ธ Alicante | 3.75 | ||
12 | ๐ช๐ฌ Cairo | 3.78 | ||
13 | ๐น๐ท Antalya | 3.81 | ||
14 | ๐ฐ๐ฟ Almaty | 3.81 | ||
15 | ๐ต๐ฆ Panama City | 3.83 | ||
16 | ๐ง๐พ Minsk | 3.85 | ||
17 | ๐ต๐ฑ Wrocลaw | 3.85 | ||
18 | ๐ถ๐ฆ Doha | 3.85 | ||
19 | ๐จ๐ณ Beijing | 3.86 | ||
20 | ๐น๐ผ Taipei | 3.86 | ||
21 | ๐ฎ๐น Turin | 3.87 | ||
22 | ๐ฏ๐ต Hiroshima | 3.87 | ||
23 | ๐บ๐ฆ Lviv | 3.88 | ||
24 | ๐ต๐ญ Manila | 3.89 | ||
25 | ๐จ๐ญ Basel | 3.9 | ||
26 | ๐บ๐ธ Las Vegas | 3.9 | ||
27 | ๐ต๐ฑ Gdansk | 3.91 | ||
28 | ๐จ๐ด Bogota | 3.91 | ||
29 | ๐ฒ๐ฝ Merida | 3.91 | ||
30 | ๐ฎ๐ฉ Kuta | 3.91 | Based on unattractiveness of visitors n=377,312 |
๐ฑโโ๏ธ Where unattractive women travel to |
||||
# | City | Attractiveness | ||
1 | ๐ฐ๐ช Nairobi | 3 | ||
2 | ๐ช๐จ Quito | 3.06 | ||
3 | ๐ณ๐ฟ Wellington | 3.1 | ||
4 | ๐ฏ๐ด Amman | 3.21 | ||
5 | ๐จ๐ฆ Quebec City | 3.21 | ||
6 | ๐ฑ๐ฆ Vientiane | 3.27 | ||
7 | ๐บ๐ธ New Orleans | 3.29 | ||
8 | ๐บ๐ธ Atlanta | 3.31 | ||
9 | ๐ต๐ท San Juan | 3.32 | ||
10 | ๐ฆ๐บ Perth | 3.32 | ||
11 | ๐ฏ๐ต Fukuoka | 3.33 | ||
12 | ๐ฑ๐ฐ Weligama | 3.34 | ||
13 | ๐ฐ๐ญ Phnom Penh | 3.38 | ||
14 | ๐จ๐ด Cali | 3.4 | ||
15 | ๐ฒ๐ฝ Guadalajara | 3.4 | ||
16 | ๐ช๐จ Cuenca | 3.42 | ||
17 | ๐จ๐ด Bogota | 3.43 | ||
18 | ๐จ๐ณ Macau | 3.44 | ||
19 | ๐ฌ๐ง Manchester | 3.47 | ||
20 | ๐ฌ๐ง Liverpool | 3.48 | ||
21 | ๐ฎ๐ฉ Denpasar | 3.49 | ||
22 | ๐ง๐ช Antwerp | 3.51 | ||
23 | ๐ต๐ฆ Panama City | 3.51 | ||
24 | ๐จ๐ด Santa Marta | 3.51 | ||
25 | ๐ฑ๐ฐ Colombo | 3.54 | ||
26 | ๐ฒ๐ฝ Merida | 3.57 | ||
27 | ๐ฌ๐ง Glasgow | 3.58 | ||
28 | ๐บ๐ธ Washington | 3.58 | ||
29 | ๐ง๐ฆ Sarajevo | 3.59 | ||
30 | ๐ณ๐ต Kathmandu | 3.59 | Based on unattractiveness of visitors n=377,312 |
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