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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 76% less COโ
7๏ธโฃ
and stays for
7 months
Remote work is now on an exponential trajectory and growing fast. With its growth, hundreds of millions of people who are now newly working remotely from home, a cafe, or coworking space, will realize they've become location independent and travel or move to new places. In this report, we try to figure out who these people are, what work do they do, and how they spend their life based on data from tens of thousands of 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: 13 minutes ago
๐ถ Nomads by age |
||||
| Age | % | |||
| 19 |
0.2%
|
|||
| 21 |
0.2%
|
|||
| 22 |
0.2%
|
|||
| 23 |
0.3%
|
|||
| 24 |
1%
|
|||
| 25 |
1%
|
|||
| 26 |
1%
|
|||
| 27 |
2%
|
|||
| 28 |
2%
|
|||
| 29 |
3%
|
|||
| 30 |
5%
|
|||
| 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=1,213 | ||
โณ๏ธ Nomads by nationality |
||||
| # | Country | People | % | |
| 1 | ๐บ๐ธ United States | 35,331,563 | 45% | |
| 2 | ๐ฌ๐ง United Kingdom | 5,511,428 | 7% | |
| 3 | ๐ท๐บ Russia | 3,665,726 | 5% | |
| 4 | ๐จ๐ฆ Canada | 3,556,589 | 5% | |
| 5 | ๐ฉ๐ช Germany | 2,953,124 | 4% | |
| 6 | ๐ซ๐ท France | 2,516,575 | 3% | |
| 7 | ๐ง๐ท Brazil | 1,906,691 | 2% | |
| 8 | ๐ฆ๐บ Australia | 1,820,023 | 2% | |
| 9 | ๐ณ๐ฑ Netherlands | 1,386,684 | 2% | |
| 10 | ๐ช๐ธ Spain | 1,325,696 | 2% | |
| 11 | ๐ฎ๐ณ India | 1,123,471 | 1% | |
| 12 | ๐บ๐ฆ Ukraine | 1,030,384 | 1% | |
| 13 | ๐ฎ๐น Italy | 937,296 | 1% | |
| 14 | ๐ต๐ฑ Poland | 898,777 | 1% | |
| 15 | ๐จ๐ญ Switzerland | 754,331 | 1% | |
| 16 | ๐ฆ๐น Austria | 616,304 | 1% | |
| 17 | ๐ธ๐ช Sweden | 526,426 | 1% | |
| 18 | ๐ฎ๐ช Ireland | 503,957 | 1% | |
| 19 | ๐น๐ท Turkey | 481,488 | 1% | |
| 20 | ๐ฎ๐ฑ Israel | 481,488 | 1% | |
| 21 | ๐ฏ๐ต Japan | 475,068 | 1% | |
| 22 | ๐จ๐ฟ Czechia | 426,919 | 1% | |
| 23 | ๐ง๐ช Belgium | 426,919 | 1% | |
| 24 | ๐ฐ๐ท South Korea | 391,610 | 1% | |
| 25 | ๐ฟ๐ฆ South Africa | 391,610 | 1% | |
| 26 | ๐ธ๐ฌ Singapore | 372,350 | 0% | |
| 27 | ๐ฒ๐ฝ Mexico | 372,350 | 0% | |
| 28 | ๐ต๐น Portugal | 369,141 | 0% | |
| 29 | ๐ฆ๐ท Argentina | 362,721 | 0% | |
| 30 | ๐ณ๐ฟ New Zealand | 346,671 | 0% | n=24,254 |
๐ถ Nomads by gender |
||||
| Gender | % | |||
| ๐จโ Men |
84%
|
|||
| ๐ฑโโ๏ธ Women |
16%
|
Last 30 days. n=79 | ||
๐ Nomads by sexuality |
||||
| Sexuality | % | |||
| ๐ Heterosexual |
87%
|
|||
| ๐ฆ Bisexual |
8%
|
|||
| ๐ณ๏ธโ๐ Gay or lesbian |
5%
|
n=14,293 | ||
๐ Nomads by beliefs |
||||
| Religion | % | |||
| ๐ซ Not religious |
54%
|
|||
| 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=7,262 | ||
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=6,447 | ||
๐ Education |
||||
| Education | % | |||
| ๐ High School |
9%
|
|||
| ๐ Higher education |
91%
|
|||
| ↱๐ Bachelor's |
54%
|
|||
| ↱๐ Master's |
34%
|
|||
| ↱๐ฉโ๐ซ PhD |
3%
|
n=14,715 | ||
โค๏ธ Nomads by relationship |
||||
| Relationship | % | |||
| ๐ Single |
66%
|
|||
| ๐ In a relationship |
34%
|
n=7,894 | ||
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=49,462 | ||
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 | $123,275 / y | |||
| Median | $85,000 / y | n=3,994 | ||
๐ฐ Nomads by employment |
||||
| Employment type | % | |||
| Full time |
41%
|
|||
| Freelance |
18%
|
|||
| Startup founder |
17%
|
|||
| Full time contractor |
9%
|
|||
| Agency |
8%
|
|||
| Other |
5%
|
|||
| Part time |
2%
|
|||
| Part time contractor |
2%
|
n=4,708 | ||
๐ก Where do nomads work from |
||||
| Place | % | |||
| ๐ก Home office |
60%
|
|||
| 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%
|
n=3,695 | ||
๐ฌ What messaging apps nomads use? |
||||
| Messaging app | % | |||
| Telegram |
47%
|
|||
|
44%
|
||||
|
5%
|
||||
|
2%
|
||||
| Snapchat |
1%
|
|||
| LINE |
0%
|
|||
|
0%
|
||||
| Slack |
0%
|
n=4,386 | ||
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=3,285 | ||
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=779 | ||
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=5,026 | ||
๐ Nomad women by diet |
||||
| Diet | % | |||
| ๐ฅฉ Eats meat |
56%
|
|||
| ๐ซ Does not eat meat |
44%
|
|||
| ↱๐ฅ Vegetarian |
19%
|
|||
| ↱๐ฅ Vegan |
15%
|
|||
| ↱๐ Pescetarian |
11%
|
n=1,162 | ||
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=9,519 | ||
๐ Nomad women by sports |
||||
| Sport | % | |||
| ๐ฅพ Hiking |
52%
|
|||
| ๐คธโโ๏ธ Yoga |
44%
|
|||
| 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=2,391 | ||
๐ต๐น Portimรฃo
๐บ๐ธ Chicago
๐บ๐ฆ Odessa
๐ญ๐บ Budapest
๐ช๐ธ Valencia
๐น๐ญ Chiang Mai
๐ Most liked cities by men |
||||
| # | City | Rating | ||
| 1 | ๐ต๐น Porto | 4.58 | ||
| 2 | ๐ช๐ธ Madrid | 4.58 | ||
| 3 | ๐ฐ๐ท Seoul | 4.50 | ||
| 4 | ๐ต๐ฑ Warsaw | 4.50 | ||
| 5 | ๐ฏ๐ต Tokyo | 4.44 | ||
| 6 | ๐ต๐ฑ Krakรณw | 4.44 | ||
| 7 | ๐จ๐ฟ Prague | 4.38 | ||
| 8 | ๐ฒ๐ฝ Mexico City | 4.29 | ||
| 9 | ๐ฟ๐ฆ Cape Town | 4.29 | ||
| 10 | ๐ฒ๐พ Penang | 4.29 | ||
| 11 | ๐ช๐ธ Valencia | 4.29 | ||
| 12 | ๐ญ๐ท Split | 4.29 | ||
| 13 | ๐ญ๐บ Budapest | 4.23 | ||
| 14 | ๐ฌ๐ท Athens | 4.17 | ||
| 15 | ๐ฉ๐ช Munich | 4.17 | n=4,777 | |
๐ Most liked cities by women |
||||
| # | City | Rating | ||
| 1 | ๐จ๐ด Medellรญn | 4.00 | ||
| 2 | ๐น๐ญ Chiang Mai | 3.75 | ||
| 3 | ๐ญ๐บ Budapest | 3.75 | ||
| 4 | ๐ฉ๐ช Berlin | 3.75 | ||
| 5 | ๐ฉ๐ช Munich | 3.75 | ||
| 6 | ๐ฆ๐น Vienna | 3.75 | ||
| 7 | ๐ฒ๐ฝ Playa del Carmen | 3.00 | n=4,777 | |
๐ Most visited cities |
||||
| # | City | % visited | ||
| 1 | ๐ฌ๐ง London | 2.28% | ||
| 2 | ๐น๐ญ Bangkok | 2.03% | ||
| 3 | ๐บ๐ธ New York City | 1.55% | ||
| 4 | ๐ฉ๐ช Berlin | 1.51% | ||
| 5 | ๐ต๐น Lisbon | 1.51% | ||
| 6 | ๐ซ๐ท Paris | 1.49% | ||
| 7 | ๐ช๐ธ Barcelona | 1.47% | ||
| 8 | ๐ณ๐ฑ Amsterdam | 1.26% | ||
| 9 | ๐บ๐ธ San Francisco | 1.19% | ||
| 10 | ๐น๐ญ Chiang Mai | 1.08% | ||
| 11 | ๐ฒ๐ฝ Mexico City | 1.01% | ||
| 12 | ๐ธ๐ฌ Singapore | 0.91% | ||
| 13 | ๐ฎ๐ฉ Canggu | 0.9% | ||
| 14 | ๐บ๐ธ Los Angeles | 0.88% | ||
| 15 | ๐น๐ท Istanbul | 0.85% | ||
| 16 | ๐ฏ๐ต Tokyo | 0.83% | ||
| 17 | ๐ญ๐บ Budapest | 0.81% | ||
| 18 | ๐ช๐ธ Madrid | 0.81% | ||
| 19 | ๐ฒ๐พ Kuala Lumpur | 0.76% | ||
| 20 | ๐จ๐ฟ Prague | 0.73% | ||
| 21 | ๐ฆ๐ช Dubai | 0.7% | ||
| 22 | ๐ฆ๐ท Buenos Aires | 0.66% | ||
| 23 | ๐จ๐ด Medellรญn | 0.64% | ||
| 24 | ๐ท๐บ Moscow | 0.62% | ||
| 25 | ๐ฎ๐น Rome | 0.59% | ||
| 26 | ๐ฆ๐น Vienna | 0.58% | ||
| 27 | ๐ญ๐ฐ Hong Kong | 0.53% | ||
| 28 | ๐ป๐ณ Ho Chi Minh City | 0.53% | ||
| 29 | ๐ฎ๐ฉ Ubud | 0.53% | ||
| 30 | ๐น๐ญ Phuket | 0.52% | n=328,638 | |
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 | ๐ณ๐ฑ Netherlands | 2% | ||
| 14 | ๐ฏ๐ต Japan | 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 | ๐ฎ๐ณ India | 1% | ||
| 22 | ๐ฒ๐พ Malaysia | 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% | ||
| 29 | ๐ญ๐บ Hungary | 1% | n=328,638 | |
๐ Avg. COโ by member traveling |
||||
| Year | COโ | |||
| 2013 |
676 kg/y
|
|||
| 2014 |
994 kg/y
|
|||
| 2015 |
1,097 kg/y
|
|||
| 2016 |
1,317 kg/y
|
|||
| 2017 |
1,511 kg/y
|
|||
| 2018 |
1,610 kg/y
|
|||
| 2019 |
1,630 kg/y
|
|||
| 2020 |
1,015 kg/y
|
|||
| 2021 |
1,018 kg/y
|
|||
| 2022 |
1,641 kg/y
|
|||
| 2023 |
1,762 kg/y
|
|||
| 2024 |
2,882 kg/y
|
|||
| Average | 1,266 kg/y | |||
| Median | 1,207 kg/y |
Based on 328,638 trips by 13,301 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 1,207 kg/y, or 76% 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 | -9% | ||
| 4 | ๐ฌ๐ง London | -21% | ||
| 5 | ๐ซ๐ท Paris | -19% | ||
| 6 | ๐ฉ๐ช Berlin | -2% | ||
| 7 | ๐ณ๐ฑ Amsterdam | +5% | ||
| 8 | ๐น๐ญ Chiang Mai | -3% | ||
| 9 | ๐ฎ๐ฉ Canggu | +1% | ||
| 10 | ๐น๐ท Istanbul | +9% | ||
| 11 | ๐ธ๐ฌ Singapore | +13% | ||
| 12 | ๐ญ๐บ Budapest | +17% | ||
| 13 | ๐ฒ๐ฝ Mexico City | -23% | ||
| 14 | ๐ฏ๐ต Tokyo | +11% | ||
| 15 | ๐จ๐ฟ Prague | +18% | median temp=17°C; n=328,638 | |
๐ฑโโ๏ธ Where women go most |
||||
| # | Tag | vs. ๐จ | ||
| 1 | ๐ต๐น Lisbon | +16% | ||
| 2 | ๐ฌ๐ง London | +26% | ||
| 3 | ๐ช๐ธ Barcelona | +10% | ||
| 4 | ๐ซ๐ท Paris | +23% | ||
| 5 | ๐น๐ญ Bangkok | -19% | ||
| 6 | ๐ฒ๐ฝ Mexico City | +30% | ||
| 7 | ๐ฉ๐ช Berlin | +2% | ||
| 8 | ๐น๐ญ Chiang Mai | +3% | ||
| 9 | ๐ณ๐ฑ Amsterdam | -5% | ||
| 10 | ๐ฎ๐ฉ Canggu | -1% | ||
| 11 | ๐ฎ๐น Rome | +21% | ||
| 12 | ๐น๐ท Istanbul | -8% | ||
| 13 | ๐ฎ๐ฉ Ubud | +25% | ||
| 14 | ๐บ๐ธ New York City | +9% | ||
| 15 | ๐ฆ๐ท Buenos Aires | +14% | median temp=18°C; n=328,638 | |
๐จ Where men go more |
||||
| # | Tag | vs. women | ||
| 1 | ๐บ๐ฆ Ukraine | +98% | ||
| 2 | ๐ท๐บ Russia | +78% | ||
| 3 | ๐ต๐ฑ Poland | +71% | ||
| 4 | ๐ท๐ด Romania | +69% | ||
| 5 | ๐ฌ๐ช Georgia | +46% | ||
| 6 | ๐ท๐ธ Serbia | +35% | ||
| 7 | ๐ญ๐ฐ Hong Kong | +31% | ||
| 8 | ๐ณ๐ฟ New Zealand | +25% | ||
| 9 | ๐ฆ๐ช United Arab Emirates | +24% | ||
| 10 | ๐จ๐ฟ Czechia | +22% | ||
| 11 | ๐ต๐ญ Philippines | +21% | ||
| 12 | ๐ณ๐ด Norway | +19% | ||
| 13 | ๐จ๐ณ China | +18% | ||
| 14 | ๐ป๐ณ Vietnam | +18% | ||
| 15 | ๐ญ๐บ Hungary | +17% | median temp=13°C; n=328,638 | |
๐ฑโโ๏ธ Where women go more |
||||
| # | Tag | vs. men | ||
| 1 | ๐ฟ๐ฆ South Africa | +56% | ||
| 2 | ๐จ๐ท Costa Rica | +47% | ||
| 3 | ๐ฒ๐ฝ Mexico | +43% | ||
| 4 | ๐ฌ๐ง United Kingdom | +27% | ||
| 5 | ๐จ๐ฑ Chile | +26% | ||
| 6 | ๐ญ๐ท Croatia | +20% | ||
| 7 | ๐ซ๐ท France | +18% | ||
| 8 | ๐ต๐ช Peru | +16% | ||
| 9 | ๐ฎ๐น Italy | +15% | ||
| 10 | ๐ฌ๐ท Greece | +12% | ||
| 11 | ๐ฆ๐ท Argentina | +10% | ||
| 12 | ๐บ๐ธ United States | +9% | ||
| 13 | ๐ต๐น Portugal | +9% | ||
| 14 | ๐ฆ๐บ Australia | +8% | ||
| 15 | ๐ช๐ธ Spain | +6% | median temp=18°C; n=328,638 | |
๐ Most liked countries |
||||
| # | Country | Rating | ||
| 1 | ๐ญ๐ท Croatia | 4.7 | ||
| 2 | ๐ฐ๐ท South Korea | 4.7 | ||
| 3 | ๐ฌ๐ท Greece | 4.65 | ||
| 4 | ๐ญ๐บ Hungary | 4.65 | ||
| 5 | ๐จ๐ฟ Czechia | 4.4 | ||
| 6 | ๐ฒ๐พ Malaysia | 4.35 | ||
| 7 | ๐ต๐ฑ Poland | 4.3 | ||
| 8 | ๐ฟ๐ฆ South Africa | 4.25 | ||
| 9 | ๐ฉ๐ฐ Denmark | 4.15 | ||
| 10 | ๐บ๐พ Uruguay | 4.15 | ||
| 11 | ๐ต๐ฆ Panama | 4.15 | ||
| 12 | ๐ช๐ธ Spain | 4.1 | ||
| 13 | ๐ซ๐ท France | 4.1 | ||
| 14 | ๐ฉ๐ช Germany | 4.05 | ||
| 15 | ๐ฎ๐น Italy | 4.05 | n=2,035 | |
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 | ๐ฒ๐ช Montenegro | 1.8 | ||
| 7 | ๐ฑ๐ฐ Sri Lanka | 2 | ||
| 8 | ๐ฑ๐ฆ Laos | 2.15 | ||
| 9 | ๐จ๐ฑ Chile | 2.25 | ||
| 10 | ๐ธ๐ด Somalia | 2.5 | ||
| 11 | ๐ช๐น Ethiopia | 2.5 | ||
| 12 | ๐ท๐ผ Rwanda | 2.5 | ||
| 13 | ๐ธ๐ณ Senegal | 2.5 | ||
| 14 | ๐ป๐ช Venezuela | 2.5 | ||
| 15 | ๐จ๐ฒ Cameroon | 2.5 | n=2,035 | |
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=319,901 | ||
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 | 200 days (7 months) | n=319,901 | ||
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% | +242% | |
| 2 | ๐ธ Web Dev | 28% | +254% | |
| 3 | ๐ Startup Founder | 27% | +134% | |
| 4 | ๐ Marketing | 15% | = | |
| 5 | ๐ SaaS | 13% | +196% | |
| 6 | ๐ฉโ๐จ Creative | 12% | -18% | |
| 7 | ๐จ UI/UX Design | 11% | +39% | |
| 8 | ๐ค Product Manager | 11% | +71% | |
| 9 | ๐ฐ Crypto | 11% | +256% | |
| 10 | ๐ Data | 11% | +108% | |
| 11 | ๐ฑ Mobile Dev | 11% | +341% | |
| 12 | ๐ฐ Finance | 10% | +129% | |
| 13 | ๐ Ecommerce | 9% | +103% | |
| 14 | ๐ค Sales | 7% | +83% | |
| 15 | ๐จโ๐ซ Education | 6% | -9% | n=18,422 |
๐ฑโโ๏ธ Nomad women work as |
||||
| # | Work | % | vs. men | |
| 1 | ๐ Marketing | 15% | 0% | |
| 2 | ๐ฉโ๐จ Creative | 15% | +22% | |
| 3 | ๐ Startup Founder | 12% | -57% | |
| 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% | +24% | |
| 9 | ๐จโ๐ซ Education | 7% | +10% | |
| 10 | ๐ Coach | 7% | +21% | |
| 11 | ๐ค Product Manager | 7% | -42% | |
| 12 | ๐ Data | 5% | -52% | |
| 13 | ๐ SaaS | 4% | -66% | |
| 14 | ๐ Ecommerce | 4% | -51% | |
| 15 | ๐ฐ Finance | 4% | -56% | n=5,681 |
๐จ Nomad men vs. women |
||||
| # | Tag | vs. women | ||
| 1 | ๐พ Game Dev | +354% | ||
| 2 | ๐ฑ Mobile Dev | +341% | ||
| 3 | ๐ Dev Ops | +305% | ||
| 4 | ๐ก Sysadmin | +295% | ||
| 5 | ๐ฐ Crypto | +256% | ||
| 6 | ๐ธ Web Dev | +254% | ||
| 7 | ๐ป Software Dev | +242% | ||
| 8 | ๐ SaaS | +196% | ||
| 9 | ๐ VR Dev | +157% | ||
| 10 | ๐ Sports | +151% | ||
| 11 | ๐บ Geo | +140% | ||
| 12 | ๐ Startup Founder | +134% | ||
| 13 | ๐ฐ Finance | +129% | ||
| 14 | ๐ Data | +108% | ||
| 15 | ๐ Ecommerce | +103% | n=22,979 | |
๐ฑโโ๏ธ Nomad women vs. men |
||||
| # | Tag | vs. men | ||
| 1 | ๐งโ๐ผ Human resources | +77% | ||
| 2 | ๐ง Psychologist | +61% | ||
| 3 | ๐ฐ Journalism | +51% | ||
| 4 | ๐จโโ๏ธ Medical | +33% | ||
| 5 | ๐ Support | +29% | ||
| 6 | ๐ค Community | +24% | ||
| 7 | ๐ Hospitality | +22% | ||
| 8 | ๐ฉโ๐จ Creative | +22% | ||
| 9 | ๐ Coach | +21% | ||
| 10 | ๐ Blogging | +20% | ||
| 11 | ๐ธ Model | +14% | ||
| 12 | ๐ Recruitment | +13% | ||
| 13 | ๐จโ๐ซ Education | +10% | ||
| 14 | ๐ฉโ๐ผ Law | +8% | n=22,979 | |
โ๏ธ Coffee
๐ Optimist
๐ฌ๐ง Speaks English
๐ COVID vaccinated
โฐ Outdoors
๐ฅพ Hiking
๐จโ Nomad men |
||||
| # | Tag | % | vs. ๐ฑโโ๏ธ | |
| 1 | โ๏ธ Coffee | 39% | +30% | |
| 2 | ๐ Optimist | 31% | +32% | |
| 3 | ๐ฌ๐ง Speaks English | 30% | +22% | |
| 4 | ๐ COVID vaccinated | 27% | +21% | |
| 5 | โฐ Outdoors | 27% | +9% | |
| 6 | ๐ฅพ Hiking | 26% | +17% | |
| 7 | ๐ถ Dogs | 26% | +10% | |
| 8 | ๐ช Fitness | 26% | +52% | |
| 9 | ๐บ Beer | 25% | +126% | |
| 10 | โ๏ธ Waking up early | 25% | +29% | |
| 11 | ๐ Staying up late | 25% | +55% | |
| 12 | ๐ง Open-minded | 24% | +23% | |
| 13 | ๐ Reading | 24% | +13% | |
| 14 | ๐ท Wine | 23% | +2% | |
| 15 | ๐ Single | 23% | +36% | n=18,422 |
๐ฑโโ๏ธ Nomad women |
||||
| # | Tag | % | vs. ๐จโ | |
| 1 | โ๏ธ Coffee | 30% | -23% | |
| 2 | โฐ Outdoors | 24% | -8% | |
| 3 | ๐ฌ๐ง Speaks English | 24% | -18% | |
| 4 | ๐ถ Dogs | 23% | -9% | |
| 5 | ๐ Optimist | 23% | -24% | |
| 6 | ๐ท Wine | 23% | -2% | |
| 7 | ๐ COVID vaccinated | 23% | -17% | |
| 8 | ๐ฅพ Hiking | 22% | -15% | |
| 9 | ๐ Reading | 21% | -11% | |
| 10 | ๐ต Tea | 21% | -1% | |
| 11 | ๐ง Open-minded | 19% | -18% | |
| 12 | ๐คธโโ๏ธ Yoga | 19% | +69% | |
| 13 | โ๏ธ Waking up early | 19% | -23% | |
| 14 | โฑ Beach | 18% | +5% | |
| 15 | ๐ธ Cocktails | 17% | -8% | n=5,681 |
๐จ Nomad men vs. women |
||||
| # | Tag | vs. ๐ฑโโ๏ธ | ||
| 1 | ๐ง Have a beard | +1,168% | ||
| 2 | ๐ช Roost Stand | +373% | ||
| 3 | ๐จ No beard | +339% | ||
| 4 | โฝ๏ธ Football | +335% | ||
| 5 | ๐งโ Short hair | +261% | ||
| 6 | ๐ง Hardstyle music | +228% | ||
| 7 | ๐ Race sports | +217% | ||
| 8 | ๐ Ice hockey | +215% | ||
| 9 | ๐ Motorcycling | +214% | ||
| 10 | ๐ช Dropout | +205% | ||
| 11 | ๐ Basketball | +201% | ||
| 12 | ๐ด Conservative politics | +191% | ||
| 13 | ๐ Table tennis | +187% | ||
| 14 | ๐พ Gaming | +176% | ||
| 15 | ๐ Skateboarding | +172% | n=22,979 | |
๐ฑโโ๏ธ Nomad women vs. men |
||||
| # | Tag | vs. ๐จ | ||
| 1 | ๐ Makeup | +2,957% | ||
| 2 | ๐ฑโโ๏ธ Long hair | +274% | ||
| 3 | ๐ Dress up | +232% | ||
| 4 | โจ Believe in astrology | +231% | ||
| 5 | โจ Astrology | +227% | ||
| 6 | ๐ช Feminism | +186% | ||
| 7 | ๐จ Drawing | +102% | ||
| 8 | ๐ฆพ Disabled | +91% | ||
| 9 | ๐ Dancing | +86% | ||
| 10 | ๐ฅ Red hair | +83% | ||
| 11 | ๐ Shopping | +70% | ||
| 12 | ๐คธโโ๏ธ Yoga | +69% | ||
| 13 | ๐ฐ๐ท Speaks Korean | +68% | ||
| 14 | ๐ป Gardening | +68% | ||
| 15 | โ๐ฟ Black | +66% | n=22,979 | |
๐ Nomads by vaccination |
||||
| Vaccinated | % | |||
| ๐ COVID vaccinated |
94%
|
|||
| ๐ Not COVID vaccinated |
6%
|
n=7,038 | ||
โค๏ธ Nomads by family |
||||
| Relationship | % | |||
| โค๏ธ Close to parents |
81%
|
|||
| ๐ Not close to parents |
19%
|
n=1,762 | ||
๐ถ Nomads by childhood |
||||
| Childhood | % | |||
| ๐ Happy childhood |
89%
|
|||
| ๐ Unhappy childhood |
11%
|
n=1,914 | ||
๐ก Homeownership amongst nomads |
||||
| Homeownership | % | |||
| ๐ก Homeowner |
53%
|
|||
| ๐ก Not a homeowner |
47%
|
n=2,076 | ||
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
๐ Volleyball
๐ In a relationship
๐ณ๏ธโ๐ LGBT
๐ธ Punk music
๐จโ Attractive men's traits |
||||
| # | Tag | Diff | ||
| 1 | ๐ In a relationship | +138% | ||
| 2 | ๐ Not COVID vaccinated | +87% | ||
| 3 | ๐ก Homeowner | +76% | ||
| 4 | โจ Believe in astrology | +75% | ||
| 5 | ๐ง Pessimist | +75% | ||
| 6 | ๐ Free diving | +72% | ||
| 7 | ๐ฌ Twitter | +71% | ||
| 8 | ๐ถ Parent | +70% | ||
| 9 | ๐ Basketball | +70% | ||
| 10 | ๐งโ Short hair | +66% | ||
| 11 | ๐ง Hiphop music | +62% | ||
| 12 | ๐ Volleyball | +59% | ||
| 13 | ๐ง Dubstep music | +55% | ||
| 14 | ๐ก Not a homeowner | +54% | ||
| 15 | ๐ iPhone | +53% | ||
| 16 | ๐ Reggae music | +52% | ||
| 17 | ๐ Ice hockey | +49% | ||
| 18 | โค๏ธ Happy childhood | +48% | ||
| 19 | ๐ Table tennis | +47% | ||
| 20 | ๐ง Drum & Bass music | +46% | ||
| 21 | ๐ฅ Soft boiled eggs | +45% | ||
| 22 | ๐ฐ Pop music | +44% | ||
| 23 | ๐งผ Clean freak | +44% | ||
| 24 | ๐ง Have a beard | +43% | ||
| 25 | ๐ฌ Facebook | +42% | ||
| 26 | ๐ธ Metal music | +42% | ||
| 27 | ๐ Massage | +40% | ||
| 28 | ๐ Country music | +40% | ||
| 29 | ๐ง House music | +39% | ||
| 30 | ๐ Kitesurfing | +39% | n=22,979 | |
๐ฑโโ๏ธ Attractive women's traits |
||||
| # | Tag | Diff | ||
| 1 | ๐ My parents separated | +343% | ||
| 2 | ๐ Table tennis | +298% | ||
| 3 | ๐ Volleyball | +261% | ||
| 4 | ๐ณ๏ธโ๐ LGBT | +250% | ||
| 5 | ๐ Shopping | +242% | ||
| 6 | ๐ง Only child | +218% | ||
| 7 | ๐ธ Punk music | +213% | ||
| 8 | ๐ฝ Libertarian politics | +199% | ||
| 9 | ๐ Running | +181% | ||
| 10 | ๐ Pescetarian | +171% | ||
| 11 | ๐จโ๐ค Partying | +161% | ||
| 12 | ๐งผ Clean freak | +153% | ||
| 13 | ๐ Makeup | +153% | ||
| 14 | ๐ฌ Social smoker | +152% | ||
| 15 | โท Skiing | +146% | ||
| 16 | ๐ Dress up | +144% | ||
| 17 | ๐ In a relationship | +143% | ||
| 18 | ๐ Surfing | +142% | ||
| 19 | ๐พ Drinking alcohol | +139% | ||
| 20 | โฝ๏ธ Football | +137% | ||
| 21 | ๐ Vanlife | +135% | ||
| 22 | ๐บ Beer | +131% | ||
| 23 | โจ Astrology | +128% | ||
| 24 | ๐ Film making | +126% | ||
| 25 | ๐ Motorcycling | +125% | ||
| 26 | ๐ด Cycling | +124% | ||
| 27 | ๐ง Techno music | +122% | ||
| 28 | ๐ธ Indie rock music | +119% | ||
| 29 | โฌ๏ธ Has no tattoos | +118% | ||
| 30 | ๐ Staying up late | +116% | n=22,979 | |
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
๐ช Skydiving
๐ Makeup
๐ด Conservative politics
๐ญ Swinging
๐ช Nexstand
๐จโ Unattractive men's traits |
||||
| # | Tag | Diff | ||
| 1 | ๐ช Skydiving | -737% | ||
| 2 | ๐ Makeup | -501% | ||
| 3 | ๐ญ Swinging | -372% | ||
| 4 | ๐ช Nexstand | -205% | ||
| 5 | ๐ Urbex | -104% | ||
| 6 | ๐ฉ Samoyeds | -83% | ||
| 7 | ๐ Single | -74% | ||
| 8 | ๐ณ Bowling | -73% | ||
| 9 | ๐ช Feminism | -70% | ||
| 10 | ๐ง Trance music | -63% | ||
| 11 | ๐ถโ๐ซ๏ธ Hang gliding | -59% | ||
| 12 | ๐ช Paragliding | -52% | ||
| 13 | ๐ฑ Pool | -52% | ||
| 14 | ๐ Paleo | -43% | ||
| 15 | ๐ Cricket | -42% | ||
| 16 | ๐ณ๏ธโ๐ Progressive politics | -40% | ||
| 17 | ๐ Buddhist | -37% | ||
| 18 | ๐ Film making | -35% | ||
| 19 | ๐ Sex positive | -33% | ||
| 20 | ๐ฅ Hard boiled eggs | -33% | ||
| 21 | ๐ป Gardening | -28% | ||
| 22 | ๐ Third Culture Kid | -28% | ||
| 23 | ๐ Kink | -26% | ||
| 24 | โพ๏ธ Baseball | -23% | ||
| 25 | ๐ค Singing | -21% | ||
| 26 | ๐ Dancing | -20% | ||
| 27 | ๐ Religious | -20% | ||
| 28 | ๐ฅ Frisbee | -19% | ||
| 29 | ๐ Motorcycling | -18% | ||
| 30 | ๐บ Breakdance | -18% | n=22,979 | |
๐ฑโโ๏ธ Unattractive women's traits |
||||
| # | Tag | Diff | ||
| 1 | ๐ฅ Messy | -1,707% | ||
| 2 | ๐ช Paragliding | -944% | ||
| 3 | ๐ด Conservative politics | -434% | ||
| 4 | ๐ฌ Slack | -333% | ||
| 5 | ๐ฌ Discord | -282% | ||
| 6 | ๐ธ Anime | -180% | ||
| 7 | ๐ช Roost Stand | -129% | ||
| 8 | ๐ฌ Snapchat | -104% | ||
| 9 | ๐ Kink | -93% | ||
| 10 | ๐ธ Badminton | -91% | ||
| 11 | ๐ฌ Instagram | -81% | ||
| 12 | ๐ถโ๐ซ๏ธ Hang gliding | -78% | ||
| 13 | ๐ฐ๐ท K-pop music | -78% | ||
| 14 | ๐ Carnivore | -48% | ||
| 15 | โค๏ธ Happy childhood | -45% | ||
| 16 | โจ Believe in astrology | -27% | ||
| 17 | ๐ Country music | -15% | ||
| 18 | ๐ Kitesurfing | -13% | ||
| 19 | ๐ฌ Facebook | -12% | ||
| 20 | ๐ถ Parent | -10% | ||
| 21 | ๐ณ Introvert | -8% | ||
| 22 | ๐ฌ Telegram | -6% | ||
| 23 | ๐ Paleo | -4% | ||
| 24 | ๐ง Garage music | -4% | ||
| 25 | ๐ช Fight sports | -3% | n=22,979 | |
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).
๐ค Community
๐ฑ Mobile Dev
๐จ UI/UX Design
๐ฉโ๐จ Creative
๐ SaaS
๐ Startup Founder
๐จโ Attractive men's jobs |
||||
| # | Tag | Diff | ||
| 1 | ๐จโโ๏ธ Medical | +60% | ||
| 2 | ๐ Recruitment | +43% | ||
| 3 | ๐จ UI/UX Design | +42% | ||
| 4 | ๐ SaaS | +37% | ||
| 5 | ๐พ Game Dev | +35% | ||
| 6 | ๐ฑ Mobile Dev | +30% | ||
| 7 | ๐ค Product Manager | +29% | ||
| 8 | ๐ Dev Ops | +24% | ||
| 9 | ๐ Startup Founder | +22% | ||
| 10 | ๐ Ecommerce | +22% | ||
| 11 | ๐ช Fitness | +22% | ||
| 12 | ๐ Marketing | +19% | ||
| 13 | ๐ VR Dev | +18% | ||
| 14 | ๐ Coach | +17% | ||
| 15 | ๐ค Sales | +16% | ||
| 16 | ๐ Sports | +15% | ||
| 17 | ๐ป Software Dev | +12% | ||
| 18 | ๐ Logistics | +11% | ||
| 19 | ๐ Data | +11% | ||
| 20 | ๐ฐ Crypto | +9% | ||
| 21 | ๐ธ Web Dev | +9% | ||
| 22 | ๐ค Community | +8% | ||
| 23 | ๐ฐ Finance | +5% | n=22,979 | |
๐ฑโโ๏ธ Attractive women's jobs |
||||
| # | Tag | Diff | ||
| 1 | ๐ค Community | +157% | ||
| 2 | ๐ฑ Mobile Dev | +113% | ||
| 3 | ๐ฉโ๐จ Creative | +105% | ||
| 4 | ๐ Blogging | +93% | ||
| 5 | ๐ Startup Founder | +76% | ||
| 6 | ๐จ UI/UX Design | +68% | ||
| 7 | ๐ Ecommerce | +68% | ||
| 8 | ๐ SaaS | +62% | ||
| 9 | ๐ Marketing | +61% | ||
| 10 | ๐ค Product Manager | +55% | ||
| 11 | ๐ฐ Finance | +51% | ||
| 12 | ๐ค Sales | +46% | ||
| 13 | ๐จโ๐ซ Education | +44% | ||
| 14 | ๐ Coach | +41% | ||
| 15 | ๐ป Software Dev | +23% | ||
| 16 | ๐ Data | +11% | ||
| 17 | ๐ธ Web Dev | +9% | n=22,979 | |
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 Hospitality
๐ธ Model
๐ฉโ๐ผ Law
๐ก Architecture
๐ฐ Journalism
๐จโ Unattractive men's jobs |
||||
| # | Tag | Diff | ||
| 1 | ๐ฉ Politics | -256% | ||
| 2 | ๐ธ Model | -90% | ||
| 3 | ๐ฉโ๐ผ Law | -85% | ||
| 4 | ๐ก Architecture | -82% | ||
| 5 | ๐ฐ Journalism | -62% | ||
| 6 | ๐งโ๐ผ Human resources | -34% | ||
| 7 | ๐ถ Adult | -33% | ||
| 8 | ๐บ Geo | -29% | ||
| 9 | ๐ Hospitality | -27% | ||
| 10 | ๐ Support | -21% | ||
| 11 | ๐ก Sysadmin | -18% | ||
| 12 | ๐ฉโ๐จ Creative | -5% | ||
| 13 | ๐จโ๐ซ Education | -4% | ||
| 14 | ๐ Blogging | -1% | n=22,979 | |
๐ฑโโ๏ธ Unattractive women's jobs |
||||
| # | Tag | Diff | ||
| 1 | ๐ฉ Politics | -1,122% | ||
| 2 | ๐ VR Dev | -536% | ||
| 3 | ๐ Hospitality | -251% | ||
| 4 | ๐ Sports | -83% | n=22,979 | |
๐จโ Where attractive men travel to |
||||
| # | City | Attractiveness | ||
| 1 | ๐ต๐น Ericeira | 5 | ||
| 2 | ๐ฆ๐บ Brisbane | 4.92 | ||
| 3 | ๐ฒ๐พ Langkawi | 4.92 | ||
| 4 | ๐ฒ๐ฝ Cabo San Lucas | 4.86 | ||
| 5 | ๐จ๐ท Tamarindo | 4.76 | ||
| 6 | ๐ฎ๐ธ Reykjavik | 4.76 | ||
| 7 | ๐บ๐ธ Boston | 4.69 | ||
| 8 | ๐ฎ๐ฉ Uluwatu | 4.63 | ||
| 9 | ๐ณ๐ด Bergen | 4.6 | ||
| 10 | ๐ฐ๐ท Busan | 4.55 | ||
| 11 | ๐ฉ๐ด Punta Cana | 4.54 | ||
| 12 | ๐ช๐ธ Mallorca | 4.53 | ||
| 13 | ๐ฟ๐ฆ Johannesburg | 4.51 | ||
| 14 | ๐ฒ๐ฝ Sayulita | 4.48 | ||
| 15 | ๐ช๐ธ Ibiza | 4.48 | ||
| 16 | ๐ฆ๐ท Mendoza | 4.45 | ||
| 17 | ๐ณ๐ฟ Auckland | 4.45 | ||
| 18 | ๐บ๐ธ Orlando | 4.45 | ||
| 19 | ๐ฉ๐ช Frankfurt | 4.44 | ||
| 20 | ๐ฑ๐ฆ Luang Prabang | 4.43 | ||
| 21 | ๐ณ๐ฟ Queenstown | 4.43 | ||
| 22 | ๐ป๐ณ Hoi An | 4.42 | ||
| 23 | ๐ฆ๐บ Melbourne | 4.42 | ||
| 24 | ๐ต๐น Faro | 4.42 | ||
| 25 | ๐ฎ๐น Palermo | 4.42 | ||
| 26 | ๐น๐ญ Ko Lanta | 4.42 | ||
| 27 | ๐ฎ๐ฑ Tel Aviv | 4.42 | ||
| 28 | ๐ณ๐ฟ Wellington | 4.42 | ||
| 29 | ๐ง๐ช Antwerp | 4.41 | ||
| 30 | ๐ญ๐ท Zadar | 4.41 | Based on attractiveness of visitors n=328,638 | |
๐ฑโโ๏ธ Where attractive women travel to |
||||
| # | City | Attractiveness | ||
| 1 | ๐น๐ญ Ko Phi Phi | 5 | ||
| 2 | ๐ญ๐ท Zadar | 4.99 | ||
| 3 | ๐ฎ๐น Amalfi | 4.99 | ||
| 4 | ๐ฎ๐น Genoa | 4.97 | ||
| 5 | ๐ต๐ฑ Warsaw | 4.96 | ||
| 6 | ๐ฉ๐ด Punta Cana | 4.96 | ||
| 7 | ๐ต๐ฑ Krakรณw | 4.89 | ||
| 8 | ๐บ๐ฆ Kyiv | 4.88 | ||
| 9 | ๐น๐ญ Ko Samui | 4.86 | ||
| 10 | ๐ฒ๐ช Budva | 4.85 | ||
| 11 | ๐ฆ๐น Salzburg | 4.78 | ||
| 12 | ๐ฐ๐ท Busan | 4.78 | ||
| 13 | ๐จ๐ฑ Valparaรญso | 4.77 | ||
| 14 | ๐ธ๐ฐ Bratislava | 4.74 | ||
| 15 | ๐ฒ๐ช Kotor | 4.73 | ||
| 16 | ๐ฒ๐ฆ Casablanca | 4.72 | ||
| 17 | ๐ฎ๐ฉ Jakarta | 4.71 | ||
| 18 | ๐บ๐ธ Orlando | 4.69 | ||
| 19 | ๐ช๐ธ Fuerteventura | 4.69 | ||
| 20 | ๐ธ๐ฎ Ljubljana | 4.67 | ||
| 21 | ๐ฆ๐น Vienna | 4.65 | ||
| 22 | ๐บ๐ธ Miami | 4.63 | ||
| 23 | ๐ซ๐ท Strasbourg | 4.63 | ||
| 24 | ๐ญ๐ท Dubrovnik | 4.62 | ||
| 25 | ๐น๐ท Antalya | 4.62 | ||
| 26 | ๐ฎ๐น Milan | 4.62 | ||
| 27 | ๐บ๐ธ Portland | 4.62 | ||
| 28 | ๐จ๐พ Larnaca | 4.61 | ||
| 29 | ๐ท๐บ Moscow | 4.61 | ||
| 30 | ๐ฎ๐ฉ Uluwatu | 4.61 | Based on attractiveness of visitors n=328,638 | |
๐จโ Where unattractive men travel to |
||||
| # | City | Attractiveness | ||
| 1 | ๐น๐ญ Pattaya | 3.22 | ||
| 2 | ๐ฎ๐ณ Goa | 3.27 | ||
| 3 | ๐ฎ๐ณ Mumbai | 3.53 | ||
| 4 | ๐ช๐ธ Alicante | 3.58 | ||
| 5 | ๐ต๐พ Asuncion | 3.63 | ||
| 6 | ๐ฒ๐ช Podgorica | 3.63 | ||
| 7 | ๐ท๐บ Moscow | 3.69 | ||
| 8 | ๐ถ๐ฆ Doha | 3.69 | ||
| 9 | ๐ฒ๐ฝ Guadalajara | 3.69 | ||
| 10 | ๐จ๐บ Havana | 3.69 | ||
| 11 | ๐ฎ๐ณ Bengaluru | 3.69 | ||
| 12 | ๐ณ๐ต Kathmandu | 3.69 | ||
| 13 | ๐ต๐ฑ Wrocลaw | 3.69 | ||
| 14 | ๐ช๐ฌ Cairo | 3.7 | ||
| 15 | ๐ฎ๐ฑ Jerusalem | 3.77 | ||
| 16 | ๐บ๐ฆ Lviv | 3.77 | ||
| 17 | ๐ฐ๐ฟ Almaty | 3.78 | ||
| 18 | ๐ฐ๐ช Nairobi | 3.79 | ||
| 19 | ๐น๐ท Antalya | 3.8 | ||
| 20 | ๐ง๐พ Minsk | 3.82 | ||
| 21 | ๐น๐ญ Pai | 3.83 | ||
| 22 | ๐ฎ๐ฉ Kuta | 3.83 | ||
| 23 | ๐ฆ๐ช Dubai | 3.83 | ||
| 24 | ๐ช๐ธ Bilbao | 3.84 | ||
| 25 | ๐จ๐ญ Geneva | 3.84 | ||
| 26 | ๐ต๐ฑ Gdansk | 3.85 | ||
| 27 | ๐ฆ๐น Salzburg | 3.88 | ||
| 28 | ๐บ๐ธ Washington | 3.88 | ||
| 29 | ๐ฎ๐ณ Delhi | 3.88 | ||
| 30 | ๐ฆ๐ฑ Tirana | 3.9 | Based on unattractiveness of visitors n=328,638 | |
๐ฑโโ๏ธ Where unattractive women travel to |
||||
| # | City | Attractiveness | ||
| 1 | ๐ช๐จ Cuenca | 2.98 | ||
| 2 | ๐ฐ๐ช Nairobi | 3.23 | ||
| 3 | ๐ช๐จ Quito | 3.23 | ||
| 4 | ๐ง๐ช Antwerp | 3.24 | ||
| 5 | ๐ช๐ธ Tarifa | 3.45 | ||
| 6 | ๐ฆ๐บ Perth | 3.46 | ||
| 7 | ๐ณ๐ฎ San Juan del Sur | 3.49 | ||
| 8 | ๐บ๐ธ Atlanta | 3.5 | ||
| 9 | ๐บ๐ธ New Orleans | 3.5 | ||
| 10 | ๐ต๐ท San Juan | 3.5 | ||
| 11 | ๐ฌ๐ง Manchester | 3.57 | ||
| 12 | ๐ฒ๐ฝ Guadalajara | 3.57 | ||
| 13 | ๐ฑ๐ฆ Vientiane | 3.61 | ||
| 14 | ๐ฏ๐ด Amman | 3.61 | ||
| 15 | ๐จ๐ด Bogota | 3.65 | ||
| 16 | ๐ฌ๐ง Liverpool | 3.65 | ||
| 17 | ๐ณ๐ฟ Wellington | 3.65 | ||
| 18 | ๐ฒ๐ฝ Guanajuato | 3.66 | ||
| 19 | ๐ฐ๐ญ Phnom Penh | 3.73 | ||
| 20 | ๐ฒ๐ฝ San Miguel de Allende | 3.74 | ||
| 21 | ๐ฎ๐ฉ Denpasar | 3.74 | ||
| 22 | ๐ฎ๐ณ Mumbai | 3.75 | ||
| 23 | ๐ณ๐ต Kathmandu | 3.79 | ||
| 24 | ๐ฒ๐ฝ San Cristรณbal de las Casas | 3.79 | ||
| 25 | ๐ฒ๐ฝ Merida | 3.79 | ||
| 26 | ๐ฎ๐ฉ Kuta | 3.79 | ||
| 27 | ๐ฒ๐ฝ Cozumel | 3.81 | ||
| 28 | ๐ต๐ฆ Panama City | 3.82 | ||
| 29 | ๐ฒ๐ฝ La Paz | 3.82 | ||
| 30 | ๐ฌ๐ง Bristol | 3.82 | Based on unattractiveness of visitors n=328,638 | |
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