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๐ถ 37-year old
๐ณ๏ธโ๐ Progressive
๐ซ Not religious
๐ Single
โ๐ป White
๐ Heterosexual
๐ฑโโ๏ธ Woman
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 72% less COโ
4๏ธโฃ
and stays for
4 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 2026.
Last updated: 50 minutes ago
๐ถ Nomads by age |
||||
| Age | % | |||
| 21 |
0.1%
|
|||
| 22 |
0.2%
|
|||
| 23 |
0.1%
|
|||
| 24 |
0.5%
|
|||
| 25 |
1%
|
|||
| 26 |
1%
|
|||
| 27 |
1%
|
|||
| 28 |
2%
|
|||
| 29 |
2%
|
|||
| 30 |
2%
|
|||
| 31 |
3%
|
|||
| 32 |
5%
|
|||
| 33 |
7%
|
|||
| 34 |
8%
|
|||
| 35 |
5%
|
|||
| 36 |
6%
|
|||
| 37 |
8%
|
|||
| 38 |
6%
|
|||
| 39 |
5%
|
|||
| 40 |
5%
|
|||
| 41 |
4%
|
|||
| 42 |
4%
|
|||
| 43 |
3%
|
|||
| 44 |
3%
|
|||
| 45 |
3%
|
n=1,013 | ||
โณ๏ธ Nomads by nationality |
||||
| # | Country | People | % | |
| 1 | ๐บ๐ธ United States | 50,752,871 | 43% | |
| 2 | ๐ฌ๐ง United Kingdom | 8,198,201 | 7% | |
| 3 | ๐จ๐ฆ Canada | 5,450,743 | 5% | |
| 4 | ๐ท๐บ Russia | 5,265,224 | 4% | |
| 5 | ๐ฉ๐ช Germany | 4,783,756 | 4% | |
| 6 | ๐ซ๐ท France | 4,041,678 | 3% | |
| 7 | ๐ง๐ท Brazil | 3,056,657 | 3% | |
| 8 | ๐ฆ๐บ Australia | 2,782,794 | 2% | |
| 9 | ๐ณ๐ฑ Netherlands | 2,155,561 | 2% | |
| 10 | ๐ช๐ธ Spain | 2,102,556 | 2% | |
| 11 | ๐ฎ๐ณ India | 1,912,619 | 2% | |
| 12 | ๐บ๐ฆ Ukraine | 1,665,260 | 1% | |
| 13 | ๐ฎ๐น Italy | 1,634,340 | 1% | |
| 14 | ๐ต๐ฑ Poland | 1,413,483 | 1% | |
| 15 | ๐จ๐ญ Switzerland | 1,201,460 | 1% | |
| 16 | ๐ฆ๐น Austria | 887,844 | 1% | |
| 17 | ๐ธ๐ช Sweden | 843,673 | 1% | |
| 18 | ๐ฏ๐ต Japan | 830,421 | 1% | |
| 19 | ๐น๐ท Turkey | 808,336 | 1% | |
| 20 | ๐ฎ๐ช Ireland | 790,667 | 1% | |
| 21 | ๐ฎ๐ฑ Israel | 733,244 | 1% | |
| 22 | ๐ง๐ช Belgium | 697,907 | 1% | |
| 23 | ๐ฐ๐ท South Korea | 680,239 | 1% | |
| 24 | ๐จ๐ฟ Czechia | 658,153 | 1% | |
| 25 | ๐ฒ๐ฝ Mexico | 622,816 | 1% | |
| 26 | ๐ฆ๐ท Argentina | 618,399 | 1% | |
| 27 | ๐ฟ๐ฆ South Africa | 613,982 | 1% | |
| 28 | ๐ต๐น Portugal | 600,730 | 1% | |
| 29 | ๐ท๐ด Romania | 556,559 | 0% | |
| 30 | ๐ธ๐ฌ Singapore | 530,056 | 0% | n=26,621 |
๐ถ Nomads by gender |
||||
| Gender | % | |||
| ๐ฑโโ๏ธ Women |
65%
|
|||
| ๐จโ Men |
35%
|
Last 30 days. n=351 | ||
๐ Nomads by sexuality |
||||
| Sexuality | % | |||
| ๐ Heterosexual |
87%
|
|||
| ๐ฆ Bisexual |
8%
|
|||
| ๐ณ๏ธโ๐ Gay or lesbian |
5%
|
n=16,267 | ||
๐ Nomads by beliefs |
||||
| Religion | % | |||
| ๐ซ Not religious |
52%
|
|||
| ๐ Spirituality |
28%
|
|||
| โช๏ธ Christianity |
10%
|
|||
| ๐ Buddhism |
3%
|
|||
| โจ Astrology |
2%
|
|||
| ๐ Islam |
2%
|
|||
| ๐ Judaism |
2%
|
|||
| ๐ Hinduism |
1%
|
|||
| ๐ณ Sikhism |
0%
|
n=8,491 | ||
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=7,716 | ||
๐ Education |
||||
| Education | % | |||
| ๐ High School |
9%
|
|||
| ๐ Higher education |
91%
|
|||
| ↱๐ Bachelor's |
54%
|
|||
| ↱๐ Master's |
34%
|
|||
| ↱๐ฉโ๐ซ PhD |
3%
|
n=17,540 | ||
โค๏ธ Nomads by relationship |
||||
| Relationship | % | |||
| ๐ Single |
67%
|
|||
| ๐ In a relationship |
33%
|
n=9,550 | ||
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=58,850 | ||
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 | $124,610 / y | |||
| Median | $85,000 / y | n=5,259 | ||
๐ฐ Nomads by employment |
||||
| Employment type | % | |||
| Full time |
38%
|
|||
| Startup founder |
18%
|
|||
| Freelance |
18%
|
|||
| Full time contractor |
9%
|
|||
| Agency |
8%
|
|||
| Other |
5%
|
|||
| Part time |
2%
|
|||
| Part time contractor |
1%
|
n=6,515 | ||
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=5,414 | ||
๐ฌ What messaging apps nomads use? |
||||
| Messaging app | % | |||
| Telegram |
48%
|
|||
|
42%
|
||||
|
5%
|
||||
| Snapchat |
3%
|
|||
|
2%
|
||||
|
0%
|
||||
| LINE |
0%
|
|||
| Slack |
0%
|
n=5,661 | ||
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=3,541 | ||
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=847 | ||
๐ฅฉ 77% of ๐จโ men eat meat
๐ฅฉ 57% of ๐ฑโโ๏ธwomen eat meat
๐ซ 38% 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 |
77%
|
|||
| ๐ซ Does not eat meat |
23%
|
|||
| ↱๐ฅ Vegan |
10%
|
|||
| ↱๐ฅ Vegetarian |
10%
|
|||
| ↱๐ Pescetarian |
4%
|
n=5,639 | ||
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=1,255 | ||
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 |
24%
|
|||
| ๐ Swimming |
23%
|
|||
| ๐คธโโ๏ธ Yoga |
21%
|
|||
| ๐ Surfing |
18%
|
|||
| โฐ Climbing |
15%
|
|||
| ๐ Diving |
15%
|
|||
| ๐ Snowboarding |
15%
|
|||
| โท Skiing |
15%
|
|||
| ๐พ Tennis |
14%
|
|||
| ๐ Motorcycling |
13%
|
|||
| ๐ช Fight sports |
11%
|
|||
| ๐ Table tennis |
9%
|
n=10,854 | ||
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=2,619 | ||
๐ฏ๐ต Tokyo
๐ต๐น Ericeira
๐บ๐ธ Chicago
๐ต๐น Portimรฃo
๐ง๐ฌ Varna
๐ญ๐ท Dubrovnik
๐ Most liked cities by men |
||||
| # | City | Rating | ||
| 1 | ๐ฏ๐ต Tokyo | 4.64 | ||
| 2 | ๐ง๐ท Rio de Janeiro | 4.44 | ||
| 3 | ๐ฒ๐ฝ Mexico City | 4.38 | ||
| 4 | ๐ธ๐ฌ Singapore | 4.38 | ||
| 5 | ๐ฏ๐ต Osaka | 4.38 | ||
| 6 | ๐ช๐ธ Madrid | 4.38 | ||
| 7 | ๐ต๐น Porto | 4.29 | ||
| 8 | ๐บ๐ธ New York City | 4.29 | ||
| 9 | ๐จ๐ฟ Prague | 4.29 | ||
| 10 | ๐ญ๐บ Budapest | 4.23 | ||
| 11 | ๐ฒ๐พ Kuala Lumpur | 4.23 | ||
| 12 | ๐น๐ญ Chiang Mai | 4.17 | ||
| 13 | ๐ฉ๐ช Munich | 4.17 | ||
| 14 | ๐ฏ๐ต Kyoto | 4.17 | ||
| 15 | ๐บ๐ธ Austin | 4.17 | n=6,779 | |
๐ Most liked cities by women |
||||
| # | City | Rating | ||
| 1 | ๐ญ๐บ Budapest | 3.75 | ||
| 2 | ๐ฒ๐ฝ Playa del Carmen | 3.75 | ||
| 3 | ๐จ๐ด Medellรญn | 3.75 | ||
| 4 | ๐บ๐ธ Los Angeles | 3.75 | ||
| 5 | ๐ฒ๐ฝ Mexico City | 3.00 | n=6,779 | |
๐ Most visited cities |
||||
| # | City | % visited | ||
| 1 | ๐น๐ญ Bangkok | 2.19% | ||
| 2 | ๐ฌ๐ง London | 2.19% | ||
| 3 | ๐บ๐ธ New York City | 1.49% | ||
| 4 | ๐ช๐ธ Barcelona | 1.49% | ||
| 5 | ๐ซ๐ท Paris | 1.47% | ||
| 6 | ๐ฉ๐ช Berlin | 1.45% | ||
| 7 | ๐ต๐น Lisbon | 1.44% | ||
| 8 | ๐ณ๐ฑ Amsterdam | 1.2% | ||
| 9 | ๐บ๐ธ San Francisco | 1.15% | ||
| 10 | ๐น๐ญ Chiang Mai | 1.08% | ||
| 11 | ๐ฒ๐ฝ Mexico City | 1% | ||
| 12 | ๐ฏ๐ต Tokyo | 0.92% | ||
| 13 | ๐ฎ๐ฉ Canggu | 0.92% | ||
| 14 | ๐ธ๐ฌ Singapore | 0.9% | ||
| 15 | ๐น๐ท Istanbul | 0.86% | ||
| 16 | ๐ช๐ธ Madrid | 0.83% | ||
| 17 | ๐บ๐ธ Los Angeles | 0.82% | ||
| 18 | ๐ฒ๐พ Kuala Lumpur | 0.81% | ||
| 19 | ๐ฆ๐ช Dubai | 0.79% | ||
| 20 | ๐ญ๐บ Budapest | 0.78% | ||
| 21 | ๐จ๐ฟ Prague | 0.71% | ||
| 22 | ๐ฆ๐ท Buenos Aires | 0.69% | ||
| 23 | ๐จ๐ด Medellรญn | 0.63% | ||
| 24 | ๐ท๐บ Moscow | 0.61% | ||
| 25 | ๐ฎ๐น Rome | 0.6% | ||
| 26 | ๐ฆ๐น Vienna | 0.58% | ||
| 27 | ๐ฐ๐ท Seoul | 0.55% | ||
| 28 | ๐ป๐ณ Ho Chi Minh City | 0.54% | ||
| 29 | ๐น๐ญ Phuket | 0.53% | ||
| 30 | ๐ญ๐ฐ Hong Kong | 0.53% | n=402,837 | |
๐ Most visited countries |
||||
| # | Country | % visited | ||
| 1 | ๐บ๐ธ United States | 14% | ||
| 2 | ๐น๐ญ Thailand | 5% | ||
| 3 | ๐ช๐ธ Spain | 5% | ||
| 4 | ๐ฉ๐ช Germany | 4% | ||
| 5 | ๐ฌ๐ง United Kingdom | 4% | ||
| 6 | ๐ฒ๐ฝ Mexico | 3% | ||
| 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 | ๐ฆ๐ช United Arab Emirates | 1% | ||
| 28 | ๐จ๐ณ China | 1% | ||
| 29 | ๐ธ๐ฌ Singapore | 1% | ||
| 30 | ๐ญ๐ท Croatia | 1% | n=402,837 | |
๐ Avg. COโ by member traveling |
||||
| Year | COโ | |||
| 2013 |
678 kg/y
|
|||
| 2014 |
989 kg/y
|
|||
| 2015 |
1,083 kg/y
|
|||
| 2016 |
1,295 kg/y
|
|||
| 2017 |
1,481 kg/y
|
|||
| 2018 |
1,554 kg/y
|
|||
| 2019 |
1,595 kg/y
|
|||
| 2020 |
1,000 kg/y
|
|||
| 2021 |
1,008 kg/y
|
|||
| 2022 |
1,584 kg/y
|
|||
| 2023 |
1,754 kg/y
|
|||
| 2024 |
1,717 kg/y
|
|||
| 2025 |
1,512 kg/y
|
|||
| 2026 |
2,663 kg/y
|
|||
| Average | 1,234 kg/y | |||
| Median | 1,387 kg/y |
Based on 402,837 trips by 15,444 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 1,387 kg/y, or 72% less COโ than the average American on travel and commuting. |
||
๐จ Where men go most |
||||
| # | Tag | vs. ๐ฑโโ๏ธ | ||
| 1 | ๐น๐ญ Bangkok | +24% | ||
| 2 | ๐ต๐น Lisbon | -16% | ||
| 3 | ๐ช๐ธ Barcelona | -11% | ||
| 4 | ๐ฌ๐ง London | -22% | ||
| 5 | ๐ซ๐ท Paris | -20% | ||
| 6 | ๐น๐ญ Chiang Mai | -2% | ||
| 7 | ๐ณ๐ฑ Amsterdam | +5% | ||
| 8 | ๐ฉ๐ช Berlin | -3% | ||
| 9 | ๐ฎ๐ฉ Canggu | -1% | ||
| 10 | ๐น๐ท Istanbul | +8% | ||
| 11 | ๐ฏ๐ต Tokyo | +13% | ||
| 12 | ๐ธ๐ฌ Singapore | +13% | ||
| 13 | ๐ฒ๐ฝ Mexico City | -20% | ||
| 14 | ๐ฒ๐พ Kuala Lumpur | +26% | ||
| 15 | ๐ญ๐บ Budapest | +19% | median temp=18°C; n=402,837 | |
๐ฑโโ๏ธ Where women go most |
||||
| # | Tag | vs. ๐จ | ||
| 1 | ๐ต๐น Lisbon | +19% | ||
| 2 | ๐ฌ๐ง London | +27% | ||
| 3 | ๐น๐ญ Bangkok | -19% | ||
| 4 | ๐ช๐ธ Barcelona | +12% | ||
| 5 | ๐ซ๐ท Paris | +26% | ||
| 6 | ๐น๐ญ Chiang Mai | +2% | ||
| 7 | ๐ฒ๐ฝ Mexico City | +25% | ||
| 8 | ๐ฉ๐ช Berlin | +3% | ||
| 9 | ๐ณ๐ฑ Amsterdam | -5% | ||
| 10 | ๐ฎ๐ฉ Canggu | +1% | ||
| 11 | ๐ฎ๐น Rome | +25% | ||
| 12 | ๐น๐ท Istanbul | -7% | ||
| 13 | ๐บ๐ธ New York City | +10% | ||
| 14 | ๐ฏ๐ต Tokyo | -11% | ||
| 15 | ๐ฎ๐ฉ Ubud | +28% | median temp=18°C; n=402,837 | |
๐จ Where men go more |
||||
| # | Tag | vs. women | ||
| 1 | ๐ท๐บ Russia | +90% | ||
| 2 | ๐ต๐ฑ Poland | +73% | ||
| 3 | ๐ท๐ด Romania | +57% | ||
| 4 | ๐ฌ๐ช Georgia | +46% | ||
| 5 | ๐ญ๐ฐ Hong Kong | +33% | ||
| 6 | ๐จ๐ณ China | +29% | ||
| 7 | ๐ฆ๐ช United Arab Emirates | +27% | ||
| 8 | ๐ท๐ธ Serbia | +25% | ||
| 9 | ๐จ๐ฟ Czechia | +24% | ||
| 10 | ๐ต๐ญ Philippines | +24% | ||
| 11 | ๐ฏ๐ต Japan | +20% | ||
| 12 | ๐ญ๐บ Hungary | +19% | ||
| 13 | ๐ณ๐ฟ New Zealand | +19% | ||
| 14 | ๐ป๐ณ Vietnam | +17% | ||
| 15 | ๐ฒ๐พ Malaysia | +17% | median temp=13°C; n=402,837 | |
๐ฑโโ๏ธ Where women go more |
||||
| # | Tag | vs. men | ||
| 1 | ๐จ๐ท Costa Rica | +52% | ||
| 2 | ๐ฟ๐ฆ South Africa | +46% | ||
| 3 | ๐ฒ๐ฝ Mexico | +38% | ||
| 4 | ๐ฌ๐ง United Kingdom | +29% | ||
| 5 | ๐ญ๐ท Croatia | +22% | ||
| 6 | ๐จ๐ฑ Chile | +21% | ||
| 7 | ๐ซ๐ท France | +21% | ||
| 8 | ๐ฎ๐น Italy | +19% | ||
| 9 | ๐ฌ๐ท Greece | +13% | ||
| 10 | ๐ต๐น Portugal | +12% | ||
| 11 | ๐ฆ๐บ Australia | +11% | ||
| 12 | ๐ต๐ช Peru | +10% | ||
| 13 | ๐ฎ๐ช Ireland | +9% | ||
| 14 | ๐ช๐ธ Spain | +8% | ||
| 15 | ๐บ๐ธ United States | +8% | median temp=18°C; n=402,837 | |
๐ Most liked countries |
||||
| # | Country | Rating | ||
| 1 | ๐ฏ๐ต Japan | 4.8 | ||
| 2 | ๐ญ๐ท Croatia | 4.6 | ||
| 3 | ๐ญ๐บ Hungary | 4.55 | ||
| 4 | ๐จ๐ฟ Czechia | 4.55 | ||
| 5 | ๐ฑ๐ป Latvia | 4.5 | ||
| 6 | ๐ต๐ฑ Poland | 4.4 | ||
| 7 | ๐ฐ๐ท South Korea | 4.4 | ||
| 8 | ๐จ๐ญ Switzerland | 4.35 | ||
| 9 | ๐ฌ๐ท Greece | 4.3 | ||
| 10 | ๐ฟ๐ฆ South Africa | 4.25 | ||
| 11 | ๐ช๐ช Estonia | 4.25 | ||
| 12 | ๐ฑ๐น Lithuania | 4.25 | ||
| 13 | ๐ฌ๐น Guatemala | 4.25 | ||
| 14 | ๐ญ๐ฐ Hong Kong | 4.15 | ||
| 15 | ๐ณ๐ต Nepal | 4.15 | n=4,021 | |
๐คฎ Least liked countries |
||||
| # | Country | Rating | ||
| 1 | ๐จ๐บ Cuba | 1 | ||
| 2 | ๐ฎ๐ท Iran | 1.65 | ||
| 3 | ๐ฌ๐ฎ Gibraltar | 1.65 | ||
| 4 | ๐ญ๐ณ Honduras | 1.65 | ||
| 5 | ๐จ๐พ Cyprus | 1.65 | ||
| 6 | ๐ฒ๐น Malta | 2.15 | ||
| 7 | ๐จ๐ฑ Chile | 2.25 | ||
| 8 | ๐ฑ๐ฐ Sri Lanka | 2.35 | ||
| 9 | ๐ธ๐ด Somalia | 2.5 | ||
| 10 | ๐ช๐น Ethiopia | 2.5 | ||
| 11 | ๐น๐ฟ Tanzania | 2.5 | ||
| 12 | ๐ง๐ง Barbados | 2.5 | ||
| 13 | ๐ธ๐ณ Senegal | 2.5 | ||
| 14 | ๐ฒ๐ณ Mongolia | 2.5 | ||
| 15 | ๐ฑ๐บ Luxembourg | 2.5 | n=4,021 | |
โฐ How long do nomads stay in one city? |
||||
| Duration | % | |||
| < 7 days |
47%
|
|||
| 7 - 30 days |
33%
|
|||
| 30 - 90 days |
14%
|
|||
| 90+ days |
6%
|
|||
| Average | 63 days (2 months) | |||
| Median | 7 days | n=392,597 | ||
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 | 129 days (4 months) | n=392,597 | ||
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% | +269% | |
| 2 | ๐ธ Web Dev | 28% | +291% | |
| 3 | ๐ Startup Founder | 28% | +148% | |
| 4 | ๐ Marketing | 15% | +6% | |
| 5 | ๐ SaaS | 14% | +212% | |
| 6 | ๐ฉโ๐จ Creative | 12% | -14% | |
| 7 | ๐จ UI/UX Design | 11% | +45% | |
| 8 | ๐ค Product Manager | 11% | +81% | |
| 9 | ๐ฐ Crypto | 11% | +276% | |
| 10 | ๐ฑ Mobile Dev | 11% | +371% | |
| 11 | ๐ Data | 11% | +113% | |
| 12 | ๐ฐ Finance | 10% | +139% | |
| 13 | ๐ Ecommerce | 9% | +115% | |
| 14 | ๐ค Sales | 7% | +94% | |
| 15 | ๐จโ๐ซ Education | 6% | -7% | n=20,539 |
๐ฑโโ๏ธ Nomad women work as |
||||
| # | Work | % | vs. men | |
| 1 | ๐ Marketing | 15% | -6% | |
| 2 | ๐ฉโ๐จ Creative | 14% | +17% | |
| 3 | ๐ Startup Founder | 11% | -60% | |
| 4 | ๐ป Software Dev | 9% | -73% | |
| 5 | ๐จ UI/UX Design | 8% | -31% | |
| 6 | ๐ค Community | 7% | +19% | |
| 7 | ๐ธ Web Dev | 7% | -74% | |
| 8 | ๐ Blogging | 7% | +15% | |
| 9 | ๐จโ๐ซ Education | 7% | +8% | |
| 10 | ๐ Coach | 6% | +16% | |
| 11 | ๐ค Product Manager | 6% | -45% | |
| 12 | ๐ Data | 5% | -53% | |
| 13 | ๐ SaaS | 4% | -68% | |
| 14 | ๐ฐ Finance | 4% | -58% | |
| 15 | ๐ Ecommerce | 4% | -54% | n=6,550 |
๐จ Nomad men vs. women |
||||
| # | Tag | vs. women | ||
| 1 | ๐ก๏ธ InfoSec | +538% | ||
| 2 | ๐ก Sysadmin | +378% | ||
| 3 | ๐ Dev Ops | +377% | ||
| 4 | ๐ฑ Mobile Dev | +371% | ||
| 5 | ๐พ Game Dev | +339% | ||
| 6 | ๐ธ Web Dev | +291% | ||
| 7 | ๐ฐ Crypto | +276% | ||
| 8 | ๐ป Software Dev | +269% | ||
| 9 | ๐ SaaS | +212% | ||
| 10 | ๐ VR Dev | +196% | ||
| 11 | ๐ Sports | +150% | ||
| 12 | ๐ Startup Founder | +148% | ||
| 13 | ๐ OF | +139% | ||
| 14 | ๐ฐ Finance | +139% | ||
| 15 | ๐บ Geo | +136% | n=25,885 | |
๐ฑโโ๏ธ Nomad women vs. men |
||||
| # | Tag | vs. men | ||
| 1 | ๐งโ๐ผ Human resources | +67% | ||
| 2 | ๐ฐ Journalism | +40% | ||
| 3 | ๐ง Psychologist | +40% | ||
| 4 | ๐ Support | +32% | ||
| 5 | ๐จโโ๏ธ Medical | +31% | ||
| 6 | ๐ Hospitality | +21% | ||
| 7 | ๐ค Community | +19% | ||
| 8 | ๐ฉโ๐จ Creative | +17% | ||
| 9 | ๐ Coach | +16% | ||
| 10 | ๐ Blogging | +15% | ||
| 11 | ๐ฉโ๐ผ Law | +12% | ||
| 12 | ๐ธ Model | +10% | ||
| 13 | ๐จโ๐ซ Education | +8% | ||
| 14 | ๐ Recruitment | +5% | n=25,885 | |
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% | +37% | |
| 2 | ๐ฌ๐ง Speaks English | 33% | +31% | |
| 3 | ๐ Optimist | 32% | +39% | |
| 4 | ๐ COVID vaccinated | 27% | +27% | |
| 5 | ๐ช Fitness | 27% | +61% | |
| 6 | โฐ Outdoors | 27% | +13% | |
| 7 | ๐ฅพ Hiking | 26% | +23% | |
| 8 | ๐ถ Dogs | 26% | +15% | |
| 9 | โ๏ธ Waking up early | 25% | +35% | |
| 10 | ๐บ Beer | 25% | +139% | |
| 11 | ๐ง Open-minded | 24% | +29% | |
| 12 | ๐ Staying up late | 24% | +64% | |
| 13 | ๐ Single | 24% | +42% | |
| 14 | ๐ Reading | 24% | +17% | |
| 15 | ๐ท Wine | 23% | +7% | n=20,539 |
๐ฑโโ๏ธ Nomad women |
||||
| # | Tag | % | vs. ๐จโ | |
| 1 | โ๏ธ Coffee | 29% | -27% | |
| 2 | ๐ฌ๐ง Speaks English | 25% | -23% | |
| 3 | โฐ Outdoors | 24% | -12% | |
| 4 | ๐ Optimist | 23% | -28% | |
| 5 | ๐ถ Dogs | 22% | -13% | |
| 6 | ๐ท Wine | 21% | -7% | |
| 7 | ๐ COVID vaccinated | 21% | -21% | |
| 8 | ๐ฅพ Hiking | 21% | -19% | |
| 9 | ๐ Reading | 20% | -14% | |
| 10 | ๐ต Tea | 20% | -6% | |
| 11 | ๐ง Open-minded | 19% | -23% | |
| 12 | ๐คธโโ๏ธ Yoga | 18% | +63% | |
| 13 | โ๏ธ Waking up early | 18% | -26% | |
| 14 | โฑ Beach | 17% | +2% | |
| 15 | ๐ช Fitness | 17% | -38% | n=6,550 |
๐จ Nomad men vs. women |
||||
| # | Tag | vs. ๐ฑโโ๏ธ | ||
| 1 | ๐ง Have a beard | +1,682% | ||
| 2 | ๐จ No beard | +443% | ||
| 3 | ๐ช Roost Stand | +421% | ||
| 4 | โฝ๏ธ Football | +381% | ||
| 5 | ๐งโ Short hair | +303% | ||
| 6 | ๐ Ice hockey | +262% | ||
| 7 | ๐ช Dropout | +256% | ||
| 8 | ๐ Race sports | +241% | ||
| 9 | ๐ Basketball | +230% | ||
| 10 | ๐ Motorcycling | +230% | ||
| 11 | ๐ง Hardstyle music | +215% | ||
| 12 | โ๏ธ Chess | +209% | ||
| 13 | ๐ Table tennis | +203% | ||
| 14 | ๐ช Fight sports | +192% | ||
| 15 | ๐ฌ Discord | +187% | n=25,885 | |
๐ฑโโ๏ธ Nomad women vs. men |
||||
| # | Tag | vs. ๐จ | ||
| 1 | ๐ Makeup | +3,017% | ||
| 2 | ๐ฑโโ๏ธ Long hair | +286% | ||
| 3 | ๐ Dress up | +214% | ||
| 4 | โจ Astrology | +206% | ||
| 5 | ๐ช Feminism | +185% | ||
| 6 | โจ Believe in astrology | +140% | ||
| 7 | ๐ฆพ Disabled | +126% | ||
| 8 | ๐จ Drawing | +93% | ||
| 9 | ๐ฅ Red hair | +79% | ||
| 10 | ๐ Dancing | +78% | ||
| 11 | ๐ Shopping | +73% | ||
| 12 | ๐ป Gardening | +71% | ||
| 13 | ๐คธโโ๏ธ Yoga | +63% | ||
| 14 | โ๐ฟ Black | +57% | ||
| 15 | ๐จ Blonde hair | +53% | n=25,885 | |
๐ Nomads by vaccination |
||||
| Vaccinated | % | |||
| ๐ COVID vaccinated |
93%
|
|||
| ๐ Not COVID vaccinated |
7%
|
n=8,165 | ||
โค๏ธ Nomads by family |
||||
| Relationship | % | |||
| โค๏ธ Close to parents |
82%
|
|||
| ๐ Not close to parents |
18%
|
n=2,293 | ||
๐ถ Nomads by childhood |
||||
| Childhood | % | |||
| ๐ Happy childhood |
89%
|
|||
| ๐ Unhappy childhood |
11%
|
n=2,467 | ||
๐ก Homeownership amongst nomads |
||||
| Homeownership | % | |||
| ๐ก Homeowner |
55%
|
|||
| ๐ก Not a homeowner |
45%
|
n=2,633 | ||
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 | +135% | ||
| 2 | ๐ก Homeowner | +58% | ||
| 3 | ๐ฅ Soft boiled eggs | +53% | ||
| 4 | ๐ฌ Twitter | +50% | ||
| 5 | ๐ง Hiphop music | +50% | ||
| 6 | ๐ Free diving | +49% | ||
| 7 | ๐ธ Padel | +47% | ||
| 8 | ๐ถ Parent | +46% | ||
| 9 | ๐งโ Short hair | +46% | ||
| 10 | ๐ฅ Messy | +44% | ||
| 11 | ๐ฌ Slack | +43% | ||
| 12 | ๐ Skateboarding | +43% | ||
| 13 | ๐ง Pessimist | +41% | ||
| 14 | ๐ง Hardstyle music | +41% | ||
| 15 | ๐ธ Badminton | +40% | ||
| 16 | ๐ Basketball | +39% | ||
| 17 | ๐ Kitesurfing | +39% | ||
| 18 | ๐ Rugby | +38% | ||
| 19 | ๐ Not COVID vaccinated | +38% | ||
| 20 | ๐ COVID vaccinated | +37% | ||
| 21 | ๐ง Dubstep music | +35% | ||
| 22 | โฝ๏ธ Football | +35% | ||
| 23 | ๐ Ice hockey | +35% | ||
| 24 | ๐ช Crossfit | +34% | ||
| 25 | ๐ผ Youngest child | +34% | ||
| 26 | ๐ก Not a homeowner | +33% | ||
| 27 | โฐ Climbing | +32% | ||
| 28 | ๐ง Have a beard | +32% | ||
| 29 | โจ Believe in astrology | +32% | ||
| 30 | ๐ iPhone | +31% | n=25,885 | |
๐ฑโโ๏ธ Most attractive women's traits |
||||
| # | Tag | Diff | ||
| 1 | ๐ My parents separated | +302% | ||
| 2 | ๐ณ๏ธโ๐ LGBT | +297% | ||
| 3 | ๐ง Only child | +266% | ||
| 4 | ๐ Volleyball | +237% | ||
| 5 | ๐ Table tennis | +217% | ||
| 6 | ๐ Shopping | +211% | ||
| 7 | ๐ Running | +200% | ||
| 8 | ๐งผ Clean freak | +192% | ||
| 9 | ๐ In a relationship | +188% | ||
| 10 | โจ Don't believe in astrology | +183% | ||
| 11 | ๐พ Tennis | +177% | ||
| 12 | ๐จโ๐ค Partying | +164% | ||
| 13 | ๐ฌ Social smoker | +163% | ||
| 14 | โท Skiing | +157% | ||
| 15 | โฝ๏ธ Football | +154% | ||
| 16 | ๐ธ Punk music | +152% | ||
| 17 | ๐ด Cycling | +145% | ||
| 18 | ๐ Surfing | +140% | ||
| 19 | ๐ Film making | +134% | ||
| 20 | โฐ Climbing | +130% | ||
| 21 | ๐ Pescetarian | +129% | ||
| 22 | ๐ Motorcycling | +128% | ||
| 23 | ๐ Swimming | +126% | ||
| 24 | ๐พ Drinking alcohol | +124% | ||
| 25 | ๐บ Beer | +123% | ||
| 26 | โฌ๏ธ Has no tattoos | +122% | ||
| 27 | ๐ Backpacking | +121% | ||
| 28 | โฑ Beach | +119% | ||
| 29 | ๐ Dress up | +116% | ||
| 30 | ๐ Makeup | +116% | n=25,885 | |
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
๐ฌ Daily smoker
๐ Bodyboarding
๐ณ Bowling
๐ด Conservative politics
๐ Makeup
๐จโ Most unattractive men's traits |
||||
| # | Tag | Diff | ||
| 1 | ๐ FetLife | -2,377% | ||
| 2 | ๐ Bodyboarding | -883% | ||
| 3 | ๐ณ Bowling | -820% | ||
| 4 | ๐ Makeup | -568% | ||
| 5 | ๐ช Skydiving | -401% | ||
| 6 | ๐ช Nexstand | -195% | ||
| 7 | ๐ช Paragliding | -139% | ||
| 8 | ๐ฑ Pool | -123% | ||
| 9 | ๐ง Garage music | -111% | ||
| 10 | ๐ Religious | -89% | ||
| 11 | ๐ฐ๐ท K-pop music | -85% | ||
| 12 | ๐ธ Anime | -79% | ||
| 13 | ๐ถโ๐ซ๏ธ Hang gliding | -77% | ||
| 14 | ๐ Single | -73% | ||
| 15 | ๐ง Trance music | -71% | ||
| 16 | ๐คฟ Snorkeling | -65% | ||
| 17 | ๐ป Gardening | -63% | ||
| 18 | ๐บ Breakdance | -53% | ||
| 19 | ๐ Paleo | -52% | ||
| 20 | ๐ Cricket | -52% | ||
| 21 | ๐ Sex positive | -44% | ||
| 22 | ๐ฌ Instagram | -44% | ||
| 23 | โพ๏ธ Baseball | -37% | ||
| 24 | ๐ Kink | -36% | ||
| 25 | ๐ญ Swinging | -34% | ||
| 26 | ๐ Urbex | -33% | ||
| 27 | ๐ฉ Samoyeds | -31% | ||
| 28 | ๐ Buddhist | -27% | ||
| 29 | ๐ฌ Discord | -26% | ||
| 30 | ๐ณ๏ธโ๐ Progressive politics | -25% | n=25,885 | |
๐ฑโโ๏ธ Most unattractive women's traits |
||||
| # | Tag | Diff | ||
| 1 | ๐ฅ Messy | -1,954% | ||
| 2 | ๐ง Pessimist | -966% | ||
| 3 | ๐ฌ Daily smoker | -888% | ||
| 4 | ๐ด Conservative politics | -576% | ||
| 5 | ๐ง Bouldering | -472% | ||
| 6 | ๐ฐ๐ท K-pop music | -420% | ||
| 7 | ๐ฌ Snapchat | -316% | ||
| 8 | โจ Believe in astrology | -261% | ||
| 9 | ๐ถโ๐ซ๏ธ Hang gliding | -212% | ||
| 10 | ๐ช Roost Stand | -134% | ||
| 11 | ๐ธ Badminton | -129% | ||
| 12 | ๐ FetLife | -108% | ||
| 13 | ๐ Skateboarding | -90% | ||
| 14 | ๐ Carnivore | -81% | ||
| 15 | ๐ก Not a homeowner | -78% | ||
| 16 | โค๏ธ Happy childhood | -45% | ||
| 17 | ๐ Country music | -42% | ||
| 18 | ๐ Kitesurfing | -39% | ||
| 19 | ๐ฑ Pool | -38% | ||
| 20 | ๐ณ Bowling | -25% | ||
| 21 | ๐ง Garage music | -22% | ||
| 22 | ๐ธ Anime | -12% | ||
| 23 | ๐ Kink | -11% | ||
| 24 | ๐ฌ Facebook | -10% | ||
| 25 | ๐ Paleo | -9% | ||
| 26 | ๐ Snowboarding | -7% | ||
| 27 | ๐ฌ Slack | -7% | n=25,885 | |
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).
๐ Recruitment
๐ฑ Mobile Dev
๐ค Community
๐ Coach
๐ SaaS
๐จ UI/UX Design
๐จโ Attractive men's jobs |
||||
| # | Tag | Diff | ||
| 1 | ๐จโโ๏ธ Medical | +55% | ||
| 2 | ๐ Recruitment | +50% | ||
| 3 | ๐ Logistics | +42% | ||
| 4 | ๐ SaaS | +39% | ||
| 5 | ๐จ UI/UX Design | +34% | ||
| 6 | ๐ค Product Manager | +34% | ||
| 7 | ๐ Ecommerce | +31% | ||
| 8 | ๐ Coach | +27% | ||
| 9 | ๐ Dev Ops | +23% | ||
| 10 | ๐ค Sales | +21% | ||
| 11 | ๐ง Psychologist | +20% | ||
| 12 | ๐ Marketing | +20% | ||
| 13 | ๐ Startup Founder | +20% | ||
| 14 | ๐ฑ Mobile Dev | +18% | ||
| 15 | ๐พ Game Dev | +17% | ||
| 16 | ๐ Data | +16% | ||
| 17 | ๐ป Software Dev | +12% | ||
| 18 | ๐ VR Dev | +10% | ||
| 19 | ๐ค Community | +5% | ||
| 20 | ๐ธ Web Dev | +2% | ||
| 21 | ๐ช Fitness | +2% | ||
| 22 | ๐ฐ Finance | +1% | n=25,885 | |
๐ฑโโ๏ธ Attractive women's jobs |
||||
| # | Tag | Diff | ||
| 1 | ๐ Recruitment | +167% | ||
| 2 | ๐ค Community | +130% | ||
| 3 | ๐ฑ Mobile Dev | +120% | ||
| 4 | ๐ฉโ๐จ Creative | +87% | ||
| 5 | ๐ Coach | +86% | ||
| 6 | ๐ช Fitness | +84% | ||
| 7 | ๐ Blogging | +84% | ||
| 8 | ๐ Startup Founder | +76% | ||
| 9 | ๐ SaaS | +70% | ||
| 10 | ๐จ UI/UX Design | +64% | ||
| 11 | ๐ฐ Journalism | +64% | ||
| 12 | ๐ป Software Dev | +64% | ||
| 13 | ๐ฐ Finance | +61% | ||
| 14 | ๐ Marketing | +59% | ||
| 15 | ๐ Ecommerce | +52% | ||
| 16 | ๐จโ๐ซ Education | +44% | ||
| 17 | ๐ค Product Manager | +40% | ||
| 18 | ๐ Data | +34% | ||
| 19 | ๐ค Sales | +27% | ||
| 20 | ๐ธ Web Dev | +2% | n=25,885 | |
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 Hospitality
๐ฉโ๐ผ Law
๐ฐ Journalism
๐ก Architecture
๐ Support
๐จโ Most unattractive men's jobs |
||||
| # | Tag | Diff | ||
| 1 | ๐ฉ Politics | -260% | ||
| 2 | ๐ฉโ๐ผ Law | -90% | ||
| 3 | ๐ฐ Journalism | -63% | ||
| 4 | ๐ก Architecture | -39% | ||
| 5 | ๐ถ Adult | -34% | ||
| 6 | ๐ Hospitality | -32% | ||
| 7 | ๐ Support | -20% | ||
| 8 | ๐ธ Model | -17% | ||
| 9 | ๐ก๏ธ InfoSec | -14% | ||
| 10 | ๐บ Geo | -12% | ||
| 11 | ๐ฐ Crypto | -12% | ||
| 12 | ๐ Sports | -6% | ||
| 13 | ๐ฉโ๐จ Creative | -6% | ||
| 14 | ๐ Blogging | -5% | ||
| 15 | ๐จโ๐ซ Education | -2% | ||
| 16 | ๐ก Sysadmin | -1% | n=25,885 | |
๐ฑโโ๏ธ Most unattractive women's jobs |
||||
| # | Tag | Diff | ||
| 1 | ๐ฉ Politics | -1,252% | ||
| 2 | ๐ VR Dev | -576% | ||
| 3 | ๐ Hospitality | -105% | ||
| 4 | ๐ Logistics | -48% | ||
| 5 | ๐ Support | -15% | n=25,885 | |
๐จโ Where attractive men travel to |
||||
| # | City | Attractiveness | ||
| 1 | ๐ฌ๐ท Mykonos | 5 | ||
| 2 | ๐ต๐น Ericeira | 4.98 | ||
| 3 | ๐ฎ๐ฉ Uluwatu | 4.98 | ||
| 4 | ๐ฒ๐ฝ Cabo San Lucas | 4.88 | ||
| 5 | ๐ธ๐ช Malmรถ | 4.85 | ||
| 6 | ๐จ๐ท Tamarindo | 4.85 | ||
| 7 | ๐ฆ๐บ Brisbane | 4.82 | ||
| 8 | ๐ช๐ธ Ibiza | 4.78 | ||
| 9 | ๐ญ๐ท Zadar | 4.69 | ||
| 10 | ๐ช๐ธ Lanzarote | 4.67 | ||
| 11 | ๐น๐ญ Ko Lanta | 4.66 | ||
| 12 | ๐ฎ๐ธ Reykjavik | 4.65 | ||
| 13 | ๐ช๐ธ Mallorca | 4.64 | ||
| 14 | ๐ช๐ธ Fuerteventura | 4.64 | ||
| 15 | ๐ฆ๐บ Melbourne | 4.63 | ||
| 16 | ๐จ๐ณ Macau | 4.62 | ||
| 17 | ๐ณ๐ฟ Auckland | 4.62 | ||
| 18 | ๐ณ๐ด Bergen | 4.61 | ||
| 19 | ๐ฒ๐ฆ Marrakesh | 4.6 | ||
| 20 | ๐ฉ๐ช Stuttgart | 4.6 | ||
| 21 | ๐ต๐น Portimรฃo | 4.59 | ||
| 22 | ๐ฌ๐ง Manchester | 4.58 | ||
| 23 | ๐ณ๐ฟ Queenstown | 4.58 | ||
| 24 | ๐ง๐ท Florianopolis | 4.57 | ||
| 25 | ๐ช๐ธ Tenerife | 4.57 | ||
| 26 | ๐ช๐ธ San Sebastian | 4.57 | ||
| 27 | ๐ฉ๐ช Frankfurt | 4.56 | ||
| 28 | ๐ณ๐ฟ Christchurch | 4.56 | ||
| 29 | ๐บ๐ธ Boston | 4.55 | ||
| 30 | ๐ต๐น Faro | 4.53 | Based on attractiveness of visitors n=402,837 | |
๐ฑโโ๏ธ Where attractive women travel to |
||||
| # | City | Attractiveness | ||
| 1 | ๐น๐ญ Ko Phi Phi | 5 | ||
| 2 | ๐ซ๐ท Cannes | 5 | ||
| 3 | ๐ญ๐ท Zadar | 4.85 | ||
| 4 | ๐ฎ๐น Genoa | 4.78 | ||
| 5 | ๐ต๐ฑ Wrocลaw | 4.72 | ||
| 6 | ๐ช๐ธ Ibiza | 4.71 | ||
| 7 | ๐ป๐ณ Nha Trang | 4.69 | ||
| 8 | ๐บ๐ธ Orlando | 4.69 | ||
| 9 | ๐ฒ๐ช Budva | 4.69 | ||
| 10 | ๐ฑ๐ฐ Galle | 4.67 | ||
| 11 | ๐ฉ๐ช Dresden | 4.65 | ||
| 12 | ๐ท๐บ Moscow | 4.63 | ||
| 13 | ๐ฆ๐บ Cairns | 4.61 | ||
| 14 | ๐น๐ญ Ko Samui | 4.61 | ||
| 15 | ๐ป๐ณ Da Lat | 4.59 | ||
| 16 | ๐ฌ๐ช Batumi | 4.58 | ||
| 17 | ๐บ๐ฆ Kyiv | 4.58 | ||
| 18 | ๐ฎ๐น Amalfi | 4.57 | ||
| 19 | ๐ฉ๐ด Punta Cana | 4.57 | ||
| 20 | ๐ฌ๐ท Rhodes | 4.55 | ||
| 21 | ๐น๐ญ Krabi | 4.55 | ||
| 22 | ๐ท๐บ Saint Petersburg | 4.54 | ||
| 23 | ๐ช๐ธ Fuerteventura | 4.54 | ||
| 24 | ๐ฎ๐ฉ Uluwatu | 4.53 | ||
| 25 | ๐จ๐พ Larnaca | 4.53 | ||
| 26 | ๐จ๐ฑ Valparaรญso | 4.51 | ||
| 27 | ๐ฎ๐ฑ Tel Aviv | 4.5 | ||
| 28 | ๐ฎ๐น Milan | 4.5 | ||
| 29 | ๐ต๐น Faro | 4.5 | ||
| 30 | ๐น๐ญ Ko Pha Ngan | 4.5 | Based on attractiveness of visitors n=402,837 | |
๐จโ Where unattractive men travel to |
||||
| # | City | Attractiveness | ||
| 1 | ๐น๐ญ Pattaya | 3.3 | ||
| 2 | ๐ฎ๐ณ Goa | 3.67 | ||
| 3 | ๐น๐ญ Hua Hin | 3.74 | ||
| 4 | ๐ฒ๐ช Podgorica | 3.74 | ||
| 5 | ๐บ๐ธ Houston | 3.74 | ||
| 6 | ๐ฐ๐ฟ Almaty | 3.74 | ||
| 7 | ๐ฎ๐ณ Bengaluru | 3.74 | ||
| 8 | ๐ช๐ธ Alicante | 3.8 | ||
| 9 | ๐ฎ๐ฉ Kuta | 3.81 | ||
| 10 | ๐ป๐ณ Nha Trang | 3.82 | ||
| 11 | ๐ณ๐ต Kathmandu | 3.82 | ||
| 12 | ๐ท๐บ Moscow | 3.83 | ||
| 13 | ๐ต๐ฆ Panama City | 3.84 | ||
| 14 | ๐ช๐ฌ Cairo | 3.85 | ||
| 15 | ๐ฏ๐ต Fukuoka | 3.87 | ||
| 16 | ๐ฎ๐ฑ Jerusalem | 3.87 | ||
| 17 | ๐บ๐ฆ Lviv | 3.9 | ||
| 18 | ๐ฌ๐ช Batumi | 3.91 | ||
| 19 | ๐ด๐ฒ Muscat | 3.93 | ||
| 20 | ๐ฏ๐ต Hiroshima | 3.94 | ||
| 21 | ๐ฆ๐ฒ Yerevan | 3.94 | ||
| 22 | ๐ฎ๐ณ Mumbai | 3.95 | ||
| 23 | ๐ฑ๐ฆ Vientiane | 3.97 | ||
| 24 | ๐ง๐พ Minsk | 3.97 | ||
| 25 | ๐ฒ๐ฝ Guadalajara | 3.97 | ||
| 26 | ๐ฎ๐น Turin | 3.98 | ||
| 27 | ๐ณ๐ฑ Rotterdam | 3.98 | ||
| 28 | ๐ต๐ฑ Gdansk | 3.98 | ||
| 29 | ๐ฉ๐ด Santo Domingo | 3.98 | ||
| 30 | ๐ช๐ธ Bilbao | 3.99 | Based on unattractiveness of visitors n=402,837 | |
๐ฑโโ๏ธ Where unattractive women travel to |
||||
| # | City | Attractiveness | ||
| 1 | ๐ฐ๐ช Nairobi | 3.1 | ||
| 2 | ๐ช๐จ Quito | 3.14 | ||
| 3 | ๐ณ๐ฟ Wellington | 3.15 | ||
| 4 | ๐ช๐จ Cuenca | 3.2 | ||
| 5 | ๐ฆ๐บ Perth | 3.27 | ||
| 6 | ๐ณ๐ฟ Queenstown | 3.32 | ||
| 7 | ๐ฑ๐ฐ Weligama | 3.36 | ||
| 8 | ๐จ๐ฆ Quebec City | 3.36 | ||
| 9 | ๐ต๐ท San Juan | 3.4 | ||
| 10 | ๐ฌ๐ง Liverpool | 3.43 | ||
| 11 | ๐บ๐ธ Atlanta | 3.43 | ||
| 12 | ๐ฏ๐ด Amman | 3.46 | ||
| 13 | ๐ฏ๐ต Fukuoka | 3.46 | ||
| 14 | ๐ฐ๐ญ Phnom Penh | 3.52 | ||
| 15 | ๐จ๐ณ Macau | 3.53 | ||
| 16 | ๐จ๐ด Bogota | 3.55 | ||
| 17 | ๐ฏ๐ฒ Montego Bay | 3.56 | ||
| 18 | ๐จ๐ณ Guangzhou | 3.61 | ||
| 19 | ๐บ๐ธ New Orleans | 3.61 | ||
| 20 | ๐ฒ๐ฝ Merida | 3.62 | ||
| 21 | ๐ฑ๐ฐ Colombo | 3.63 | ||
| 22 | ๐ต๐ฆ Panama City | 3.63 | ||
| 23 | ๐ฎ๐ฉ Denpasar | 3.64 | ||
| 24 | ๐ฑ๐ฆ Vientiane | 3.64 | ||
| 25 | ๐ง๐ฆ Sarajevo | 3.64 | ||
| 26 | ๐ป๐ณ Sa Pa | 3.67 | ||
| 27 | ๐ง๐ฌ Bansko | 3.67 | ||
| 28 | ๐ฌ๐ง Glasgow | 3.68 | ||
| 29 | ๐ฒ๐ฆ Essaouira | 3.68 | ||
| 30 | ๐ฒ๐ฝ Guadalajara | 3.69 | Based on unattractiveness of visitors n=402,837 | |
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