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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
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 Nomad List 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. Nomad List 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 Nomad List 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 "Nomad List" (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 Nomad List and the fastest growing remote work hubs of 2024.
Last updated: 31 minutes ago
๐ถ Nomads by age |
||||
Age | % | |||
19 |
0.2%
|
|||
21 |
0.3%
|
|||
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 |
8%
|
|||
36 |
6%
|
|||
37 |
6%
|
|||
38 |
5%
|
|||
39 |
5%
|
|||
40 |
4%
|
|||
41 |
3%
|
|||
42 |
3%
|
|||
43 |
2%
|
|||
44 |
2%
|
n=1,232 |
โณ๏ธ Nomads by nationality |
||||
# | Country | People | % | |
1 | ๐บ๐ธ United States | 37,756,492 | 45% | |
2 | ๐ฌ๐ง United Kingdom | 5,901,366 | 7% | |
3 | ๐ท๐บ Russia | 3,896,808 | 5% | |
4 | ๐จ๐ฆ Canada | 3,852,564 | 5% | |
5 | ๐ฉ๐ช Germany | 3,219,546 | 4% | |
6 | ๐ซ๐ท France | 2,732,870 | 3% | |
7 | ๐ง๐ท Brazil | 2,072,625 | 2% | |
8 | ๐ฆ๐บ Australia | 1,970,525 | 2% | |
9 | ๐ณ๐ฑ Netherlands | 1,490,657 | 2% | |
10 | ๐ช๐ธ Spain | 1,429,397 | 2% | |
11 | ๐ฎ๐ณ India | 1,238,810 | 1% | |
12 | ๐บ๐ฆ Ukraine | 1,112,887 | 1% | |
13 | ๐ฎ๐น Italy | 1,038,014 | 1% | |
14 | ๐ต๐ฑ Poland | 973,351 | 1% | |
15 | ๐จ๐ญ Switzerland | 809,991 | 1% | |
16 | ๐ฆ๐น Austria | 660,245 | 1% | |
17 | ๐ธ๐ช Sweden | 568,355 | 1% | |
18 | ๐ฏ๐ต Japan | 547,935 | 1% | |
19 | ๐ฎ๐ช Ireland | 541,129 | 1% | |
20 | ๐ฎ๐ฑ Israel | 520,709 | 1% | |
21 | ๐น๐ท Turkey | 513,902 | 1% | |
22 | ๐ง๐ช Belgium | 466,256 | 1% | |
23 | ๐จ๐ฟ Czechia | 459,449 | 1% | |
24 | ๐ฐ๐ท South Korea | 435,626 | 1% | |
25 | ๐ฟ๐ฆ South Africa | 425,416 | 1% | |
26 | ๐ต๐น Portugal | 401,592 | 0% | |
27 | ๐ฒ๐ฝ Mexico | 401,592 | 0% | |
28 | ๐ธ๐ฌ Singapore | 398,189 | 0% | |
29 | ๐ฆ๐ท Argentina | 387,979 | 0% | |
30 | ๐ณ๐ฟ New Zealand | 370,962 | 0% | n=24,600 |
๐ถ Nomads by gender |
||||
Gender | % | |||
๐จโ Men |
86%
|
|||
๐ฑโโ๏ธ Women |
14%
|
Last 30 days. n=135 |
๐ Nomads by sexuality |
||||
Sexuality | % | |||
๐ Heterosexual |
87%
|
|||
๐ฆ Bisexual |
8%
|
|||
๐ณ๏ธโ๐ Gay or lesbian |
5%
|
n=14,609 |
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=7,481 |
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=6,678 |
๐ Education |
||||
Education | % | |||
๐ High School |
9%
|
|||
๐ Higher education |
91%
|
|||
↱๐ Bachelor's |
54%
|
|||
↱๐ Master's |
34%
|
|||
↱๐ฉโ๐ซ PhD |
3%
|
n=15,167 |
โค๏ธ Nomads by relationship |
||||
Relationship | % | |||
๐ Single |
66%
|
|||
๐ In a relationship |
34%
|
n=8,168 |
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=50,965 |
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 | $123,825 / y | |||
Median | $85,000 / y | n=4,203 |
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=5,001 |
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=3,988 |
๐ฌ What messaging apps nomads use? |
||||
Messaging app | % | |||
Telegram |
47%
|
|||
44%
|
||||
5%
|
||||
2%
|
||||
Snapchat |
1%
|
|||
LINE |
0%
|
|||
0%
|
||||
Slack |
0%
|
n=4,615 |
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=3,328 |
โ๏ธ Nomad women by politics |
||||
Politics | % | |||
๐ณ๏ธโ๐ Progressive |
72%
|
|||
โ๏ธ Non-progressive |
28%
|
|||
↱๐ฝ Libertarian |
13%
|
|||
↱โ๏ธ Centrist |
12%
|
|||
↱๐ด Conservative |
3%
|
n=784 |
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=5,134 |
๐ Nomad women by diet |
||||
Diet | % | |||
๐ฅฉ Eats meat |
56%
|
|||
๐ซ Does not eat meat |
44%
|
|||
↱๐ฅ Vegetarian |
18%
|
|||
↱๐ฅ Vegan |
15%
|
|||
↱๐ Pescetarian |
11%
|
n=1,178 |
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 Diving |
16%
|
|||
๐ Snowboarding |
16%
|
|||
โท Skiing |
16%
|
|||
๐พ Tennis |
14%
|
|||
๐ Motorcycling |
13%
|
|||
๐ช Fight sports |
11%
|
|||
๐ช Crossfit |
9%
|
n=9,724 |
๐ Nomad women by sports |
||||
Sport | % | |||
๐ฅพ Hiking |
52%
|
|||
๐คธโโ๏ธ Yoga |
45%
|
|||
๐ช Fitness |
39%
|
|||
๐ Swimming |
24%
|
|||
๐ Running |
21%
|
|||
๐ด Cycling |
18%
|
|||
๐ Diving |
15%
|
|||
๐ Surfing |
14%
|
|||
โฐ Climbing |
13%
|
|||
โท Skiing |
12%
|
|||
๐พ Tennis |
10%
|
|||
๐ Snowboarding |
9%
|
|||
๐ช Crossfit |
5%
|
|||
๐ Motorcycling |
5%
|
|||
๐ช Fight sports |
5%
|
n=2,425 |
๐ต๐น Portimรฃo
๐บ๐ธ Chicago
๐ต๐ฑ Warsaw
๐บ๐ฆ Odessa
๐ฏ๐ต Tokyo
๐ช๐ธ Valencia
๐ Most liked cities by men |
||||
# | City | Rating | ||
1 | ๐ฒ๐ฝ Mexico City | 4.58 | ||
2 | ๐ช๐ธ Madrid | 4.58 | ||
3 | ๐ฏ๐ต Tokyo | 4.55 | ||
4 | ๐ต๐น Porto | 4.55 | ||
5 | ๐ต๐ฑ Warsaw | 4.50 | ||
6 | ๐ฐ๐ท Seoul | 4.50 | ||
7 | ๐ช๐ธ Valencia | 4.44 | ||
8 | ๐จ๐ฟ Prague | 4.38 | ||
9 | ๐ฌ๐ท Athens | 4.38 | ||
10 | ๐ฒ๐พ Penang | 4.29 | ||
11 | ๐ญ๐บ Budapest | 4.29 | ||
12 | ๐ฉ๐ช Munich | 4.29 | ||
13 | ๐น๐ญ Chiang Mai | 4.23 | ||
14 | ๐ฟ๐ฆ Cape Town | 4.17 | ||
15 | ๐น๐ผ Taipei | 4.17 | n=4,799 |
๐ Most liked cities by women |
||||
# | City | Rating | ||
1 | ๐ฉ๐ช Berlin | 3.75 | ||
2 | ๐ญ๐บ Budapest | 3.75 | ||
3 | ๐ง๐ฌ Sofia | 3.75 | ||
4 | ๐ฉ๐ช Munich | 3.75 | ||
5 | ๐จ๐ด Medellรญn | 3.75 | ||
6 | ๐บ๐ธ Los Angeles | 3.75 | ||
7 | ๐ฒ๐ฝ Playa del Carmen | 3.00 | n=4,799 |
๐ Most visited cities |
||||
# | City | % visited | ||
1 | ๐ฌ๐ง London | 2.26% | ||
2 | ๐น๐ญ Bangkok | 2.05% | ||
3 | ๐บ๐ธ New York City | 1.54% | ||
4 | ๐ฉ๐ช Berlin | 1.5% | ||
5 | ๐ต๐น Lisbon | 1.5% | ||
6 | ๐ซ๐ท Paris | 1.49% | ||
7 | ๐ช๐ธ Barcelona | 1.48% | ||
8 | ๐ณ๐ฑ Amsterdam | 1.25% | ||
9 | ๐บ๐ธ San Francisco | 1.17% | ||
10 | ๐น๐ญ Chiang Mai | 1.07% | ||
11 | ๐ฒ๐ฝ Mexico City | 1% | ||
12 | ๐ธ๐ฌ Singapore | 0.91% | ||
13 | ๐ฎ๐ฉ Canggu | 0.9% | ||
14 | ๐บ๐ธ Los Angeles | 0.87% | ||
15 | ๐ฏ๐ต Tokyo | 0.85% | ||
16 | ๐น๐ท Istanbul | 0.85% | ||
17 | ๐ญ๐บ Budapest | 0.81% | ||
18 | ๐ช๐ธ Madrid | 0.81% | ||
19 | ๐ฒ๐พ Kuala Lumpur | 0.78% | ||
20 | ๐จ๐ฟ Prague | 0.73% | ||
21 | ๐ฆ๐ช Dubai | 0.71% | ||
22 | ๐ฆ๐ท Buenos Aires | 0.66% | ||
23 | ๐จ๐ด Medellรญn | 0.64% | ||
24 | ๐ท๐บ Moscow | 0.62% | ||
25 | ๐ฎ๐น Rome | 0.59% | ||
26 | ๐ฆ๐น Vienna | 0.59% | ||
27 | ๐ป๐ณ Ho Chi Minh City | 0.53% | ||
28 | ๐ฎ๐ฉ Ubud | 0.53% | ||
29 | ๐ญ๐ฐ Hong Kong | 0.53% | ||
30 | ๐น๐ญ Phuket | 0.52% | n=340,939 |
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 | ๐ฆ๐บ Australia | 1% | ||
20 | ๐ต๐ฑ Poland | 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 | ๐ญ๐ท Croatia | 1% | ||
28 | ๐ธ๐ฌ Singapore | 1% | n=340,939 |
๐ Avg. COโ by member traveling |
||||
Year | COโ | |||
2013 |
677 kg/y
|
|||
2014 |
1,014 kg/y
|
|||
2015 |
1,094 kg/y
|
|||
2016 |
1,315 kg/y
|
|||
2017 |
1,505 kg/y
|
|||
2018 |
1,603 kg/y
|
|||
2019 |
1,632 kg/y
|
|||
2020 |
1,015 kg/y
|
|||
2021 |
1,018 kg/y
|
|||
2022 |
1,632 kg/y
|
|||
2023 |
1,783 kg/y
|
|||
2024 |
2,213 kg/y
|
|||
Average | 1,296 kg/y | |||
Median | 1,290 kg/y |
Based on 340,939 trips by 13,649 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 1,290 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 | +23% | ||
2 | ๐ต๐น Lisbon | -14% | ||
3 | ๐ช๐ธ Barcelona | -10% | ||
4 | ๐ฌ๐ง London | -21% | ||
5 | ๐ซ๐ท Paris | -18% | ||
6 | ๐ฉ๐ช Berlin | -1% | ||
7 | ๐ณ๐ฑ Amsterdam | +5% | ||
8 | ๐น๐ญ Chiang Mai | -3% | ||
9 | ๐ฎ๐ฉ Canggu | +4% | ||
10 | ๐น๐ท Istanbul | +7% | ||
11 | ๐ธ๐ฌ Singapore | +13% | ||
12 | ๐ฒ๐ฝ Mexico City | -22% | ||
13 | ๐ญ๐บ Budapest | +15% | ||
14 | ๐ฏ๐ต Tokyo | +13% | ||
15 | ๐ฒ๐พ Kuala Lumpur | +26% | median temp=18°C; n=340,939 |
๐ฑโโ๏ธ Where women go most |
||||
# | Tag | vs. ๐จ | ||
1 | ๐ต๐น Lisbon | +17% | ||
2 | ๐ฌ๐ง London | +27% | ||
3 | ๐ช๐ธ Barcelona | +12% | ||
4 | ๐ซ๐ท Paris | +22% | ||
5 | ๐น๐ญ Bangkok | -19% | ||
6 | ๐ฒ๐ฝ Mexico City | +28% | ||
7 | ๐ฉ๐ช Berlin | +1% | ||
8 | ๐น๐ญ Chiang Mai | +3% | ||
9 | ๐ณ๐ฑ Amsterdam | -5% | ||
10 | ๐ฎ๐น Rome | +24% | ||
11 | ๐ฎ๐ฉ Canggu | -4% | ||
12 | ๐น๐ท Istanbul | -7% | ||
13 | ๐ฎ๐ฉ Ubud | +26% | ||
14 | ๐บ๐ธ New York City | +8% | ||
15 | ๐ธ๐ฌ Singapore | -12% | median temp=18°C; n=340,939 |
๐จ Where men go more |
||||
# | Tag | vs. women | ||
1 | ๐บ๐ฆ Ukraine | +89% | ||
2 | ๐ท๐บ Russia | +73% | ||
3 | ๐ต๐ฑ Poland | +69% | ||
4 | ๐ท๐ด Romania | +59% | ||
5 | ๐ฌ๐ช Georgia | +45% | ||
6 | ๐ท๐ธ Serbia | +33% | ||
7 | ๐ณ๐ฟ New Zealand | +30% | ||
8 | ๐ญ๐ฐ Hong Kong | +27% | ||
9 | ๐ฆ๐ช United Arab Emirates | +24% | ||
10 | ๐จ๐ฟ Czechia | +22% | ||
11 | ๐ฒ๐พ Malaysia | +20% | ||
12 | ๐ฆ๐น Austria | +18% | ||
13 | ๐ต๐ญ Philippines | +18% | ||
14 | ๐ณ๐ด Norway | +17% | ||
15 | ๐ฏ๐ต Japan | +17% | median temp=13°C; n=340,939 |
๐ฑโโ๏ธ Where women go more |
||||
# | Tag | vs. men | ||
1 | ๐ฟ๐ฆ South Africa | +50% | ||
2 | ๐จ๐ท Costa Rica | +43% | ||
3 | ๐ฒ๐ฝ Mexico | +41% | ||
4 | ๐ฌ๐ง United Kingdom | +28% | ||
5 | ๐จ๐ฑ Chile | +21% | ||
6 | ๐ญ๐ท Croatia | +18% | ||
7 | ๐ฎ๐น Italy | +18% | ||
8 | ๐ซ๐ท France | +18% | ||
9 | ๐ฌ๐ท Greece | +16% | ||
10 | ๐ต๐น Portugal | +10% | ||
11 | ๐ต๐ช Peru | +10% | ||
12 | ๐ฆ๐บ Australia | +8% | ||
13 | ๐ช๐ธ Spain | +8% | ||
14 | ๐ฆ๐ท Argentina | +7% | ||
15 | ๐บ๐ธ United States | +6% | median temp=18°C; n=340,939 |
๐ Most liked countries |
||||
# | Country | Rating | ||
1 | ๐ฐ๐ท South Korea | 4.75 | ||
2 | ๐ฌ๐ท Greece | 4.75 | ||
3 | ๐ญ๐บ Hungary | 4.65 | ||
4 | ๐ญ๐ท Croatia | 4.6 | ||
5 | ๐จ๐ฟ Czechia | 4.4 | ||
6 | ๐บ๐พ Uruguay | 4.4 | ||
7 | ๐ต๐ฑ Poland | 4.3 | ||
8 | ๐ฒ๐พ Malaysia | 4.25 | ||
9 | ๐ช๐ฌ Egypt | 4.25 | ||
10 | ๐ฉ๐ฐ Denmark | 4.15 | ||
11 | ๐ฟ๐ฆ South Africa | 4.15 | ||
12 | ๐ฎ๐ช Ireland | 4.15 | ||
13 | ๐ต๐ฆ Panama | 4.15 | ||
14 | ๐ฎ๐น Italy | 4 | ||
15 | ๐ฉ๐ช Germany | 4 | n=2,047 |
๐คฎ Least liked countries |
||||
# | Country | Rating | ||
1 | ๐ฎ๐ฑ Israel | 1.65 | ||
2 | ๐ฎ๐ท Iran | 1.65 | ||
3 | ๐ฒ๐ฉ Moldova | 1.65 | ||
4 | ๐ญ๐ณ Honduras | 1.65 | ||
5 | ๐ด Kurdistan | 1.65 | ||
6 | ๐จ๐ฑ Chile | 2 | ||
7 | ๐ฑ๐ฐ Sri Lanka | 2 | ||
8 | ๐ฑ๐ฆ Laos | 2.2 | ||
9 | ๐ธ๐ด Somalia | 2.5 | ||
10 | ๐ถ๐ฆ Qatar | 2.5 | ||
11 | ๐ฌ๐ฎ Gibraltar | 2.5 | ||
12 | ๐ป๐ช Venezuela | 2.5 | ||
13 | ๐ธ๐ณ Senegal | 2.5 | ||
14 | ๐ฒ๐น Malta | 2.5 | ||
15 | ๐ธ๐ฐ Slovakia | 2.5 | n=2,047 |
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=331,970 |
๐ก How long do nomads stay in one country? |
||||
Duration | % | |||
< 7 days |
0%
|
|||
7 - 30 days |
60%
|
|||
30 - 90 days |
27%
|
|||
90+ days |
13%
|
|||
Average | 189 days (6 months) | n=331,970 |
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% | +243% | |
2 | ๐ธ Web Dev | 28% | +261% | |
3 | ๐ Startup Founder | 27% | +136% | |
4 | ๐ Marketing | 15% | +1% | |
5 | ๐ SaaS | 13% | +197% | |
6 | ๐ฉโ๐จ Creative | 12% | -18% | |
7 | ๐จ UI/UX Design | 11% | +39% | |
8 | ๐ค Product Manager | 11% | +71% | |
9 | ๐ฐ Crypto | 11% | +259% | |
10 | ๐ Data | 11% | +107% | |
11 | ๐ฑ Mobile Dev | 11% | +346% | |
12 | ๐ฐ Finance | 10% | +131% | |
13 | ๐ Ecommerce | 9% | +103% | |
14 | ๐ค Sales | 7% | +81% | |
15 | ๐จโ๐ซ Education | 6% | -9% | n=18,696 |
๐ฑโโ๏ธ Nomad women work as |
||||
# | Work | % | vs. men | |
1 | ๐ Marketing | 15% | -1% | |
2 | ๐ฉโ๐จ Creative | 15% | +22% | |
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% | +20% | |
8 | ๐ค Community | 7% | +23% | |
9 | ๐จโ๐ซ Education | 7% | +10% | |
10 | ๐ Coach | 7% | +23% | |
11 | ๐ค Product Manager | 7% | -41% | |
12 | ๐ Data | 5% | -52% | |
13 | ๐ SaaS | 4% | -66% | |
14 | ๐ฐ Finance | 4% | -57% | |
15 | ๐ Ecommerce | 4% | -51% | n=5,705 |
๐จ Nomad men vs. women |
||||
# | Tag | vs. women | ||
1 | ๐พ Game Dev | +355% | ||
2 | ๐ฑ Mobile Dev | +346% | ||
3 | ๐ Dev Ops | +321% | ||
4 | ๐ก Sysadmin | +306% | ||
5 | ๐ธ Web Dev | +261% | ||
6 | ๐ฐ Crypto | +259% | ||
7 | ๐ป Software Dev | +243% | ||
8 | ๐ SaaS | +197% | ||
9 | ๐ VR Dev | +154% | ||
10 | ๐ Sports | +146% | ||
11 | ๐บ Geo | +140% | ||
12 | ๐ Startup Founder | +136% | ||
13 | ๐ฐ Finance | +131% | ||
14 | ๐ OF | +114% | ||
15 | ๐ Data | +107% | n=23,307 |
๐ฑโโ๏ธ Nomad women vs. men |
||||
# | Tag | vs. men | ||
1 | ๐งโ๐ผ Human resources | +72% | ||
2 | ๐ง Psychologist | +52% | ||
3 | ๐ฐ Journalism | +48% | ||
4 | ๐จโโ๏ธ Medical | +37% | ||
5 | ๐ Support | +29% | ||
6 | ๐ Coach | +23% | ||
7 | ๐ค Community | +23% | ||
8 | ๐ Hospitality | +23% | ||
9 | ๐ฉโ๐จ Creative | +22% | ||
10 | ๐ Blogging | +20% | ||
11 | ๐ Recruitment | +14% | ||
12 | ๐ธ Model | +11% | ||
13 | ๐จโ๐ซ Education | +10% | ||
14 | ๐ฉโ๐ผ Law | +9% | n=23,307 |
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 | 39% | +29% | |
2 | ๐ Optimist | 31% | +32% | |
3 | ๐ฌ๐ง Speaks English | 30% | +22% | |
4 | ๐ COVID vaccinated | 28% | +20% | |
5 | โฐ Outdoors | 27% | +9% | |
6 | ๐ฅพ Hiking | 26% | +17% | |
7 | ๐ช Fitness | 26% | +51% | |
8 | ๐ถ Dogs | 26% | +9% | |
9 | ๐บ Beer | 25% | +125% | |
10 | โ๏ธ Waking up early | 25% | +29% | |
11 | ๐ Staying up late | 25% | +54% | |
12 | ๐ง Open-minded | 24% | +22% | |
13 | ๐ Reading | 24% | +11% | |
14 | ๐ท Wine | 23% | +1% | |
15 | ๐ Single | 23% | +34% | n=18,696 |
๐ฑโโ๏ธ Nomad women |
||||
# | Tag | % | vs. ๐จโ | |
1 | โ๏ธ Coffee | 31% | -22% | |
2 | ๐ฌ๐ง Speaks English | 25% | -18% | |
3 | โฐ Outdoors | 25% | -8% | |
4 | ๐ถ Dogs | 24% | -8% | |
5 | ๐ Optimist | 24% | -24% | |
6 | ๐ท Wine | 23% | -1% | |
7 | ๐ COVID vaccinated | 23% | -17% | |
8 | ๐ฅพ Hiking | 22% | -15% | |
9 | ๐ Reading | 21% | -10% | |
10 | ๐ต Tea | 21% | -1% | |
11 | ๐ง Open-minded | 20% | -18% | |
12 | ๐คธโโ๏ธ Yoga | 19% | +70% | |
13 | โ๏ธ Waking up early | 19% | -22% | |
14 | โฑ Beach | 18% | +6% | |
15 | ๐ธ Cocktails | 17% | -7% | n=5,705 |
๐จ Nomad men vs. women |
||||
# | Tag | vs. ๐ฑโโ๏ธ | ||
1 | ๐ง Have a beard | +1,248% | ||
2 | ๐ช Roost Stand | +375% | ||
3 | ๐จ No beard | +343% | ||
4 | โฝ๏ธ Football | +342% | ||
5 | ๐งโ Short hair | +263% | ||
6 | ๐ Ice hockey | +259% | ||
7 | ๐ Race sports | +224% | ||
8 | ๐ง Hardstyle music | +214% | ||
9 | ๐ด Conservative politics | +211% | ||
10 | ๐ Motorcycling | +211% | ||
11 | ๐ช Dropout | +211% | ||
12 | ๐ Table tennis | +188% | ||
13 | ๐ Basketball | +182% | ||
14 | ๐พ Gaming | +175% | ||
15 | ๐ Skateboarding | +171% | n=23,307 |
๐ฑโโ๏ธ Nomad women vs. men |
||||
# | Tag | vs. ๐จ | ||
1 | ๐ Makeup | +2,915% | ||
2 | ๐ฑโโ๏ธ Long hair | +276% | ||
3 | ๐ Dress up | +232% | ||
4 | โจ Astrology | +229% | ||
5 | โจ Believe in astrology | +216% | ||
6 | ๐ช Feminism | +190% | ||
7 | ๐ฆพ Disabled | +112% | ||
8 | ๐จ Drawing | +100% | ||
9 | ๐ฅ Red hair | +90% | ||
10 | ๐ Dancing | +88% | ||
11 | ๐ฐ๐ท K-pop music | +80% | ||
12 | ๐ Shopping | +76% | ||
13 | ๐คธโโ๏ธ Yoga | +70% | ||
14 | ๐ป Gardening | +70% | ||
15 | โ๐ฟ Black | +64% | n=23,307 |
๐ Nomads by vaccination |
||||
Vaccinated | % | |||
๐ COVID vaccinated |
94%
|
|||
๐ Not COVID vaccinated |
6%
|
n=7,254 |
โค๏ธ Nomads by family |
||||
Relationship | % | |||
โค๏ธ Close to parents |
81%
|
|||
๐ Not close to parents |
19%
|
n=1,870 |
๐ถ Nomads by childhood |
||||
Childhood | % | |||
๐ Happy childhood |
89%
|
|||
๐ Unhappy childhood |
11%
|
n=2,015 |
๐ก Homeownership amongst nomads |
||||
Homeownership | % | |||
๐ก Homeowner |
53%
|
|||
๐ก Not a homeowner |
47%
|
n=2,175 |
Attractiveness is based on the proportion of people liking or disliking a person based on their photo on Nomad List'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 My parents separated
๐ Table tennis
๐ณ๏ธโ๐ LGBT
๐ Volleyball
๐ In a relationship
๐ Shopping
๐จโ Attractive men's traits |
||||
# | Tag | Diff | ||
1 | ๐ธ Padel | +173% | ||
2 | ๐ In a relationship | +128% | ||
3 | โจ Believe in astrology | +94% | ||
4 | ๐ Not COVID vaccinated | +81% | ||
5 | ๐ Basketball | +78% | ||
6 | ๐ก Homeowner | +69% | ||
7 | ๐ฌ Twitter | +68% | ||
8 | ๐ Free diving | +66% | ||
9 | ๐งโ Short hair | +60% | ||
10 | ๐ง Hiphop music | +56% | ||
11 | ๐ Volleyball | +56% | ||
12 | ๐ Ice hockey | +54% | ||
13 | ๐ง Dubstep music | +53% | ||
14 | ๐ถ Parent | +53% | ||
15 | ๐ฅ Soft boiled eggs | +52% | ||
16 | ๐งผ Clean freak | +51% | ||
17 | ๐ก Not a homeowner | +49% | ||
18 | ๐ง Pessimist | +47% | ||
19 | ๐ iPhone | +47% | ||
20 | โ๏ธ Chess | +47% | ||
21 | ๐ Rugby | +44% | ||
22 | ๐ Table tennis | +43% | ||
23 | โค๏ธ Happy childhood | +43% | ||
24 | ๐ง Hardstyle music | +42% | ||
25 | ๐ง House music | +40% | ||
26 | โค๏ธ Close to my parents | +37% | ||
27 | ๐ Kitesurfing | +36% | ||
28 | ๐ผ Youngest child | +36% | ||
29 | โฝ๏ธ Football | +34% | ||
30 | ๐ช Crossfit | +34% | n=23,307 |
๐ฑโโ๏ธ Attractive women's traits |
||||
# | Tag | Diff | ||
1 | ๐ My parents separated | +320% | ||
2 | ๐ณ๏ธโ๐ LGBT | +299% | ||
3 | ๐ Table tennis | +279% | ||
4 | ๐ Shopping | +251% | ||
5 | ๐ง Only child | +233% | ||
6 | ๐ Volleyball | +232% | ||
7 | ๐ Running | +212% | ||
8 | ๐ธ Punk music | +202% | ||
9 | ๐ Makeup | +200% | ||
10 | ๐ฝ Libertarian politics | +192% | ||
11 | ๐งผ Clean freak | +174% | ||
12 | ๐จโ๐ค Partying | +154% | ||
13 | ๐ Dress up | +148% | ||
14 | ๐ Motorcycling | +147% | ||
15 | ๐ Surfing | +144% | ||
16 | ๐ฌ Social smoker | +144% | ||
17 | ๐ In a relationship | +144% | ||
18 | ๐ท Blues music | +137% | ||
19 | โท Skiing | +137% | ||
20 | ๐ด Cycling | +135% | ||
21 | โจ Astrology | +130% | ||
22 | ๐ Pescetarian | +127% | ||
23 | ๐ Swimming | +124% | ||
24 | ๐บ Beer | +123% | ||
25 | ๐ Vanlife | +122% | ||
26 | ๐ช Fitness | +119% | ||
27 | ๐พ Drinking alcohol | +119% | ||
28 | ๐ธ Indie rock music | +118% | ||
29 | ๐ท Jazz music | +118% | ||
30 | ๐ Film making | +116% | n=23,307 |
Attractiveness is based on the proportion of people liking or disliking a person based on their photo on Nomad List'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.
๐ช Paragliding
๐ FetLife
๐ฌ Slack
๐ Makeup
๐ฌ Discord
๐ญ Swinging
๐จโ Unattractive men's traits |
||||
# | Tag | Diff | ||
1 | ๐ FetLife | -1,006% | ||
2 | ๐ Makeup | -564% | ||
3 | ๐ญ Swinging | -431% | ||
4 | ๐ช Nexstand | -223% | ||
5 | ๐ณ Bowling | -112% | ||
6 | ๐ Urbex | -110% | ||
7 | ๐ช Skydiving | -81% | ||
8 | ๐ Single | -71% | ||
9 | ๐ง Trance music | -69% | ||
10 | ๐ถโ๐ซ๏ธ Hang gliding | -68% | ||
11 | ๐ป Gardening | -56% | ||
12 | ๐ฉ Samoyeds | -56% | ||
13 | ๐ช Feminism | -52% | ||
14 | ๐ Sex positive | -51% | ||
15 | ๐ Kink | -49% | ||
16 | ๐ Paleo | -40% | ||
17 | ๐ณ๏ธโ๐ Progressive politics | -40% | ||
18 | ๐ฌ Slack | -34% | ||
19 | ๐จโ๐ฆฒ Bald | -30% | ||
20 | ๐ฅ Hard boiled eggs | -30% | ||
21 | ๐ช Paragliding | -30% | ||
22 | ๐ Buddhist | -28% | ||
23 | ๐ Film making | -26% | ||
24 | ๐ Third Culture Kid | -24% | ||
25 | ๐บ Breakdance | -23% | ||
26 | ๐ Unhappy childhood | -22% | ||
27 | โ๏ธ Private pilot | -22% | ||
28 | ๐ฌ Discord | -21% | ||
29 | ๐ Cricket | -20% | ||
30 | โ๏ธ Doesn't want kids | -20% | n=23,307 |
๐ฑโโ๏ธ Unattractive women's traits |
||||
# | Tag | Diff | ||
1 | ๐ฅ Messy | -1,752% | ||
2 | ๐ช Paragliding | -1,021% | ||
3 | ๐ฌ Slack | -552% | ||
4 | ๐ฌ Discord | -422% | ||
5 | ๐ด Conservative politics | -422% | ||
6 | ๐ธ Anime | -291% | ||
7 | ๐ฐ๐ท K-pop music | -187% | ||
8 | ๐ช Roost Stand | -135% | ||
9 | ๐ถโ๐ซ๏ธ Hang gliding | -135% | ||
10 | ๐ฌ Snapchat | -135% | ||
11 | ๐ Kink | -103% | ||
12 | ๐ธ Badminton | -101% | ||
13 | ๐ Carnivore | -58% | ||
14 | โจ Believe in astrology | -41% | ||
15 | ๐ Country music | -25% | ||
16 | ๐ฌ Instagram | -23% | ||
17 | ๐ก Not a homeowner | -21% | ||
18 | ๐ฌ Facebook | -19% | ||
19 | ๐ Kitesurfing | -17% | ||
20 | ๐ถ Parent | -16% | ||
21 | ๐ณ Introvert | -12% | ||
22 | โค๏ธ Happy childhood | -10% | ||
23 | ๐ง Garage music | -7% | ||
24 | ๐ช Fight sports | -6% | ||
25 | ๐ Paleo | -4% | n=23,307 |
Attractiveness is based on the proportion of people liking or disliking a person based on their photo on Nomad List'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).
๐ก Architecture
๐ฑ Mobile Dev
๐ค Community
๐ SaaS
๐จ UI/UX Design
๐ช Fitness
๐จโ Attractive men's jobs |
||||
# | Tag | Diff | ||
1 | ๐จโโ๏ธ Medical | +44% | ||
2 | ๐ Recruitment | +42% | ||
3 | ๐จ UI/UX Design | +40% | ||
4 | ๐ SaaS | +35% | ||
5 | ๐พ Game Dev | +29% | ||
6 | ๐ฑ Mobile Dev | +28% | ||
7 | ๐ค Product Manager | +26% | ||
8 | ๐ Ecommerce | +23% | ||
9 | ๐ Marketing | +21% | ||
10 | ๐ค Sales | +20% | ||
11 | ๐ Startup Founder | +19% | ||
12 | ๐ Dev Ops | +15% | ||
13 | ๐ Logistics | +14% | ||
14 | ๐ VR Dev | +14% | ||
15 | ๐ Coach | +14% | ||
16 | ๐ป Software Dev | +13% | ||
17 | ๐ช Fitness | +12% | ||
18 | ๐ธ Web Dev | +9% | ||
19 | ๐ฐ Finance | +6% | ||
20 | ๐ค Community | +6% | ||
21 | ๐ Data | +6% | ||
22 | ๐ฐ Crypto | +4% | n=23,307 |
๐ฑโโ๏ธ Attractive women's jobs |
||||
# | Tag | Diff | ||
1 | ๐ก Architecture | +371% | ||
2 | ๐ค Community | +128% | ||
3 | ๐ฑ Mobile Dev | +110% | ||
4 | ๐ช Fitness | +105% | ||
5 | ๐ฉโ๐จ Creative | +98% | ||
6 | ๐ SaaS | +90% | ||
7 | ๐ Blogging | +87% | ||
8 | ๐ Startup Founder | +84% | ||
9 | ๐จ UI/UX Design | +81% | ||
10 | ๐ Coach | +77% | ||
11 | ๐ค Sales | +74% | ||
12 | ๐ Ecommerce | +64% | ||
13 | ๐ค Product Manager | +61% | ||
14 | ๐ Marketing | +60% | ||
15 | ๐จโ๐ซ Education | +49% | ||
16 | ๐ฐ Finance | +29% | ||
17 | ๐ป Software Dev | +27% | ||
18 | ๐ธ Web Dev | +8% | n=23,307 |
Attractiveness is based on the proportion of people liking or disliking a person based on their photo on Nomad List'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 | -455% | ||
2 | ๐ OF | -210% | ||
3 | ๐ฉโ๐ผ Law | -64% | ||
4 | ๐ฐ Journalism | -54% | ||
5 | ๐งโ๐ผ Human resources | -53% | ||
6 | ๐ธ Model | -53% | ||
7 | ๐ถ Adult | -40% | ||
8 | ๐ Hospitality | -35% | ||
9 | ๐ก Architecture | -26% | ||
10 | ๐ Support | -19% | ||
11 | ๐ก Sysadmin | -16% | ||
12 | ๐บ Geo | -7% | ||
13 | ๐จโ๐ซ Education | -5% | ||
14 | ๐ฉโ๐จ Creative | -4% | ||
15 | ๐ Sports | -4% | ||
16 | ๐ Blogging | -1% | n=23,307 |
๐ฑโโ๏ธ Unattractive women's jobs |
||||
# | Tag | Diff | ||
1 | ๐ฉ Politics | -1,126% | ||
2 | ๐ VR Dev | -552% | ||
3 | ๐ Sports | -96% | ||
4 | ๐ Hospitality | -81% | ||
5 | ๐ Data | -7% | ||
6 | ๐ Support | -1% | n=23,307 |
๐จโ Where attractive men travel to |
||||
# | City | Attractiveness | ||
1 | ๐ฆ๐บ Brisbane | 5 | ||
2 | ๐ต๐น Ericeira | 5 | ||
3 | ๐ฎ๐ฉ Uluwatu | 4.96 | ||
4 | ๐จ๐ท Tamarindo | 4.85 | ||
5 | ๐ฒ๐ฝ Cabo San Lucas | 4.83 | ||
6 | ๐ฉ๐ช Frankfurt | 4.71 | ||
7 | ๐ฐ๐ท Busan | 4.69 | ||
8 | ๐ฒ๐พ Langkawi | 4.69 | ||
9 | ๐น๐ญ Ko Phi Phi | 4.69 | ||
10 | ๐ฎ๐ธ Reykjavik | 4.66 | ||
11 | ๐บ๐ธ Boston | 4.65 | ||
12 | ๐ฟ๐ฆ Johannesburg | 4.62 | ||
13 | ๐ช๐ธ Ibiza | 4.62 | ||
14 | ๐ต๐น Faro | 4.57 | ||
15 | ๐ณ๐ฟ Queenstown | 4.57 | ||
16 | ๐น๐ญ Ko Lanta | 4.57 | ||
17 | ๐ณ๐ฟ Christchurch | 4.52 | ||
18 | ๐น๐ญ Ao Nang | 4.52 | ||
19 | ๐ณ๐ด Bergen | 4.52 | ||
20 | ๐ฆ๐บ Melbourne | 4.52 | ||
21 | ๐ป๐ณ Hoi An | 4.5 | ||
22 | ๐ช๐ธ Seville | 4.5 | ||
23 | ๐ช๐ธ Mallorca | 4.5 | ||
24 | ๐ญ๐ท Zadar | 4.5 | ||
25 | ๐ฆ๐ท Bariloche | 4.5 | ||
26 | ๐จ๐ณ Macau | 4.5 | ||
27 | ๐ฑ๐ฆ Luang Prabang | 4.5 | ||
28 | ๐จ๐ณ Beijing | 4.48 | ||
29 | ๐ฎ๐ฉ Denpasar | 4.47 | ||
30 | ๐ณ๐ฟ Wellington | 4.47 | Based on attractiveness of visitors n=340,939 |
๐ฑโโ๏ธ Where attractive women travel to |
||||
# | City | Attractiveness | ||
1 | ๐น๐ญ Ko Phi Phi | 5 | ||
2 | ๐ญ๐ท Zadar | 4.98 | ||
3 | ๐ฎ๐น Genoa | 4.93 | ||
4 | ๐บ๐ฆ Kyiv | 4.87 | ||
5 | ๐ฒ๐ช Budva | 4.85 | ||
6 | ๐ฎ๐น Amalfi | 4.85 | ||
7 | ๐ง๐ฆ Mostar | 4.8 | ||
8 | ๐ฆ๐น Salzburg | 4.78 | ||
9 | ๐บ๐ธ Orlando | 4.78 | ||
10 | ๐ต๐ฑ Warsaw | 4.77 | ||
11 | ๐น๐ญ Ko Samui | 4.77 | ||
12 | ๐ฎ๐ฑ Tel Aviv | 4.75 | ||
13 | ๐จ๐ฑ Valparaรญso | 4.75 | ||
14 | ๐ช๐ธ Fuerteventura | 4.74 | ||
15 | ๐ฉ๐ด Punta Cana | 4.73 | ||
16 | ๐ฌ๐ท Mykonos | 4.71 | ||
17 | ๐ธ๐ฐ Bratislava | 4.7 | ||
18 | ๐ฐ๐ท Busan | 4.7 | ||
19 | ๐ฒ๐ช Kotor | 4.66 | ||
20 | ๐ต๐น Ericeira | 4.65 | ||
21 | ๐ฉ๐ด Santo Domingo | 4.63 | ||
22 | ๐น๐ญ Krabi | 4.62 | ||
23 | ๐ซ๐ท Strasbourg | 4.62 | ||
24 | ๐ฎ๐ฉ Jakarta | 4.62 | ||
25 | ๐ท๐บ Moscow | 4.62 | ||
26 | ๐ฎ๐น Milan | 4.61 | ||
27 | ๐จ๐พ Larnaca | 4.6 | ||
28 | ๐ช๐ธ Gran Canaria | 4.6 | ||
29 | ๐บ๐ธ Portland | 4.6 | ||
30 | ๐ช๐ธ Malaga | 4.6 | Based on attractiveness of visitors n=340,939 |
๐จโ Where unattractive men travel to |
||||
# | City | Attractiveness | ||
1 | ๐น๐ญ Pattaya | 3.17 | ||
2 | ๐ฎ๐ณ Goa | 3.34 | ||
3 | ๐ฒ๐ช Podgorica | 3.59 | ||
4 | ๐ฎ๐ณ Mumbai | 3.65 | ||
5 | ๐บ๐ธ Houston | 3.67 | ||
6 | ๐จ๐ณ Guangzhou | 3.7 | ||
7 | ๐ฒ๐ฝ Guadalajara | 3.71 | ||
8 | ๐ถ๐ฆ Doha | 3.73 | ||
9 | ๐ณ๐ต Kathmandu | 3.75 | ||
10 | ๐ฏ๐ต Fukuoka | 3.75 | ||
11 | ๐ฎ๐ณ Bengaluru | 3.75 | ||
12 | ๐ช๐ธ Alicante | 3.75 | ||
13 | ๐ท๐บ Moscow | 3.76 | ||
14 | ๐ฎ๐ฑ Jerusalem | 3.77 | ||
15 | ๐ง๐พ Minsk | 3.78 | ||
16 | ๐ฆ๐น Salzburg | 3.78 | ||
17 | ๐บ๐ฆ Lviv | 3.78 | ||
18 | ๐ช๐ฌ Cairo | 3.78 | ||
19 | ๐จ๐พ Larnaca | 3.82 | ||
20 | ๐ต๐ฑ Gdansk | 3.83 | ||
21 | ๐น๐ท Antalya | 3.83 | ||
22 | ๐ฌ๐ง Glasgow | 3.85 | ||
23 | ๐ต๐ฆ Panama City | 3.86 | ||
24 | ๐ฐ๐ฟ Almaty | 3.87 | ||
25 | ๐ฐ๐ช Nairobi | 3.87 | ||
26 | ๐บ๐ธ Washington | 3.87 | ||
27 | ๐น๐ญ Pai | 3.88 | ||
28 | ๐จ๐บ Havana | 3.89 | ||
29 | ๐ต๐ฑ Wrocลaw | 3.89 | ||
30 | ๐ฒ๐ฝ Oaxaca | 3.89 | Based on unattractiveness of visitors n=340,939 |
๐ฑโโ๏ธ Where unattractive women travel to |
||||
# | City | Attractiveness | ||
1 | ๐ฐ๐ช Nairobi | 3.18 | ||
2 | ๐ช๐จ Quito | 3.3 | ||
3 | ๐ฆ๐บ Perth | 3.42 | ||
4 | ๐บ๐ธ New Orleans | 3.46 | ||
5 | ๐ฌ๐ง Liverpool | 3.46 | ||
6 | ๐ณ๐ฟ Wellington | 3.49 | ||
7 | ๐ณ๐ฎ San Juan del Sur | 3.5 | ||
8 | ๐ต๐ท San Juan | 3.51 | ||
9 | ๐บ๐ธ Atlanta | 3.51 | ||
10 | ๐ฒ๐ฝ Guadalajara | 3.52 | ||
11 | ๐ฏ๐ต Fukuoka | 3.52 | ||
12 | ๐ง๐ช Antwerp | 3.53 | ||
13 | ๐จ๐ฆ Quebec City | 3.55 | ||
14 | ๐ฌ๐ง Manchester | 3.57 | ||
15 | ๐ฒ๐ฝ Guanajuato | 3.59 | ||
16 | ๐ฑ๐ฆ Vientiane | 3.6 | ||
17 | ๐ฏ๐ด Amman | 3.62 | ||
18 | ๐ฌ๐ง Bristol | 3.65 | ||
19 | ๐ช๐จ Cuenca | 3.69 | ||
20 | ๐ฒ๐ฝ San Miguel de Allende | 3.72 | ||
21 | ๐ฐ๐ญ Phnom Penh | 3.72 | ||
22 | ๐ต๐ฆ Panama City | 3.73 | ||
23 | ๐จ๐ด Bogota | 3.73 | ||
24 | ๐ช๐ธ San Sebastian | 3.76 | ||
25 | ๐ณ๐ต Kathmandu | 3.77 | ||
26 | ๐ฌ๐ง Glasgow | 3.77 | ||
27 | ๐ฒ๐ฝ Cozumel | 3.82 | ||
28 | ๐ฒ๐ฝ Puebla | 3.82 | ||
29 | ๐ฒ๐ฝ San Cristรณbal de las Casas | 3.83 | ||
30 | ๐ง๐ฌ Bansko | 3.83 | Based on unattractiveness of visitors n=340,939 |
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